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Swee Lay Thein: Good
morning, everybody,

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I think we are
running a bit late,

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so we must go and get
started as soon as we can.

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I really like to
extend a huge welcome

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to all of you on behalf
of the organizing committee,

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which is myself, Monika,
Jennifer, and John Tisdale

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to the 17th Sickle
Cell in focus meeting.

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I am so delighted
to see so many in person,

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but in fact more than 500
actually registered.

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And they will be
listening online,

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and that is the reason
why we are a bit late,

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because we want to make
sure that these guys

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who've registered
can actually tune in.

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So, the housekeeping things
will come in a bit later,

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because I think
we should get started ASAP.

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And with that I will
like to introduce,

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Professor Minerva Thame,

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who is the dean of the medical
school in Jamaica and --

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Is she coming in person?

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[laughter]

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Swee Lay Thein: Oh, Welcome.
Would you like to come and talk?

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Thank you so much, I didn't
realize you were there waiting.

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Minerva Thame: Thank
you, very much.

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Swee Lay Thein: Thank
you for coming.

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Minerva Thame: Yes,
I'm here in person.

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I think the last time
we were virtual, right?

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The last meeting, so
here is my opportunity

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to get to see all
of these faces.

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So, chair, delegates
from all over the world,

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colleagues, good morning.

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Thank you for inviting me
to bring greetings

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at the 17th Annual Sickle
Cell in Focus Conference.

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I am delighted that
the National Heart, Lung,

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and Blood Institute is cohosting
the 24th Annual Conference

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for the University
of the West Indies

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once again. Such collaboration

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helps to build and
strengthen institutions

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as they share in scholarship.

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I want to also recognize
the powerful speakers

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we have on this agenda

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to present from
both Institutions

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who no doubt will give us a
treat over the next two days.

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Sickle Cell Disease

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is such an important disease
for us here in Jamaica.

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One in 300 babies are born
in Jamaica with homozygous SS,

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while one in 500
are born with a C disease.

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Ten percent of our population
carries a sickle cell trait.

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With the figures, the burden
of disease in Jamaica,

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is quite high.

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Fortunately for us,
sickle cell disease

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has been extensively
studied in Jamacia,

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and these studies have informed

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and led to improve
management of our children

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with sickle cell disease.

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And has improved significantly
the rate of survival.

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Many of our children
use to die very young.

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But due to research conducted,

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which have led to the
implementation of policies,

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the lifespan has
improved significantly.

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So much has the life spanned
improved that the survival

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has now seen our children
growing up to adulthood,

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and into reproductive age.

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This has therefore,
allowed us to do more studies

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on pregnant women
with sickle cell disease,

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which is has been able
to add valuable knowledge

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to the global literature.

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Professor Graham Serjeant,
who is dear to my heart.

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Who has mentored
me for many years;

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who I still work with,

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has been a name
that's synonymous

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with sickle cell
disease in Jamacia.

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He was the first director
of the sickle cell unit.

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And following the work done
on his long-life birth cohort.

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He has added through
his research,

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knowledge which we now have.

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Other persons have worked
within the sickle cell unit,

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and I will not call names,
because I'd get into trouble.

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But they have done
extensive work,

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but one of them which I must
say I am very proud of is;

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a newborn screening, which
now is a reality in Jamacia.

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And a very important
initiative for our island.

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We have so much more
work to do as we strive

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to serve this important
group within our population.

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This conference will
continue to educate us

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and from discussions, I
am sure that new ideas

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and research questions
will emerge.

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We will receive updates on,

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screening for sickle
cell disease,

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complexity of common
complications

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in sickle cell disease,

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such as pain management,
sleep and reproductive health,

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therapies for
sickle cell disease,

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both curative and noncurative,

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and ongoing challenges
in the management

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of sickle cell complications.

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I wish you all a very successful
and fruitful conference.

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And I know the participants will
be exposed to rich information,

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which will enhance our knowledge
of sickle cell disease.

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And we will serve this
very important population.

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Thank you very much.

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[applause]

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Swee Lay Thein: Thank
you, Professor Thame.

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So, we -- Dr. Childs, who is
the director of initial VI

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[phonetic sp],
unfortunately, hoped to come,

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he had to cancel
at the last minute,

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but he will give welcome remarks
which we will now present.

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I just hope this
be ready [sic].

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Okay, Thank you, Ric.

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Richard Childs: --
Healthcare professionals

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and advocates, my name
is Dr. Richard Childs,

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and I am the scientific director
at the National Heart, Lung,

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and Blood Institute or NHLBI

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at the National
Institutes of Health.

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And it is my distinct pleasure
to welcome all of you

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to the 17th Annual Sickle Cell
in Focus Conference,

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co-hosted by both the NHLBI

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and the University
of the West Indies.

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This year we're excited
to gather both in person

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in beautiful Kingston,
Jamacia and virtually reflected

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on the global importance
of this event,

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and the broad reach
of our mission.

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While we may not all be
in the same physical space,

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the urgency of our mission,
and the impact of our work,

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are just as powerful.
Sickle cell disease

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remains a significant public
health challenge,

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effecting over
100,000 U.S. citizens

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and millions of
patients world-wide.

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It's a disease that
brings complexities,

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and inequities that
we as a community

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must continue to address.

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This annual conference
serves as a vital platform

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to share the latest advances
in scientific research,

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in clinical care, and
global health strategies,

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as we work together to improve
the lives of those living with

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and suffering from
sickle cell disease.

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At the NHLBI, our commitment
to sickle cell research

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is unwavering.

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We've made remarkable
strides in both curative

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and noncurative therapies,

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while also focusing
on innovative treatments

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that address the
diverse complications

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associated with this disease.

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Some of the key initiatives
that we are advancing

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include the cure sickle
cell initiative.

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Which is working to
accelerate the development

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of genetic therapies

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aimed to find a way to
cure sickle cell disease.

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This bold endeavor
holds the potential

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to transform the future
of treatment for this disorder,

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and just this year has
resulted in two new FDA

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approved therapies
using gene therapy.

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Our focus on health
disparities aims to ensure

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that those disproportionately
affected by sickle cell disease,

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particular in

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the African-American
and minority communities,

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receive equitable care, and
opportunities to participate

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in cutting edge research
and clinical trials.

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This year's Sickle Cell
in Focus Conference

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will address several critical
and important themes,

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including updates on screening
for sickle cell disease,

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pain management, sleep,
and reproductive health,

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and the complexities of curative
and noncurative therapies.

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We will also delve
into ongoing challenges

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that many patients face
in managing this condition,

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including complications
such as stroke, organ damage,

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and chronic pain.

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Importantly, the voices of
the patient's and clinicians

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will shape much of the
dialogue of this meeting.

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Allowing us to collectively
explore new ways

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to approach treatment and care.
The agenda in this meeting

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is packed with world-class
educational content

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featuring renowned experts,
who will share their insights

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on both the latest
scientific development

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and real-world
patient experiences.

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Our sessions will include
interactive panels,

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where clinicians, researchers,
and patients will come together

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to discuss the future of sickle
cell management and treatment,

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focusing on both cutting
edge innovations,

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and the everyday challenges

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that are associated
with this disorder.

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We are especially grateful
for the partnership

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between the NHLBI and
the University of West Indies

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and the Sickle Cell Unit.

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This collaboration which
continues to grow and thrive,

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underscores the global
nature of our work.

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Particularly in regions where
sickle cell disease is endemic.

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Together we can address
not only the scientific

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and clinical aspects
of this disease,

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but also the social and
systemic barriers to its care.

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In closing, I want to emphasis

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the importance of
this conference,

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not just as a forum
for scientific exchange,

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but as a source of hope
for the sickle cell community.

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It's through events like these
where we come together,

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share knowledge, and
build collaborations,

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that we make tangible
progress toward a world

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where sickle cell disease
will no longer impose

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the significant burden
that it does today.

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I want to thank all of you for
your attendance of this meeting,

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your dedication to the cause,

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and I look forward to the
engaging discussions,

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and the invaluable insights that
will ensue from this conference.

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Let's make the next two days,
impactful, innovative,

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and inspiring for the future
of sickle cell disease

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care and research.

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I wish all of you
a great conference.

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Swee Lay Thein: Can you hear me?
Yes, I can hear myself now.

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[laughs] Good
morning, every one,

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and my own very warm welcome
to beautiful Jamacia,

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please enjoy the
scenery, in the breaks,

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not right now [laughs].
[laughter]

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Swee Lay Thein: I really want
to thank our two leaders,

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Minerva Thame the
head of her school,

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head of her faculty
of medical sciences

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and Ric Child from NHLBI

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for the inspiring,
very hopeful words,

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and words of collaboration
and engagement

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in moving the field forward.

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Sorry for the delay, so we will
get straight into session one.

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And to start us off --

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by the way if you
do the QR code,

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it will take you straight
to the booklet, okay,

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with the whole agenda as well as
detailed bios of our speakers.

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So please take a
moment to do that

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and the QR codes are
all around the room,

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and on your tables probably.

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We'll go right into
our first speaker.

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00:13:26,773 --> 00:13:28,775
Welcoming, Dr. Daniel Dexter,

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who is training in
pediatric hematology.

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And is currently
a hematology registrar

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at King's College
hospital, London, UK.

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He will speak to us
on point of care testing,

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the promise and the
rule. Welcome, Daniel.

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Daniel Dexter: Thank
you everybody.

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00:13:49,295 --> 00:13:53,366
Female Speaker: [inaudible]
King's College [inaudible]

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00:13:53,366 --> 00:13:54,634
Daniel Dexter: Yes,
sorry, just started.

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00:13:54,634 --> 00:13:55,835
Female Speaker: [inaudible]
[laughter]

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00:13:55,835 --> 00:13:59,305
Daniel Dexter: Oh, okay.
Is there a clicker?

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00:14:01,641 --> 00:14:03,543
Thank you, very much.

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00:14:03,543 --> 00:14:09,248
Female Speaker:
[inaudible] point.

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00:14:09,248 --> 00:14:10,717
Male Speaker: To the back

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00:14:10,717 --> 00:14:11,984
Female Speaker: To the back

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00:14:11,984 --> 00:14:13,820
Daniel Dexter: Okay,
technical issues,

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00:14:13,820 --> 00:14:17,824
we'll learn from my mistakes.
I just wanted to start by

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00:14:17,824 --> 00:14:19,358
thanking the organizers
for inviting me here.

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00:14:19,358 --> 00:14:22,028
It's a really great honor
to speak in front of all of you.

247
00:14:22,028 --> 00:14:25,064
I follow many of your research,
throughout my career.

248
00:14:25,665 --> 00:14:27,767
I have been invited
to -- my name's Dan,

249
00:14:27,767 --> 00:14:30,503
and I'm a hematology registrar
at King's in London.

250
00:14:30,503 --> 00:14:33,339
And I have been invited to speak
about exciting new developments

251
00:14:33,339 --> 00:14:35,875
in point of care testing
for sickle cell disease.

252
00:14:37,877 --> 00:14:41,714
Oh, it's working, so
the global prevalence

253
00:14:41,714 --> 00:14:43,683
of sickle cell
disorders is growing.

254
00:14:43,683 --> 00:14:45,084
Last year in
the [unintelligible]

255
00:14:45,084 --> 00:14:46,819
the global burden
of disease study,

256
00:14:47,453 --> 00:14:51,891
which drew upon all available
national epidemiological data

257
00:14:51,891 --> 00:14:53,860
for sickle cell determined

258
00:14:53,860 --> 00:14:55,828
that upwards of half
a million infants

259
00:14:55,828 --> 00:14:58,631
will be born every year
with sickle cell disorder.

260
00:14:58,631 --> 00:15:00,900
Estimates do vary,
and Fred Peal's [phonetic sp]

261
00:15:00,900 --> 00:15:05,037
work estimates around
300,000 to 350,000 infants

262
00:15:05,037 --> 00:15:07,373
will be born with sickle cell
anemia each year.

263
00:15:08,207 --> 00:15:11,778
Yet presently most infants
born with a sickle cell disorder

264
00:15:11,778 --> 00:15:13,613
will not obtain
a formal diagnosis.

265
00:15:14,313 --> 00:15:16,282
Access to diagnosis
is most scarce,

266
00:15:16,282 --> 00:15:18,518
where the burden
of disease is greatest.

267
00:15:18,518 --> 00:15:20,353
This is also true
of access to care.

268
00:15:21,187 --> 00:15:23,422
As we know, the majority
of sickle cell disease

269
00:15:23,422 --> 00:15:26,025
affected births occur
in Sub-Saharan Africa

270
00:15:26,559 --> 00:15:29,295
where health resource
scarcity is most acute.

271
00:15:29,295 --> 00:15:33,399
This is reflected in profound
inequities of disease outcomes.

272
00:15:34,367 --> 00:15:35,835
The true extent
of sickle cell's

273
00:15:35,835 --> 00:15:37,436
impact on individuals
in societies

274
00:15:37,436 --> 00:15:39,972
is hidden with
in global health statistics.

275
00:15:39,972 --> 00:15:42,341
The map on the left
of the screen from the GBD,

276
00:15:43,276 --> 00:15:45,978
oh, I've gone backwards, sorry,

277
00:15:45,978 --> 00:15:49,282
GBD study illustrates
the significant discrepancy

278
00:15:49,282 --> 00:15:51,884
of available data
for SCD by country.

279
00:15:53,152 --> 00:15:55,988
Data capture is really lucky
in remote rural settings,

280
00:15:55,988 --> 00:15:58,591
especial in Africa,
much more granular in detail

281
00:15:58,591 --> 00:16:00,493
than better resourced nations.

282
00:16:01,527 --> 00:16:04,297
Sickle cell is comparative
neglected disease for funding,

283
00:16:04,297 --> 00:16:06,699
when you think about the funding
for cystic fibrosis

284
00:16:06,699 --> 00:16:10,703
in high income countries
or HIV in low-income settings.

285
00:16:11,304 --> 00:16:13,306
What we do know is that
sickle cell is a major

286
00:16:13,306 --> 00:16:16,142
and underestimated cause
of early childhood mortality,

287
00:16:16,142 --> 00:16:18,344
and it places a huge burden
on health resources

288
00:16:18,344 --> 00:16:19,712
in low-income settings.

289
00:16:19,712 --> 00:16:22,114
The demand for screening
has never been greater.

290
00:16:23,749 --> 00:16:27,420
Oops, sorry, did you click? Oop.

291
00:16:31,357 --> 00:16:32,925
So why do we want to screen?

292
00:16:32,925 --> 00:16:34,927
Well, early diagnosis
acts as the gateway

293
00:16:34,927 --> 00:16:37,263
to timely and lifesaving
interventions.

294
00:16:37,263 --> 00:16:38,497
The seminole [phonetic sp]

295
00:16:38,497 --> 00:16:41,067
Jamaican Cohort Study,
as was mentioned earlier,

296
00:16:41,601 --> 00:16:43,569
demonstrated the impact
of early diagnosis

297
00:16:43,569 --> 00:16:45,504
when twinned
to low-cost interventions

298
00:16:45,504 --> 00:16:47,273
such as parental counselling
and [unintelligible]

299
00:16:47,273 --> 00:16:49,342
prophylaxes in achieving
a reduction

300
00:16:49,342 --> 00:16:51,143
in childhood mortality.

301
00:16:51,143 --> 00:16:52,945
In recent decades,
we have seen the development

302
00:16:52,945 --> 00:16:54,614
of national newborn
screening programs

303
00:16:54,614 --> 00:16:57,183
across North America, Europe
and also in Brazil.

304
00:16:57,817 --> 00:17:00,152
These sizable
linguistical endeavors,

305
00:17:00,152 --> 00:17:04,357
benefit from economies of scale,
and timely identification,

306
00:17:04,357 --> 00:17:07,560
and enrollment of positive
infants into comprehensive care,

307
00:17:07,560 --> 00:17:09,962
has transformed
the prognosis of infants

308
00:17:09,962 --> 00:17:12,064
born with the disease.

309
00:17:12,064 --> 00:17:14,667
In the UK, sickle cell
is the most common test

310
00:17:14,667 --> 00:17:17,169
that we screen for on
the newborn screening program.

311
00:17:17,169 --> 00:17:20,006
Effecting roughly one and two
and a half thousand births.

312
00:17:21,207 --> 00:17:23,075
Ninety-nine percent
of our children in the UK

313
00:17:23,075 --> 00:17:25,511
with sickle cell disease
reach adulthood.

314
00:17:25,511 --> 00:17:27,713
Just last year, France
has moved from a targeted

315
00:17:27,713 --> 00:17:29,415
to a universal
screening approach.

316
00:17:30,983 --> 00:17:33,753
We have the tools, to not
just impact mortality,

317
00:17:33,753 --> 00:17:35,254
but also support a better life

318
00:17:35,254 --> 00:17:37,423
for those born with
sickle cell everywhere.

319
00:17:37,957 --> 00:17:40,860
Comprehensive care
goes beyond prophylaxes

320
00:17:40,860 --> 00:17:42,228
and reactive measures.

321
00:17:42,228 --> 00:17:44,864
Hydroxyurea, so you say urea,
we say carbalites

322
00:17:44,864 --> 00:17:46,098
[phonetic sp]

323
00:17:46,098 --> 00:17:47,633
continues to
demonstrate the ability

324
00:17:47,633 --> 00:17:49,835
to effectively modify disease,

325
00:17:49,835 --> 00:17:53,105
reduce complications,
and improve prognosis.

326
00:17:53,105 --> 00:17:55,408
Ground breaking studies,
such as the Reach Studies,

327
00:17:55,408 --> 00:17:56,842
conducted in Africa,

328
00:17:56,842 --> 00:17:59,745
demonstrated that it's safe and
effective in limited resource

329
00:17:59,745 --> 00:18:02,014
settings with malaria
aminesity [phonetic sp].

330
00:18:02,014 --> 00:18:04,684
This includes using
the maximum dosing strategy,

331
00:18:04,684 --> 00:18:06,285
which achieved best outcomes.

332
00:18:06,786 --> 00:18:08,888
Yet as we enter
the era of gene therapy,

333
00:18:08,888 --> 00:18:10,923
and cure, potentially;

334
00:18:10,923 --> 00:18:12,858
diagnosis is still
inaccessible to most,

335
00:18:12,858 --> 00:18:15,061
which represents
a tragic missed opportunity

336
00:18:15,561 --> 00:18:17,463
to avoid countless
preventable deaths.

337
00:18:18,230 --> 00:18:19,498
Over the past 30 years,

338
00:18:19,498 --> 00:18:21,767
pioneering newborn
screening programs

339
00:18:21,767 --> 00:18:23,603
in the Caribbean and Africa

340
00:18:23,603 --> 00:18:25,004
have made significant
achievements

341
00:18:25,004 --> 00:18:27,306
in demonstrating the
feasibility of screening.

342
00:18:28,074 --> 00:18:30,009
Kumasi, the garden
city in Ghana,

343
00:18:30,009 --> 00:18:34,113
was the first African country
to establish a pilot program.

344
00:18:35,081 --> 00:18:37,616
Most pilots operate using a
centralized laboratory approach,

345
00:18:37,616 --> 00:18:40,319
which is reliant on
laboratory-based techniques,

346
00:18:40,319 --> 00:18:42,054
but these programs have
supported to development

347
00:18:42,054 --> 00:18:43,856
of national
reference laboratories

348
00:18:43,856 --> 00:18:46,192
and epidemiological data
registries.

349
00:18:46,792 --> 00:18:48,661
And they have also been
able to link diagnosis

350
00:18:48,661 --> 00:18:50,262
to comprehensive care.

351
00:18:53,165 --> 00:18:57,536
But what has prevented the scale
up of this pilot programs?

352
00:18:58,371 --> 00:19:00,373
It's to do with the
challenges inherent

353
00:19:00,373 --> 00:19:02,642
with the centralized
screening approach.

354
00:19:02,642 --> 00:19:05,745
Laboratory best
techniques can be costly,

355
00:19:06,312 --> 00:19:08,547
they require highly
trained personnel,

356
00:19:08,547 --> 00:19:10,216
and in the experience
of the Uganda pilot,

357
00:19:10,216 --> 00:19:12,184
that was the most
costly factor of all,

358
00:19:13,085 --> 00:19:15,187
steady supply of
re-agency consumables,

359
00:19:15,187 --> 00:19:18,224
and access to technical support
when they break down.

360
00:19:18,224 --> 00:19:21,027
Also, there is significant
linguistical barriers.

361
00:19:21,594 --> 00:19:23,663
How do you reach all of the
infants that you need to screen,

362
00:19:23,663 --> 00:19:25,598
especially in rural settings?

363
00:19:25,598 --> 00:19:28,100
How do you maintain
these extensive sample

364
00:19:28,100 --> 00:19:30,002
transport networks?

365
00:19:30,002 --> 00:19:32,538
Also, when diagnosis is not
at the point of care,

366
00:19:33,839 --> 00:19:35,074
there is a long
turn around time.

367
00:19:35,074 --> 00:19:38,944
How do you contact trace
your positive infants?

368
00:19:39,812 --> 00:19:43,182
It can be hard sometimes
to reach rural addresses,

369
00:19:43,182 --> 00:19:45,785
and this has led to a
significant loss to follow up.

370
00:19:47,253 --> 00:19:49,488
Other barriers
include data management,

371
00:19:49,488 --> 00:19:52,491
the ethical obligation
to link diagnosis to care,

372
00:19:53,059 --> 00:19:54,794
and not be underestimated,

373
00:19:54,794 --> 00:19:57,063
the acceptability of
screening to communities.

374
00:19:57,997 --> 00:20:00,966
In Uganda they screen
each child for $4.67,

375
00:20:02,034 --> 00:20:04,437
but the turn around time
is around 16 days.

376
00:20:04,970 --> 00:20:06,872
And the Angolan
experience is around

377
00:20:06,872 --> 00:20:09,375
just over 50 percent of
their screened positive infants

378
00:20:09,375 --> 00:20:11,444
were actually enrolled
in comprehensive care.

379
00:20:11,444 --> 00:20:13,946
So, there's a big
missed opportunity.

380
00:20:16,215 --> 00:20:17,516
Just a brief overview

381
00:20:17,516 --> 00:20:19,685
of the conventional
screening diagnostics.

382
00:20:20,219 --> 00:20:22,888
They are mostly electric
phoretic techniques,

383
00:20:22,888 --> 00:20:26,759
but you do have notable
mentions for high-output fancy

384
00:20:26,759 --> 00:20:28,227
things like Tandem
Mass Spectrometry,

385
00:20:28,227 --> 00:20:30,129
and a greater role
for DNA sequencing.

386
00:20:31,464 --> 00:20:34,600
I'll briefly touch upon the two
most commonly used ones,

387
00:20:34,600 --> 00:20:36,535
which are HPLC,

388
00:20:36,535 --> 00:20:39,305
which is a qualitive as
well as a quantitive assay.

389
00:20:40,973 --> 00:20:43,109
It requires highly
trained operators;

390
00:20:43,109 --> 00:20:45,211
it's rapid in high output.

391
00:20:45,211 --> 00:20:47,213
It can help rationalize
ambiguous results,

392
00:20:47,213 --> 00:20:48,414
by other methods.

393
00:20:48,414 --> 00:20:51,917
But it requires availability of
sophisticated technical supports

394
00:20:51,917 --> 00:20:54,453
and lots of consumables.
It's relatively expensive.

395
00:20:55,087 --> 00:20:56,455
By contrast isoelectric

396
00:20:56,455 --> 00:20:59,024
focusing which you can see
here with the nice bands,

397
00:20:59,925 --> 00:21:02,495
is a semiautomated mostly
qualitive measure.

398
00:21:03,596 --> 00:21:05,030
We can run lots
of large volumes,

399
00:21:05,030 --> 00:21:09,168
and it's cheaper than HPLC.
And this is the modality

400
00:21:09,168 --> 00:21:12,605
that many of the pilot
programs use in Africa.

401
00:21:14,507 --> 00:21:17,009
So why are we excited
about point of care testing?

402
00:21:17,777 --> 00:21:20,045
For over a decade now
these point-of-care test

403
00:21:20,045 --> 00:21:23,382
have been highly impactful
in HIV and malaria programming.

404
00:21:24,083 --> 00:21:27,787
They provide diagnosis
at the point of need,

405
00:21:29,588 --> 00:21:32,258
and they essentially
eliminate turnaround times,

406
00:21:32,825 --> 00:21:34,527
and impact loss to follow up.

407
00:21:34,527 --> 00:21:37,496
They are ideally suited
to the primary care setting.

408
00:21:37,496 --> 00:21:39,798
And I know there is
lots of movement now

409
00:21:39,798 --> 00:21:42,134
looking to see if
sickle cell screening

410
00:21:42,134 --> 00:21:44,870
can be optimized for the
immunization clinic setting,

411
00:21:44,870 --> 00:21:47,473
much less busy than
the crazy environment

412
00:21:47,473 --> 00:21:48,741
of a post-natal ward.

413
00:21:48,741 --> 00:21:51,544
And there is a very high uptake
of immunization in countries

414
00:21:51,544 --> 00:21:53,412
with a high sickle cell burden.

415
00:21:53,412 --> 00:21:56,315
Also, the persistence of
fetal hemoglobin permits

416
00:21:56,315 --> 00:21:58,584
an extended window for
screening of sickle cell

417
00:21:58,584 --> 00:22:01,253
compared to other congenital
metabolic disorders,

418
00:22:01,253 --> 00:22:03,656
which need treatment in
the first weeks of life.

419
00:22:04,390 --> 00:22:07,593
Point of care test tend to
be user friendly, portable,

420
00:22:07,593 --> 00:22:09,028
and people are
familiar with them,

421
00:22:09,028 --> 00:22:10,963
think pregnancy test,
now COVID test.

422
00:22:11,797 --> 00:22:14,266
Affordability is a
big big factor here.

423
00:22:15,201 --> 00:22:18,270
Now, financial mechanism

424
00:22:18,270 --> 00:22:21,574
such as the global funds
pool procurement mechanism,

425
00:22:21,574 --> 00:22:23,876
we have a single buyer,
a tough negotiate --

426
00:22:23,876 --> 00:22:27,813
they can negotiate hard with
companies to get very low cost

427
00:22:28,414 --> 00:22:31,850
for the HIV/malaria test,
down to 30 cents a test.

428
00:22:31,850 --> 00:22:35,988
And then order millions of the
tests on sustainable supply,

429
00:22:35,988 --> 00:22:37,990
which they distribute
to their partners.

430
00:22:38,524 --> 00:22:39,758
This is the kind of thing

431
00:22:39,758 --> 00:22:42,061
which can make testing
more affordable.

432
00:22:44,563 --> 00:22:47,533
Just a brief nod to
"this old chestnut."

433
00:22:47,533 --> 00:22:48,767
[laughter]

434
00:22:48,767 --> 00:22:51,470
Daniel Dexter: Sickle cell
solubility test still in use,

435
00:22:51,470 --> 00:22:53,105
not confined to history,
just to say,

436
00:22:53,105 --> 00:22:56,275
it's not appropriate
for newborn screening,

437
00:22:56,275 --> 00:22:59,345
because it's inaccurate in large
amounts of hemoglobin F,

438
00:22:59,912 --> 00:23:02,314
and doesn't differentiate
between sickle and trait,

439
00:23:02,314 --> 00:23:04,083
but it's still widely used.

440
00:23:06,285 --> 00:23:10,823
So, just to talk about some
sickle cell specific challenges

441
00:23:10,823 --> 00:23:12,424
that point of care
test manufacturers

442
00:23:12,424 --> 00:23:14,260
and designers
need to overcome.

443
00:23:14,860 --> 00:23:18,397
It's really important that
any test can differentiate

444
00:23:18,397 --> 00:23:19,999
between disease and trait.

445
00:23:20,933 --> 00:23:23,002
The tests need to be
accurate in samples

446
00:23:23,002 --> 00:23:25,971
with high amounts of
hemoglobin F. Ninety percent

447
00:23:25,971 --> 00:23:29,174
of a fetal blood sample
might constitute hemoglobin F.

448
00:23:30,009 --> 00:23:31,710
The need to have low
limits of detection

449
00:23:31,710 --> 00:23:34,146
for the hemoglobin variance
they are looking for.

450
00:23:34,847 --> 00:23:38,183
So, at least under 10 percent
for hemoglobins S, C, and A,

451
00:23:39,618 --> 00:23:41,287
ideally, around 4-5 percent.

452
00:23:42,521 --> 00:23:44,923
We should praise
the ability of test

453
00:23:44,923 --> 00:23:46,692
to diagnosis compound
heterozygotes

454
00:23:46,692 --> 00:23:48,827
or at least recognize
the limitations

455
00:23:48,827 --> 00:23:50,329
if they cannot do that,

456
00:23:50,329 --> 00:23:52,464
as I will talk about
in a couple of slides.

457
00:23:53,165 --> 00:23:55,768
Also, in transfused patients

458
00:23:55,768 --> 00:23:58,537
if you have very low limits
of detection of HbA,

459
00:23:58,537 --> 00:24:01,407
and you're a transfused patient
with sickle cell disease.

460
00:24:01,974 --> 00:24:03,876
And you have one of these tests,

461
00:24:03,876 --> 00:24:07,012
they might test as having trait
rather than disease.

462
00:24:12,384 --> 00:24:14,019
So, lateral flow immunoassays:
this is an antibody-based format

463
00:24:14,019 --> 00:24:15,287
which has been the workhorse

464
00:24:15,287 --> 00:24:17,823
of point of care
modalities for years.

465
00:24:19,658 --> 00:24:20,993
The qualities
of these antibodies

466
00:24:20,993 --> 00:24:24,596
is essential to determining
the accuracy of the test [sic].

467
00:24:24,596 --> 00:24:25,998
The use of monoclonal antibodies

468
00:24:25,998 --> 00:24:27,900
tends to lead to a
more specific test.

469
00:24:28,467 --> 00:24:30,402
Also in the manufacture process,

470
00:24:30,402 --> 00:24:31,837
the amount of antibody
in the device

471
00:24:31,837 --> 00:24:34,306
is very important
to the test performance.

472
00:24:34,306 --> 00:24:36,575
They can be competitive
or sandwich formats,

473
00:24:36,575 --> 00:24:39,678
which will affect how they are
read in terms of their results.

474
00:24:40,179 --> 00:24:43,215
But they are self-contained,
disposable, cheap, and familiar.

475
00:24:44,049 --> 00:24:46,118
They require no electricity,

476
00:24:46,118 --> 00:24:47,853
and we have two well
established test

477
00:24:47,853 --> 00:24:49,621
for sickle cell disease
with [unintelligible]

478
00:24:49,621 --> 00:24:50,856
in this format.

479
00:24:50,856 --> 00:24:53,959
And as I will talk about,
there is a tidal wave of test

480
00:24:53,959 --> 00:24:57,529
coming from India
in the same format.

481
00:25:01,100 --> 00:25:06,872
So, in the process of updating
my previous paper on this topic,

482
00:25:07,439 --> 00:25:10,109
I was looking at the --

483
00:25:10,109 --> 00:25:11,777
the Indian government
announced last year

484
00:25:11,777 --> 00:25:13,979
that they want to try an
eliminate sickle cell disease.

485
00:25:13,979 --> 00:25:15,581
India has the third
highest incident

486
00:25:15,581 --> 00:25:17,416
of sickle cell
births every year.

487
00:25:17,416 --> 00:25:20,085
They want to screen 17 million
people in three years,

488
00:25:20,719 --> 00:25:22,554
mostly in primary care.

489
00:25:22,554 --> 00:25:25,424
And Indian industry
has responded by producing

490
00:25:26,125 --> 00:25:29,528
15 new point-of-care tests
in the last year alone,

491
00:25:29,528 --> 00:25:31,797
which have all been
validated by the government.

492
00:25:31,797 --> 00:25:33,399
They're commercially available.

493
00:25:34,333 --> 00:25:36,068
Now, I got sent this document

494
00:25:36,068 --> 00:25:38,604
from the Indian Council
of Medical Research,

495
00:25:38,604 --> 00:25:40,305
and my eyeballs almost
fell out of my head.

496
00:25:40,305 --> 00:25:41,507
Because I thought
that we only had

497
00:25:41,507 --> 00:25:44,042
two actual lateral flow tests,
but there are so many now.

498
00:25:44,042 --> 00:25:46,345
I must say that the validation
processes are quite opaque,

499
00:25:46,345 --> 00:25:47,613
and I haven't been able to find

500
00:25:47,613 --> 00:25:50,249
any peer review of the
validation processes.

501
00:25:50,249 --> 00:25:51,917
I think there has been
some [unintelligible]

502
00:25:51,917 --> 00:25:53,685
report that some of the tests
aren't performing

503
00:25:53,685 --> 00:25:56,722
as well in the field as well
as the validation data suggest.

504
00:25:57,723 --> 00:25:59,391
So, the Indian FDA,

505
00:25:59,391 --> 00:26:02,428
the CDSCO has reclassified
sickle cell diagnostics

506
00:26:02,428 --> 00:26:03,662
to a more stringent class;

507
00:26:03,662 --> 00:26:05,597
I think to get some
oversight on this.

508
00:26:06,298 --> 00:26:09,334
However, this kind of
industry activity

509
00:26:09,334 --> 00:26:11,937
might lead to a lowered
cost of tests in the future.

510
00:26:14,773 --> 00:26:19,211
So, just a quick run through
of HemoType and SickleSCAN.

511
00:26:19,211 --> 00:26:24,817
HemoType is a competitive
lateral flow test

512
00:26:24,817 --> 00:26:27,986
which means the result is read,

513
00:26:27,986 --> 00:26:31,323
a positive result is discerned
by the absence of a line.

514
00:26:32,524 --> 00:26:33,759
It's performed in five steps.

515
00:26:33,759 --> 00:26:36,595
It's a monoclonal based test,
no buffers required.

516
00:26:36,595 --> 00:26:39,498
You put some blood into some
water into a test tube,

517
00:26:39,498 --> 00:26:42,901
insert the test strip,
wait for ten minutes,

518
00:26:42,901 --> 00:26:44,369
don't undercook it
or overcook it,

519
00:26:44,369 --> 00:26:46,071
because it can
affect the reading,

520
00:26:48,040 --> 00:26:51,076
and it gives you result.

521
00:26:51,076 --> 00:26:56,615
The Sickle SCAN test is a very
neat test in a cartridge format.

522
00:26:56,615 --> 00:26:58,851
It is a sandwich type
polyclonal test,

523
00:26:58,851 --> 00:27:01,420
polyclonal antibodies.
It does require a buffer,

524
00:27:01,420 --> 00:27:04,389
but that's applied in the pack
and it runs in five minutes.

525
00:27:06,692 --> 00:27:10,996
This is just a
screen, just a graph,

526
00:27:10,996 --> 00:27:14,299
just to show you some basic
technical details of the test.

527
00:27:14,299 --> 00:27:18,003
I've included an Indian test
just out of interest.

528
00:27:18,003 --> 00:27:19,605
It was a rather
arbitrary choice.

529
00:27:19,605 --> 00:27:20,772
SickleCheck were
the only company

530
00:27:20,772 --> 00:27:23,075
that responded to my
deluge of emails,

531
00:27:23,075 --> 00:27:24,943
I was trying to see
what's out there.

532
00:27:26,445 --> 00:27:29,882
So, they detect
hemoglobin A, S, and C,

533
00:27:29,882 --> 00:27:31,250
but not in the case
of SickleCheck,

534
00:27:31,250 --> 00:27:32,484
which only has A and S,

535
00:27:32,484 --> 00:27:35,854
so, its geographical
relevance is less.

536
00:27:35,854 --> 00:27:37,723
They have low
limits of detection.

537
00:27:37,723 --> 00:27:40,792
The cost is the
crucial factor here

538
00:27:40,792 --> 00:27:44,763
and HemoType is the cheapest,
retailing for $1.49.

539
00:27:45,764 --> 00:27:48,667
They are stable at room
temperature for up to two years.

540
00:27:51,203 --> 00:27:53,238
Field validation: these
are accurate test,

541
00:27:53,238 --> 00:27:54,606
and there were a
number of studies

542
00:27:54,606 --> 00:27:57,409
with HemoType and SickleSCAN
in peer review literature,

543
00:27:57,409 --> 00:28:00,679
of course many settings in Asia,
and Africa, and the Caribbean.

544
00:28:03,515 --> 00:28:06,451
I won't talk about the
most exciting studies,

545
00:28:06,451 --> 00:28:07,853
that I'll leave to
other speakers today.

546
00:28:07,853 --> 00:28:10,522
But they have been validated
in newborn screening frame work

547
00:28:10,522 --> 00:28:12,858
as effective tools,
which is very exciting.

548
00:28:18,196 --> 00:28:19,398
Operational issues:
There was some concern

549
00:28:19,398 --> 00:28:21,133
about the
counterintuitive readings

550
00:28:21,133 --> 00:28:23,969
of a HemoType test,
but the papers,

551
00:28:23,969 --> 00:28:26,505
and the experience of users
with actual training

552
00:28:26,505 --> 00:28:28,473
and retraining of
healthcare workers,

553
00:28:29,474 --> 00:28:31,476
these issues
can be ironed out.

554
00:28:31,476 --> 00:28:34,146
The SickleSCAN has a
relatively weak HbA band,

555
00:28:35,447 --> 00:28:37,082
but in general the
experience with these tests

556
00:28:37,082 --> 00:28:41,019
are effective and
impactful [sic].

557
00:28:41,019 --> 00:28:42,421
One more thing about HemoType

558
00:28:42,421 --> 00:28:43,889
is that you can use it not
just with whole blood,

559
00:28:43,889 --> 00:28:47,292
but with debiased samples
too, try blood spots.

560
00:28:48,794 --> 00:28:50,729
Now for something
completely different,

561
00:28:52,264 --> 00:28:54,232
the Hemex Gazelle is
a completely different class

562
00:28:54,232 --> 00:28:56,101
of point-of-care-test.

563
00:28:56,101 --> 00:28:59,805
It can be described as
a portable laboratory of sorts,

564
00:28:59,805 --> 00:29:01,607
an electro
phoresies in a box.

565
00:29:02,874 --> 00:29:04,676
It relies on a
disposable cartridge,

566
00:29:05,744 --> 00:29:06,979
which you insert into a box

567
00:29:06,979 --> 00:29:08,614
which retails in
Africa for $800.

568
00:29:09,214 --> 00:29:11,016
The cartridges cost
$2.00 to $2.50;

569
00:29:11,750 --> 00:29:14,119
within the cartridge
you have a cellulose acid

570
00:29:14,119 --> 00:29:17,055
gel electro phoresies
with two electrodes either end.

571
00:29:17,689 --> 00:29:21,326
You put it into the box
and apply the blood sample,

572
00:29:21,893 --> 00:29:24,296
and as the electrical
field is applied

573
00:29:24,296 --> 00:29:25,764
and the hemoglobins migrate,

574
00:29:25,764 --> 00:29:29,134
and image acquisition system
takes lots of pictures.

575
00:29:29,134 --> 00:29:31,036
Which is read by a very
sophisticated software,

576
00:29:31,036 --> 00:29:33,171
and the software is
the crucial thing here,

577
00:29:33,171 --> 00:29:37,376
because it's permitted expanding
capability of the device

578
00:29:37,376 --> 00:29:38,977
with different iterations of it.

579
00:29:39,678 --> 00:29:44,149
It detects not only A, S, and C,
but hemoglobin F, E, and A2.

580
00:29:46,018 --> 00:29:50,022
The results can be uploaded
to a cloud application

581
00:29:50,022 --> 00:29:51,757
which is good for
data management.

582
00:29:51,757 --> 00:29:53,992
And they have neat printout
which can be emailed to patients

583
00:29:53,992 --> 00:29:56,061
or saved on your computer.

584
00:29:56,061 --> 00:29:58,530
Its battery run or plugged
into electrical means.

585
00:29:58,530 --> 00:30:03,702
It takes one sample; it can run
one sample every 10 minutes.

586
00:30:03,702 --> 00:30:05,737
It is also multi-model,

587
00:30:05,737 --> 00:30:08,173
and the company
provide cartridges

588
00:30:08,173 --> 00:30:10,175
which can diagnosis malaria,

589
00:30:10,709 --> 00:30:13,645
and they are looking in
to developing tests

590
00:30:13,645 --> 00:30:15,480
for full blood count too.

591
00:30:16,915 --> 00:30:19,685
The device is said to able
to last around 10,000 tests,

592
00:30:19,685 --> 00:30:21,286
so 3 to 5 years.

593
00:30:24,022 --> 00:30:26,291
It's performed
well in the field.

594
00:30:27,159 --> 00:30:30,162
The initial iteration was not
suitable for newborn screening,

595
00:30:30,162 --> 00:30:33,799
because the limit of detection
for hemoglobin S was too high.

596
00:30:33,799 --> 00:30:35,033
But a software update

597
00:30:35,033 --> 00:30:37,135
means now the limits
of detection is 4 percent,

598
00:30:37,135 --> 00:30:40,739
and it is validated and accurate
for newborn screening

599
00:30:40,739 --> 00:30:44,476
for sickle cell disease.
There was some issues I think,

600
00:30:44,476 --> 00:30:46,445
with some normal
variant hemoglobin

601
00:30:46,445 --> 00:30:47,646
being misdiagnosed as trait,

602
00:30:47,646 --> 00:30:51,717
but that just confirms why we
need a different methodology

603
00:30:51,717 --> 00:30:54,453
as a confirmatory test [sic].

604
00:30:54,453 --> 00:30:57,622
This test also enables
beta thalassemia diagnosis

605
00:30:57,622 --> 00:30:59,825
because a software
update enables

606
00:30:59,825 --> 00:31:01,560
hemoglobin A2 quantification.

607
00:31:02,194 --> 00:31:06,665
So, it's quite a powerful
potential in this device.

608
00:31:08,867 --> 00:31:11,203
And this device
is too been validated

609
00:31:11,203 --> 00:31:14,239
in a newborn screening
framework in Ghana.

610
00:31:17,943 --> 00:31:23,782
Oh wait, have we been
there already?

611
00:31:23,782 --> 00:31:26,218
Oh, sorry, I think, I've
got an extra slide here.

612
00:31:29,187 --> 00:31:31,323
One last thing,
you can use this device

613
00:31:31,323 --> 00:31:33,792
for hemoglobin F quantification.

614
00:31:33,792 --> 00:31:37,429
It has been used
in this regard in Ghana

615
00:31:37,429 --> 00:31:39,798
as well as Epostraeha
[phonetic sp].

616
00:31:39,798 --> 00:31:41,733
This means you can use it

617
00:31:41,733 --> 00:31:45,504
for sophisticated
Hydroxyurea monitoring.

618
00:31:46,104 --> 00:31:47,472
Can't we get our patients up?

619
00:31:47,472 --> 00:31:49,474
We can really monitor
how effective treatments

620
00:31:49,474 --> 00:31:50,675
is going for them [sic].

621
00:31:50,675 --> 00:31:53,178
There is a brief
slide on licensing.

622
00:31:54,446 --> 00:31:57,783
They're licensed across much
of Africa, Asia, and Europe.

623
00:31:59,785 --> 00:32:02,187
I just wanted to mention
the reassured criteria.

624
00:32:03,021 --> 00:32:07,125
These are the WHO checklist
really to help us access

625
00:32:07,125 --> 00:32:11,897
what the suitability
of new point-of-care tests

626
00:32:11,897 --> 00:32:14,065
following com settings
as they come online.

627
00:32:14,065 --> 00:32:16,368
And I think, without
laboring the point,

628
00:32:16,368 --> 00:32:18,470
the tests that I have
discussed today,

629
00:32:18,470 --> 00:32:20,539
do fulfill most
of these criteria.

630
00:32:26,745 --> 00:32:29,014
However, questions
remain as to the impact

631
00:32:29,014 --> 00:32:32,150
that these tests will have.
Am I on the right screen?

632
00:32:32,150 --> 00:32:35,554
I am. The affordable
tests threshold

633
00:32:36,454 --> 00:32:38,657
is likely to vary country
to country.

634
00:32:38,657 --> 00:32:41,960
Currently, the tests
cost $1.50 to $2.50 each,

635
00:32:41,960 --> 00:32:44,462
but in reality, this is unlikely
to reflect the true costs

636
00:32:44,462 --> 00:32:47,165
when tariffs and distribution
fees are factored in.

637
00:32:47,165 --> 00:32:51,136
In which invariable raise
costs by several orders.

638
00:32:52,237 --> 00:32:54,339
In my opinion, we need to reduce
the costs of these test

639
00:32:54,339 --> 00:32:55,941
to achieve true affordability.

640
00:32:56,474 --> 00:32:59,244
And we need to find ways
of maintaining a steady supply

641
00:32:59,244 --> 00:33:00,812
of them to get them
into the hands of the people

642
00:33:00,812 --> 00:33:02,414
that want to use them.

643
00:33:03,014 --> 00:33:05,684
Reference laboratories
with goal standing tests

644
00:33:05,684 --> 00:33:07,819
remain important for
confirmatory testing,

645
00:33:08,386 --> 00:33:10,722
but also for developing
lab infrastructure

646
00:33:10,722 --> 00:33:12,524
and rationalizing
ambiguous results.

647
00:33:13,191 --> 00:33:16,528
There might come a point
where lab-based methods

648
00:33:16,528 --> 00:33:19,898
can make efficiencies
in low-income countries

649
00:33:19,898 --> 00:33:21,266
that help them achieve
cost efficiency

650
00:33:21,266 --> 00:33:22,868
through economies of scale.

651
00:33:24,035 --> 00:33:27,305
Furthermore, we need to
identify optimal strategies

652
00:33:27,305 --> 00:33:29,374
for how we use these
point-of-care tests.

653
00:33:30,709 --> 00:33:32,878
As the market becomes
more competitive,

654
00:33:32,878 --> 00:33:35,714
there will be validation
and regulatory issues

655
00:33:35,714 --> 00:33:37,616
to ensure that only
the effective and quality test

656
00:33:37,616 --> 00:33:39,618
get licensed.

657
00:33:39,618 --> 00:33:41,786
Other wide issued central
to effective screening,

658
00:33:41,786 --> 00:33:44,289
require addressing
as well including,

659
00:33:44,289 --> 00:33:45,991
how to manage
and potentiate data,

660
00:33:46,691 --> 00:33:48,860
ensuring diagnosis
is linked to care,

661
00:33:48,860 --> 00:33:52,764
and building acceptability
of screening in communities.

662
00:33:54,232 --> 00:33:57,636
Strategies to Reduce
Cost: I am not sure

663
00:33:57,636 --> 00:33:59,437
what's happened to
that image there.

664
00:34:00,672 --> 00:34:03,074
So, in effort to
funding strategy

665
00:34:03,074 --> 00:34:04,910
such as the pool
procurement mechanism

666
00:34:04,910 --> 00:34:06,811
would be very helpful here.

667
00:34:06,811 --> 00:34:10,215
ASH, with their Cancer program
are using a similar method

668
00:34:10,215 --> 00:34:12,350
to buy up millions
of point-of-care tests

669
00:34:12,350 --> 00:34:13,585
which they then distribute

670
00:34:13,585 --> 00:34:16,821
to their partner
countries and labs.

671
00:34:18,056 --> 00:34:20,058
It also guarantees
a sustainable supply.

672
00:34:21,927 --> 00:34:23,528
We need more government support,

673
00:34:24,896 --> 00:34:26,565
not just for
budgetary commitments

674
00:34:26,565 --> 00:34:28,300
to sickle cell programs,

675
00:34:28,300 --> 00:34:31,937
but also can we get them
to waive taxes on resources

676
00:34:31,937 --> 00:34:34,005
used in sickle cell
care and screening?

677
00:34:34,005 --> 00:34:37,842
To reduce the tariffs
that we have to pay

678
00:34:37,842 --> 00:34:39,744
to import these devices.

679
00:34:40,712 --> 00:34:43,281
And maybe it's a
bit pie in the sky,

680
00:34:43,281 --> 00:34:46,251
but if we could manufacture
point-of-care tests

681
00:34:46,251 --> 00:34:47,519
and hydroxy carmide

682
00:34:47,519 --> 00:34:50,956
[phonetic sp]in Africa and then
coordinate their distribution

683
00:34:50,956 --> 00:34:53,391
throughout the continent
to reduce the cost.

684
00:34:55,493 --> 00:34:58,897
So, in summary, we have
available affective

685
00:34:58,897 --> 00:35:00,098
point-of-care test.

686
00:35:00,098 --> 00:35:02,534
They're commercially
available; we can buy them.

687
00:35:02,534 --> 00:35:03,969
They are affective;
and they're accurate,

688
00:35:03,969 --> 00:35:05,570
and people are using them.

689
00:35:06,204 --> 00:35:08,873
The gazelle device is quite
a sophisticated test,

690
00:35:08,873 --> 00:35:13,311
which can add more than just
screening, has clinical utility.

691
00:35:13,979 --> 00:35:15,680
There are more
products emerging,

692
00:35:16,781 --> 00:35:18,483
and these point-of-care tests

693
00:35:18,483 --> 00:35:19,884
are likely to be
highly effective tools

694
00:35:19,884 --> 00:35:23,655
that supports our efforts to
increase access to diagnosis.

695
00:35:23,655 --> 00:35:25,290
However, challenges
still remain:

696
00:35:26,725 --> 00:35:28,860
We need to achieve
true affordability;

697
00:35:28,860 --> 00:35:30,629
We need to ensure quality;

698
00:35:30,629 --> 00:35:32,197
And there is still
a very important role

699
00:35:32,197 --> 00:35:35,166
for lab-based approaches
as the goal standards.

700
00:35:37,102 --> 00:35:40,171
Thank you very much.
I hope I kept to time.

701
00:35:41,473 --> 00:35:47,645
[applause]

702
00:35:47,645 --> 00:35:49,247
Swee Lay Thein: Don't go,
you might have questions.

703
00:35:49,247 --> 00:35:50,482
Daniel Dexter: Oh, sorry, yeah.

704
00:35:50,482 --> 00:35:52,717
Swee Lay Thein: [laughs] Thank
you, so much, Dr. Dexter.

705
00:35:52,717 --> 00:35:54,319
We'll open the floor
for questions,

706
00:35:54,319 --> 00:35:56,721
and as you get your
questions together,

707
00:35:57,822 --> 00:36:02,861
I'm also wanting to say, welcome
to our zoom participants.

708
00:36:02,861 --> 00:36:05,730
And please do go ahead and
post your questions in zoom

709
00:36:05,730 --> 00:36:07,332
as well if you have one.

710
00:36:09,467 --> 00:36:14,706
Anything for Dr. Dexter.
You were so clear.

711
00:36:14,706 --> 00:36:15,974
Female Speaker: Can
I ask one question?

712
00:36:15,974 --> 00:36:17,242
Daniel Dexter: Sure.

713
00:36:17,242 --> 00:36:19,878
Female Speaker: So, near the end
from what you're telling me,

714
00:36:19,878 --> 00:36:22,080
the Gazelle might
be an [inaudible]

715
00:36:22,080 --> 00:36:23,681
investment in the long term.

716
00:36:25,216 --> 00:36:28,953
It cost a bit more to start with
but then for the

717
00:36:30,455 --> 00:36:37,062
[inaudible] that you can make.

718
00:36:37,662 --> 00:36:41,066
Daniel Dexter: I think,
it is very setting specific.

719
00:36:41,699 --> 00:36:44,569
I think the capabilities
of a device like Gazelle

720
00:36:44,569 --> 00:36:48,440
might add so much to rural
or rather remote locations

721
00:36:48,440 --> 00:36:53,978
which might not have access
to quantification for example.

722
00:36:55,647 --> 00:36:58,616
It's still relatively low cost
compared to other measures.

723
00:36:59,350 --> 00:37:00,752
I think it also --

724
00:37:00,752 --> 00:37:02,854
I know that some people
are using HemoType

725
00:37:03,655 --> 00:37:08,326
as a mass screening tool. I
think, it comes down to cost

726
00:37:08,326 --> 00:37:13,364
and what other resources
are available in each setting.

727
00:37:13,364 --> 00:37:16,301
But certainly, I think
the multi-model dynamic

728
00:37:16,301 --> 00:37:17,902
of this device is really useful.

729
00:37:18,503 --> 00:37:20,939
Female Speaker: So,
in the end, probably,

730
00:37:20,939 --> 00:37:23,308
you might want to
[unintelligible]

731
00:37:23,308 --> 00:37:26,411
level screening which is cheap
that can reach many people,

732
00:37:27,112 --> 00:37:30,515
and then if there are
any [unintelligible]

733
00:37:30,515 --> 00:37:31,783
you could send [unintelligible]

734
00:37:31,783 --> 00:37:34,652
maybe. Is that correct?
It might be a good option.

735
00:37:34,652 --> 00:37:36,254
Daniel Dexter: Yes,
I think that's --

736
00:37:37,155 --> 00:37:38,456
I think that probably
speakers today

737
00:37:38,456 --> 00:37:42,327
will talk about platforms
exactly like this.

738
00:37:42,327 --> 00:37:43,828
So, using the
point-of-care tests

739
00:37:43,828 --> 00:37:45,430
as the initial screening tool,

740
00:37:46,131 --> 00:37:52,036
and then having confirmatory
testing in a lab-based assay.

741
00:37:52,036 --> 00:37:55,540
However, a mentor of
mine in Uganda, is --

742
00:37:55,540 --> 00:37:57,242
they are doing the
complete opposite.

743
00:37:57,242 --> 00:38:00,712
They're relying on
IEF for screening,

744
00:38:00,712 --> 00:38:04,649
and they use HemoType in their
lab as a confirmatory test.

745
00:38:05,383 --> 00:38:10,588
So, I think, when I talked about
identifying optimal strategies,

746
00:38:10,588 --> 00:38:12,490
I think, they're still
being investigated,

747
00:38:12,490 --> 00:38:16,027
but definitely point-of-care
tests allow flexibility

748
00:38:18,062 --> 00:38:19,697
for screening
and diagnostic options

749
00:38:19,697 --> 00:38:21,299
which is incredibly useful.

750
00:38:26,104 --> 00:38:27,806
Male Speaker: Great
review, thank you.

751
00:38:27,806 --> 00:38:30,975
Could you talk a little bit
more about the heterogeneity

752
00:38:31,976 --> 00:38:34,812
of the different programs
at least throughout Africa?

753
00:38:34,812 --> 00:38:38,216
You alluded to it a little bit
among different countries.

754
00:38:38,216 --> 00:38:40,685
But I guess the other thing
related to affordability,

755
00:38:40,685 --> 00:38:42,453
so, two questions really is:

756
00:38:42,453 --> 00:38:45,356
The differences that you've seen
in terms of strategies

757
00:38:45,356 --> 00:38:49,494
among different nations
where you've studied [sic].

758
00:38:49,494 --> 00:38:51,830
But also, the issue
not only of affordability,

759
00:38:51,830 --> 00:38:53,865
but the distribution.
Right, distribution,

760
00:38:53,865 --> 00:38:55,867
how do you get these tests
from one place to another?

761
00:38:55,867 --> 00:38:59,270
The real practical aspects of
scalability and distributions.

762
00:39:00,438 --> 00:39:02,173
Daniel Dexter: Great questions.

763
00:39:02,173 --> 00:39:04,175
I know that other speakers
today will be talking

764
00:39:04,175 --> 00:39:07,078
to these specifics
of this amazing programs,

765
00:39:07,745 --> 00:39:10,615
inspiring programs across Africa
and the Caribbean now.

766
00:39:13,084 --> 00:39:15,353
So, what I can tell you
is that there is

767
00:39:15,353 --> 00:39:17,855
a mixture of
lab-based screening.

768
00:39:17,855 --> 00:39:21,092
So, in Uganda they
coopted existing

769
00:39:21,092 --> 00:39:24,429
sample transport linguistics
for HIV/EID

770
00:39:24,429 --> 00:39:26,965
that U.S. funded
for over 15 years.

771
00:39:27,565 --> 00:39:30,201
And they were already
transporting dry blood spots

772
00:39:31,102 --> 00:39:35,907
for HIV screening,
and Cincinnati sponsored

773
00:39:35,907 --> 00:39:37,442
just taking another
one of those blood spots,

774
00:39:37,442 --> 00:39:41,980
and they set up a IEF lab
in comparlor [phonetic sp]

775
00:39:41,980 --> 00:39:44,816
and they screened
over 100,000 infants

776
00:39:44,816 --> 00:39:46,084
within two or three years;

777
00:39:46,084 --> 00:39:47,952
and they developed some
incredible [unintelligible]

778
00:39:47,952 --> 00:39:49,821
data as a result.
And they used that data

779
00:39:49,821 --> 00:39:51,656
to develop a targeted
screening strategy

780
00:39:51,656 --> 00:39:53,758
to folk in the
high burden areas.

781
00:39:53,758 --> 00:39:58,863
Other places, however,
they still struggle.

782
00:39:58,863 --> 00:40:00,798
They couldn't scale it
to the whole country.

783
00:40:00,798 --> 00:40:03,334
I know that's -- other speakers
today will talk about today

784
00:40:03,334 --> 00:40:05,303
what they are doing in
places like Nigeria,

785
00:40:05,303 --> 00:40:07,972
using point-of-care
testing in the Caribbean.

786
00:40:08,673 --> 00:40:10,375
So, I think there are
a lots of things going on,

787
00:40:10,375 --> 00:40:14,445
but I think we are going to move
away from strictly lab-based

788
00:40:14,445 --> 00:40:18,182
to a kind of hybrid approach,
incorporating point of care.

789
00:40:18,716 --> 00:40:20,919
And the finally questions
about distribution,

790
00:40:20,919 --> 00:40:22,353
maybe we need a
businessman up here,

791
00:40:22,353 --> 00:40:24,422
but I think there is one place,

792
00:40:24,422 --> 00:40:28,192
one pharmaceutical is
the only company in Africa

793
00:40:28,192 --> 00:40:32,230
which makes hydroxycarminide
[phonetic sp].

794
00:40:32,230 --> 00:40:35,133
I am not sure, but I think
if we could work out ways

795
00:40:35,133 --> 00:40:37,135
to manufacture
and coordinate distribution;

796
00:40:37,135 --> 00:40:39,070
it would be incredible
powerful to reduce

797
00:40:39,070 --> 00:40:42,907
cost and increase access
to test and medication.

798
00:40:43,474 --> 00:40:48,613
[applause]

799
00:40:48,613 --> 00:40:51,582
Swee Lay Thein: Thank you so
much for setting the stage

800
00:40:51,582 --> 00:40:56,587
for the next part of the
session on screening

801
00:40:56,587 --> 00:40:58,222
for sickle cell disease,

802
00:40:58,222 --> 00:41:05,163
and for this new on screening
updates part of our agenda,

803
00:41:05,697 --> 00:41:07,832
we have four panel speakers.

804
00:41:07,832 --> 00:41:09,901
I'm going to introduce
them one by one

805
00:41:09,901 --> 00:41:13,204
and invite them to come
and sit at the table here.

806
00:41:13,705 --> 00:41:15,640
So, I will introduce
all four at one time,

807
00:41:15,640 --> 00:41:19,310
so you will not be interrupted
by me when they do their talks.

808
00:41:19,310 --> 00:41:23,281
And the questions and discussion
for this part of the panel

809
00:41:23,281 --> 00:41:25,516
will be at the end
of the fore talks.

810
00:41:25,516 --> 00:41:26,718
So, first off,

811
00:41:26,718 --> 00:41:29,020
we start with Jennifer
Knight-Madden Knight-Madden.

812
00:41:29,020 --> 00:41:30,788
Jennifer Knight-Madden
is a professor

813
00:41:30,788 --> 00:41:33,024
of pediatric pulmonology
and clinic research

814
00:41:33,024 --> 00:41:35,026
at the Sickle Cell Unit
in Jamacia.

815
00:41:35,026 --> 00:41:36,894
She's an examiner
and member of specialty

816
00:41:36,894 --> 00:41:40,198
board of the Childhood
and Adolescent Health at UWI

817
00:41:40,198 --> 00:41:43,301
as well as honorary
consultant

818
00:41:43,301 --> 00:41:46,504
at the University Hospital
of the West Indies,

819
00:41:46,504 --> 00:41:49,674
and she will speak to newborn
screening in the Caribbean.

820
00:41:50,708 --> 00:41:54,946
Next up, we have Dr. Obi Nnodu,
she is a professor of hematology

821
00:41:54,946 --> 00:41:57,048
and blood transfusion
and director

822
00:41:57,048 --> 00:41:59,717
for the Center of Excellence
for Sickle Cell Disease Research

823
00:41:59,717 --> 00:42:03,988
and Training at the University
of Abuja in Nigeria,

824
00:42:03,988 --> 00:42:08,893
and Obi will
speak to Africa.

825
00:42:11,763 --> 00:42:15,233
Third speaker is Dr.
Raffaella Colombatti.

826
00:42:16,067 --> 00:42:18,669
She is a pediatric
hematologist, oncologist

827
00:42:18,669 --> 00:42:21,205
at the Pediatric Hematology
Oncology Unit Azienda Ospedale

828
00:42:21,205 --> 00:42:25,376
in the University
of Padova, Italy,

829
00:42:26,010 --> 00:42:28,646
and she will speak to
well-resourced countries,

830
00:42:28,646 --> 00:42:30,248
mainly Europe.

831
00:42:30,815 --> 00:42:34,819
And our fourth speaker will be
Dr. Ana Cristina Silva-Pinto.

832
00:42:34,819 --> 00:42:36,354
She is currently the coordinator

833
00:42:36,354 --> 00:42:38,089
of the Sickle Cell
Disease Program

834
00:42:38,089 --> 00:42:41,692
at General Hospital of Ribeiriao
Preto medical school

835
00:42:41,692 --> 00:42:45,530
University of Sao Paulo,
and she will speak to all low-,

836
00:42:45,530 --> 00:42:49,200
or middle-income countries
mainly India and Brazil.

837
00:42:49,200 --> 00:42:53,104
So, let's go and I'll
invite the speakers,

838
00:42:53,104 --> 00:42:55,740
one after the other
to make their presentations.

839
00:42:55,740 --> 00:42:58,242
Phase three, we don't
have the monitor screen

840
00:42:58,242 --> 00:43:00,845
up for some reason
please. Thank you.

841
00:43:03,781 --> 00:43:10,721
Jennifer Knight-Madden:
Good morning,

842
00:43:10,721 --> 00:43:12,757
if you could bring up
my slides, please.

843
00:43:12,757 --> 00:43:16,093
Welcome everybody to Jamacia,
I know there are several people

844
00:43:16,093 --> 00:43:17,962
who are here for the
very first time,

845
00:43:17,962 --> 00:43:20,531
and we are delighted
to have you with us.

846
00:43:22,400 --> 00:43:25,770
So today, I am actually kicking
off with the Caribbean,

847
00:43:26,604 --> 00:43:28,940
and we do need the monitor.

848
00:43:31,275 --> 00:43:35,413
Next slide please, oh clicker.

849
00:43:38,950 --> 00:43:45,089
Okay so, the Caribbean is home
to about 44 million people,

850
00:43:45,089 --> 00:43:47,825
and we have the
highest incidents

851
00:43:47,825 --> 00:43:49,994
outside of West Africa.

852
00:43:50,595 --> 00:43:53,531
But you know, when Daniel
talked about context

853
00:43:53,531 --> 00:43:55,600
that's really an issue.

854
00:43:55,600 --> 00:44:02,006
So, we have -- okay,
we are going to talk

855
00:44:02,006 --> 00:44:03,841
about different aspects
of the Caribbean,

856
00:44:03,841 --> 00:44:06,744
including the
geography, the history,

857
00:44:06,744 --> 00:44:08,946
the politics, the economics,

858
00:44:09,480 --> 00:44:12,884
because all of these
things actually impact

859
00:44:12,884 --> 00:44:16,354
on what is the best
choice in terms

860
00:44:16,354 --> 00:44:18,122
of what you're going to use.

861
00:44:18,789 --> 00:44:25,463
So, I -- [inaudible]

862
00:44:25,463 --> 00:44:26,664
Jennifer Knight-Madden:
Can I what?

863
00:44:26,664 --> 00:44:27,965
[inaudible]

864
00:44:27,965 --> 00:44:29,267
Jennifer Knight-Madden:
Oh, it's over there.

865
00:44:29,267 --> 00:44:31,502
Okay, well everybody
look over there.

866
00:44:31,502 --> 00:44:33,337
[laughter]

867
00:44:33,337 --> 00:44:35,206
Jennifer Knight-Madden:
Right, so,

868
00:44:35,206 --> 00:44:37,975
we are going to look
at newborn screening

869
00:44:37,975 --> 00:44:40,811
from the point of view
of countries that have started,

870
00:44:40,811 --> 00:44:42,914
had pilots, whether
they're screening now,

871
00:44:43,581 --> 00:44:46,517
and the methods,
and the choices,

872
00:44:47,051 --> 00:44:49,954
and then of course the
poll in collaboration.

873
00:44:52,256 --> 00:44:56,160
So, the Caribbean,
it sits between

874
00:44:57,495 --> 00:44:58,963
North America,
South America,

875
00:44:58,963 --> 00:45:01,132
and Central America
in the Caribbean Sea.

876
00:45:01,933 --> 00:45:03,868
So, some places
on the internet will tell you

877
00:45:03,868 --> 00:45:05,970
that there are
several hundred islands,

878
00:45:05,970 --> 00:45:07,738
and if you go
to the Bohemian side,

879
00:45:07,738 --> 00:45:10,241
they say they have
several hundred islands;

880
00:45:10,241 --> 00:45:12,343
and then you add
in the keys and everything

881
00:45:12,343 --> 00:45:14,345
and you can see that geography
is a real problem.

882
00:45:14,345 --> 00:45:15,580
[laughter]

883
00:45:15,580 --> 00:45:17,615
Jennifer Knight-Madden: Because
you can't drive,

884
00:45:18,216 --> 00:45:23,254
you have to fly, right.
So even in the small islands,

885
00:45:23,254 --> 00:45:24,822
you know, the leeward
and windward island,

886
00:45:24,822 --> 00:45:27,858
it's an issue getting samples
from place to place.

887
00:45:29,927 --> 00:45:33,030
So that determines
what makes the most sense.

888
00:45:34,532 --> 00:45:38,202
Now, just to tell you
that the yellow is Spanish.

889
00:45:39,403 --> 00:45:41,505
All right, so the main land
around us apart

890
00:45:41,505 --> 00:45:45,610
from the U.S. and Belize,
they mostly speak Spanish.

891
00:45:46,310 --> 00:45:48,412
French is spoken in Haiti,

892
00:45:48,946 --> 00:45:51,816
which alone, accounts for
a quarter of our population.

893
00:45:52,483 --> 00:45:55,152
And in the overseas
territories of France,

894
00:45:56,153 --> 00:45:58,356
and so that's actually
quite interesting

895
00:45:58,356 --> 00:46:01,192
because of the politics
and economics the best care

896
00:46:01,826 --> 00:46:04,595
is in the French part
of the Caribbean.

897
00:46:04,595 --> 00:46:06,964
And the worst care
is in the French part

898
00:46:06,964 --> 00:46:10,868
of the Caribbean,
because Haiti as I'll show you

899
00:46:10,868 --> 00:46:15,373
is actually the only low-middle
income country in the Caribbean.

900
00:46:15,373 --> 00:46:17,008
I find this quite shocking.

901
00:46:17,008 --> 00:46:20,745
But all of those circles are
actually high-income countries.

902
00:46:21,679 --> 00:46:23,247
But, you know,
when I looked at

903
00:46:23,247 --> 00:46:25,750
what the definition
of high-income countries is,

904
00:46:26,917 --> 00:46:28,586
if you add up the income
of the country,

905
00:46:28,586 --> 00:46:31,389
divide it by the population,
so per capitol,

906
00:46:31,389 --> 00:46:33,190
and it's more than $14.000.00

907
00:46:33,190 --> 00:46:34,725
U.S. dollars,
then you're high income.

908
00:46:34,725 --> 00:46:35,926
[talking simultaneously]

909
00:46:35,926 --> 00:46:37,128
Jennifer Knight-Madden: But no,

910
00:46:37,128 --> 00:46:38,863
you compare that
to say the U.S.,

911
00:46:38,863 --> 00:46:40,898
which is like $60,000
or $70,000, right?

912
00:46:41,999 --> 00:46:43,200
You can see that,

913
00:46:43,200 --> 00:46:46,404
and to be low income you have
to be less than like $1500.

914
00:46:46,404 --> 00:46:51,308
I mean, whoa, yeah so,
Haiti is lower middle income,

915
00:46:51,308 --> 00:46:54,011
and the ones that don't have
circles like us,

916
00:46:54,011 --> 00:46:56,080
were upper middle income.
And this is important,

917
00:46:56,080 --> 00:46:58,282
because it means that we can't
get some of the grants,

918
00:46:58,282 --> 00:47:00,985
we can't publish
in some of the journals

919
00:47:00,985 --> 00:47:03,421
without paying
and all of that kind of stuff.

920
00:47:03,421 --> 00:47:04,789
So, economics does matter.

921
00:47:04,789 --> 00:47:06,691
The other thing is
with the languages,

922
00:47:07,358 --> 00:47:09,593
in sickle cell
we all talk to each other.

923
00:47:09,593 --> 00:47:11,128
Not very common
in the Caribbean,

924
00:47:11,128 --> 00:47:13,164
but in sickle cell it works.

925
00:47:13,164 --> 00:47:14,865
And in transport,
I can't see it from here,

926
00:47:14,865 --> 00:47:16,701
because I am old
and I have great hair.

927
00:47:16,701 --> 00:47:18,402
[talking simultaneously]

928
00:47:18,402 --> 00:47:19,770
Jennifer Knight-Madden: We're
back, oh, thank God.

929
00:47:19,770 --> 00:47:21,005
[laughter]

930
00:47:21,005 --> 00:47:23,574
Jennifer Knight-Madden: So,
okay, so $123.00 U.S. dollar

931
00:47:23,574 --> 00:47:25,943
to send a one-pound envelope

932
00:47:25,943 --> 00:47:27,678
between countries
in the Caribbean.

933
00:47:28,713 --> 00:47:32,016
So, if did that once a week,
you're looking at $6,400

934
00:47:32,016 --> 00:47:35,252
that might not sound like a lot,
but that's for one pound.

935
00:47:35,986 --> 00:47:38,155
Suppose it's more
than that, right?

936
00:47:38,155 --> 00:47:40,991
The cost goes up and up,
so you have to think about that.

937
00:47:42,193 --> 00:47:44,962
Now in terms
of collaboration, COSCA

938
00:47:44,962 --> 00:47:47,031
which is the
Caribbean Association

939
00:47:47,031 --> 00:47:49,266
of Sickle Cell Associates
is a patient group,

940
00:47:49,800 --> 00:47:53,370
and they used to be very active
and they had sort of died out,

941
00:47:53,370 --> 00:47:54,839
but they are trying
to come back again.

942
00:47:54,839 --> 00:47:57,374
So, we're going to try
and encourage that,

943
00:47:57,374 --> 00:48:00,111
because politicians
listen to people

944
00:48:00,111 --> 00:48:02,246
more than they listen
to scientist.

945
00:48:02,246 --> 00:48:06,217
So, we need our patients
to advocate for changes.

946
00:48:06,884 --> 00:48:08,352
The SickKid Caribbean Initiative

947
00:48:08,352 --> 00:48:10,621
that with Cancer
as well as hematology

948
00:48:11,188 --> 00:48:14,725
and we've kind of moved on
to a different phase,

949
00:48:14,725 --> 00:48:17,928
but they did train
two hema[phonetic sp]

950
00:48:17,928 --> 00:48:19,797
pediatric hema
people in Jamacia

951
00:48:19,797 --> 00:48:21,232
and a few more
around the region.

952
00:48:21,232 --> 00:48:23,200
So, it was, you know,
very helpful.

953
00:48:23,801 --> 00:48:27,438
CAREST as I said goes across
Spanish, French, English,

954
00:48:27,438 --> 00:48:29,106
so the president
is from Guadeloupe,

955
00:48:29,106 --> 00:48:32,143
I am a vice president
and our other vice president

956
00:48:32,143 --> 00:48:35,412
is from Cuba,
and we've done screening;

957
00:48:35,412 --> 00:48:38,015
we've done pilots
in several countries.

958
00:48:39,350 --> 00:48:42,019
Now we have a working group
which so far

959
00:48:42,019 --> 00:48:43,621
has the countries involved.

960
00:48:44,188 --> 00:48:46,190
And we can learn
a lot from this.

961
00:48:46,190 --> 00:48:49,093
The first thing is that
most places have pilot data.

962
00:48:49,894 --> 00:48:51,562
And that's mostly
through CAREST,

963
00:48:53,397 --> 00:48:55,466
expect for Belize
where we're trying.

964
00:48:55,466 --> 00:48:59,537
But the problem is that people
got pilot data when CAREST,

965
00:48:59,537 --> 00:49:02,473
we subsidized, but then
they haven't continued it,

966
00:49:02,473 --> 00:49:04,708
because the government
hasn't taken it on.

967
00:49:04,708 --> 00:49:06,777
So, in all those countries
there are champions

968
00:49:06,777 --> 00:49:08,779
trying to get this done,

969
00:49:08,779 --> 00:49:11,015
but what I want you
to also look at is;

970
00:49:11,015 --> 00:49:14,018
if you accept what is on the
internet in terms of population,

971
00:49:14,018 --> 00:49:15,820
birth rate and estimated births

972
00:49:15,820 --> 00:49:18,255
as well as the incidents
of sickle cell disease.

973
00:49:18,255 --> 00:49:19,590
You can see in some countries

974
00:49:19,590 --> 00:49:21,258
you might have
six births a year,

975
00:49:21,926 --> 00:49:25,830
as against Haiti
where you have close to 2,000.

976
00:49:25,830 --> 00:49:27,231
So, we need
to work on Haiti,

977
00:49:27,231 --> 00:49:29,567
because they are not
screening universally.

978
00:49:30,367 --> 00:49:34,371
Right, but in a place
where you have 1400 births

979
00:49:34,939 --> 00:49:37,675
that's going to affect which
kind of machine you can use.

980
00:49:37,675 --> 00:49:39,310
You don't need HPLC for sure.

981
00:49:41,378 --> 00:49:42,847
So, which one
are we going to use?

982
00:49:42,847 --> 00:49:45,683
The choices depend
on many factors.

983
00:49:45,683 --> 00:49:47,785
So, is it something
you do at the bed side?

984
00:49:47,785 --> 00:49:49,019
Do we have time?

985
00:49:49,019 --> 00:49:51,121
Is it something where you take
it from the [unintelligible]

986
00:49:51,121 --> 00:49:55,259
natal unit to the lab
in the hospital and do it there?

987
00:49:56,460 --> 00:49:58,896
That may be helpful.
Is it quantitative?

988
00:49:59,496 --> 00:50:00,831
Do you have to
send it overseas?

989
00:50:00,831 --> 00:50:02,132
So, for most
of the small islands,

990
00:50:02,132 --> 00:50:03,834
you would have to
send it overseas.

991
00:50:03,834 --> 00:50:05,369
Can you upload the data?

992
00:50:05,369 --> 00:50:07,371
So, from a public health
point of view,

993
00:50:07,371 --> 00:50:12,343
you actually have a data base.
And what is the cost?

994
00:50:12,343 --> 00:50:15,813
We need to get the cost
locally for Hemotype S,C.

995
00:50:15,813 --> 00:50:19,483
That cost is for
20,000 tests, right,

996
00:50:19,483 --> 00:50:22,486
but you can see that were
talking about 8 and 10

997
00:50:22,486 --> 00:50:27,391
and up dollars per test, right.
And why is that?

998
00:50:27,391 --> 00:50:30,594
It is because we have to
bring it to the Caribbean, okay.

999
00:50:30,594 --> 00:50:32,296
So that makes a difference
and of course,

1000
00:50:32,296 --> 00:50:34,531
how soon you get the results.
If you get it right away,

1001
00:50:34,531 --> 00:50:36,233
you can get the child
into clinic,

1002
00:50:36,734 --> 00:50:39,303
whereas, HPLC, you have to go
find them afterwards.

1003
00:50:40,771 --> 00:50:43,173
So, the collaboration,
it depends on the willingness

1004
00:50:43,173 --> 00:50:45,943
of the vendors
to meet us partway as we heard.

1005
00:50:45,943 --> 00:50:49,179
It depends on the willingness
of the ministries of help

1006
00:50:49,179 --> 00:50:50,915
to make it a priority.

1007
00:50:50,915 --> 00:50:54,285
And we want to use Pan American
Health Organization mechanism,

1008
00:50:54,285 --> 00:50:58,255
where we could buy as a region
and then as a rotating fund

1009
00:50:58,255 --> 00:51:00,524
which would bring down
the cost for everybody.

1010
00:51:01,158 --> 00:51:04,595
So, there are many things that
we have to take into account,

1011
00:51:04,595 --> 00:51:06,563
but we need to get
the screening going,

1012
00:51:06,563 --> 00:51:11,835
because as we know it completely
changes mortality and morbidity.

1013
00:51:11,835 --> 00:51:15,072
So, in Jamacia now if you're
born, you're screened at birth,

1014
00:51:15,072 --> 00:51:17,708
you come to clinic,
the mortality is the same

1015
00:51:17,708 --> 00:51:19,543
whether they have sickle cell
or not.

1016
00:51:20,711 --> 00:51:22,980
And that's what we want
for all region.

1017
00:51:22,980 --> 00:51:26,016
That's what we want
for all world. Thank you.

1018
00:51:27,518 --> 00:51:43,334
[applause]

1019
00:51:43,867 --> 00:51:45,336
Obi Nnodu: Good morning,
everyone,

1020
00:51:45,336 --> 00:51:47,571
I want to thank the organizers

1021
00:51:47,571 --> 00:51:53,944
for giving me the opportunity
to make this presentation.

1022
00:51:53,944 --> 00:51:56,513
If you can please
pull up my slide.

1023
00:52:05,522 --> 00:52:07,424
I hope you haven't
started the timer,

1024
00:52:08,225 --> 00:52:10,361
because I've gone --
[laughs]

1025
00:52:10,361 --> 00:52:12,596
-- I've gone through
several [unintelligible]

1026
00:52:12,596 --> 00:52:15,733
and several seas to come
and give a 10-minute talk.

1027
00:52:16,300 --> 00:52:18,068
[laughter]

1028
00:52:18,068 --> 00:52:20,871
Obi Nnodu: Okay, so,
I use this outline,

1029
00:52:21,405 --> 00:52:24,742
and so the background
is like Daniel said

1030
00:52:24,742 --> 00:52:27,444
and also as Jennifer
has alluded.

1031
00:52:28,145 --> 00:52:31,882
We have a lot of pilot programs;
we have had in the past,

1032
00:52:31,882 --> 00:52:34,218
which we have not been able
to stay up

1033
00:52:34,785 --> 00:52:37,755
for the reasons that we have
heard, you know, today.

1034
00:52:40,124 --> 00:52:43,027
Another thing when,
I did the evaluation

1035
00:52:43,027 --> 00:52:48,265
or the assessment
of the WHO sickle cell strategy

1036
00:52:48,265 --> 00:52:51,735
across high budget countries,
one thing was very clear.

1037
00:52:51,735 --> 00:52:55,706
There was only one country
that had budgetary and location

1038
00:52:55,706 --> 00:52:57,508
for sickle cell programs

1039
00:52:58,175 --> 00:53:00,444
that is the newborn screen
in [unintelligible]

1040
00:53:00,444 --> 00:53:02,713
that [unintelligible]
republic

1041
00:53:02,713 --> 00:53:08,252
and think that's probably
because of [unintelligible]

1042
00:53:08,252 --> 00:53:10,054
means they work.

1043
00:53:10,054 --> 00:53:11,388
And so, the budgetary,

1044
00:53:11,388 --> 00:53:13,991
they are not making
budgetary at location

1045
00:53:13,991 --> 00:53:15,259
so when you have
[unintelligible]

1046
00:53:15,259 --> 00:53:17,461
coming to set up
pilot program

1047
00:53:17,461 --> 00:53:21,865
and that doesn't go too far
once the funding has gone.

1048
00:53:22,499 --> 00:53:25,469
In recent years,
we've had several initiatives

1049
00:53:26,537 --> 00:53:30,007
to address these problem
of pilot programs.

1050
00:53:30,707 --> 00:53:34,445
One is the American Society
of Hematology Consort Program.

1051
00:53:34,945 --> 00:53:37,414
The second one is
what you have heard now

1052
00:53:37,414 --> 00:53:40,217
about the use of point
of care technology

1053
00:53:40,217 --> 00:53:42,519
that is coming into stream

1054
00:53:42,519 --> 00:53:46,890
now across different counties
for newborn screening.

1055
00:53:46,890 --> 00:53:51,128
And then the third one is
the implementation science study

1056
00:53:51,662 --> 00:53:53,764
of the Sickle Pan
African Research

1057
00:53:53,764 --> 00:53:57,401
Consortium which you know
is the NIHI

1058
00:53:57,401 --> 00:54:01,271
infrastructure grant for sickle
cell disease in across Africa,

1059
00:54:01,271 --> 00:54:04,074
which I will talk about
a little bit later.

1060
00:54:04,074 --> 00:54:07,044
But for CONSA, CONSA
is a program

1061
00:54:07,044 --> 00:54:09,346
of the American Society
of Hematology

1062
00:54:09,980 --> 00:54:11,882
with African Hematology

1063
00:54:11,882 --> 00:54:15,719
to demonstrate the feasibility
of newborn screening

1064
00:54:15,719 --> 00:54:18,455
and early
therapeutic interventions

1065
00:54:18,455 --> 00:54:20,023
through African government.

1066
00:54:20,023 --> 00:54:24,228
In order to encourage them
to do newborn screening

1067
00:54:24,228 --> 00:54:26,830
because it's actually possible.

1068
00:54:26,830 --> 00:54:29,500
And we have seven
African countries,

1069
00:54:29,500 --> 00:54:31,101
as you can see on the map.

1070
00:54:32,736 --> 00:54:36,173
CONSA is led by
national coordinators

1071
00:54:36,173 --> 00:54:40,911
with designated clinical
catchment areas in each country.

1072
00:54:41,778 --> 00:54:45,315
And we have been
screening between 10,000

1073
00:54:45,315 --> 00:54:48,619
to 16,000 babies
a year per country.

1074
00:54:48,619 --> 00:54:53,023
And we have the babies
are expected

1075
00:54:53,023 --> 00:54:56,260
to go into
to follow-up care;

1076
00:54:56,260 --> 00:54:59,763
but we are finding,
as you can see the data later,

1077
00:54:59,763 --> 00:55:03,634
that this plan to enroll
the babies into follow-up care

1078
00:55:03,634 --> 00:55:06,136
has really not been
working to well.

1079
00:55:06,136 --> 00:55:10,274
Because only 42 percent
on average of the babies

1080
00:55:10,274 --> 00:55:11,575
are turning up.

1081
00:55:11,575 --> 00:55:14,077
And that's for
a number of reasons.

1082
00:55:15,012 --> 00:55:18,248
So, you screen babies, and they
disappear into the bush,

1083
00:55:18,248 --> 00:55:23,020
and you're not able
to meet up with your goal.

1084
00:55:24,321 --> 00:55:27,491
So, we have a trained
health care workers

1085
00:55:27,491 --> 00:55:29,960
on use of the protocol.

1086
00:55:29,960 --> 00:55:32,563
We have trained them
on the DBS collections,

1087
00:55:33,230 --> 00:55:37,601
ongoing training, retraining
on laboratory analysis,

1088
00:55:37,601 --> 00:55:39,836
using the [unintelligible]
platform,

1089
00:55:39,836 --> 00:55:42,773
as well as a quality insurance
processes [phonetic sp].

1090
00:55:42,773 --> 00:55:45,242
We are also training
the health care worker,

1091
00:55:45,242 --> 00:55:48,145
because it happens
that the CONSA countries

1092
00:55:48,145 --> 00:55:51,815
are also the Sickle Pan Africa
Research Consortium

1093
00:55:52,749 --> 00:55:54,851
have developed a uniform,

1094
00:55:54,851 --> 00:55:57,221
multi-level management
guidelines.

1095
00:55:57,221 --> 00:55:58,889
So, we are training
the healthcare workers

1096
00:55:58,889 --> 00:56:00,624
on the use of the guidelines.

1097
00:56:00,624 --> 00:56:03,627
And also, to know when
to refer the babies,

1098
00:56:03,627 --> 00:56:06,863
you know, for [unintelligible].

1099
00:56:06,863 --> 00:56:09,833
We are also finding out that
the mother's do not want

1100
00:56:09,833 --> 00:56:13,737
to go to do those big
pediatric sickle cell clinics

1101
00:56:13,737 --> 00:56:15,372
in [unintelligible] hospitals.

1102
00:56:15,372 --> 00:56:18,675
They prefer to stay at the
primary healthcare center.

1103
00:56:18,675 --> 00:56:21,845
Then we are also training
the families on education

1104
00:56:21,845 --> 00:56:25,816
and carrying out a community
sanitization and awareness.

1105
00:56:26,817 --> 00:56:29,286
So, these are some of the
things that we are doing,

1106
00:56:29,286 --> 00:56:31,655
but when we see the picture.

1107
00:56:31,655 --> 00:56:33,690
I will show you
pictures of Nigeria.

1108
00:56:33,690 --> 00:56:36,560
So, data quality is being
taken care of with

1109
00:56:36,560 --> 00:56:40,897
on site centralized training
to improve documentation,

1110
00:56:40,897 --> 00:56:42,399
sample collection,

1111
00:56:42,399 --> 00:56:46,870
also to ensure that the
samples are properly dried,

1112
00:56:46,870 --> 00:56:49,072
especially during
the rainy season.

1113
00:56:49,072 --> 00:56:50,507
They are stored properly

1114
00:56:50,507 --> 00:56:52,609
and they are sent
to the central laboratory.

1115
00:56:52,609 --> 00:56:56,046
We are also training the
models [phonetic sp]

1116
00:56:56,046 --> 00:56:57,814
on how to take care
of the babies.

1117
00:56:57,814 --> 00:57:00,584
We are training journalist
on sickle cell disease

1118
00:57:00,584 --> 00:57:03,153
so that they can
develop programs

1119
00:57:03,153 --> 00:57:04,788
through greater awareness.

1120
00:57:04,788 --> 00:57:08,258
We are doing community entry,
and then we are, you know,

1121
00:57:08,258 --> 00:57:10,627
involving the community,
going to the chiefs,

1122
00:57:10,627 --> 00:57:14,264
and getting them to send
the mothers for screening,

1123
00:57:14,264 --> 00:57:17,401
and also to make sure
that they encourage them

1124
00:57:17,401 --> 00:57:19,069
to come for
rudimentary to care.

1125
00:57:19,937 --> 00:57:22,472
Okay, thank you, so
our preliminary works

1126
00:57:22,472 --> 00:57:25,042
with the second one
is point of care,

1127
00:57:25,042 --> 00:57:27,010
and thank God that
Daniel has spoken

1128
00:57:27,010 --> 00:57:28,979
so I don't have
to say too much.

1129
00:57:28,979 --> 00:57:31,548
But our preliminary work
had demonstrated

1130
00:57:31,548 --> 00:57:35,585
high sensitivity and
specificity of point of care

1131
00:57:36,186 --> 00:57:38,822
even when applied to
newborn screening program.

1132
00:57:38,822 --> 00:57:40,791
Now you see the number
of publications

1133
00:57:40,791 --> 00:57:43,427
that have come as
a result of that.

1134
00:57:43,427 --> 00:57:45,996
So, the third one
is the initiative

1135
00:57:45,996 --> 00:57:47,531
of the Sickle Pan Africa

1136
00:57:47,531 --> 00:57:50,600
Research Consortium newborn
screening program

1137
00:57:50,600 --> 00:57:53,337
which is an implementation
of science-based program.

1138
00:57:53,337 --> 00:57:58,742
So, for this one
we have six countries,

1139
00:57:58,742 --> 00:58:05,115
and then in Nigeria
we have 25 sites for this NBS

1140
00:58:05,115 --> 00:58:09,086
in Pan African Consortium
meet program,

1141
00:58:09,086 --> 00:58:13,657
and then within the SFT
for CONSA we have 25 sites.

1142
00:58:13,657 --> 00:58:16,293
For we are working
across multiple sites

1143
00:58:16,293 --> 00:58:19,563
with all of these screening
programs that I'm talking about.

1144
00:58:20,364 --> 00:58:24,034
So within the context of Sickle
Pan African Research Consortium,

1145
00:58:24,835 --> 00:58:26,903
which you know is
an infrastructure grant,

1146
00:58:26,903 --> 00:58:29,873
we have a registry
of over 34,

1147
00:58:31,141 --> 00:58:34,211
000 sickle cell patients
in the disease registry,

1148
00:58:34,211 --> 00:58:38,682
and what we are using is for
this implementation site

1149
00:58:38,682 --> 00:58:42,652
we want to use the DBS
point of care test,

1150
00:58:42,652 --> 00:58:45,322
which we evaluated
and found to be feasible

1151
00:58:45,856 --> 00:58:49,292
to assess the performance
characteristics

1152
00:58:49,292 --> 00:58:54,364
of DBS POCT to IEF and HPLC,

1153
00:58:54,364 --> 00:58:58,034
and then to use
that the DBS POCT

1154
00:58:58,034 --> 00:59:01,104
to do a screening
within the countries;

1155
00:59:01,104 --> 00:59:03,173
and then to look at the context

1156
00:59:03,774 --> 00:59:05,742
through a focused
group discussion

1157
00:59:05,742 --> 00:59:07,544
and in depth interviews.

1158
00:59:07,544 --> 00:59:10,947
And then findings are
going to be very important

1159
00:59:10,947 --> 00:59:13,717
when we design the newborn
screening program

1160
00:59:13,717 --> 00:59:14,918
for the government

1161
00:59:14,918 --> 00:59:17,487
to be able to scale up
newborn screening programs.

1162
00:59:17,988 --> 00:59:19,389
And then we found out,

1163
00:59:19,389 --> 00:59:21,658
okay this is really not
the correct slide.

1164
00:59:21,658 --> 00:59:25,729
But with regard to patients,
parents and caregivers,

1165
00:59:25,729 --> 00:59:27,431
they like point of care,

1166
00:59:27,964 --> 00:59:32,002
and they prefer post-natal wards
and immunization clinics.

1167
00:59:32,002 --> 00:59:34,404
And they also want
to be educated.

1168
00:59:34,404 --> 00:59:36,106
With regards to policymaker,

1169
00:59:36,106 --> 00:59:38,742
they understand
all that is going on,

1170
00:59:38,742 --> 00:59:42,612
and they want us to be able
to have more education programs

1171
00:59:43,313 --> 00:59:47,451
for the [unintelligible]

1172
00:59:47,451 --> 00:59:48,819
and beyond [unintelligible]

1173
00:59:48,819 --> 00:59:53,356
that there should be
budgetary allocation

1174
00:59:53,356 --> 00:59:54,991
for sickle cell disease.

1175
00:59:54,991 --> 00:59:58,028
Then, for the part
of healthcare workers,

1176
00:59:58,028 --> 01:00:02,299
they understand newborn
screening should be included,

1177
01:00:02,299 --> 01:00:05,435
you know, to lead should be done
in order to lead

1178
01:00:05,435 --> 01:00:08,004
to better health outcomes
and improve,

1179
01:00:08,004 --> 01:00:11,041
they understand that.
But they are feeling that,

1180
01:00:11,041 --> 01:00:14,444
you know, having been spoilt
by the HIV screening program,

1181
01:00:14,444 --> 01:00:18,482
that the PEPFAR program,
that the mothers need incentive

1182
01:00:18,482 --> 01:00:20,617
to encourage them
to bring the babies,

1183
01:00:20,617 --> 01:00:23,353
and they are also
advocating for that.

1184
01:00:23,353 --> 01:00:25,188
I don't know
how that will happen,

1185
01:00:25,188 --> 01:00:28,558
but everybody understands
that collaboration

1186
01:00:28,558 --> 01:00:29,893
between community leaders

1187
01:00:29,893 --> 01:00:31,394
and all the different
stakeholders

1188
01:00:31,394 --> 01:00:34,564
are quite important
to be able to get this done.

1189
01:00:34,564 --> 01:00:37,934
So, in carrying out, you can see
that we've been doing newborn

1190
01:00:37,934 --> 01:00:40,203
screening
across multiple platforms,

1191
01:00:40,203 --> 01:00:43,707
across multiple institutions,
across different countries.

1192
01:00:44,241 --> 01:00:46,943
So, we find that interaction
with the stakeholders

1193
01:00:46,943 --> 01:00:48,278
is important

1194
01:00:48,278 --> 01:00:51,882
in order to understand the
peculiarities of the content,

1195
01:00:51,882 --> 01:00:56,219
because we can have an IEF
or HPLC-based program,

1196
01:00:56,219 --> 01:00:59,356
and you come and put it in
a context that it will not work.

1197
01:00:59,356 --> 01:01:02,058
Then these barriers
that we are identifying

1198
01:01:02,058 --> 01:01:05,128
are very important
for us to address,

1199
01:01:05,128 --> 01:01:08,665
as well as enablers
that we have identified

1200
01:01:08,665 --> 01:01:11,501
to scale up those enablers
in order to be able

1201
01:01:11,501 --> 01:01:14,237
to give universal
newborn screening.

1202
01:01:14,237 --> 01:01:17,073
We also feel that policymakers
should --

1203
01:01:17,707 --> 01:01:20,176
yeah, okay,
I'm going to stop soon.

1204
01:01:22,112 --> 01:01:25,782
So, we need more awareness
in order

1205
01:01:25,782 --> 01:01:30,153
to get everyone to know
that this screening exists,

1206
01:01:30,153 --> 01:01:32,522
and that's why we are
working with the media.

1207
01:01:32,522 --> 01:01:37,294
My personal opinion is that
after observing the challenges

1208
01:01:37,294 --> 01:01:40,397
across our countries
in our context,

1209
01:01:40,397 --> 01:01:43,533
I feel that IEF is good,

1210
01:01:43,533 --> 01:01:48,038
but if you're doing a program
that after 23,000 patients,

1211
01:01:48,038 --> 01:01:50,740
you're still getting
some false positives,

1212
01:01:50,740 --> 01:01:55,178
maybe we need to look
at some other alternatives.

1213
01:01:55,178 --> 01:01:58,615
Also, the observed kit failures
in some

1214
01:01:58,615 --> 01:02:04,254
POCTs require closer scrutiny.
We feel that a DBS point of care

1215
01:02:04,854 --> 01:02:06,957
gives us the opportunity
for confirmatory

1216
01:02:06,957 --> 01:02:11,361
testing by IEF or HPLC
with another point,

1217
01:02:11,361 --> 01:02:15,932
or with another point of care
testing, and molecular testing.

1218
01:02:15,932 --> 01:02:19,769
And molecular
POCTs could help to resolve,

1219
01:02:19,769 --> 01:02:24,040
you know, discordant results,
resolve diagnostic challenges,

1220
01:02:24,040 --> 01:02:28,211
and would be a natural evolution
in order to phenotype

1221
01:02:28,211 --> 01:02:32,782
the babies identified with SED
for subsequent follow-up

1222
01:02:32,782 --> 01:02:35,418
and for future
personalized medicine

1223
01:02:35,418 --> 01:02:37,053
and for novel treatments.

1224
01:02:37,053 --> 01:02:38,955
So, these are
my acknowledgments,

1225
01:02:38,955 --> 01:02:41,558
and I want to thank you,
and this is my team.

1226
01:02:41,558 --> 01:02:43,159
Thank you very much.

1227
01:02:44,094 --> 01:02:51,234
[applause]

1228
01:02:51,234 --> 01:02:52,602
Female Speaker: So,
first of all,

1229
01:02:52,602 --> 01:02:54,938
thank you for inviting me
to give the update

1230
01:02:54,938 --> 01:03:00,477
on the European setting,
and if you can put my slide on.

1231
01:03:03,046 --> 01:03:05,415
It's wonderful to be here
for the first time

1232
01:03:05,415 --> 01:03:07,917
and meeting many colleagues
and friends in person.

1233
01:03:09,486 --> 01:03:12,822
While I wait my slide, okay,
so what I --

1234
01:03:12,822 --> 01:03:16,026
these are my disclosures.
What I will present

1235
01:03:16,026 --> 01:03:18,995
are some of the European
setting specificities,

1236
01:03:18,995 --> 01:03:21,965
guidelines that we have
currently in European countries,

1237
01:03:21,965 --> 01:03:24,100
and the current situation
of screening,

1238
01:03:24,100 --> 01:03:27,604
some of the challenges
of how to prove

1239
01:03:27,604 --> 01:03:31,941
that NBS has an impact
on outcomes and benefits,

1240
01:03:31,941 --> 01:03:34,844
and also the challenges of
the communication of the results

1241
01:03:34,844 --> 01:03:37,647
to affected children
and carriers.

1242
01:03:38,314 --> 01:03:39,916
So, when we talk about Europe,

1243
01:03:39,916 --> 01:03:43,053
it's a geographical
but also political area,

1244
01:03:43,887 --> 01:03:47,223
and every country has its own
health system or systems.

1245
01:03:47,223 --> 01:03:49,959
But there are common grounds
for protocol, politics,

1246
01:03:49,959 --> 01:03:53,396
and funding, especially
within the European Union,

1247
01:03:53,396 --> 01:03:57,634
which, as you know, has U.K.
outside of it since a few years.

1248
01:03:58,268 --> 01:04:01,905
We have a population
of around 450 million people,

1249
01:04:02,439 --> 01:04:06,142
and 38 of these
were born outside Europe.

1250
01:04:06,142 --> 01:04:07,377
And this, of course,

1251
01:04:07,377 --> 01:04:09,546
has an impact
on screening and diagnosis,

1252
01:04:10,080 --> 01:04:13,616
also considering that these
people mainly come from areas

1253
01:04:13,616 --> 01:04:17,220
where mutation of the beta and
the alpha globin gene are common

1254
01:04:17,220 --> 01:04:20,557
and are of a huge variety.

1255
01:04:21,057 --> 01:04:23,026
And this increases
the challenges for,

1256
01:04:23,026 --> 01:04:24,627
especially in the future,

1257
01:04:25,195 --> 01:04:29,399
for different genotypes
and phenotypes that can appear.

1258
01:04:29,399 --> 01:04:31,768
Now, the main four countries
are Germany,

1259
01:04:31,768 --> 01:04:33,336
France,
Italy, and Spain,

1260
01:04:33,336 --> 01:04:36,873
and you can see where
the immigrants come from.

1261
01:04:36,873 --> 01:04:38,842
And as I said, they come
from the Middle East,

1262
01:04:38,842 --> 01:04:41,244
Sub-Saharan Africa,
and Southern Asia.

1263
01:04:42,712 --> 01:04:46,015
Number of newborns in Europe,
3.8 million.

1264
01:04:46,015 --> 01:04:48,485
So, this is
our catchment population,

1265
01:04:48,485 --> 01:04:50,286
although the fertility rate
is different,

1266
01:04:50,286 --> 01:04:52,222
it's highest
currently in France,

1267
01:04:52,922 --> 01:04:56,092
which has a population
of around 30,000-36,000

1268
01:04:56,092 --> 01:05:00,396
sickle cell patients estimated.
So, what about the guidelines?

1269
01:05:00,396 --> 01:05:02,899
The U.K. was a pioneer
in developing guidelines

1270
01:05:02,899 --> 01:05:04,734
for newborn screening,
but every country

1271
01:05:04,734 --> 01:05:08,238
now has national guidelines
in their own national language.

1272
01:05:08,238 --> 01:05:11,641
And we published
a consensus in 2018

1273
01:05:12,776 --> 01:05:16,780
recommending universal newborn
screening in all Western Europe.

1274
01:05:16,780 --> 01:05:19,649
Recently, the British Society
of Hematology

1275
01:05:19,649 --> 01:05:22,685
included a guideline not only
on a newborn screening,

1276
01:05:22,685 --> 01:05:24,721
but prenatal
and antenatal screening,

1277
01:05:24,721 --> 01:05:26,623
so a comprehensive
guideline.

1278
01:05:26,623 --> 01:05:29,092
And funded by
the European Commission

1279
01:05:29,092 --> 01:05:30,794
and the European
Reference Network

1280
01:05:30,794 --> 01:05:32,495
for Rare Blood Disorders,

1281
01:05:32,495 --> 01:05:34,998
the national guidelines,
eight of them,

1282
01:05:34,998 --> 01:05:37,233
have been
translated in English.

1283
01:05:37,233 --> 01:05:39,769
And now there's a big group
in Europe

1284
01:05:39,769 --> 01:05:41,871
of specialist
pediatric hematologists

1285
01:05:41,871 --> 01:05:45,441
working on the harmonization
of all diagnostic pathways,

1286
01:05:45,441 --> 01:05:48,912
but also clinical pathways for
acute and chronic complication.

1287
01:05:48,912 --> 01:05:51,881
And we hope to finish
this work next year,

1288
01:05:51,881 --> 01:05:53,783
and so share with everybody.

1289
01:05:54,851 --> 01:05:56,219
What about the current
situation?

1290
01:05:56,219 --> 01:05:59,556
Well, the U.K. has national
antenatal and newborn screening.

1291
01:06:00,256 --> 01:06:02,592
There are several
national universal

1292
01:06:02,592 --> 01:06:04,327
newborn screening
in Spain, Germany,

1293
01:06:04,327 --> 01:06:07,263
the Netherlands, Belgium,
and France overseas territories;

1294
01:06:08,064 --> 01:06:11,534
national targeted in France;
national universal prenatal,

1295
01:06:11,534 --> 01:06:14,504
antenatal, and preconceptual
in Greece and Cyprus;

1296
01:06:14,504 --> 01:06:16,272
antenatal targeted in Denmark.

1297
01:06:16,840 --> 01:06:18,708
There were some pilots
conducted in Italy,

1298
01:06:18,708 --> 01:06:19,943
Portugal, and Ireland,

1299
01:06:19,943 --> 01:06:22,879
which unfortunately
have not yet been able

1300
01:06:23,513 --> 01:06:25,815
to implement national
newborn screening,

1301
01:06:25,815 --> 01:06:28,985
even though you can see Portugal
has the highest frequency

1302
01:06:28,985 --> 01:06:32,889
of sickle cell disease estimated
in the newborn population.

1303
01:06:32,889 --> 01:06:34,791
We must not forget that
in Europe,

1304
01:06:34,791 --> 01:06:37,227
sickle cell disease
is considered a rare disease.

1305
01:06:37,894 --> 01:06:40,597
But this means that patients
and individuals

1306
01:06:40,597 --> 01:06:43,700
with sickle cell disease risk of
being neglected more than once,

1307
01:06:43,700 --> 01:06:44,934
because they are rare,

1308
01:06:44,934 --> 01:06:48,771
because they are immigrant
or descendants of immigrants,

1309
01:06:48,771 --> 01:06:51,841
and because they have
a different color of the skin

1310
01:06:51,841 --> 01:06:55,311
compared to what is considered
the average European.

1311
01:06:57,680 --> 01:06:59,082
This is just a situation
of Italy,

1312
01:06:59,082 --> 01:07:01,851
sadly,
because of lack of consent

1313
01:07:01,851 --> 01:07:04,854
among the European
hematology community,

1314
01:07:04,854 --> 01:07:06,823
in spite of the figures
that you see

1315
01:07:07,357 --> 01:07:08,958
that are higher
than other countries,

1316
01:07:08,958 --> 01:07:11,928
we were not able yet
to get newborn screening

1317
01:07:11,928 --> 01:07:14,264
at a national level,
only regional level.

1318
01:07:14,998 --> 01:07:16,432
What about the methods?

1319
01:07:16,432 --> 01:07:19,702
Some countries use cord blood;
others use heel prick samples.

1320
01:07:20,403 --> 01:07:24,207
The method used -- almost
all countries use two tests,

1321
01:07:24,207 --> 01:07:26,342
but Spain uses
only one test.

1322
01:07:26,342 --> 01:07:29,612
And the confirmation is
performed only when the patient

1323
01:07:29,612 --> 01:07:32,916
is referred to the pediatric
hematology oncology unit.

1324
01:07:32,916 --> 01:07:34,984
And there have been
some nice pilots

1325
01:07:34,984 --> 01:07:37,954
with mass spectrometry
and genetic analysis,

1326
01:07:37,954 --> 01:07:41,925
for example, mass spectrometry
in France or genetic analysis

1327
01:07:41,925 --> 01:07:43,593
and mass spectrometry
in Germany.

1328
01:07:44,227 --> 01:07:49,499
I found very interesting the one
that's unifying the screening

1329
01:07:49,499 --> 01:07:52,135
of immune deficiencies,
muscular atrophy,

1330
01:07:52,135 --> 01:07:53,536
and sickle cell disease
together,

1331
01:07:53,536 --> 01:07:55,305
because these diseases
were recently

1332
01:07:55,305 --> 01:07:57,307
added in the newborn
screening program

1333
01:07:57,307 --> 01:07:59,809
in several countries,
Italy included.

1334
01:08:03,146 --> 01:08:05,682
What about the data
registration and numbers?

1335
01:08:05,682 --> 01:08:08,985
There are several evaluation
programs on the coverage.

1336
01:08:08,985 --> 01:08:11,154
The best is the U.K., again.

1337
01:08:11,154 --> 01:08:15,725
But what is really a driving
point in European countries

1338
01:08:15,725 --> 01:08:17,493
is prospective
data collection.

1339
01:08:17,493 --> 01:08:20,063
Patients are screened,
but then they are enrolled

1340
01:08:20,063 --> 01:08:22,065
in comprehensive
follow-up programs,

1341
01:08:22,065 --> 01:08:24,500
and now they're enrolled
in national registries,

1342
01:08:24,500 --> 01:08:27,971
or the countries that don't have
them in the European registries.

1343
01:08:27,971 --> 01:08:29,639
And there has been harmonization

1344
01:08:29,639 --> 01:08:32,408
of the definition
of the phenotype

1345
01:08:32,408 --> 01:08:34,978
and the complication
in all European countries,

1346
01:08:34,978 --> 01:08:37,213
and we hope this will
give information in the future.

1347
01:08:37,213 --> 01:08:39,616
We do not have
European numbers

1348
01:08:39,616 --> 01:08:42,118
on the overall number
of newborns screened yet,

1349
01:08:42,118 --> 01:08:43,553
only national data.

1350
01:08:43,553 --> 01:08:46,322
And the estimate is more
than 60,000 individuals

1351
01:08:46,322 --> 01:08:47,623
living in Europe.

1352
01:08:47,623 --> 01:08:49,759
And these are just
some of the examples

1353
01:08:49,759 --> 01:08:51,461
of the output in data

1354
01:08:51,995 --> 01:08:54,697
of the hemoglobinopathies
screening programs

1355
01:08:54,697 --> 01:08:56,499
and registries
from a few countries.

1356
01:08:57,066 --> 01:08:59,135
Now, I am going to highlight
Germany,

1357
01:08:59,135 --> 01:09:02,405
because Germans always,
when they start something,

1358
01:09:02,405 --> 01:09:05,375
they move forward.
They started screening in 2021,

1359
01:09:05,375 --> 01:09:07,677
already have 11 laboratories
that are active,

1360
01:09:07,677 --> 01:09:09,846
screened more than
1 million babies,

1361
01:09:09,846 --> 01:09:12,315
and everybody's enrolled
in a registry.

1362
01:09:12,315 --> 01:09:16,452
And what they manage with this
wide collection of data

1363
01:09:16,452 --> 01:09:18,888
and having in a few years
insight in the disease

1364
01:09:18,888 --> 01:09:21,024
natural history
in their population --

1365
01:09:21,024 --> 01:09:22,692
so the genetic characteristic,

1366
01:09:22,692 --> 01:09:25,161
the phenotype of
certain manifestations.

1367
01:09:25,161 --> 01:09:29,132
So, in effect,
coupling screening

1368
01:09:29,132 --> 01:09:30,867
with data collection
is important.

1369
01:09:31,701 --> 01:09:35,872
Is communication of the result
to affected families of children

1370
01:09:35,872 --> 01:09:37,407
affected is mandatory,

1371
01:09:37,407 --> 01:09:40,476
but of the carrier status
is not allowed in Germany

1372
01:09:41,177 --> 01:09:43,579
due to the history
during Second World War.

1373
01:09:44,180 --> 01:09:45,481
And there have been evaluation

1374
01:09:45,481 --> 01:09:47,517
of recent
communication strategies,

1375
01:09:47,517 --> 01:09:53,489
both to the affected children,
families, and the carriers.

1376
01:09:53,489 --> 01:09:56,125
So, it's important
to continue this evaluation.

1377
01:09:56,659 --> 01:09:57,927
What about the outcomes

1378
01:09:57,927 --> 01:09:59,696
and the benefits
of newborn screening?

1379
01:09:59,696 --> 01:10:03,066
Are we really capable of proving
that it's beneficial?

1380
01:10:03,633 --> 01:10:06,202
Now, I was surprised
by this sentence

1381
01:10:06,202 --> 01:10:10,306
that was presented at
the National German Hematology

1382
01:10:10,306 --> 01:10:12,608
Screening Meeting
last year:

1383
01:10:12,608 --> 01:10:15,044
Screening reduces
early morbidity and mortality,

1384
01:10:15,044 --> 01:10:16,679
but to what extent is unclear

1385
01:10:16,679 --> 01:10:18,414
and will probably
remain unclear.

1386
01:10:18,414 --> 01:10:22,018
Is it true, or have a way
to demonstrate this?

1387
01:10:22,018 --> 01:10:23,619
Now, in France, for example,

1388
01:10:24,320 --> 01:10:26,255
they demonstrated
that there are many failures

1389
01:10:26,255 --> 01:10:27,890
in the targeted
screening programs.

1390
01:10:27,890 --> 01:10:29,992
So, this is a way
to address the problems.

1391
01:10:30,493 --> 01:10:34,330
But another way is looking
at the global disease burden

1392
01:10:34,330 --> 01:10:36,132
that was cited before.

1393
01:10:36,132 --> 01:10:39,669
We were surprised that
in the U.S., sickle cell disease

1394
01:10:39,669 --> 01:10:43,639
is not one of the most common
causes of death under five.

1395
01:10:43,639 --> 01:10:46,509
But look at Europe.
In many European countries,

1396
01:10:46,509 --> 01:10:48,511
sickle cell disease
is between the third

1397
01:10:48,511 --> 01:10:49,946
and the sixth cause of death,

1398
01:10:49,946 --> 01:10:52,315
even in my region,
which is the northeast of Italy.

1399
01:10:52,315 --> 01:10:54,884
So, is it because this data
was collected

1400
01:10:54,884 --> 01:10:57,754
before many newborn screenings
scaled up,

1401
01:10:57,754 --> 01:10:59,856
or is it before
we have other issues?

1402
01:10:59,856 --> 01:11:02,792
I think we will need to reassess
this in a few years.

1403
01:11:03,526 --> 01:11:06,429
Nevertheless, how did
countries in Europe

1404
01:11:06,429 --> 01:11:08,598
look at the benefits
of newborn screening?

1405
01:11:08,598 --> 01:11:11,000
This is a paper
that came out recently

1406
01:11:11,000 --> 01:11:13,369
in American Journal
of Hematology by the Dutch.

1407
01:11:13,369 --> 01:11:14,570
They have a newborn screening.

1408
01:11:14,570 --> 01:11:17,640
They have a national
prospective data collection

1409
01:11:17,640 --> 01:11:20,309
that allows them to evaluate
how good their care is.

1410
01:11:20,309 --> 01:11:23,513
74 percent are treated
with hydroxyurea.

1411
01:11:23,513 --> 01:11:25,515
And in fact,
there was a reduction

1412
01:11:25,515 --> 01:11:27,984
in mortality
from before to after.

1413
01:11:27,984 --> 01:11:29,619
But morbidity remains high,

1414
01:11:29,619 --> 01:11:32,889
especially in the 0-4 age group
with acute events,

1415
01:11:33,523 --> 01:11:36,125
except acute chest,
with worsened over age,

1416
01:11:36,125 --> 01:11:37,827
and also the chronic
complication.

1417
01:11:38,494 --> 01:11:40,463
Similar figures in Spain.

1418
01:11:40,463 --> 01:11:43,065
Newborn screening,
prospective data collection,

1419
01:11:43,065 --> 01:11:45,601
and comparison of mortality
and acute morbidity

1420
01:11:45,601 --> 01:11:47,003
with other newborn cohorts.

1421
01:11:47,003 --> 01:11:51,240
Reduction of mortality,
but same morbidity. France.

1422
01:11:51,240 --> 01:11:55,044
France does not have a national
universal newborn screening,

1423
01:11:55,044 --> 01:11:56,379
nor a national registry.

1424
01:11:56,379 --> 01:11:58,614
So, this was
a retrospective review.

1425
01:11:58,614 --> 01:12:00,883
Nevertheless,
the survival was high.

1426
01:12:01,450 --> 01:12:05,054
HU was prescribed
in only 30.7 percent.

1427
01:12:05,054 --> 01:12:09,225
But the conclusion was there was
still a high risk of morbidity

1428
01:12:09,225 --> 01:12:11,294
and burden of disease.

1429
01:12:11,294 --> 01:12:15,097
So, my conclusions are the NBS
programs are developing

1430
01:12:15,097 --> 01:12:16,299
and scaling up in Europe,

1431
01:12:16,299 --> 01:12:17,767
although with
different strategies.

1432
01:12:17,767 --> 01:12:19,368
But this might not be bad,

1433
01:12:19,368 --> 01:12:22,038
because there is no one size
fits all,

1434
01:12:22,038 --> 01:12:23,573
even for neighboring countries.

1435
01:12:23,573 --> 01:12:27,143
Data collection at national and
European level is prioritized

1436
01:12:27,143 --> 01:12:30,179
and is being harmonized
to allow comparison of data.

1437
01:12:30,179 --> 01:12:32,515
There is the need
to improve communication

1438
01:12:32,515 --> 01:12:34,450
and patients' communities'
involvement.

1439
01:12:34,450 --> 01:12:37,019
And, of course, we still have to
overcome some challenges

1440
01:12:37,019 --> 01:12:38,254
of cost,

1441
01:12:38,254 --> 01:12:41,958
prejudice, lack of uniform voice
among stakeholders,

1442
01:12:41,958 --> 01:12:45,661
and different other priorities
in times of budget constraints.

1443
01:12:45,661 --> 01:12:48,898
So, I thank the European
colleagues working on this.

1444
01:12:48,898 --> 01:12:50,499
I probably forgot somebody.

1445
01:12:50,499 --> 01:12:53,002
We have a long road ahead,
which might not be straight,

1446
01:12:53,002 --> 01:12:55,738
but nevertheless,
we need to continue walking.

1447
01:12:56,339 --> 01:12:57,707
Thank you all
for your attention,

1448
01:12:57,707 --> 01:13:00,977
and of course, our patients
and patient association.

1449
01:13:02,478 --> 01:13:09,752
[applause]

1450
01:13:09,752 --> 01:13:11,454
Female Speaker: I'd like
to thank the organizers

1451
01:13:11,454 --> 01:13:14,790
for inviting me to talk about
newborn screening in Brazil,

1452
01:13:14,790 --> 01:13:16,158
my country.

1453
01:13:16,158 --> 01:13:24,400
And I would talk a bit
about India in afterwards.

1454
01:13:26,969 --> 01:13:30,940
Well, in Brazil,
the National Screening Program

1455
01:13:30,940 --> 01:13:33,009
was launched in 2001.

1456
01:13:34,410 --> 01:13:39,815
And in 2005, the National
Program for Sickle Cell Disease

1457
01:13:39,815 --> 01:13:42,752
and Other Hemoglobinopathies
was launched.

1458
01:13:43,719 --> 01:13:48,157
And in 2006, our scientific
committee was funded.

1459
01:13:49,091 --> 01:13:52,428
And this scientific committee
wrote

1460
01:13:52,428 --> 01:13:54,830
our National Protocol
for Hydroxyurea

1461
01:13:54,830 --> 01:13:58,467
Use, Transfusion
and Iron Chelation,

1462
01:13:59,435 --> 01:14:04,607
our TCD screening program,
and bone marrow transplantation.

1463
01:14:04,607 --> 01:14:10,946
So, we have all these programs
since the last decade.

1464
01:14:11,514 --> 01:14:13,149
Well, I don't know
if you all know

1465
01:14:13,149 --> 01:14:16,118
that Brazil has
a public health system.

1466
01:14:16,118 --> 01:14:19,288
It's called SUS,
Sistema Único de Saúde.

1467
01:14:20,122 --> 01:14:24,427
And its assistance
begins in primary care,

1468
01:14:24,427 --> 01:14:26,295
actually in neonatal
screening,

1469
01:14:26,862 --> 01:14:30,599
responsible for first
procedures of prevention,

1470
01:14:30,599 --> 01:14:34,837
such as prophylaxis with
penicillin and vaccination.

1471
01:14:34,837 --> 01:14:37,740
And it goes all the way
to reference centers

1472
01:14:37,740 --> 01:14:42,712
that will take part
with TCD screening,

1473
01:14:43,245 --> 01:14:46,682
magnetic resonances,
and bone marrow transplantation.

1474
01:14:48,985 --> 01:14:53,322
Data from newborn screening
started to come

1475
01:14:53,322 --> 01:14:58,094
and to be published in 2007.
And with this map here

1476
01:14:58,094 --> 01:15:01,564
that shows the prevalence
of sickle cell trait,

1477
01:15:01,564 --> 01:15:05,835
of course, its prevalence
is bigger in Bahia,

1478
01:15:05,835 --> 01:15:09,171
the state of Bahia,
the first capital of Brazil

1479
01:15:10,840 --> 01:15:14,043
when it was part
of the Portuguese empire.

1480
01:15:15,244 --> 01:15:18,614
The prevalence ranges
from two percent

1481
01:15:19,181 --> 01:15:21,283
in the very south of Brazil,

1482
01:15:21,283 --> 01:15:25,521
where we don't have that much
influence of our descendants,

1483
01:15:25,521 --> 01:15:26,822
until six percent.

1484
01:15:26,822 --> 01:15:30,259
In my region, it's 2.5 percent,
the state of São Paulo.

1485
01:15:30,893 --> 01:15:34,597
And data -- this is new data
already, data from the CISNET,

1486
01:15:34,597 --> 01:15:37,199
the National Registry
for Newborn Screening,

1487
01:15:38,401 --> 01:15:42,004
ranges between 1,500
to 2,000 newborns

1488
01:15:42,004 --> 01:15:44,640
with sickle cell disease
every year in Brazil.

1489
01:15:44,640 --> 01:15:46,742
But this may be
underestimated,

1490
01:15:46,742 --> 01:15:49,211
because, as you will see
in my presentation,

1491
01:15:49,912 --> 01:15:52,014
the coverage
of newborn screening,

1492
01:15:52,014 --> 01:15:55,117
which is universal in Brazil,
is not 100 percent.

1493
01:15:57,686 --> 01:16:00,423
So, talking about newborn
screening,

1494
01:16:00,423 --> 01:16:04,660
it started in 2001
in the southeast region.

1495
01:16:05,327 --> 01:16:08,597
That means state
of Minas Gerais,

1496
01:16:08,597 --> 01:16:11,267
Rio de Janeiro,
and São Paulo State,

1497
01:16:11,267 --> 01:16:17,973
the three most populated
and richest states.

1498
01:16:17,973 --> 01:16:20,843
São Paulo has three
screening centers,

1499
01:16:20,843 --> 01:16:27,283
because it has 45 million people
living only in São Paulo State.

1500
01:16:27,817 --> 01:16:30,085
Brazil has 200 million people.

1501
01:16:30,085 --> 01:16:33,489
One-fourth, almost,
lives in São Paulo.

1502
01:16:33,489 --> 01:16:37,293
So, it's a huge state
when it comes to numbers.

1503
01:16:38,194 --> 01:16:42,264
It's all 100 percent
performed by HPLC nationwide.

1504
01:16:43,265 --> 01:16:49,905
And we finished training
and implementing HPLC

1505
01:16:49,905 --> 01:16:53,342
for newborn screening
in Brazil in 2013,

1506
01:16:54,410 --> 01:16:58,547
with at least 80 percent
of the newborns coverage.

1507
01:17:00,449 --> 01:17:03,619
We divided the implementation
of newborn screening in Brazil

1508
01:17:03,619 --> 01:17:06,455
into four phases.
Now we are heading to the fifth.

1509
01:17:06,989 --> 01:17:10,759
But first phase phenylketonuria
congenital hypothyroidism.

1510
01:17:11,293 --> 01:17:15,231
Phase two, sickle cell disease.
Phase three, cystic fibrosis.

1511
01:17:15,231 --> 01:17:18,067
And phase four,
congenital adrenal hyperplasia

1512
01:17:18,067 --> 01:17:19,668
and biotinidase deficiency.

1513
01:17:21,137 --> 01:17:24,507
Now, as you can see, and you can
follow the Brazilian map,

1514
01:17:24,507 --> 01:17:27,009
this is the evolution
of neonatal screening program

1515
01:17:27,009 --> 01:17:29,111
in Brazil.

1516
01:17:29,111 --> 01:17:34,650
As you can see,
from 2010 until 2013-2012,

1517
01:17:35,384 --> 01:17:39,188
there were some states
in phase one with light blue.

1518
01:17:39,855 --> 01:17:46,428
But in August 2013, they were
all screening untill phase two,

1519
01:17:46,428 --> 01:17:49,431
at least which covers
sickle cell disease.

1520
01:17:49,431 --> 01:17:56,305
And in 2014, all the nation
was screening until phase four.

1521
01:17:57,039 --> 01:17:59,441
And the coverage ranges.

1522
01:17:59,441 --> 01:18:04,013
In São Paulo State,
it's above 95 percent.

1523
01:18:04,013 --> 01:18:05,347
So, in São Paulo State,

1524
01:18:05,347 --> 01:18:07,917
almost 100 percent
of the newborns are screened.

1525
01:18:09,184 --> 01:18:14,156
But it's not the reality
of our entire nation,

1526
01:18:14,156 --> 01:18:16,258
because Brazil is so big.

1527
01:18:16,258 --> 01:18:19,595
We are considered
a middle-income country.

1528
01:18:19,595 --> 01:18:23,632
But we have, inside Brazil,
low-income regions,

1529
01:18:23,632 --> 01:18:26,068
middle-income regions,
and high-income regions.

1530
01:18:26,068 --> 01:18:34,243
So, it's very complex to really
have an orchestra

1531
01:18:34,243 --> 01:18:37,413
of all the things
we have to do in sickle cell

1532
01:18:37,413 --> 01:18:39,882
with the differences
among states.

1533
01:18:40,449 --> 01:18:43,852
But, as you can compare,
the first map I showed you,

1534
01:18:44,386 --> 01:18:49,191
there was no data regarding the
center of Brazil in the north.

1535
01:18:49,191 --> 01:18:53,062
And now this presentation
includes this publication

1536
01:18:53,062 --> 01:18:54,663
of 2018,

1537
01:18:54,663 --> 01:18:58,567
that we already have some data
from the center-west

1538
01:18:58,567 --> 01:19:00,369
and the northeast part
of Brazil.

1539
01:19:01,070 --> 01:19:04,440
Of course, the state of Bahia
is the most prevalent one

1540
01:19:04,440 --> 01:19:09,578
because we have
a lot of influence

1541
01:19:09,578 --> 01:19:11,180
of Afro-descended people there.

1542
01:19:13,449 --> 01:19:16,218
But we are facing
some challenges.

1543
01:19:17,152 --> 01:19:19,455
Newborn screening
faced a drawback in Brazil

1544
01:19:19,455 --> 01:19:23,959
since 2019 with the switch
of the government.

1545
01:19:24,493 --> 01:19:29,365
So, we had a government
between 2019 and 2022

1546
01:19:29,365 --> 01:19:34,003
that didn't take any care
of sickle cell disease,

1547
01:19:34,003 --> 01:19:36,138
didn't look at minorities,

1548
01:19:36,138 --> 01:19:38,807
and didn't give
almost any budget

1549
01:19:38,807 --> 01:19:40,643
to our public health system.

1550
01:19:41,810 --> 01:19:46,815
With reduced budget, the sickle
cell screening program

1551
01:19:46,815 --> 01:19:50,285
was reduced to less than
80 percent coverage

1552
01:19:50,285 --> 01:19:51,920
in most of the states of

1553
01:19:51,920 --> 01:19:53,455
And our national registry
the poorest regions,

1554
01:19:53,455 --> 01:19:55,190
north and northeast of Brazil.

1555
01:19:55,691 --> 01:19:58,827
And our national registry
is called Web Hemoglobinopatia,

1556
01:19:58,827 --> 01:20:02,898
it's still incomplete.
But since last year,

1557
01:20:02,898 --> 01:20:06,335
we're putting many more
reference centers on board.

1558
01:20:07,770 --> 01:20:10,673
But we are concerned
about the disparities

1559
01:20:10,673 --> 01:20:12,875
that we face in our country,

1560
01:20:12,875 --> 01:20:15,210
with poor health support
for sickle cell patients

1561
01:20:15,210 --> 01:20:18,714
in the northern states
of the country.

1562
01:20:19,481 --> 01:20:23,752
Well, but there is light
at the end of the tunnel.

1563
01:20:23,752 --> 01:20:26,155
We have a new government
since last year,

1564
01:20:26,755 --> 01:20:29,692
and that raised
sickle cell disease

1565
01:20:29,692 --> 01:20:31,860
as one of its priorities,

1566
01:20:31,860 --> 01:20:35,130
re-established our scientific
committee --which I'm a member.

1567
01:20:35,130 --> 01:20:38,133
I was a member, and then
they shut down the committees,

1568
01:20:38,133 --> 01:20:40,602
the scientific committees.
We are all volunteers.

1569
01:20:41,704 --> 01:20:45,274
We don't cost a dime
for the government,

1570
01:20:45,274 --> 01:20:47,810
but they shut down in 2019.

1571
01:20:47,810 --> 01:20:54,383
So, everything was in darkness,
and now it restarted again.

1572
01:20:54,383 --> 01:20:59,254
And we started training
neurologists and doctors

1573
01:20:59,254 --> 01:21:01,757
to perform newborn TCD

1574
01:21:01,757 --> 01:21:06,428
because the federal government
bought the machines,

1575
01:21:06,428 --> 01:21:09,198
but the doctors didn't know
how to do that.

1576
01:21:09,198 --> 01:21:12,434
So, we started
in our institution,

1577
01:21:12,935 --> 01:21:16,605
with a collaboration of
the Department of Neurology.

1578
01:21:16,605 --> 01:21:20,809
We had many, many doctors
coming from all over the country

1579
01:21:20,809 --> 01:21:23,912
to be trained to perform
a transcranial Doppler.

1580
01:21:24,980 --> 01:21:28,884
And last year, we finally had
our National Sickle Cell

1581
01:21:28,884 --> 01:21:32,421
Disease Congress, sponsored
by the Ministry of Health.

1582
01:21:33,388 --> 01:21:35,524
It was supposed to be
every two years,

1583
01:21:35,524 --> 01:21:39,895
but the last one was in 2017.
And then darkness came,

1584
01:21:39,895 --> 01:21:44,199
and then now we are out
of darkness again, thank God.

1585
01:21:44,199 --> 01:21:45,968
And next year,
we're going to have

1586
01:21:45,968 --> 01:21:49,471
our 10th National Congress
in September

1587
01:21:49,471 --> 01:21:51,707
in the center of Brazil,

1588
01:21:51,707 --> 01:21:54,610
to try to develop
sickle cell disease

1589
01:21:54,610 --> 01:21:56,545
in the center-west part
of the country.

1590
01:21:57,679 --> 01:22:00,215
Thank you very much
for your attention.

1591
01:22:00,215 --> 01:22:04,620
[applause]

1592
01:22:04,620 --> 01:22:07,055
Well, yes, I changed
my presentation,

1593
01:22:07,055 --> 01:22:09,491
but they didn't put
the new presentation in,

1594
01:22:09,491 --> 01:22:11,860
because I just realized
that I was going to talk

1595
01:22:11,860 --> 01:22:14,329
about India yesterday night.

1596
01:22:14,329 --> 01:22:19,635
But, well, I don't know
if you can have the presentation

1597
01:22:19,635 --> 01:22:24,173
I uploaded this morning.

1598
01:22:24,173 --> 01:22:25,774
Male Speaker: You uploaded it
down there?

1599
01:22:26,708 --> 01:22:28,010
Female Speaker: No,
with that lady there,

1600
01:22:28,010 --> 01:22:29,611
that she's going.

1601
01:22:31,947 --> 01:22:37,286
Yeah. Well, yes. See, I updated
even with the flag.

1602
01:22:37,820 --> 01:22:39,621
[laughter]

1603
01:22:39,621 --> 01:22:41,690
Okay, let's go.

1604
01:22:44,092 --> 01:22:45,994
Of course, I know
more about my country,

1605
01:22:45,994 --> 01:22:51,733
but I was surprised to note
that it is estimated

1606
01:22:51,733 --> 01:22:54,837
that 15 percent
of the world's neonates

1607
01:22:54,837 --> 01:22:57,005
with sickle cell disease
are born in India.

1608
01:22:57,940 --> 01:23:00,742
Two-thirds are born in Africa,
15 percent in India,

1609
01:23:00,742 --> 01:23:07,950
so it's almost, what, 80 percent
Africa and India together.

1610
01:23:07,950 --> 01:23:12,955
So, it's a very important
country to look for.

1611
01:23:12,955 --> 01:23:16,725
And there is no national
neonatal screening program

1612
01:23:16,725 --> 01:23:18,327
for sickle cell disease yet.

1613
01:23:18,894 --> 01:23:22,164
But it started,
as this publication

1614
01:23:23,765 --> 01:23:25,634
was published in 2018.

1615
01:23:26,468 --> 01:23:30,606
This presentation shows a few
newborn screening programs

1616
01:23:30,606 --> 01:23:34,409
that has been initiated
in the last five or six years,

1617
01:23:34,409 --> 01:23:37,579
so in the last decade.

1618
01:23:37,579 --> 01:23:41,917
As you can see in this map
of the Indian country,

1619
01:23:41,917 --> 01:23:43,952
you can see some regions

1620
01:23:43,952 --> 01:23:47,656
where they implemented
universal screening

1621
01:23:47,656 --> 01:23:49,758
and targeted screening,

1622
01:23:49,758 --> 01:23:52,661
mostly in the northern part
of the country.

1623
01:23:53,762 --> 01:23:57,366
And I was surprised
to see the prevalence.

1624
01:23:59,535 --> 01:24:01,303
Those are the states
and districts

1625
01:24:01,303 --> 01:24:04,606
at the beginning of the table.
But then number of screening --

1626
01:24:04,606 --> 01:24:10,679
I'm sorry, well,
number of screened babies

1627
01:24:12,180 --> 01:24:17,019
and the percentage of the S
mutation -- I was surprised.

1628
01:24:17,019 --> 01:24:24,293
One region was 45 percent,
the Maharashtra Nagpur district.

1629
01:24:24,293 --> 01:24:30,098
Look at that, 45 percent
of sickle cell trait.

1630
01:24:31,500 --> 01:24:36,138
That's a lot. And compared
to Brazil, I was shocked.

1631
01:24:36,138 --> 01:24:38,740
And number of sickle cell
disease patients

1632
01:24:39,741 --> 01:24:44,212
in this last table.
So the numbers are pretty great.

1633
01:24:44,212 --> 01:24:47,382
And, of course,
this is a pilot in some regions.

1634
01:24:49,017 --> 01:24:55,223
But since 2010,
it has been initiated.

1635
01:24:55,223 --> 01:24:59,294
They already screened
over 18,000 babies

1636
01:25:00,128 --> 01:25:04,333
and found almost 3,000 sickle
cell disease individuals

1637
01:25:04,333 --> 01:25:07,703
and 300 babies
with sickle cell disease

1638
01:25:07,703 --> 01:25:09,838
and 3,000 sickle cell trait.

1639
01:25:09,838 --> 01:25:14,309
But now, last year,
they launched that program

1640
01:25:14,309 --> 01:25:16,979
that the first speaker
told us --

1641
01:25:16,979 --> 01:25:19,748
the Sickle Cell
Anemia Elimination Mission.

1642
01:25:21,249 --> 01:25:27,622
And their aim is to turn
neonatal screening universal

1643
01:25:27,622 --> 01:25:29,324
in all Indian country.

1644
01:25:30,592 --> 01:25:34,930
And so, I think
they have started with,

1645
01:25:35,497 --> 01:25:38,633
and then they are trying,
as you said,

1646
01:25:38,633 --> 01:25:46,475
many kinds of newborn points
of care to see which one is good

1647
01:25:46,475 --> 01:25:51,279
and not so expensive
to become nationwide use.

1648
01:25:51,279 --> 01:25:53,615
So, I think we are going
to hear a lot more

1649
01:25:53,615 --> 01:25:56,885
about India's newborn screening
the next few years.

1650
01:25:58,153 --> 01:25:59,721
Thank you.

1651
01:25:59,721 --> 01:26:05,994
[applause]

1652
01:26:05,994 --> 01:26:08,397
Female Speaker: Thank you
so much to the four speakers.

1653
01:26:09,031 --> 01:26:12,367
It's striking to note
the similarities,

1654
01:26:12,367 --> 01:26:16,138
but especially how different
the programs must be.

1655
01:26:16,838 --> 01:26:19,107
And we must realize
that the different methods used

1656
01:26:19,107 --> 01:26:21,009
and continue to learn
from each other.

1657
01:26:21,710 --> 01:26:26,114
It really was four great talks.
So, thank you so very much.

1658
01:26:26,114 --> 01:26:30,952
And 10 minutes is not a long
time to speak for regions.

1659
01:26:30,952 --> 01:26:33,655
I know Jennifer could speak
maybe an hour on Jamaica alone

1660
01:26:33,655 --> 01:26:36,792
because of the wealth
of information

1661
01:26:36,792 --> 01:26:39,361
and what we have learned
over the last few years

1662
01:26:39,361 --> 01:26:40,595
about newborn screening

1663
01:26:40,595 --> 01:26:42,597
and what strategies work
and what don't.

1664
01:26:43,198 --> 01:26:44,433
Open for questions.

1665
01:26:44,433 --> 01:26:46,101
I'm trying to follow
in the Zoom.

1666
01:26:46,101 --> 01:26:48,103
I'm not seeing
much questions.

1667
01:26:48,103 --> 01:26:49,704
I'm only seeing requests
for CMEs.

1668
01:26:49,704 --> 01:26:52,808
Yes. Go ahead, Dr. Little.
Is there a mic there?

1669
01:26:54,843 --> 01:27:04,119
Jane Little: Thanks.
I'm Jane Little.

1670
01:27:04,119 --> 01:27:05,720
I'm from the University
of North Carolina.

1671
01:27:05,720 --> 01:27:08,523
That was really
so enlightening.

1672
01:27:08,523 --> 01:27:10,125
I had

1673
01:27:10,792 --> 01:27:31,113
[inaudible]

1674
01:27:31,680 --> 01:27:33,615
-- if you could comment
about that, that'd be great.

1675
01:27:33,615 --> 01:27:35,951
And the second question
I had is --

1676
01:27:35,951 --> 01:27:39,688
it's so annoying to me
that we have newborn screening

1677
01:27:39,688 --> 01:27:41,490
and then we don't
have registries.

1678
01:27:41,490 --> 01:27:46,094
And I've been boring people
about this, I think,

1679
01:27:46,094 --> 01:27:47,362
for a very long time.

1680
01:27:47,362 --> 01:27:49,965
And I wonder if you guys
could talk about ways

1681
01:27:49,965 --> 01:27:52,100
that we could try to link
newborn screening

1682
01:27:52,634 --> 01:27:54,836
to registries
that we can all learn from

1683
01:27:54,836 --> 01:27:57,172
because we're not learning
from each other.

1684
01:27:57,172 --> 01:27:58,773
And I think
that's just a shame.

1685
01:28:00,308 --> 01:28:04,045
And you'll hear me
say that again. Thank you.

1686
01:28:09,951 --> 01:28:15,190
Female Speaker: Can you --
I don't want to mess with this.

1687
01:28:15,190 --> 01:28:17,259
Can you hear me?

1688
01:28:17,259 --> 01:28:19,694
Do we have problems
with the microphone?

1689
01:28:19,694 --> 01:28:23,899
You want to come here?
No. No. Are you listening?

1690
01:28:23,899 --> 01:28:25,867
Yeah. We're listening. Okay.

1691
01:28:26,535 --> 01:28:31,339
Well, of course, politics is --

1692
01:28:33,608 --> 01:28:36,578
they are in charge of the
money, of the budget.

1693
01:28:36,578 --> 01:28:39,281
So, when it comes to
newborn screening,

1694
01:28:40,115 --> 01:28:46,254
which we were talking about,
it costs a lot of money.

1695
01:28:46,254 --> 01:28:50,325
Especially if you're talking
about in the whole region

1696
01:28:50,325 --> 01:28:55,630
or in a very big country,
universal screening,

1697
01:28:56,364 --> 01:28:59,000
it takes money, and
it takes expertise,

1698
01:28:59,000 --> 01:29:02,804
and it's a continuum.
That's the problem.

1699
01:29:02,804 --> 01:29:05,907
You can launch the program,
you can put some budget,

1700
01:29:05,907 --> 01:29:07,676
but it needs to be lifelong.

1701
01:29:09,044 --> 01:29:11,913
And the problem is
if you switch government

1702
01:29:11,913 --> 01:29:15,584
and the government has
the power to just stop

1703
01:29:17,052 --> 01:29:22,090
giving money to the program,
the program is going to die.

1704
01:29:22,757 --> 01:29:25,961
So, whether you put this aside

1705
01:29:26,595 --> 01:29:29,364
of what the government
can do -- no.

1706
01:29:30,265 --> 01:29:33,635
By law, you need
to give 10 percent

1707
01:29:33,635 --> 01:29:36,805
of the GDP to healthcare.

1708
01:29:36,805 --> 01:29:40,375
But otherwise, you are
going to be in their hands.

1709
01:29:40,375 --> 01:29:45,714
And if it happens like
we had in Brazil,

1710
01:29:45,714 --> 01:29:48,717
a government that
doesn't care, actually,

1711
01:29:49,351 --> 01:29:51,052
to the health of the people.

1712
01:29:51,052 --> 01:29:53,888
Actually, he told
that there were too many

1713
01:29:53,888 --> 01:29:58,026
Brazilians reading Brazil.
It's a very big problem.

1714
01:30:00,462 --> 01:30:05,100
The programs just were
paused or stopped,

1715
01:30:05,100 --> 01:30:09,871
especially in poor states.

1716
01:30:09,871 --> 01:30:12,474
The state of São Paulo
didn't change

1717
01:30:14,843 --> 01:30:17,145
because it's the
richest state we have.

1718
01:30:17,145 --> 01:30:21,082
But in some regions where
the federal government budget

1719
01:30:22,017 --> 01:30:24,653
is essential, it will not.

1720
01:30:24,653 --> 01:30:28,623
So, vote cautiously.
Voting is important.

1721
01:30:31,593 --> 01:30:33,795
Public health
systems is important

1722
01:30:33,795 --> 01:30:37,532
because the people
cannot afford treatment.

1723
01:30:37,532 --> 01:30:39,801
We perform bone
marrow transplantations

1724
01:30:39,801 --> 01:30:42,437
for free in Brazil.
Not for everyone,

1725
01:30:42,437 --> 01:30:45,473
because we don't have
that many reference centers

1726
01:30:45,473 --> 01:30:46,875
for bone marrow
transplantations.

1727
01:30:46,875 --> 01:30:53,515
It's our goal to start
new reference centers

1728
01:30:53,515 --> 01:30:56,985
for bone marrow transplantations
because gene therapy is coming.

1729
01:30:57,752 --> 01:30:59,187
Yes, but gene therapy --

1730
01:30:59,187 --> 01:31:03,158
you cannot perform that
in an outpatient.

1731
01:31:03,658 --> 01:31:07,629
So, you need to have hospital
beds and reference centers.

1732
01:31:07,629 --> 01:31:10,965
So, we are trying to start
with reference centers

1733
01:31:10,965 --> 01:31:12,567
for bone marrow transplantations

1734
01:31:13,568 --> 01:31:17,238
to have at least one
reference center in each state.

1735
01:31:17,238 --> 01:31:18,473
Because what happens today,

1736
01:31:18,473 --> 01:31:22,744
everyone comes to São Paulo
State to perform BMT.

1737
01:31:23,411 --> 01:31:25,480
And they have to
wait in a long line

1738
01:31:25,480 --> 01:31:28,083
because we have the state
of São Paulo people

1739
01:31:28,083 --> 01:31:30,018
and the other states
coming together.

1740
01:31:30,018 --> 01:31:32,754
So, if we have one
reference center

1741
01:31:32,754 --> 01:31:35,023
like we do in
newborn screening,

1742
01:31:35,023 --> 01:31:38,259
one reference center for newborn
screening in each state,

1743
01:31:38,259 --> 01:31:41,830
one reference center
for sickle cell disease care,

1744
01:31:41,830 --> 01:31:45,066
and one for bone
marrow transplantation,

1745
01:31:45,066 --> 01:31:46,701
I think we're going
to be good to go.

1746
01:31:46,701 --> 01:31:47,969
Female Speaker: I think
we'll stop there.

1747
01:31:47,969 --> 01:31:50,538
I know you had
another bit to your talk,

1748
01:31:50,538 --> 01:31:56,544
but we are 20 minutes delayed,
and we have a long program.

1749
01:31:56,544 --> 01:32:01,383
So, I'm going to encourage --
I'm sorry to cut short --

1750
01:32:02,017 --> 01:32:05,553
because this has really been an
exciting panel and these talks.

1751
01:32:05,553 --> 01:32:07,789
We need to speak about
the registry, et cetera.

1752
01:32:07,789 --> 01:32:09,023
But let's mingle.

1753
01:32:09,023 --> 01:32:11,993
We have a 10 minute
only for a break.

1754
01:32:11,993 --> 01:32:14,829
We are hoping to cut off
by seven to eight minutes

1755
01:32:14,829 --> 01:32:17,799
so we can try to get
back on schedule.

1756
01:32:17,799 --> 01:32:19,701
So, thank you so much,

1757
01:32:20,268 --> 01:32:22,704
all of you,
excellent presenters,

1758
01:32:22,704 --> 01:32:24,839
for leading the morning,
as well as

1759
01:32:24,839 --> 01:32:26,941
[inaudible].
Thank you so much.

1760
01:32:26,941 --> 01:32:29,844
Let's have a short
break -- 10 minutes.

1761
01:32:29,844 --> 01:32:32,013
Zoomers, as well,
can take a stretch break,

1762
01:32:32,013 --> 01:32:35,683
and we'll meet back at 10:30.

1763
01:32:35,683 --> 01:32:41,489
Female Speaker: Okay, welcome
back to session two of day one.

1764
01:32:42,557 --> 01:32:46,261
We all know how complex
sickle cell disease is,

1765
01:32:46,261 --> 01:32:47,862
affecting multiple organs,

1766
01:32:48,963 --> 01:32:53,802
and collaboration across
disciplines is so important.

1767
01:32:54,769 --> 01:32:57,272
And as I come to understand
sickle cell disease,

1768
01:32:57,939 --> 01:33:01,176
it's really very much
a biomechanical disease,

1769
01:33:01,176 --> 01:33:03,011
even though we keep
talking about the root

1770
01:33:03,011 --> 01:33:06,214
cause being hemoglobin
S polymerization.

1771
01:33:07,182 --> 01:33:10,151
But the rascal that
carries out the damage

1772
01:33:10,151 --> 01:33:12,854
is really the red cells
and what it does,

1773
01:33:12,854 --> 01:33:15,123
the red cell membrane skeleton.

1774
01:33:15,123 --> 01:33:19,327
So, I'm so delighted
to actually chair this session

1775
01:33:19,327 --> 01:33:21,162
because we want to talk about

1776
01:33:21,162 --> 01:33:26,267
how we can clinically translate
bioengineering and biophysics

1777
01:33:26,267 --> 01:33:27,635
to better understand

1778
01:33:27,635 --> 01:33:29,971
the pathophysiology
of sickle cell disease.

1779
01:33:30,972 --> 01:33:34,843
And I also have a slight
change in the program.

1780
01:33:35,844 --> 01:33:40,815
Dr. Alan Docter has to give
another virtual presentation,

1781
01:33:40,815 --> 01:33:42,584
so he will follow Wilbur.

1782
01:33:43,284 --> 01:33:46,488
But first, let me start
with Dr. Wilbur Lam,

1783
01:33:47,222 --> 01:33:49,724
who is a tenured
professor of pediatrics

1784
01:33:49,724 --> 01:33:53,895
and biomedical engineering
at Emory University

1785
01:33:53,895 --> 01:33:56,064
and the Georgia
Institute of Technology.

1786
01:33:57,065 --> 01:34:00,001
Wilbur is also the associate
dean of innovation

1787
01:34:00,001 --> 01:34:03,004
at Emory University
School of Medicine.

1788
01:34:03,004 --> 01:34:08,142
Wilbur is no stranger to SCIF,
and I'm so delighted

1789
01:34:08,142 --> 01:34:10,311
that he could make it
in person this time.

1790
01:34:10,912 --> 01:34:12,514
Thank you very much, Wilbur.

1791
01:34:13,047 --> 01:34:15,483
The other thing I want
to remind all speakers is,

1792
01:34:16,117 --> 01:34:19,220
we have to be very strict with
timing. Nona [phonetic sp]

1793
01:34:19,220 --> 01:34:22,924
will show me when time's
up after 25 minutes.

1794
01:34:22,924 --> 01:34:24,893
I will actually
physically yank you off,

1795
01:34:26,494 --> 01:34:27,862
so be warned,

1796
01:34:27,862 --> 01:34:31,866
because we cannot eat
into other speakers' time.

1797
01:34:32,901 --> 01:34:34,502
Thank you, Wilbur.

1798
01:34:36,771 --> 01:34:39,440
Wilbur Lam: Okay,
I better hurry.

1799
01:34:39,440 --> 01:34:42,577
I don't want to be wrestled
by Svila [phonetic sp].

1800
01:34:42,577 --> 01:34:45,780
So thank you so much
for having me,

1801
01:34:46,347 --> 01:34:50,552
and thank you for letting me
talk about a topic

1802
01:34:50,552 --> 01:34:53,121
that I personally think
about quite a bit,

1803
01:34:53,121 --> 01:34:57,926
and also to show that there's a
growing community in this field.

1804
01:34:57,926 --> 01:35:02,397
So, I'll talk about this
technology called microfluidics.

1805
01:35:02,397 --> 01:35:03,998
And it's something,
like I said,

1806
01:35:03,998 --> 01:35:06,534
I've certainly been
thinking about for a while.

1807
01:35:07,335 --> 01:35:10,305
And I should give
my disclosures,

1808
01:35:10,305 --> 01:35:14,609
first of all, that
I am a co-founder

1809
01:35:14,609 --> 01:35:17,078
of a couple of
diagnostic companies.

1810
01:35:17,078 --> 01:35:21,115
And also, that this talk
is actually not done just by me,

1811
01:35:21,115 --> 01:35:25,219
but a couple of my close
collaborators in Atlanta --

1812
01:35:25,219 --> 01:35:28,856
Dr. Vivian Sheehan and
also Kendall Williams

1813
01:35:28,856 --> 01:35:30,825
and Bev Rogers, who
are pathologists.

1814
01:35:30,825 --> 01:35:32,193
So, clinical laboratorians

1815
01:35:32,193 --> 01:35:33,928
who work in the field
of diagnostics.

1816
01:35:33,928 --> 01:35:35,363
And that's actually
one point that I want

1817
01:35:35,363 --> 01:35:37,665
to make-that we here,
as clinicians,

1818
01:35:37,665 --> 01:35:40,101
need to work with
our pathology colleagues

1819
01:35:40,101 --> 01:35:43,071
when we're really talking
about new diagnostic tests,

1820
01:35:43,071 --> 01:35:45,607
because this is what
they think about 24/7,

1821
01:35:45,607 --> 01:35:49,210
how to bring something
to practice and implement it.

1822
01:35:49,210 --> 01:35:52,647
Okay. So, you know,
Sui-Lei [phonetic sp],

1823
01:35:52,647 --> 01:35:54,682
when you invited me
to give this talk,

1824
01:35:54,682 --> 01:35:57,585
it really reminded me
of when I first gave it.

1825
01:35:57,585 --> 01:36:02,357
So this goes back to 2013,

1826
01:36:02,357 --> 01:36:06,494
when you invited me to give
a very similar talk in London.

1827
01:36:06,494 --> 01:36:11,733
And this is June 7, 2013.
And I believe when we met,

1828
01:36:11,733 --> 01:36:13,434
Sui-Lei, you looked
at me and you said,

1829
01:36:13,434 --> 01:36:14,769
"You look like a schoolboy."

1830
01:36:14,769 --> 01:36:15,970
[laughter]

1831
01:36:15,970 --> 01:36:18,339
I do not have that
problem anymore, right?

1832
01:36:20,608 --> 01:36:24,912
So, in fact, just the other day,
one of my grad students and I --

1833
01:36:24,912 --> 01:36:27,048
my brand-new grad student
and I -- we were walking,

1834
01:36:27,048 --> 01:36:29,684
and we have these doors
at Georgia Tech

1835
01:36:29,684 --> 01:36:32,387
where you put your key card.
And I put my wallet on.

1836
01:36:32,387 --> 01:36:36,924
My wallet dropped, and
she sees my driver's license.

1837
01:36:36,924 --> 01:36:38,293
She sees my date of birth.

1838
01:36:38,293 --> 01:36:40,828
She turns ashen. And I
said, "What's wrong?"

1839
01:36:40,828 --> 01:36:43,464
She goes, "I didn't know
you were that old."

1840
01:36:44,832 --> 01:36:46,534
And I can tell
she's already thinking,

1841
01:36:46,534 --> 01:36:47,869
"Oh my God, I need a new Ph.D.

1842
01:36:47,869 --> 01:36:50,705
advisor because this guy's
going to be dead by next year."

1843
01:36:50,705 --> 01:36:52,607
Anyway, so thank you
for the opportunity.

1844
01:36:52,607 --> 01:36:54,809
But it also shows
that this is stuff

1845
01:36:54,809 --> 01:36:57,478
that we've been thinking
about as a field for a while.

1846
01:36:57,478 --> 01:37:01,282
We talked about a technology
called microfluidics

1847
01:37:01,282 --> 01:37:05,320
and how that could help us move
the field of sickle cell disease

1848
01:37:05,320 --> 01:37:09,457
and potentially as a biomarker
or diagnostic tool.

1849
01:37:10,191 --> 01:37:12,627
So what is this? What
is this weird word?

1850
01:37:12,627 --> 01:37:16,731
So, really, all it is
is just a small gadget

1851
01:37:17,632 --> 01:37:20,568
in which it deals
with small amounts of fluid

1852
01:37:21,402 --> 01:37:23,604
in these little tiny channels.
It's about plumbing.

1853
01:37:23,604 --> 01:37:26,708
And when you shrink down,
it allows a few things.

1854
01:37:26,708 --> 01:37:28,810
It reduces reagent consumption,

1855
01:37:28,810 --> 01:37:32,046
increases speed,
analytical performance,

1856
01:37:32,046 --> 01:37:35,616
allows automation, integration
of different complex workflows,

1857
01:37:35,616 --> 01:37:37,885
maybe multi-parameter testing,

1858
01:37:37,885 --> 01:37:42,724
and the possibility of
point-of-care clinical testing.

1859
01:37:43,324 --> 01:37:47,028
So, there have been technologies
that have been moved

1860
01:37:47,028 --> 01:37:50,331
into clinical implementation,
and large companies like Abbott

1861
01:37:50,331 --> 01:37:53,201
have already made products
in this space.

1862
01:37:53,201 --> 01:37:56,404
From the research side,
we're already all doing this.

1863
01:37:56,404 --> 01:37:59,140
So you might have heard
of spatial transcriptomics,

1864
01:37:59,140 --> 01:38:00,408
single-cell sequencing.

1865
01:38:00,408 --> 01:38:02,710
Those all leverage
these technologies

1866
01:38:02,710 --> 01:38:04,812
that are technically
called microfluidics.

1867
01:38:05,346 --> 01:38:06,614
So what are microfluidics?

1868
01:38:06,614 --> 01:38:08,416
Well, really, it's
the technology

1869
01:38:08,416 --> 01:38:10,952
that you all have right
now on your laptops,

1870
01:38:10,952 --> 01:38:13,654
on your cell phones.
It's microchip technologies.

1871
01:38:13,654 --> 01:38:16,591
Microchip technologies
that have been pivoted

1872
01:38:16,591 --> 01:38:18,593
and changed a little bit --
modified a little bit.

1873
01:38:18,593 --> 01:38:22,797
Instead of metallic
silicon chips,

1874
01:38:22,797 --> 01:38:25,833
we're now dealing, in
general, with a polymer.

1875
01:38:25,833 --> 01:38:28,569
With typically,
the most common polymer

1876
01:38:28,569 --> 01:38:32,240
is something called
polymethyldialoxane, PDMS.

1877
01:38:32,240 --> 01:38:33,541
And it's transparent.

1878
01:38:33,541 --> 01:38:36,010
It's really good for
things like microscopy.

1879
01:38:36,010 --> 01:38:38,379
It also happens to
be gas-permeable,

1880
01:38:38,379 --> 01:38:40,281
which is nice for us
in sickle cell disease

1881
01:38:40,281 --> 01:38:42,750
because then we can mess
with oxygen tension.

1882
01:38:42,750 --> 01:38:44,418
It can be functionalized.

1883
01:38:44,418 --> 01:38:46,554
It can be integrated
with other sensors.

1884
01:38:46,554 --> 01:38:49,023
One not-so-great thing, which
I'll come back to later,

1885
01:38:49,023 --> 01:38:51,159
is that this is not so great
for manufacturing.

1886
01:38:51,159 --> 01:38:53,327
Now, again, if we're thinking
of an actual product,

1887
01:38:53,327 --> 01:38:55,797
those are important
things to consider.

1888
01:38:55,797 --> 01:39:03,070
Okay. So this was my very first
foray into using microfluidics.

1889
01:39:03,070 --> 01:39:04,939
This is something I made
as a grad student many,

1890
01:39:04,939 --> 01:39:06,240
many years ago now.

1891
01:39:06,240 --> 01:39:08,109
And I took blood
from a healthy subject

1892
01:39:08,109 --> 01:39:09,410
when I was in grad school.

1893
01:39:09,410 --> 01:39:11,379
No one wanted to sit next
to me in grad school

1894
01:39:11,379 --> 01:39:13,281
because I always
stuck them for blood.

1895
01:39:13,281 --> 01:39:17,318
And then I took the same device
and brought it to my clinic

1896
01:39:17,318 --> 01:39:21,389
when I was a fellow
in pediatric hematology/oncology

1897
01:39:21,389 --> 01:39:22,957
at University of
California, San Francisco,

1898
01:39:22,957 --> 01:39:26,160
and I just perfused a sickle
cell patient's blood --

1899
01:39:26,160 --> 01:39:27,795
whole blood -- and you
can see right then

1900
01:39:27,795 --> 01:39:30,264
and there, wow,
there's something here.

1901
01:39:30,264 --> 01:39:32,800
That these relatively
simple devices,

1902
01:39:32,800 --> 01:39:34,101
when put under a microscope,

1903
01:39:34,101 --> 01:39:38,739
can recapitulate aspects
of sickle cell pathophysiology.

1904
01:39:38,739 --> 01:39:41,776
Okay, so can we translate
these technologies

1905
01:39:41,776 --> 01:39:45,046
to study sickle cell disease?
And now the question is,

1906
01:39:45,046 --> 01:39:47,915
can we even bring them
to the clinical side?

1907
01:39:47,915 --> 01:39:51,652
Can we make clinical decisions
with assays like these?

1908
01:39:51,652 --> 01:39:54,422
That's the big question that the
field is trying to deal with.

1909
01:39:54,422 --> 01:39:56,591
So, a little bit
of what my lab does,

1910
01:39:56,591 --> 01:39:59,660
since I've been in Atlanta
the last 12 or 13 years now,

1911
01:39:59,660 --> 01:40:01,863
we study the biophysics
of hematology.

1912
01:40:01,863 --> 01:40:05,233
And we also create
new technologies

1913
01:40:05,233 --> 01:40:07,835
and new devices with
microfluidics, and so forth.

1914
01:40:07,835 --> 01:40:09,203
We're always very interested

1915
01:40:09,203 --> 01:40:11,172
in trying to translate
these devices

1916
01:40:11,172 --> 01:40:13,908
that we make into
point-of-care diagnostics,

1917
01:40:13,908 --> 01:40:15,676
even home-based diagnostics,

1918
01:40:15,676 --> 01:40:17,945
and then bringing them back
to the patients

1919
01:40:17,945 --> 01:40:19,380
that I see on a
regular basis.

1920
01:40:19,380 --> 01:40:21,816
So, that's the space
that my laboratory lives in.

1921
01:40:22,450 --> 01:40:26,821
And this was something
I originally talked about,

1922
01:40:26,821 --> 01:40:29,991
Svila, in 2013. It was a
technology we developed

1923
01:40:30,691 --> 01:40:32,693
in which we grow
endothelial cells

1924
01:40:32,693 --> 01:40:34,362
in these very,
very small channels.

1925
01:40:34,362 --> 01:40:37,899
The lab -- not myself anymore,
but the guys in the lab --

1926
01:40:37,899 --> 01:40:39,600
can almost grow
endothelial cells in anything.

1927
01:40:39,600 --> 01:40:40,835
That was pretty crazy.

1928
01:40:40,835 --> 01:40:43,237
But this was a study
that we published

1929
01:40:43,237 --> 01:40:46,440
in 2012 in collaboration
with Russell Ware.

1930
01:40:46,440 --> 01:40:49,143
And what we showed is
that, yeah, in general,

1931
01:40:49,143 --> 01:40:51,045
these things kind of work.

1932
01:40:51,045 --> 01:40:54,782
They're good to study aspects
of sickle cell disease.

1933
01:40:54,782 --> 01:40:59,153
What you have here is
blood from a patient

1934
01:40:59,153 --> 01:41:04,458
with hemoglobin SS on the left,
blood from a patient

1935
01:41:04,458 --> 01:41:07,962
also with hemoglobin
S on hydroxyurea.

1936
01:41:07,962 --> 01:41:11,499
We now use these videos
in our clinic in Atlanta

1937
01:41:11,499 --> 01:41:14,168
to show patients, like,
"Look, this is what happens.

1938
01:41:14,168 --> 01:41:15,536
This is why
hydroxyurea is good."

1939
01:41:15,536 --> 01:41:16,771
Okay, great.

1940
01:41:16,771 --> 01:41:19,440
So this microvascular
chip platform

1941
01:41:20,007 --> 01:41:23,010
can serve as an in
vitro model of disease.

1942
01:41:23,010 --> 01:41:25,079
That's great for
different applications.

1943
01:41:25,079 --> 01:41:28,716
So, fast forward a little bit.
What else can microfluidics do?

1944
01:41:28,716 --> 01:41:30,117
Well, it's really good
for research.

1945
01:41:30,117 --> 01:41:32,286
In fact, there's
a brand-new paper

1946
01:41:32,286 --> 01:41:35,589
that's still in press in Blood.
I won't belabor the point,

1947
01:41:35,589 --> 01:41:37,325
but we have actually
used microfluidics

1948
01:41:37,325 --> 01:41:39,927
to figure out a new
aspect of pathophysiology

1949
01:41:39,927 --> 01:41:42,563
in sickle cell disease
when it comes to vasculopathy.

1950
01:41:43,965 --> 01:41:46,167
I can talk to you
about this for an hour.

1951
01:41:46,167 --> 01:41:49,971
But the bottom line is that,
using microfluidic platforms,

1952
01:41:49,971 --> 01:41:53,374
we have shown that
the biophysical alterations

1953
01:41:53,374 --> 01:41:55,509
of sickle cells themselves

1954
01:41:56,344 --> 01:42:00,615
enable them to marginate more
toward the vascular wall,

1955
01:42:00,615 --> 01:42:03,184
therefore causing
the endothelial cells

1956
01:42:03,918 --> 01:42:05,720
to become more inflamed.

1957
01:42:05,720 --> 01:42:08,489
So, this is a new aspect
of vasculopathy

1958
01:42:08,489 --> 01:42:10,191
that is distinct
from vaso-occlusion,

1959
01:42:10,191 --> 01:42:13,594
that's distinct from hemolysis,
it's distinct from adhesion,

1960
01:42:13,594 --> 01:42:18,466
but maybe it allows us to think
about how this vasculopathy

1961
01:42:18,466 --> 01:42:20,901
is connected with
sickle cell disease.

1962
01:42:20,901 --> 01:42:24,505
And maybe it can help us
explain the pathophysiology

1963
01:42:24,505 --> 01:42:27,641
of the underlying vasculopathy
that then predisposes to stroke,

1964
01:42:27,641 --> 01:42:28,943
like in our kids.

1965
01:42:28,943 --> 01:42:32,279
So, again, great
platform to answer

1966
01:42:32,279 --> 01:42:33,914
some of these
research questions.

1967
01:42:33,914 --> 01:42:35,883
And this was done
by Christina Caruso,

1968
01:42:35,883 --> 01:42:37,218
who's a junior faculty
in the lab

1969
01:42:37,218 --> 01:42:39,286
and a pediatric
hematologist/oncologist

1970
01:42:39,286 --> 01:42:40,888
who will be moving
to New York.

1971
01:42:40,888 --> 01:42:44,625
Sad for us, but she's starting
her own faculty position.

1972
01:42:45,159 --> 01:42:47,862
Okay. So, what value, then,

1973
01:42:47,862 --> 01:42:51,165
do these assays bring
to our field in hematology?

1974
01:42:51,165 --> 01:42:54,935
Again, I told you,
great as enabling research.

1975
01:42:54,935 --> 01:42:57,505
They're good in
vitro disease models.

1976
01:42:57,505 --> 01:42:59,840
They're also very
good at using --

1977
01:42:59,840 --> 01:43:03,411
if you have questions about
specific mechanisms of action.

1978
01:43:03,411 --> 01:43:05,146
You can now take
a reductionist approach

1979
01:43:05,146 --> 01:43:07,515
to really tease out some of
these biophysical aspects

1980
01:43:07,515 --> 01:43:09,650
when there is a drug
that's related.

1981
01:43:09,650 --> 01:43:12,620
So, pharma has come
to us recently --

1982
01:43:12,620 --> 01:43:15,823
all the pharmaceutical companies
that you guys know about --

1983
01:43:15,823 --> 01:43:17,792
when they're wanting
to explore questions

1984
01:43:17,792 --> 01:43:20,895
about their therapeutic agent
in sickle cell disease.

1985
01:43:20,895 --> 01:43:22,763
We've had several
contracts with them.

1986
01:43:23,330 --> 01:43:25,766
Great as pre-diagnostic tools.

1987
01:43:25,766 --> 01:43:28,169
And I'll focus on
that prefix, "pre."

1988
01:43:29,437 --> 01:43:31,005
And in informing
clinical trials.

1989
01:43:31,005 --> 01:43:34,675
So, Marcus Carden, when he was
a fellow in my laboratory,

1990
01:43:34,675 --> 01:43:38,512
did some really interesting
experiments using microfluidics,

1991
01:43:38,512 --> 01:43:41,615
showing that when you
give different IV fluids --

1992
01:43:41,615 --> 01:43:44,452
different clinically
available IV fluids --

1993
01:43:44,452 --> 01:43:46,754
the adhesion and the
deformability actually change.

1994
01:43:46,754 --> 01:43:50,524
And that actually begot
several large clinical trials.

1995
01:43:50,524 --> 01:43:52,860
And the most recent one
was just published,

1996
01:43:52,860 --> 01:43:55,196
I think, this month,
really showing

1997
01:43:55,196 --> 01:43:56,530
that, yeah, normal saline

1998
01:43:56,530 --> 01:43:59,300
compared to lactated
Ringer's is actually bad.

1999
01:43:59,300 --> 01:44:03,537
So, microfluidics were a great
way to generate a hypothesis.

2000
01:44:03,537 --> 01:44:05,639
So, all this is great,

2001
01:44:05,639 --> 01:44:10,244
but the question really is
clinical translation, right?

2002
01:44:10,244 --> 01:44:13,247
Can these things really
be used to inform

2003
01:44:13,247 --> 01:44:14,615
clinical decision-making?

2004
01:44:14,615 --> 01:44:16,617
So the field has
gotten much bigger.

2005
01:44:16,617 --> 01:44:18,285
So I have plenty of
friends now in this field,

2006
01:44:18,285 --> 01:44:20,221
many of whom you
collaborate with them.

2007
01:44:21,655 --> 01:44:23,290
If you look at the
number of papers

2008
01:44:23,290 --> 01:44:25,159
published in sickle cell
disease and microfluidics,

2009
01:44:25,159 --> 01:44:29,363
it's certainly come up
since I've been in this space.

2010
01:44:29,363 --> 01:44:31,732
So, there's groups
like Nicola Karr [phonetic sp]

2011
01:44:31,732 --> 01:44:36,837
and Conrad in Brazil,
Umut Gurkan's group in Case,

2012
01:44:36,837 --> 01:44:42,543
and Sarah Du in Florida,
Dave Wood in Minnesota.

2013
01:44:42,543 --> 01:44:44,612
All of these are people
in our community

2014
01:44:44,612 --> 01:44:45,913
that are all developing

2015
01:44:45,913 --> 01:44:48,549
and leveraging
microfluidic technologies

2016
01:44:48,549 --> 01:44:50,751
to really push the field
for sickle cell disease,

2017
01:44:50,751 --> 01:44:53,387
but also constantly
asking the question,

2018
01:44:53,387 --> 01:44:57,625
can we use these things
for clinical decision-making?

2019
01:44:58,259 --> 01:44:59,460
Luckily, there's
a few groups

2020
01:44:59,460 --> 01:45:02,129
that have already
started companies to work

2021
01:45:02,129 --> 01:45:03,964
with folks like yourselves
in the industry.

2022
01:45:03,964 --> 01:45:09,136
Patrick Hines has Functional
Fluidics, Umut's Biochip Labs --

2023
01:45:09,136 --> 01:45:12,239
all are trying to leverage
these devices

2024
01:45:13,174 --> 01:45:18,879
as assays that can try to inform
clinical decision-making.

2025
01:45:18,879 --> 01:45:21,415
All right. Now, I'm going
to give a slight detour

2026
01:45:21,415 --> 01:45:24,785
about things that I've done that
I think is hopefully related.

2027
01:45:24,785 --> 01:45:29,924
So I lead an NIH-funded

2028
01:45:29,924 --> 01:45:32,226
via the National Institute
of Biomedical Imaging

2029
01:45:32,226 --> 01:45:33,494
and Bioengineering,

2030
01:45:33,494 --> 01:45:35,229
where the good Dr. Platt
now works.

2031
01:45:36,363 --> 01:45:40,968
And we are part of the NIH's
Point of Care Technologies

2032
01:45:40,968 --> 01:45:44,071
Research Network. We
are here in Atlanta.

2033
01:45:44,071 --> 01:45:45,906
We have a very, very,
very long name.

2034
01:45:46,540 --> 01:45:49,410
Our nickname is just ACME
for short, so we just say ACME.

2035
01:45:49,910 --> 01:45:53,981
So, the reason I mention this
is because before 2020,

2036
01:45:53,981 --> 01:45:56,984
we were charged with
helping other folks

2037
01:45:56,984 --> 01:46:00,421
develop point-of-care tests
for numerous applications,

2038
01:46:00,421 --> 01:46:05,059
not just sickle cell disease.
And then this happened, right?

2039
01:46:05,059 --> 01:46:11,098
So I was called to a
Zoom on April 20, 2020.

2040
01:46:11,098 --> 01:46:12,933
Okay, so it was
a while ago now.

2041
01:46:12,933 --> 01:46:15,703
And remember, Zoom
had just started.

2042
01:46:15,703 --> 01:46:17,104
So I remember waking up.

2043
01:46:17,104 --> 01:46:20,074
It was like 07:30 a.m.
I was straight out of bed.

2044
01:46:20,074 --> 01:46:22,309
I go to my e-mail.
It says, oh, NIH Zoom.

2045
01:46:22,309 --> 01:46:24,712
And I push on it. Remember,
I just got out of bed.

2046
01:46:24,712 --> 01:46:26,680
I don't have a shirt on, right?

2047
01:46:26,680 --> 01:46:28,482
So on the other
end was this guy.

2048
01:46:29,583 --> 01:46:32,987
So, former NIH director
Francis Collins.

2049
01:46:32,987 --> 01:46:35,322
And I'm like
immediately, oh, my God.

2050
01:46:35,322 --> 01:46:37,291
I couldn't find the button
to turn off the camera

2051
01:46:37,291 --> 01:46:38,892
because it was brand new.

2052
01:46:39,593 --> 01:46:42,429
I'm like ducking under
and I'm screaming to my wife,

2053
01:46:42,429 --> 01:46:44,465
get me a shirt.

2054
01:46:44,465 --> 01:46:48,936
So, what had happened
was Dr. Collins explained to me

2055
01:46:48,936 --> 01:46:52,539
that there's this new disease.
We need new diagnostics.

2056
01:46:52,539 --> 01:46:55,142
We need point-of-care
diagnostics.

2057
01:46:55,142 --> 01:46:58,445
And you are the director
of your center that's part

2058
01:46:58,445 --> 01:47:01,181
of our NIH point-of-care
technologies network.

2059
01:47:01,181 --> 01:47:03,751
We're going to create
a brand-new initiative.

2060
01:47:03,751 --> 01:47:06,654
And it was going to be
called the RADx Initiative --

2061
01:47:06,654 --> 01:47:08,622
Rapid Acceleration
of Diagnostics.

2062
01:47:08,622 --> 01:47:12,459
So, what that meant was that at
the beginning of the pandemic,

2063
01:47:12,459 --> 01:47:14,895
the United States government
actually turned itself

2064
01:47:14,895 --> 01:47:16,563
into almost
a venture capitalist

2065
01:47:17,931 --> 01:47:21,201
when it came
to identifying, vetting,

2066
01:47:21,201 --> 01:47:24,705
and then mass-producing
rapid diagnostic tests.

2067
01:47:25,339 --> 01:47:28,509
So, if you think about
how long it takes,

2068
01:47:28,509 --> 01:47:30,978
and this will be relevant
at the end of my discussion,

2069
01:47:30,978 --> 01:47:33,514
how long it takes
a diagnostic test

2070
01:47:33,514 --> 01:47:36,850
to actually come to market,
once the biomarker is validated,

2071
01:47:36,850 --> 01:47:41,221
it takes, on average,
10 to 15 years to get to market.

2072
01:47:41,221 --> 01:47:42,823
That is the average.

2073
01:47:42,823 --> 01:47:48,062
What RADx's goal was to shrink
that down to one to two years.

2074
01:47:48,062 --> 01:47:49,897
And frankly,
it actually worked.

2075
01:47:49,897 --> 01:47:53,100
But what it entailed
was this kind

2076
01:47:53,100 --> 01:47:56,603
of very venture
capitalist-like perspective

2077
01:47:56,603 --> 01:47:59,139
where they took
in all applications.

2078
01:47:59,139 --> 01:48:01,175
We had over 1,000 applications,

2079
01:48:01,175 --> 01:48:02,910
and there was going to be
this vetting process.

2080
01:48:02,910 --> 01:48:05,346
Phase 1 is going to be
a Shark Tank-like process,

2081
01:48:05,346 --> 01:48:07,715
and that was named
by a couple senators

2082
01:48:07,715 --> 01:48:09,183
who, I guess,
watch TV a lot,

2083
01:48:09,183 --> 01:48:11,318
and they said,
let's do it like Shark Tank.

2084
01:48:11,318 --> 01:48:13,020
And then there's validation.

2085
01:48:13,020 --> 01:48:14,755
So, that's where
our center came in,

2086
01:48:14,755 --> 01:48:18,459
because we were part
of the network,

2087
01:48:18,459 --> 01:48:21,829
and our core capabilities

2088
01:48:21,829 --> 01:48:24,565
was about technology
and engineering.

2089
01:48:24,565 --> 01:48:27,167
So, we functioned
as the verification center

2090
01:48:27,167 --> 01:48:31,705
for the entire NIH when it came
to COVID-19 diagnostics.

2091
01:48:31,705 --> 01:48:34,508
So, every
single COVID rapid test

2092
01:48:34,508 --> 01:48:38,379
that entered the U.S. market
came to us first for evaluation.

2093
01:48:38,379 --> 01:48:39,813
So how did we do this?

2094
01:48:39,813 --> 01:48:42,683
We created a huge
infrastructure, a giant biobank.

2095
01:48:42,683 --> 01:48:45,219
We actually have
the largest COVID-19 biobank

2096
01:48:45,219 --> 01:48:47,421
in the country at Emory
and at Georgia Tech.

2097
01:48:47,421 --> 01:48:51,025
Every single variant,
every single genetic mutation.

2098
01:48:51,625 --> 01:48:56,397
We were one of the first to use
our biosafety level 3 labs,

2099
01:48:56,397 --> 01:48:57,731
and we were also
one of the first

2100
01:48:57,731 --> 01:48:59,199
to actually go out
to the communities

2101
01:48:59,199 --> 01:49:03,404
and collect all these samples,
all drive-thrus and so forth.

2102
01:49:03,404 --> 01:49:05,839
And importantly, and this
goes back to my conversation

2103
01:49:05,839 --> 01:49:07,374
I'll talk about a little bit,

2104
01:49:07,374 --> 01:49:11,078
we learned about how to assess
technology readiness level.

2105
01:49:11,078 --> 01:49:13,981
Like, when is something mature
enough to go to the next step?

2106
01:49:13,981 --> 01:49:17,551
And usability and human factors
we found is so important,

2107
01:49:17,551 --> 01:49:18,952
and I'll come back
to all that.

2108
01:49:18,952 --> 01:49:21,455
Okay, so this is just
the summary

2109
01:49:21,455 --> 01:49:23,524
of everything that
we've done for RADx.

2110
01:49:23,524 --> 01:49:27,861
The point is, we remain very
active for other diseases.

2111
01:49:27,861 --> 01:49:29,696
Right now, we're helping them
deal with H5N1,

2112
01:49:29,696 --> 01:49:30,898
you know, bird flu.

2113
01:49:30,898 --> 01:49:34,735
That's a major issue,
but also related to hepatitis B,

2114
01:49:34,735 --> 01:49:37,538
which is now
Francis Collins' big --

2115
01:49:38,539 --> 01:49:40,374
hepatitis C, excuse me --

2116
01:49:40,374 --> 01:49:43,944
one of his big initiatives
with the Biden administration.

2117
01:49:44,778 --> 01:49:48,582
And what we've learned, however,
is some really important things

2118
01:49:48,582 --> 01:49:50,517
that can translate
to other diagnostics,

2119
01:49:50,517 --> 01:49:52,486
including those
with microfluidics.

2120
01:49:52,486 --> 01:49:54,955
So, RADx did what
it was supposed to do --

2121
01:49:54,955 --> 01:49:56,990
force fast failure.

2122
01:49:56,990 --> 01:50:00,527
But out of the ones that failed,
why did they fail, right?

2123
01:50:00,527 --> 01:50:01,762
What lessons we have
learned here?

2124
01:50:01,762 --> 01:50:03,297
So, we did an analysis here.

2125
01:50:03,297 --> 01:50:05,098
I'm going to speed up
a little bit,

2126
01:50:05,098 --> 01:50:08,202
but the bottom line
is that we found

2127
01:50:08,202 --> 01:50:10,103
that out of all the tests
that failed,

2128
01:50:10,103 --> 01:50:12,906
and these are COVID tests,
the main reason they failed

2129
01:50:12,906 --> 01:50:16,376
wasn't that they didn't work
technologically;

2130
01:50:16,376 --> 01:50:19,947
it was that they couldn't
be manufactured easily.

2131
01:50:19,947 --> 01:50:24,184
The design wasn't so great
that it allowed the user

2132
01:50:24,184 --> 01:50:27,154
to have it be messed up,

2133
01:50:27,154 --> 01:50:28,755
you know,
mess it up all the time,

2134
01:50:28,755 --> 01:50:31,325
and usability -- those were
really the key factors

2135
01:50:31,325 --> 01:50:32,693
that would kill the technology.

2136
01:50:32,693 --> 01:50:35,496
It wasn't how sensitive it was,
it wasn't how specific it was --

2137
01:50:35,496 --> 01:50:37,130
it was usually
these things, right?

2138
01:50:37,130 --> 01:50:40,434
So, we're really taking
those lessons learned.

2139
01:50:41,134 --> 01:50:46,173
So we're also learning
quite a bit about human factors.

2140
01:50:46,173 --> 01:50:48,809
So, I think, we had
a few speakers talk

2141
01:50:48,809 --> 01:50:51,178
about lateral flow tests,
and so forth.

2142
01:50:51,178 --> 01:50:53,146
Well, you can actually
mess that up

2143
01:50:53,146 --> 01:50:54,481
in terms of its manufacture

2144
01:50:54,481 --> 01:50:58,585
if you mislabel
the control and test line.

2145
01:50:58,585 --> 01:51:01,989
The bottom line here is that
we have started to create

2146
01:51:01,989 --> 01:51:05,392
a whole set of knowledge
when it comes to human factors

2147
01:51:05,392 --> 01:51:08,495
and how it can be applied
to point-of-care tests,

2148
01:51:08,495 --> 01:51:09,863
including those
for microfluidics.

2149
01:51:09,863 --> 01:51:12,165
So, now we're collaborating
with the FDA,

2150
01:51:12,165 --> 01:51:15,769
who want us to help them
craft microfluidic guidelines

2151
01:51:15,769 --> 01:51:18,071
in terms of bringing
those technologies

2152
01:51:18,071 --> 01:51:20,874
to clinical practice,

2153
01:51:20,874 --> 01:51:22,476
and especially
at the point-of-care.

2154
01:51:22,476 --> 01:51:24,144
So, sometimes simplicity

2155
01:51:24,144 --> 01:51:25,879
actually trumps
technological features.

2156
01:51:25,879 --> 01:51:27,614
That's something
that we've learned quite a bit,

2157
01:51:27,614 --> 01:51:28,849
and we're RADx.

2158
01:51:28,849 --> 01:51:30,517
Okay, so how do we
bring that all back?

2159
01:51:30,517 --> 01:51:32,786
You know, what are we thinking
of when we talk about,

2160
01:51:32,786 --> 01:51:35,122
like Sui-Lei said,
how in hematology,

2161
01:51:35,122 --> 01:51:36,957
and especially
in sickle cell disease,

2162
01:51:36,957 --> 01:51:39,359
we're dealing with
a mechanical disease, right?

2163
01:51:39,359 --> 01:51:40,961
So, there's some issues here.

2164
01:51:41,528 --> 01:51:46,900
And we were part
of a workshop in 2021

2165
01:51:46,900 --> 01:51:49,736
that the NHLBI wanted us
to really talk about.

2166
01:51:49,736 --> 01:51:51,371
You know, how do
we bring microfluidics

2167
01:51:51,371 --> 01:51:54,408
to the forefront
of clinical medicine?

2168
01:51:54,408 --> 01:51:57,277
And a group of us,
led by myself,

2169
01:51:57,277 --> 01:52:00,213
Dave Wood, and Umut Gurkan,
we actually convened

2170
01:52:01,048 --> 01:52:04,351
all the brain trust
of microfluidics engineers

2171
01:52:04,351 --> 01:52:05,886
and hematologists,

2172
01:52:05,886 --> 01:52:08,655
and we came up
with a framework about,

2173
01:52:08,655 --> 01:52:10,857
well, what are
all the issues?

2174
01:52:10,857 --> 01:52:12,459
So, I mentioned some of them
already,

2175
01:52:12,459 --> 01:52:14,695
but what you can see
in general here,

2176
01:52:14,695 --> 01:52:16,063
in the interest of time,

2177
01:52:16,063 --> 01:52:18,398
is when you're dealing
with blood

2178
01:52:18,398 --> 01:52:20,434
and you've got to load
blood into something,

2179
01:52:20,434 --> 01:52:22,903
you've got all these pumps
and you've got these pipes --

2180
01:52:22,903 --> 01:52:24,271
that can screw things up.

2181
01:52:24,271 --> 01:52:27,574
When you're dealing with all
these complex interconnections,

2182
01:52:27,574 --> 01:52:28,842
that can screw things up.

2183
01:52:28,842 --> 01:52:32,913
When you're designing things
that aren't for the end user

2184
01:52:32,913 --> 01:52:35,382
in mind, for example,
if it's at the point of care,

2185
01:52:35,382 --> 01:52:38,352
then it has to be designed
for someone who operates there,

2186
01:52:38,352 --> 01:52:40,887
maybe a nurse, maybe even
a clinical technician --

2187
01:52:40,887 --> 01:52:42,689
not someone with a Ph.D.

2188
01:52:42,689 --> 01:52:44,524
So, those have
always been problems

2189
01:52:44,524 --> 01:52:47,694
that have stymied the field.
We've identified these problems.

2190
01:52:48,495 --> 01:52:53,567
Often, when we're talking about
microfluidics, we show it off.

2191
01:52:53,567 --> 01:52:55,002
We show,
"Oh, look how small it is.

2192
01:52:55,002 --> 01:52:57,004
Look how great it is."
You know what?

2193
01:52:57,004 --> 01:53:00,173
There's usually a lot more
other equipment around it.

2194
01:53:00,173 --> 01:53:03,076
In fact, one of my friends
at Penn, Scott Diamond,

2195
01:53:03,076 --> 01:53:07,414
he says the joke
about this field

2196
01:53:07,414 --> 01:53:09,483
is that we call it
"lab on a chip,"

2197
01:53:09,483 --> 01:53:11,985
but it's actually
"lab around a chip."

2198
01:53:11,985 --> 01:53:14,087
So, sometimes there's
a giant microscope.

2199
01:53:14,087 --> 01:53:16,657
Sometimes there's like
a $100,000

2200
01:53:16,657 --> 01:53:19,293
to $500,000 microscope
that's attached to it.

2201
01:53:19,293 --> 01:53:21,728
I'm like, "Well, that's not
quite point of care."

2202
01:53:22,629 --> 01:53:25,032
So, those are things
that we're talking about.

2203
01:53:25,032 --> 01:53:27,334
Also, now that we're
dealing with blood --

2204
01:53:27,334 --> 01:53:29,403
and if we're talking
about things like viscosity,

2205
01:53:29,403 --> 01:53:31,405
which we talk about all the time
in sickle cell disease --

2206
01:53:31,405 --> 01:53:32,606
guess what?

2207
01:53:32,606 --> 01:53:34,241
That's actually really complex,

2208
01:53:34,241 --> 01:53:37,010
especially when you're talking
about the microscale,

2209
01:53:37,010 --> 01:53:41,181
which, inconveniently,
is the point,

2210
01:53:41,181 --> 01:53:44,451
the site of pathophysiology
or a lot of the pathophysiology

2211
01:53:44,451 --> 01:53:46,153
we think is going on
with sickle cell disease.

2212
01:53:46,153 --> 01:53:49,389
So, here's some old-school
fluid mechanics for you.

2213
01:53:49,389 --> 01:53:54,061
So, all I need to show you
is that blood viscosity changes

2214
01:53:54,061 --> 01:53:56,697
when you're at different
parts of the circulation.

2215
01:53:56,697 --> 01:54:01,168
The faster the blood flow is,
the lower the viscosity.

2216
01:54:01,168 --> 01:54:04,871
The slower the blood flow is,
the higher the viscosity

2217
01:54:04,871 --> 01:54:06,773
because these red cells
clump together --

2218
01:54:06,773 --> 01:54:08,075
the rouleaux formation.

2219
01:54:08,075 --> 01:54:11,545
You guys might know about that.
That actually affects viscosity.

2220
01:54:11,545 --> 01:54:13,914
And also hematocrit,
as you can imagine.

2221
01:54:14,514 --> 01:54:17,417
When hematocrit changes, that is
the major driver of viscosity.

2222
01:54:17,417 --> 01:54:19,352
So, when you suddenly
are dealing with patients

2223
01:54:19,352 --> 01:54:21,655
that have different hematocrit
or different hemoglobin levels,

2224
01:54:21,655 --> 01:54:24,558
guess what? By virtue of that,
their viscosity changes.

2225
01:54:24,558 --> 01:54:27,761
And, also, by the way,
the diameter of your channel --

2226
01:54:27,761 --> 01:54:29,529
the diameter
of your blood vessel --

2227
01:54:29,529 --> 01:54:31,364
that affects
your blood viscosity.

2228
01:54:31,364 --> 01:54:33,600
So, when you're
at the macroscale,

2229
01:54:33,600 --> 01:54:35,969
the word viscosity
doesn't even mean anything.

2230
01:54:35,969 --> 01:54:37,471
You don't even know
what it means.

2231
01:54:37,471 --> 01:54:39,740
So, that's one ding.

2232
01:54:39,740 --> 01:54:42,943
Another ding is that sickle cell
disease, in and of itself,

2233
01:54:42,943 --> 01:54:44,945
by virtue of having
hemoglobin S,

2234
01:54:44,945 --> 01:54:47,748
further increases
complexity of blood viscosity.

2235
01:54:47,748 --> 01:54:50,283
So, I'm going
to talk about that.

2236
01:54:50,283 --> 01:54:54,788
So all this means is that
clinical implementation

2237
01:54:54,788 --> 01:54:57,524
of sickle cell microfluidics
is hard.

2238
01:54:57,524 --> 01:55:00,093
So, when we brought in our
clinical laboratorians,

2239
01:55:00,093 --> 01:55:02,295
they said, "Okay, well, here
are your guidelines here.

2240
01:55:02,295 --> 01:55:05,031
You really need to think
about all these things."

2241
01:55:05,031 --> 01:55:07,000
And I'm going to have to
just gloss over it

2242
01:55:07,000 --> 01:55:08,301
in the interest of time.

2243
01:55:08,301 --> 01:55:10,303
But you need to think
about not only

2244
01:55:10,303 --> 01:55:12,806
when you start your
proof-of-concept pilot studies,

2245
01:55:12,806 --> 01:55:14,741
which many papers have done
and many groups have done.

2246
01:55:14,741 --> 01:55:16,343
We always start
with a great paper, like,

2247
01:55:16,343 --> 01:55:18,945
"Look what we could do."
But now you need to optimize.

2248
01:55:18,945 --> 01:55:21,882
Now you need to characterize
things like sample stability.

2249
01:55:21,882 --> 01:55:24,484
You now need to think
about precision.

2250
01:55:24,484 --> 01:55:26,720
You need to think about
analytical sensitivity

2251
01:55:26,720 --> 01:55:28,288
and specificity.
What's your reference range?

2252
01:55:28,288 --> 01:55:30,824
What's your limit
of detectability?

2253
01:55:30,824 --> 01:55:32,759
Where's your linearity range?

2254
01:55:32,759 --> 01:55:35,028
So these are all things
that clinical laboratorians

2255
01:55:35,028 --> 01:55:36,296
think about all the time.

2256
01:55:36,296 --> 01:55:39,099
So, if we think about
the trouble spots

2257
01:55:39,099 --> 01:55:40,834
with sickle cell disease --

2258
01:55:40,834 --> 01:55:42,436
well, first of all,
we don't even know

2259
01:55:42,436 --> 01:55:46,439
what a good negative control
or a positive control is.

2260
01:55:46,439 --> 01:55:47,707
We can think of some,

2261
01:55:47,707 --> 01:55:49,442
but implementing them
is not so easy.

2262
01:55:49,442 --> 01:55:52,312
Your COVID test
has a control line,

2263
01:55:52,312 --> 01:55:53,814
has a positive control line.

2264
01:55:53,814 --> 01:55:55,348
We need to do something
similar to that.

2265
01:55:55,348 --> 01:56:00,453
We haven't gone to that.
One key point is variability.

2266
01:56:00,453 --> 01:56:03,123
Variability is actually
a hallmark of the disease,

2267
01:56:03,123 --> 01:56:05,325
whether you're talking about
interpatient variability,

2268
01:56:05,325 --> 01:56:06,960
intrapatient variability.

2269
01:56:06,960 --> 01:56:09,462
You draw a blood sample
from a patient on Monday.

2270
01:56:09,462 --> 01:56:10,931
You draw another one
on Thursday.

2271
01:56:10,931 --> 01:56:12,365
It could be
completely different.

2272
01:56:12,365 --> 01:56:15,602
And we're even learning that
there's intrasample variability.

2273
01:56:16,403 --> 01:56:18,805
You look within one milliliter
of a blood sample

2274
01:56:18,805 --> 01:56:20,941
compared to another milliliter
of the same blood sample --

2275
01:56:20,941 --> 01:56:22,275
it could be completely
different.

2276
01:56:22,275 --> 01:56:24,477
So, these are things
that we're challenged with.

2277
01:56:24,477 --> 01:56:25,912
But having said that,

2278
01:56:25,912 --> 01:56:28,882
the field is moving
toward that direction --

2279
01:56:28,882 --> 01:56:33,053
doing a lot of what I call
boring but important studies:

2280
01:56:33,053 --> 01:56:36,356
user repeatability, looking at
multi-site comparisons,

2281
01:56:36,356 --> 01:56:38,758
the CV, coefficient
of variability.

2282
01:56:38,758 --> 01:56:40,560
These are all things
that the field

2283
01:56:40,560 --> 01:56:42,362
is starting to move towards --

2284
01:56:42,362 --> 01:56:45,198
looking at sample stability
and storage.

2285
01:56:45,198 --> 01:56:47,400
And yeah, we can demonstrate,
for example,

2286
01:56:47,400 --> 01:56:52,239
with an adhesion assay based on
red cell adhesion to laminin,

2287
01:56:52,239 --> 01:56:54,174
stuff that many of us
have known,

2288
01:56:54,174 --> 01:56:58,044
many of our own researchers
in this audience

2289
01:56:58,044 --> 01:56:59,613
have demonstrated decades ago.

2290
01:57:00,347 --> 01:57:02,482
Translating it
to a microfluidic assay --

2291
01:57:02,482 --> 01:57:04,284
we need to do that.
So, we're able to show

2292
01:57:04,284 --> 01:57:06,453
the genotypic differences
that we expect.

2293
01:57:07,420 --> 01:57:10,490
And then we're even moving
toward devices,

2294
01:57:10,490 --> 01:57:13,960
like in this case
from Ümit Gurkan's lab,

2295
01:57:13,960 --> 01:57:16,863
where we're able to maybe
obviate the need for microscopy,

2296
01:57:16,863 --> 01:57:19,199
starting to integrate sensors
into this.

2297
01:57:19,199 --> 01:57:22,002
And again, getting a sense
of whether or not

2298
01:57:22,002 --> 01:57:25,538
we can differentiate
different genotypes,

2299
01:57:25,538 --> 01:57:27,641
and hopefully even
getting a sense of,

2300
01:57:27,641 --> 01:57:31,711
could we start to predict
who has VOC versus not?

2301
01:57:33,246 --> 01:57:34,447
From our own laboratory --

2302
01:57:34,447 --> 01:57:36,383
I'm wrapping up
the last couple of slides --

2303
01:57:36,383 --> 01:57:38,718
we also have been working
with pharma

2304
01:57:38,718 --> 01:57:42,122
to look at efficacy
of new therapeutics.

2305
01:57:42,122 --> 01:57:43,456
So, in this system here,

2306
01:57:43,456 --> 01:57:45,592
we have our endothelialized
microfluidic,

2307
01:57:45,592 --> 01:57:48,428
and we're staining white cells
and blood cells.

2308
01:57:48,428 --> 01:57:51,631
And in this case,
it's a new P-selectin inhibitor,

2309
01:57:52,232 --> 01:57:54,868
a synthetic PSG01 glycopeptide.

2310
01:57:54,868 --> 01:57:57,270
And we're trying to do
these studies

2311
01:57:57,270 --> 01:58:00,273
where we can
differentiate a signal

2312
01:58:00,273 --> 01:58:02,475
from these
different therapeutics.

2313
01:58:02,475 --> 01:58:05,779
Okay. But again, controls
and standards are needed.

2314
01:58:05,779 --> 01:58:08,715
Okay. So, one solution
for microfluidics is --

2315
01:58:09,249 --> 01:58:10,450
don't use microfluidics.

2316
01:58:10,450 --> 01:58:12,752
I'm being halfway
facetious here.

2317
01:58:12,752 --> 01:58:15,722
But this is actually a project
that my own lab has undergone,

2318
01:58:15,722 --> 01:58:19,192
where we have an anemia test.
It was a microfluidic,

2319
01:58:19,192 --> 01:58:21,928
but we decided that
it would cause too much error.

2320
01:58:21,928 --> 01:58:24,464
When you shrink down
a microfluidic, a little bubble,

2321
01:58:24,464 --> 01:58:26,499
a little piece of dust,
that can kill the whole thing.

2322
01:58:26,499 --> 01:58:28,068
So, we said, "Forget that.

2323
01:58:28,068 --> 01:58:30,870
We're just going to use
a bigger chamber."

2324
01:58:30,870 --> 01:58:33,039
And we have
an anemia test here where,

2325
01:58:33,039 --> 01:58:37,043
based on the color
of the chemical change,

2326
01:58:37,043 --> 01:58:39,145
it correlates
with hemoglobin levels.

2327
01:58:39,145 --> 01:58:41,014
Sensitivity and specificity
is not too bad --

2328
01:58:41,014 --> 01:58:42,415
I won't go over it too much.

2329
01:58:42,415 --> 01:58:47,020
This was FDA cleared
by the U.S. FDA in 2017.

2330
01:58:47,020 --> 01:58:51,024
It is now licensed
to our company,

2331
01:58:51,024 --> 01:58:53,727
and we got prescription
home use just last year.

2332
01:58:53,727 --> 01:58:56,997
So, sometimes getting rid of the
microfluidic is the way to go.

2333
01:58:56,997 --> 01:59:02,102
Okay. So analysis is another way
we can do things.

2334
01:59:02,102 --> 01:59:07,040
So, with the advent of machine
learning and AI, we said,

2335
01:59:07,040 --> 01:59:09,609
"What if we create
some open-source software

2336
01:59:09,609 --> 01:59:10,810
to help the field?"

2337
01:59:10,810 --> 01:59:16,683
So, anyone with a microfluidic
can download our software,

2338
01:59:16,683 --> 01:59:19,586
and we can help
do automated analysis

2339
01:59:19,586 --> 01:59:22,822
and even plug-and-play machine
learning algorithms.

2340
01:59:22,822 --> 01:59:24,624
Just push of a button,
we can help explore it.

2341
01:59:24,624 --> 01:59:25,825
So, that's all part of it.

2342
01:59:25,825 --> 01:59:28,294
Okay. So, here's my last slide.
Where are we?

2343
01:59:29,262 --> 01:59:31,431
Well, we actually,
unfortunately,

2344
01:59:31,431 --> 01:59:34,067
chose to work
with a very complex disease --

2345
01:59:34,067 --> 01:59:37,504
with few, if any,
validated clinical markers,

2346
01:59:37,504 --> 01:59:40,607
with clinical endpoints that are
difficult to define or quantify.

2347
01:59:40,607 --> 01:59:43,309
All of you are involved
with clinical trials.

2348
01:59:43,309 --> 01:59:45,311
How do you define
your pain endpoints?

2349
01:59:45,311 --> 01:59:46,513
It's always tricky.

2350
01:59:46,513 --> 01:59:49,549
It involves a very complex
bio sample -- whole blood.

2351
01:59:49,549 --> 01:59:52,252
And heterogeneity,
in and of itself,

2352
01:59:52,252 --> 01:59:54,954
is a hallmark of the disease.
So, where are we headed?

2353
01:59:55,789 --> 01:59:59,726
I would say that we're
getting there [laughs].

2354
01:59:59,726 --> 02:00:01,594
This is my last few slides.

2355
02:00:01,594 --> 02:00:04,931
This, in some ways, is just how
long the process takes, right?

2356
02:00:04,931 --> 02:00:07,834
We have proof of concept
at trying to figure out

2357
02:00:07,834 --> 02:00:10,770
the right pathway
to implementation is never fast.

2358
02:00:10,770 --> 02:00:12,839
And we are literally
building planes as we fly them.

2359
02:00:12,839 --> 02:00:15,075
When I talk to the clinical
pathologist, they say,

2360
02:00:15,075 --> 02:00:17,944
"Sure, we'll help
you refine your device."

2361
02:00:17,944 --> 02:00:20,346
"What's the biomarker?" We said,
"Oh, we don't have one yet."

2362
02:00:20,346 --> 02:00:21,714
Like,
"Why are you making something

2363
02:00:21,714 --> 02:00:22,949
you don't have a biomarker yet?"

2364
02:00:22,949 --> 02:00:24,851
"Well, we're making something
to figure out the biomarker."

2365
02:00:24,851 --> 02:00:26,820
And they're like,
"That's ass backwards."

2366
02:00:26,820 --> 02:00:28,555
They're like, "Yeah, I know.

2367
02:00:28,555 --> 02:00:31,124
But that is where
we are as a field, right?

2368
02:00:31,124 --> 02:00:34,094
So more longitudinal
studies is needed.

2369
02:00:34,094 --> 02:00:38,031
And it may be that single assays
may be less clinically useful

2370
02:00:38,031 --> 02:00:39,933
than a panel of biomarkers."

2371
02:00:39,933 --> 02:00:43,970
We do see some possibilities
of the analysis part, right?

2372
02:00:43,970 --> 02:00:46,206
Data science tools
can probably help us.

2373
02:00:46,206 --> 02:00:48,675
And maybe we need to consider
that microfluidic assays

2374
02:00:48,675 --> 02:00:50,043
may actually not be
the path forward.

2375
02:00:50,043 --> 02:00:56,783
Maybe the way to best predict
vaso-occlusive episodes

2376
02:00:56,783 --> 02:00:58,551
is not with whole blood.

2377
02:00:58,551 --> 02:01:00,453
Maybe it is
an omics-based approach.

2378
02:01:00,453 --> 02:01:02,956
Vivian Sheehan just published a
nice commentary a few months ago

2379
02:01:02,956 --> 02:01:04,958
describing maybe
that's a possibility.

2380
02:01:04,958 --> 02:01:08,495
Anyway, I would like to end
with thanking my lab,

2381
02:01:08,495 --> 02:01:10,396
thanking our collaborators,
thanking our funding.

2382
02:01:10,396 --> 02:01:17,303
Thank you. Okay.

2383
02:01:17,303 --> 02:01:18,505
[applause]

2384
02:01:18,505 --> 02:01:19,906
Female Speaker: Yeah.
Because you will

2385
02:01:19,906 --> 02:01:21,708
take questions
of each speaker,

2386
02:01:21,708 --> 02:01:24,377
since Dr. Alan Docter
[phonetic sp]

2387
02:01:24,377 --> 02:01:27,514
has to leave
after the second talk.

2388
02:01:28,047 --> 02:01:31,584
So any questions, anybody?

2389
02:01:32,752 --> 02:01:34,921
Manu, I see you get up.
Are you going to ask questions?

2390
02:01:34,921 --> 02:01:36,122
Male Speaker: I'll wait for
the rest.

2391
02:01:36,122 --> 02:01:39,025
Female Speaker: Oh, Okay.
I see a hand up there.

2392
02:01:40,894 --> 02:01:42,095
Scott Peselak: This is Scott.

2393
02:01:42,095 --> 02:01:44,664
Sorry. Scott Peselak from UPenn.
Really great talk.

2394
02:01:44,664 --> 02:01:46,332
I'm just curious
if you have thought about ways

2395
02:01:46,332 --> 02:01:48,067
to differentiate
between cell-intrinsic

2396
02:01:48,067 --> 02:01:50,336
and cell-extrinsic aspects

2397
02:01:50,336 --> 02:01:53,039
that might affect microfluidic
flow in your system

2398
02:01:53,039 --> 02:01:54,374
and just in general.

2399
02:01:54,374 --> 02:01:55,909
Because, you know,
in the patient's hydroxyurea,

2400
02:01:55,909 --> 02:01:57,410
obviously, we get increased
fetal hemoglobin,

2401
02:01:57,410 --> 02:01:59,379
but also modulate a lot of other
aspects of whole blood, too.

2402
02:01:59,379 --> 02:02:02,448
Wilbur Lam: The answer is yes,
and we can talk later.

2403
02:02:02,448 --> 02:02:04,050
Scott Peselak: Okay.
Sounds good.

2404
02:02:05,785 --> 02:02:07,153
Female Speaker: Just one.

2405
02:02:07,153 --> 02:02:09,155
Oh, sorry, Mary Lou
[phonetic sp]. I'm sorry.

2406
02:02:09,155 --> 02:02:11,925
Mary Lou: One thing
that has concerned me

2407
02:02:11,925 --> 02:02:18,031
with adhesion assays generally
in a longitudinal sense

2408
02:02:18,031 --> 02:02:24,704
is that I can hypothesize
that the most adherent cells --

2409
02:02:24,704 --> 02:02:26,272
the most adherent red cells,

2410
02:02:27,707 --> 02:02:32,679
will actually kind of disappear
from the circulation

2411
02:02:32,679 --> 02:02:37,217
during a vaso-occlusive episode
because they are adherent.

2412
02:02:37,217 --> 02:02:42,822
And so that it would be possible
to get really the opposite

2413
02:02:42,822 --> 02:02:47,093
of what you expect in these
kind of microfluidic assays,

2414
02:02:47,093 --> 02:02:50,530
or for that matter,
in our less microfluidic assays

2415
02:02:50,530 --> 02:02:52,232
that my own lab uses.

2416
02:02:52,232 --> 02:02:55,201
And I was just wondering
if you have thoughts about that.

2417
02:03:02,141 --> 02:03:04,777
Wilbur Lam: Yes, we have.
In fact, in some of the studies,

2418
02:03:04,777 --> 02:03:07,313
we have actually seen
exactly the opposite, right,

2419
02:03:07,313 --> 02:03:09,315
where in the acute setting,

2420
02:03:10,083 --> 02:03:13,019
we actually see
a decrease in adhesion,

2421
02:03:13,019 --> 02:03:17,724
and then later on,
it goes back to baseline.

2422
02:03:17,724 --> 02:03:20,493
And I think I didn't have time
to go over it real quick,

2423
02:03:20,493 --> 02:03:22,695
but I think we as a field
really need to figure out

2424
02:03:22,695 --> 02:03:24,731
exactly how we want
to use these things, right?

2425
02:03:24,731 --> 02:03:27,867
Are we trying to diagnose
a vaso-occlusive event?

2426
02:03:27,867 --> 02:03:29,269
Are we trying to predict?

2427
02:03:29,269 --> 02:03:33,139
Or are we trying to also maybe,
if we do it longitudinally,

2428
02:03:33,673 --> 02:03:36,442
are these tools to maybe
demonstrate resolution

2429
02:03:36,442 --> 02:03:38,144
or convalescence
of these episodes?

2430
02:03:38,144 --> 02:03:42,915
All these are questions
that we're dealing with,

2431
02:03:42,915 --> 02:03:45,118
and I think it's all about
getting more data

2432
02:03:45,818 --> 02:03:47,553
and getting as much as we can

2433
02:03:47,553 --> 02:03:50,556
because I think we need to have
an unbiased approach here

2434
02:03:50,556 --> 02:03:53,926
and not be so focused
on our hypothesis that,

2435
02:03:53,926 --> 02:03:56,296
oh, yeah, adhesion is going

2436
02:03:56,296 --> 02:03:58,931
to directly correlate
with some event.

2437
02:03:58,931 --> 02:04:02,001
It may be, like you said,
it may be the complete opposite.

2438
02:04:02,001 --> 02:04:05,705
So really trying to take
a non-biased approach

2439
02:04:05,705 --> 02:04:07,974
to all the data,
getting as much data as we can,

2440
02:04:07,974 --> 02:04:09,575
I think is the way to go, yeah.

2441
02:04:11,511 --> 02:04:17,750
Male Speaker: I was wondering
if you've ever used

2442
02:04:17,750 --> 02:04:21,854
the microfluidics
for selection purposes,

2443
02:04:21,854 --> 02:04:24,290
so if you're looking
for a particular cell,

2444
02:04:25,191 --> 02:04:27,360
whether or not, like,
for example,

2445
02:04:27,360 --> 02:04:30,930
can you discriminate
a sickle red cell from an adult

2446
02:04:32,598 --> 02:04:36,202
or even a fetal cell
using microfluidics?

2447
02:04:37,904 --> 02:04:39,472
Wilbur Lam: Yes.
So from the research side,

2448
02:04:39,472 --> 02:04:43,109
we have, and, you know,
the best way to think about it

2449
02:04:43,109 --> 02:04:45,712
is these are physiologic systems

2450
02:04:45,712 --> 02:04:48,514
that are easily coupled
with microscopy, right,

2451
02:04:48,514 --> 02:04:50,350
so staining
for whatever subsets.

2452
02:04:50,350 --> 02:04:51,651
We've certainly done that.

2453
02:04:51,651 --> 02:04:54,220
And, yeah, we've seen a lot
of things that we would expect.

2454
02:04:54,220 --> 02:04:58,157
You know, reticulocytes tend
to be very adhesive in these.

2455
02:04:58,157 --> 02:04:59,992
Male Speaker: But are we
selecting for possibility?

2456
02:04:59,992 --> 02:05:01,327
Wilbur Lam: Well, you could,
right?

2457
02:05:01,327 --> 02:05:03,563
You could do this
downstream selection.

2458
02:05:04,197 --> 02:05:09,168
There are fancier fluidics where
you can trigger a valve to open

2459
02:05:09,168 --> 02:05:11,904
so that you see
a population that you want,

2460
02:05:11,904 --> 02:05:13,239
and it can go
to a certain bucket,

2461
02:05:13,239 --> 02:05:17,377
almost like akin to, like,
a flow cytometry sorter, right?

2462
02:05:17,377 --> 02:05:18,811
There are ways to do that.

2463
02:05:18,811 --> 02:05:22,915
And some groups,
including ours to some extent,

2464
02:05:22,915 --> 02:05:24,617
have done
that selection process.

2465
02:05:25,785 --> 02:05:27,120
Female Speaker: So, Wilbur,

2466
02:05:27,120 --> 02:05:29,389
I have one question
before I let you go.

2467
02:05:30,056 --> 02:05:33,593
So all these fancy devices
that you have,

2468
02:05:33,593 --> 02:05:36,696
you all call it vibrant
or whatever,

2469
02:05:36,696 --> 02:05:38,931
and try to simulate
the, you know,

2470
02:05:38,931 --> 02:05:40,666
the blood flow
through capillaries.

2471
02:05:41,434 --> 02:05:46,172
Why can't they do it in vivo,
in real time,

2472
02:05:46,172 --> 02:05:48,441
just like we use
pulse oximetry?

2473
02:05:48,441 --> 02:05:51,577
So then you take away
all these other complications,

2474
02:05:51,577 --> 02:05:56,816
and then there is still
some intrapatient variability,

2475
02:05:56,816 --> 02:05:58,418
but at least for
long-duration flow.

2476
02:05:58,418 --> 02:05:59,619
Wilbur Lam: Yeah.

2477
02:05:59,619 --> 02:06:02,121
So I don't disagree with you,
Sui-Lei [phonetic sp].

2478
02:06:02,121 --> 02:06:06,993
I think there will always be
a role for in vivo techniques,

2479
02:06:06,993 --> 02:06:08,361
and there have been.

2480
02:06:08,361 --> 02:06:12,665
So there are, for example,
ultrasound-like devices

2481
02:06:12,665 --> 02:06:15,101
where you can
actually measure flow.

2482
02:06:15,635 --> 02:06:18,337
There are oximetry devices now

2483
02:06:18,337 --> 02:06:22,742
that can even get a sense of
blood flow, even intracranially.

2484
02:06:22,742 --> 02:06:25,044
Like you can get
a slice of it under,

2485
02:06:25,044 --> 02:06:27,780
so for example, Erin Buckley,
who's a bioengineer at Emory,

2486
02:06:27,780 --> 02:06:29,248
you know, she's done
a lot of work

2487
02:06:29,248 --> 02:06:31,317
in the sickle cell field
as well in this.

2488
02:06:31,884 --> 02:06:34,253
Everything has pros and cons,
Sui-Lei.

2489
02:06:34,253 --> 02:06:36,389
So the cons to what
you're talking about,

2490
02:06:36,389 --> 02:06:37,723
and we've demonstrated this,

2491
02:06:37,723 --> 02:06:39,459
is you take some of those
in vivo ones,

2492
02:06:39,459 --> 02:06:41,427
you do it on the finger,
it gives a readout.

2493
02:06:41,427 --> 02:06:43,162
You go to the next finger,

2494
02:06:43,162 --> 02:06:44,997
it's a totally different
readout, right?

2495
02:06:44,997 --> 02:06:46,666
Female Speaker: Even the
same person?

2496
02:06:46,666 --> 02:06:48,000
Wilbur Lam: Even the same
person, right?

2497
02:06:48,000 --> 02:06:51,304
So again, we're talking
about heterogeneity, right?

2498
02:06:51,304 --> 02:06:54,607
Unfortunately,
it's a hallmark of the disease.

2499
02:06:55,608 --> 02:06:58,244
Every single technology
has its own pros and cons.

2500
02:06:58,244 --> 02:07:02,448
My own expectation
is in the next 10 to 20 years,

2501
02:07:02,448 --> 02:07:04,884
we will see a lot more of these
things out in the market.

2502
02:07:04,884 --> 02:07:06,953
Each will have a specific niche,

2503
02:07:06,953 --> 02:07:09,455
and each will have a specific
clinical use case

2504
02:07:09,455 --> 02:07:11,891
that we might not even be able
to predict right now.

2505
02:07:11,891 --> 02:07:14,260
Female Speaker: But just tell
them to use the same finger,

2506
02:07:14,260 --> 02:07:16,229
and don't change to,
you know,

2507
02:07:17,363 --> 02:07:19,832
the other thing
is the nail polish

2508
02:07:19,832 --> 02:07:22,568
which they use too,
especially for the women.

2509
02:07:22,568 --> 02:07:25,905
So I think I'm going
to introduce the next --

2510
02:07:25,905 --> 02:07:27,507
oh, there's one more question.

2511
02:07:31,644 --> 02:07:33,279
Female Speaker: So Wilbur,
I'm really excited.

2512
02:07:33,279 --> 02:07:36,482
I remember asking you to put
those videos in the clinic

2513
02:07:36,482 --> 02:07:38,084
while I was at Emory.

2514
02:07:38,684 --> 02:07:41,721
Applicability. So these things
are really nice, good,

2515
02:07:41,721 --> 02:07:43,789
but how well are
we using them?

2516
02:07:43,789 --> 02:07:46,359
The videos you've
got of blood flow,

2517
02:07:46,359 --> 02:07:49,328
showing the blood flow
of the sickle patient on HU

2518
02:07:49,328 --> 02:07:51,297
and the one who's not,

2519
02:07:51,297 --> 02:07:55,034
has it changed
your HU compliance?

2520
02:07:58,871 --> 02:08:00,439
Wilbur Lam: We'll have to ask
our colleagues that.

2521
02:08:00,439 --> 02:08:03,009
I don't know, actually.
I mean, we use it in the clinic,

2522
02:08:03,009 --> 02:08:05,144
and I do say,
at least anecdotally,

2523
02:08:05,144 --> 02:08:07,647
when I see a patient
and I show that to them.

2524
02:08:08,281 --> 02:08:11,384
So, I've actually had a couple
of parents actually say,

2525
02:08:11,384 --> 02:08:13,953
"Oh, I heard you got this video,
can you show it to my kid?"

2526
02:08:13,953 --> 02:08:16,022
And yeah, what's nice about it

2527
02:08:16,022 --> 02:08:18,057
is that every kid
has a phone now,

2528
02:08:18,057 --> 02:08:19,725
so I just, you know,
give it to them.

2529
02:08:19,725 --> 02:08:22,194
So they see it on a platform
that they're used to.

2530
02:08:22,194 --> 02:08:27,033
I anecdotally have personally at
least gotten positive feedback

2531
02:08:27,033 --> 02:08:29,969
from at least a handful of kids
where they're, eh,

2532
02:08:29,969 --> 02:08:31,437
and then they see it
and they're like,

2533
02:08:31,437 --> 02:08:33,806
you know,
I'm going to show my age, right?

2534
02:08:33,806 --> 02:08:36,709
For those of you who remember
the, "This is your brain,

2535
02:08:36,709 --> 02:08:38,811
this is your brain on drugs,"
right?

2536
02:08:38,811 --> 02:08:41,514
So I use that type of analogy,
all right?

2537
02:08:41,514 --> 02:08:43,082
This is your blood
not on hydria,

2538
02:08:43,082 --> 02:08:44,584
this is your blood hydria,
and they're like,

2539
02:08:44,584 --> 02:08:46,686
"All right, maybe
I should do that, yeah."

2540
02:08:48,120 --> 02:08:50,623
Female Speaker: I'm chuckling
because when you told a story

2541
02:08:50,623 --> 02:08:54,160
about your student picking up
your driver's license,

2542
02:08:54,160 --> 02:08:57,530
it's like me, you know,
is refused our age, too.

2543
02:08:57,530 --> 02:09:00,232
We used to keep our lab
books, you know, books.

2544
02:09:00,232 --> 02:09:02,635
So she looked at the book,
she said, "Oh my God."

2545
02:09:02,635 --> 02:09:05,004
I said, "Yes,
before you were born."

2546
02:09:05,004 --> 02:09:08,074
[laughter]

2547
02:09:08,074 --> 02:09:11,777
Okay, this is what David
Van Roy used to tell me:

2548
02:09:12,411 --> 02:09:14,480
"Before you were born."

2549
02:09:14,480 --> 02:09:16,415
So now I tell it
to the students.

2550
02:09:17,550 --> 02:09:21,787
Okay, so now time's up.
Yes, no, no. Yes, absolutely.

2551
02:09:22,455 --> 02:09:27,360
Okay, so I have great pleasure
to introduce Dr. Alan Docter,

2552
02:09:28,094 --> 02:09:31,063
who actually we have not met,

2553
02:09:31,063 --> 02:09:35,935
but I heard his presentation
and one of our extramural,

2554
02:09:35,935 --> 02:09:40,406
you know, talks that
were given in the NHLBI.

2555
02:09:40,406 --> 02:09:43,376
And I thought, "Wow, this is
so relevant to us."

2556
02:09:43,909 --> 02:09:48,514
So Dr. Alan Docter
is professor of pediatrics

2557
02:09:48,514 --> 02:09:51,283
and bioengineering
at the University of Maryland

2558
02:09:51,283 --> 02:09:54,453
School of Medicine.
And he's going to talk to us

2559
02:09:54,453 --> 02:09:58,124
about the role
of red blood cell ENOS

2560
02:09:58,124 --> 02:10:00,259
in optimizing
red cell phenotype

2561
02:10:00,793 --> 02:10:04,664
during circulation.
Thank you so much.

2562
02:10:04,664 --> 02:10:05,865
[applause]

2563
02:10:05,865 --> 02:10:11,804
Alan Docter: Thank you, Sui-Lei,

2564
02:10:11,804 --> 02:10:17,243
and thanks for the opportunity
to show this work to you all.

2565
02:10:18,911 --> 02:10:20,179
It's going to be
a bit different

2566
02:10:20,179 --> 02:10:22,782
than the other talks
that you've heard.

2567
02:10:22,782 --> 02:10:27,420
And to confess, I'm not
a sickle cell specialist,

2568
02:10:27,420 --> 02:10:30,523
not even a hematologist.
I'm an intensivist.

2569
02:10:31,757 --> 02:10:38,264
But so what is the point,
really,

2570
02:10:38,264 --> 02:10:40,266
and why is this of interest?

2571
02:10:40,266 --> 02:10:43,135
So the principal task
for red blood cells

2572
02:10:43,703 --> 02:10:47,673
is to move oxygen
from lungs to respiring cells.

2573
02:10:47,673 --> 02:10:49,041
That's the point.

2574
02:10:49,041 --> 02:10:51,110
And they're within
a delivery system

2575
02:10:51,110 --> 02:10:53,713
that includes the heart
and lungs and vascular tree.

2576
02:10:54,280 --> 02:10:56,649
And it's not just that.

2577
02:10:56,649 --> 02:10:59,085
The point is to be
able to adapt.

2578
02:10:59,952 --> 02:11:04,690
So right now, your oxygen
consumption is not so great,

2579
02:11:05,357 --> 02:11:08,794
especially after eating
a little maybe, you know,

2580
02:11:08,794 --> 02:11:12,631
but if you get up
and say there was a fire alarm

2581
02:11:12,631 --> 02:11:14,433
and we had to go down
the stairs,

2582
02:11:14,433 --> 02:11:17,103
you have to suddenly increase
your oxygen consumption.

2583
02:11:17,103 --> 02:11:20,172
So the system
has to be adaptive.

2584
02:11:20,172 --> 02:11:22,842
And in fact, when we evolved,

2585
02:11:24,343 --> 02:11:27,847
there was a sort
of a 400-million-year forward

2586
02:11:27,847 --> 02:11:30,182
genetic screen evolution, right,

2587
02:11:30,750 --> 02:11:36,155
which favored people who could
run away from tigers very fast

2588
02:11:36,155 --> 02:11:40,092
and rapidly scale
their oxygen delivery.

2589
02:11:40,693 --> 02:11:43,329
And so red cells
have a big part in that.

2590
02:11:43,329 --> 02:11:44,997
It's not commonly appreciated.

2591
02:11:44,997 --> 02:11:49,235
So one of the systems I'm going
to talk about is this ENOS.

2592
02:11:49,235 --> 02:11:50,970
For those that don't know
what ENOS is,

2593
02:11:50,970 --> 02:11:54,073
that's an enzyme
that makes nitric oxide.

2594
02:11:54,073 --> 02:11:56,008
Most people have heard
of nitric oxide.

2595
02:11:56,675 --> 02:11:59,779
Nitric oxide is a very important
signaling molecule

2596
02:11:59,779 --> 02:12:03,115
that coordinates
oxygen physiology.

2597
02:12:03,883 --> 02:12:10,422
And so red cells dispense this
molecule in our vascular tree

2598
02:12:11,624 --> 02:12:16,362
in a way that supports
oxygen delivery homeostasis

2599
02:12:16,362 --> 02:12:19,265
under stress.
And that's really important.

2600
02:12:20,132 --> 02:12:23,035
Turns out that sickle red cells
don't do that so well,

2601
02:12:23,035 --> 02:12:24,637
even when they're not sickling.

2602
02:12:25,204 --> 02:12:30,209
And so we are studying
red cells,

2603
02:12:30,209 --> 02:12:33,345
which are surprisingly
poorly understood,

2604
02:12:33,979 --> 02:12:36,982
and identifying
some new phenotype features

2605
02:12:36,982 --> 02:12:40,786
that are relevant
to oxygen delivery homeostasis

2606
02:12:40,786 --> 02:12:43,055
and particularly relevant
to sickle cell disease.

2607
02:12:43,055 --> 02:12:45,624
And so that's what I'm going
to talk to you about.

2608
02:12:45,624 --> 02:12:48,294
So this may be
a new drug target.

2609
02:12:50,095 --> 02:12:51,330
These are my disclosures.

2610
02:12:51,330 --> 02:12:53,632
There's nothing important
or relevant

2611
02:12:53,632 --> 02:12:55,501
to what I'm talking
about here today.

2612
02:12:56,135 --> 02:12:59,271
And so the oxygen
delivery system

2613
02:12:59,271 --> 02:13:01,307
that I'm talking about
is this cascade,

2614
02:13:01,941 --> 02:13:06,345
really, of, you know,
interlinked systems

2615
02:13:07,246 --> 02:13:12,084
that coordinate compensation
for coupling

2616
02:13:12,084 --> 02:13:15,221
between oxygen delivery
and consumption when it changes.

2617
02:13:15,221 --> 02:13:18,624
So, it might go up
and you need to deliver more,

2618
02:13:18,624 --> 02:13:20,793
or the availability
might go down,

2619
02:13:20,793 --> 02:13:24,330
like you have asthma
or sleep apnea or pneumonia,

2620
02:13:24,330 --> 02:13:26,265
or you go to altitude,

2621
02:13:26,265 --> 02:13:28,968
and, or you may have
a lower cardiac output.

2622
02:13:29,535 --> 02:13:32,204
Whatever it is,
you still have to balance

2623
02:13:32,204 --> 02:13:35,040
the delivery and consumption
or we've got problem.

2624
02:13:35,808 --> 02:13:38,811
And those problems
are quite obvious

2625
02:13:38,811 --> 02:13:40,079
when you're taking
care of patients

2626
02:13:40,079 --> 02:13:42,114
with sickle cell disease.

2627
02:13:42,114 --> 02:13:45,117
Red cells are at two points
in the system,

2628
02:13:45,784 --> 02:13:49,555
capturing the oxygen in the lung
and releasing it in tissue.

2629
02:13:49,555 --> 02:13:53,125
Those are paradoxically
opposites, right?

2630
02:13:53,125 --> 02:13:56,161
So the same cell has to do
one thing in the lung

2631
02:13:56,161 --> 02:14:00,232
and another thing in your muscle
and do it effectively and well.

2632
02:14:00,232 --> 02:14:04,303
Why? How does that happen?
And it turns out that red cells

2633
02:14:04,303 --> 02:14:06,238
are actually pretty
sophisticated,

2634
02:14:06,238 --> 02:14:08,107
as I'll point out.

2635
02:14:08,107 --> 02:14:12,378
So, this is a study
that was done quite a while ago

2636
02:14:12,912 --> 02:14:15,414
asking this simple question,
right?

2637
02:14:15,948 --> 02:14:19,218
So what governs blood
flow distribution?

2638
02:14:19,218 --> 02:14:21,820
It wasn't really understood.
Nobody got it.

2639
02:14:21,820 --> 02:14:25,991
It's not like we're studying
what governs cardiac output

2640
02:14:25,991 --> 02:14:28,594
or what governs how
to stabilize blood pressure.

2641
02:14:28,594 --> 02:14:32,665
What governs blood flow routing?
Okay.

2642
02:14:32,665 --> 02:14:34,600
So right now
you're routing blood

2643
02:14:34,600 --> 02:14:38,704
through about a tenth of your
potential sort of capillaries.

2644
02:14:40,039 --> 02:14:44,910
We are really not perfusing
most of what we can perfuse.

2645
02:14:44,910 --> 02:14:47,713
And everybody that's exercised
or gone to the gym

2646
02:14:47,713 --> 02:14:49,715
and you see the people
who take their pictures

2647
02:14:49,715 --> 02:14:51,417
and they're all
pumped up, right?

2648
02:14:51,417 --> 02:14:54,219
That's because there's
an increase in blood flow.

2649
02:14:54,219 --> 02:14:55,554
It's not the muscle.

2650
02:14:55,554 --> 02:14:57,790
It's the muscles
are engorged with blood.

2651
02:14:58,457 --> 02:15:01,360
That's because you can
suddenly really scale

2652
02:15:01,360 --> 02:15:04,096
by logs how
much blood flow goes.

2653
02:15:04,096 --> 02:15:08,267
So why? Nobody figured.
Nobody really understood that.

2654
02:15:08,267 --> 02:15:10,536
And rather famous physiologist,

2655
02:15:10,536 --> 02:15:12,504
for those of you
who may have heard of Guyton,

2656
02:15:12,504 --> 02:15:16,075
right, asked this question,
simple question,

2657
02:15:16,075 --> 02:15:19,345
and there was a big idea
back in the '50s

2658
02:15:19,345 --> 02:15:21,480
that this was
the autonomic nervous system

2659
02:15:21,480 --> 02:15:24,850
that nerves somehow opened
and closed blood vessels.

2660
02:15:24,850 --> 02:15:29,355
And so he did something
that we can't really do

2661
02:15:29,355 --> 02:15:33,559
to companion animals anymore.
He had this spinal preparation.

2662
02:15:33,559 --> 02:15:36,428
So, he decoupled
the autonomic nervous system

2663
02:15:36,428 --> 02:15:37,963
from the periphery,

2664
02:15:37,963 --> 02:15:39,865
and he isolated
the femoral artery

2665
02:15:39,865 --> 02:15:41,700
and the femoral vein
from a dog

2666
02:15:41,700 --> 02:15:44,003
and did a really simple,
beautiful experiment.

2667
02:15:44,536 --> 02:15:47,873
He put a flask of blood
above the femoral artery

2668
02:15:48,507 --> 02:15:51,110
and measured how fast
it took for it to empty.

2669
02:15:52,344 --> 02:15:53,545
That's it.

2670
02:15:53,545 --> 02:15:54,947
And then he did that with blood

2671
02:15:54,947 --> 02:15:59,084
that was progressively
less well oxygenated.

2672
02:15:59,084 --> 02:16:02,554
You can see the x-axis there
on the left starts with 100

2673
02:16:02,554 --> 02:16:04,023
and goes to zero.

2674
02:16:04,023 --> 02:16:06,725
So, that's 100 percent
saturation of the oxygen

2675
02:16:06,725 --> 02:16:09,695
in the blood on the top,
and then to zero.

2676
02:16:09,695 --> 02:16:12,464
And the y-axis is
how fast the flow rate,

2677
02:16:12,464 --> 02:16:13,665
how fast did it run out.

2678
02:16:13,665 --> 02:16:16,702
You can see the blood ran out.
That's relative.

2679
02:16:16,702 --> 02:16:19,571
So the blood ran out
like five times,

2680
02:16:19,571 --> 02:16:20,806
three and a half --
sorry --

2681
02:16:20,806 --> 02:16:25,010
three and a half times faster
with fully desaturated blood

2682
02:16:25,010 --> 02:16:26,879
than fully saturated blood.

2683
02:16:27,579 --> 02:16:30,315
Now, how's that possible?
You can ask Wilbur.

2684
02:16:30,315 --> 02:16:32,251
He'll tell you
the blood's not that --

2685
02:16:32,851 --> 02:16:35,054
it's not less viscous,
so to speak.

2686
02:16:35,054 --> 02:16:37,589
It's not becoming easier to go.

2687
02:16:37,589 --> 02:16:40,726
It's actually the impedance to
flow in the circulatory system

2688
02:16:40,726 --> 02:16:44,730
is changing as a function of how
well oxygenated the blood is.

2689
02:16:44,730 --> 02:16:48,233
And it turns out if you look
at the bottom, same x-axis,

2690
02:16:48,233 --> 02:16:53,172
y-axis shows oxygen delivery,
which is content times flow.

2691
02:16:53,806 --> 02:16:57,576
The flow is increasing
just enough to stabilize

2692
02:16:57,576 --> 02:16:59,111
the O2 delivery.

2693
02:16:59,111 --> 02:17:02,381
And then it falls off in a
linear fashion around the time

2694
02:17:02,381 --> 02:17:04,917
where we start to see problems
in the hospital

2695
02:17:04,917 --> 02:17:07,453
where we can't compensate
for hypoxia,

2696
02:17:07,453 --> 02:17:09,555
saturations around 70 or so.

2697
02:17:10,823 --> 02:17:17,196
So, he wrote in a prescient way,
"It's possible that red cells

2698
02:17:17,196 --> 02:17:20,966
prevent accumulation
of inhibitor or release a factor

2699
02:17:20,966 --> 02:17:22,968
that enhances
vascular responsiveness."

2700
02:17:22,968 --> 02:17:25,003
Pretty clever guy.

2701
02:17:25,003 --> 02:17:27,506
Took a while to figure
out what that was.

2702
02:17:28,073 --> 02:17:31,810
So, only recently
do we understand

2703
02:17:31,810 --> 02:17:37,282
that red cells
monitor oxygen gradients

2704
02:17:37,282 --> 02:17:41,520
and either dispense or sequester
nitric oxide in response

2705
02:17:41,520 --> 02:17:47,392
to those gradients to match
impedance to flow to demand.

2706
02:17:47,926 --> 02:17:51,330
And so red cells entering a
very well-perfused blood vessel

2707
02:17:51,330 --> 02:17:54,600
will sequester this vasodilator,

2708
02:17:54,600 --> 02:17:58,036
and they leave behind a slightly
smaller vessel than they enter.

2709
02:17:58,036 --> 02:18:02,141
And red cells that enter
a hypoxic blood vessel

2710
02:18:02,941 --> 02:18:04,943
add the amount of nitric oxide,

2711
02:18:04,943 --> 02:18:07,679
and they leave behind
a slightly bigger vessel.

2712
02:18:07,679 --> 02:18:10,215
This is happening
on a millisecond time scale,

2713
02:18:10,782 --> 02:18:15,087
with trillions of red cells all
like itty bitty little IO chips

2714
02:18:15,087 --> 02:18:18,524
flying around your circulation
asking, "Is there enough oxygen?

2715
02:18:18,524 --> 02:18:19,925
Is there enough?
Is there enough?

2716
02:18:19,925 --> 02:18:22,728
You want a little more?
You have too much?"

2717
02:18:22,728 --> 02:18:24,763
So every red cell
is asking that question

2718
02:18:24,763 --> 02:18:27,032
and adjusting
the blood vessel size.

2719
02:18:27,633 --> 02:18:31,503
And that doesn't happen so well
with sickle red cells.

2720
02:18:32,104 --> 02:18:33,705
I'll explain why.

2721
02:18:34,640 --> 02:18:38,610
So, the adaptive change.
I told you about this already.

2722
02:18:39,111 --> 02:18:41,713
Okay.
Red cell phenotype is adapting,

2723
02:18:42,581 --> 02:18:45,817
and it turns out that
the phenotype is oscillating

2724
02:18:45,817 --> 02:18:47,352
during circulatory transit.

2725
02:18:47,352 --> 02:18:49,388
So, red cells that are
going through arteries

2726
02:18:49,388 --> 02:18:52,925
are different than the red cells
that are returning in veins.

2727
02:18:52,925 --> 02:18:54,560
They have different
oxygen affinity,

2728
02:18:54,560 --> 02:18:56,929
different deformability,
different chemistry,

2729
02:18:56,929 --> 02:18:58,564
different energy metabolism.

2730
02:18:59,164 --> 02:19:01,633
And in fact, they're doing
this in proportion

2731
02:19:01,633 --> 02:19:04,703
to the amount of oxygen
lack or availability.

2732
02:19:05,370 --> 02:19:10,375
And so that is happening
on a subacute time scale

2733
02:19:10,375 --> 02:19:12,811
or acute time scale
during circulatory transit,

2734
02:19:12,811 --> 02:19:14,680
which is what
I'll talk about today.

2735
02:19:14,680 --> 02:19:18,250
Subacute time scale, which is
like high altitude adaptation --

2736
02:19:18,250 --> 02:19:21,286
everybody knows red cells
change during that.

2737
02:19:21,286 --> 02:19:24,756
They can also change with
anemia, sustained anemia,

2738
02:19:24,756 --> 02:19:27,793
or stress,
or increased odor consumption,

2739
02:19:27,793 --> 02:19:29,261
and then a chronic time scale

2740
02:19:29,261 --> 02:19:32,397
where the actual
transcriptional phenotype

2741
02:19:32,397 --> 02:19:34,533
is part
of the adaptive change.

2742
02:19:35,167 --> 02:19:38,303
So, the failure of red cell
phenotype adaptation

2743
02:19:38,303 --> 02:19:41,974
contributes to morbidity
and non-hematologic disease.

2744
02:19:41,974 --> 02:19:43,175
That's newly understood,

2745
02:19:43,175 --> 02:19:45,510
but it's also
an underappreciated part

2746
02:19:45,510 --> 02:19:48,780
of hematologic disease
as in sickle cell.

2747
02:19:49,681 --> 02:19:51,383
And here
we're going to focus.

2748
02:19:51,383 --> 02:19:54,519
So mature red cells
harbor a functional ENOS.

2749
02:19:54,519 --> 02:19:56,221
Without getting
into those details,

2750
02:19:56,221 --> 02:19:58,957
a lot of people think
mature red cells,

2751
02:19:58,957 --> 02:20:01,460
like,
they forget their cells.

2752
02:20:02,027 --> 02:20:06,098
Like it's just an envelope
of hemoglobin,

2753
02:20:06,098 --> 02:20:07,833
and when we talk about it,
we just say, like,

2754
02:20:07,833 --> 02:20:09,134
"What's the hemoglobin?"
Right?

2755
02:20:09,134 --> 02:20:12,371
Nobody is asking, like, well,
how well does it work?

2756
02:20:12,971 --> 02:20:16,508
Like in what other disease,
what other specialty?

2757
02:20:16,508 --> 02:20:19,745
You don't see cardiologists
counting myocytes, right?

2758
02:20:19,745 --> 02:20:22,414
Or a nephrologist
counting nephrons.

2759
02:20:22,414 --> 02:20:24,216
They like,
"How well does it work?

2760
02:20:24,850 --> 02:20:26,418
Like, I'm sorry,

2761
02:20:26,418 --> 02:20:28,820
but hematologists
like count the cells,

2762
02:20:28,820 --> 02:20:31,323
but don't always ask
how well they work.

2763
02:20:32,024 --> 02:20:34,493
And that's
an important distinction."

2764
02:20:34,493 --> 02:20:36,895
And people forget they actually
are really complex,

2765
02:20:36,895 --> 02:20:38,163
as I'll show you.

2766
02:20:38,163 --> 02:20:41,900
These are mature red cells
that have this signaling in it.

2767
02:20:41,900 --> 02:20:44,102
And people's like,
"That can't be true."

2768
02:20:44,102 --> 02:20:48,907
And so it was a big revolution
back in the day or 10 years ago

2769
02:20:48,907 --> 02:20:50,275
or so when people said,

2770
02:20:50,275 --> 02:20:52,778
"Oh, this is going on
in mature red cells."

2771
02:20:53,478 --> 02:20:55,447
So, what I'm going to do
is show you --

2772
02:20:56,348 --> 02:20:57,716
go through this kind of fast --

2773
02:20:57,716 --> 02:21:00,485
some of them like proof
that red cells

2774
02:21:00,485 --> 02:21:03,055
are doing this sophisticated
signaling,

2775
02:21:03,055 --> 02:21:05,424
and then explain what it does

2776
02:21:06,024 --> 02:21:08,026
and how it helps support
oxygen delivery,

2777
02:21:08,026 --> 02:21:12,431
and then show you a bit about
why it doesn't work in human,

2778
02:21:12,431 --> 02:21:14,366
in sickle cell disease.

2779
02:21:14,366 --> 02:21:17,135
So, this is an assay
that's reporting the amount

2780
02:21:17,135 --> 02:21:20,472
of nitric oxide being generated
inside a red cell.

2781
02:21:21,273 --> 02:21:24,609
And first of all, that red cells
even do that was new,

2782
02:21:24,609 --> 02:21:27,813
but it turns out that red cells
do that

2783
02:21:27,813 --> 02:21:29,981
as a response
to how much oxygen they have.

2784
02:21:31,416 --> 02:21:35,253
So this is on the y-axis,
is time on the right.

2785
02:21:35,253 --> 02:21:38,223
Left y-axis,
on the x-axis is time.

2786
02:21:38,223 --> 02:21:42,027
On the right y-axis
is hemoglobin oxygen content.

2787
02:21:42,027 --> 02:21:44,496
The left is the amount
of NO being produced.

2788
02:21:45,230 --> 02:21:48,500
And you can see that
in the circles,

2789
02:21:48,500 --> 02:21:51,036
the red cells are,
have oxygenated.

2790
02:21:51,036 --> 02:21:53,338
The squares,
they're deoxygenated.

2791
02:21:53,338 --> 02:21:55,273
And when you deoxygenate
the red cell,

2792
02:21:55,273 --> 02:21:57,576
it makes more nitric oxide.
Okay.

2793
02:21:59,344 --> 02:22:03,281
Turns out that
if you take red cells from mice

2794
02:22:03,281 --> 02:22:06,952
that don't have nitric oxide
synthase, this doesn't happen.

2795
02:22:07,652 --> 02:22:10,389
Okay.
That kind of makes sense,

2796
02:22:10,389 --> 02:22:15,127
but people used to think
it was nitric oxide

2797
02:22:15,127 --> 02:22:18,163
that was getting captured
from endothelial cells

2798
02:22:18,163 --> 02:22:19,664
and then processed
in red cells.

2799
02:22:19,664 --> 02:22:22,901
In fact, there was a Nobel prize
for that wrong idea,

2800
02:22:22,901 --> 02:22:25,971
but red cells
actually make their own.

2801
02:22:27,973 --> 02:22:31,009
So how does that work?

2802
02:22:31,009 --> 02:22:33,011
Like, how does the enzyme
get turned on?

2803
02:22:33,678 --> 02:22:37,783
So, we started thinking
about calcium and calcium

2804
02:22:37,783 --> 02:22:41,653
signaling activates nitric oxide
synthase in other cells.

2805
02:22:41,653 --> 02:22:44,723
Does calcium signaling work
like this in red cells?

2806
02:22:44,723 --> 02:22:47,859
And red cells have a channel
called Piezo1,

2807
02:22:47,859 --> 02:22:49,728
which is,
opens mechanically.

2808
02:22:50,562 --> 02:22:53,331
So here, without going
into the details,

2809
02:22:53,331 --> 02:22:57,102
we're looking at how much
calcium is produced

2810
02:22:57,102 --> 02:22:58,904
with the same construct.

2811
02:22:58,904 --> 02:23:01,339
Okay.
We're deoxygenating the cells.

2812
02:23:01,339 --> 02:23:04,843
And blue is deoxygenated,
red is oxygenated,

2813
02:23:04,843 --> 02:23:07,946
and open squares, we've
taken away all the calcium.

2814
02:23:07,946 --> 02:23:10,849
You can see that
deoxygenated red cells

2815
02:23:11,349 --> 02:23:13,418
have more calcium coming in.

2816
02:23:13,418 --> 02:23:18,290
And if we block this specific
channel with the GSM TX,

2817
02:23:18,290 --> 02:23:19,658
you don't get it.

2818
02:23:19,658 --> 02:23:23,395
So Piezo1 is opening
in red cells,

2819
02:23:23,962 --> 02:23:26,731
and Piezo1 is
bringing in calcium

2820
02:23:26,731 --> 02:23:28,733
when red cells deoxygenate.

2821
02:23:28,733 --> 02:23:31,636
So, there's a problem there that
I'm going to have to deal with

2822
02:23:31,636 --> 02:23:35,240
because Piezo1 is only supposed
to open when cells deform,

2823
02:23:36,241 --> 02:23:37,943
and it's a mechanical channel.

2824
02:23:37,943 --> 02:23:40,946
So, how is it opening when red
cells are just sitting still?

2825
02:23:41,580 --> 02:23:43,181
But we'll talk about that.

2826
02:23:43,715 --> 02:23:46,017
Now, the other thing
that's interesting is that

2827
02:23:46,017 --> 02:23:50,255
the ENOS, this enzyme, is flying
around inside the red cells.

2828
02:23:50,255 --> 02:23:54,359
It's moving from the cytoplasm
out to the periphery.

2829
02:23:54,359 --> 02:23:55,827
And of course,
we're showing here

2830
02:23:55,827 --> 02:23:58,463
there's none in the
ENOS-deficient red cells.

2831
02:23:59,097 --> 02:24:03,668
On the left under red is this
enzyme in oxygenated red cells,

2832
02:24:03,668 --> 02:24:07,205
and on the right under blue,
it's in deoxygenated red cells.

2833
02:24:07,205 --> 02:24:09,074
You see it's moving
to the membrane,

2834
02:24:09,975 --> 02:24:12,143
and that's also
kind of strange.

2835
02:24:12,143 --> 02:24:15,380
This is migrating back
and forth inside red cells,

2836
02:24:15,380 --> 02:24:18,917
and how could that be happening?
And really, to really be sure,

2837
02:24:18,917 --> 02:24:23,154
these are optical tomography
sessions through red cells.

2838
02:24:23,154 --> 02:24:27,058
You can see it's very
clearly dispersed and not.

2839
02:24:27,692 --> 02:24:30,128
And these are the mouse cells.

2840
02:24:30,128 --> 02:24:34,299
So it's definitely happening.
And this is further --

2841
02:24:34,299 --> 02:24:36,034
we're quantifying
the fluorescence --

2842
02:24:36,034 --> 02:24:37,903
and you can see
that difference.

2843
02:24:37,903 --> 02:24:41,039
And if you prevent
the conformational change

2844
02:24:41,039 --> 02:24:43,375
that red cells
make when they deoxygenate,

2845
02:24:43,375 --> 02:24:44,643
you prevent that change.

2846
02:24:44,643 --> 02:24:47,679
So it's actually beginning
with this conformational change.

2847
02:24:47,679 --> 02:24:49,581
It's not the amount of oxygen.

2848
02:24:50,715 --> 02:24:56,154
So also, if you open
the calcium channel

2849
02:24:56,154 --> 02:24:57,789
without deoxygenating
the red cell,

2850
02:24:57,789 --> 02:25:00,058
you can make nitric oxide move.

2851
02:25:00,058 --> 02:25:04,763
So, it's a calcium signal
that hemoglobin is deoxygenating

2852
02:25:04,763 --> 02:25:06,498
and causing the calcium
to come in.

2853
02:25:07,032 --> 02:25:13,004
So then, what's next?
There's some phosphorylation.

2854
02:25:13,004 --> 02:25:15,574
So ENOS has complex regulation,

2855
02:25:15,574 --> 02:25:19,711
and it is getting phosphorylated
in a particular pattern

2856
02:25:19,711 --> 02:25:23,715
in deoxygenated red cells
that promotes activation.

2857
02:25:23,715 --> 02:25:27,052
And that pattern
can be recapitulated

2858
02:25:27,052 --> 02:25:29,454
with all the signaling
that I'm talking about.

2859
02:25:29,454 --> 02:25:32,958
You deoxygenate the red cell,
you open the calcium channel,

2860
02:25:33,525 --> 02:25:36,428
you prevent the hemoglobin
conformation change,

2861
02:25:36,428 --> 02:25:39,264
you can cause
the correct pattern.

2862
02:25:39,264 --> 02:25:45,370
So, we see that the hemoglobin
conformation is changing,

2863
02:25:45,370 --> 02:25:47,472
calcium is coming in,

2864
02:25:47,472 --> 02:25:50,308
ENOS is migrating,
it's getting phosphorylated

2865
02:25:50,308 --> 02:25:55,447
and producing nitric oxide.
And again, we can produce --

2866
02:25:55,447 --> 02:26:00,151
this is just data confirming
again in a different way --

2867
02:26:00,151 --> 02:26:02,387
that we can not
only recapitulate

2868
02:26:02,387 --> 02:26:03,755
the phosphorylation pattern,

2869
02:26:03,755 --> 02:26:08,093
we can recapitulate the amount
of nitric oxide being produced.

2870
02:26:08,893 --> 02:26:10,962
So the real question is,

2871
02:26:10,962 --> 02:26:13,465
how's this all getting started
in the first place?

2872
02:26:14,332 --> 02:26:18,937
So I'm like, how does
a mechanical channel open

2873
02:26:18,937 --> 02:26:20,305
without the cell
being deformed?

2874
02:26:20,305 --> 02:26:22,974
Well, it turns out
red cells have myosin,

2875
02:26:23,708 --> 02:26:27,545
and there's a special form
called non-muscle myosin

2876
02:26:28,213 --> 02:26:29,781
that we wondered,

2877
02:26:29,781 --> 02:26:32,984
"Maybe this is pulling
the Piezo1 channel open."

2878
02:26:33,752 --> 02:26:39,958
It turns out if you block
this protein, non-muscle myosin,

2879
02:26:39,958 --> 02:26:43,495
then you can prevent
the deoxygenation-induced

2880
02:26:44,095 --> 02:26:46,798
opening of the calcium channel

2881
02:26:46,798 --> 02:26:48,667
and the production
of nitric oxide.

2882
02:26:49,534 --> 02:26:52,937
So, what's going on
is hemoglobin conformation

2883
02:26:52,937 --> 02:26:54,172
is changing,

2884
02:26:54,172 --> 02:26:56,241
it's docking
on a special protein

2885
02:26:56,241 --> 02:26:59,844
in the membrane that's
activating non-muscle myosin.

2886
02:26:59,844 --> 02:27:04,015
Non-muscle myosin is
pulling open a calcium channel.

2887
02:27:04,015 --> 02:27:09,554
Calcium is coming into the cell,
causing nitric oxide to migrate

2888
02:27:09,554 --> 02:27:12,991
and get activated
and then produce nitric oxide.

2889
02:27:13,758 --> 02:27:16,528
That's a lot for an envelope
with hemoglobin.

2890
02:27:18,797 --> 02:27:19,998
So then, what happens?

2891
02:27:19,998 --> 02:27:22,534
What happens after
the nitric oxide is made?

2892
02:27:23,234 --> 02:27:26,171
It signals ubiquitously
in a system

2893
02:27:26,171 --> 02:27:29,808
called protein S-nitrosylation,
which is like phosphorylation.

2894
02:27:31,509 --> 02:27:33,745
We looked at this,
and this pattern --

2895
02:27:33,745 --> 02:27:37,415
the heat map -- you can see
these are membrane on the left,

2896
02:27:38,183 --> 02:27:39,784
the cytoplasm on the right,

2897
02:27:40,351 --> 02:27:43,121
deoxygenated red cells
in the left panel,

2898
02:27:43,121 --> 02:27:46,591
left sort of column,
and oxygenated on the right.

2899
02:27:46,591 --> 02:27:51,896
You can see that the pattern
of NO nitric oxide on protein

2900
02:27:51,896 --> 02:27:54,933
is totally different.
These are thousands of proteins

2901
02:27:54,933 --> 02:27:59,371
that are changing as a function
of nitric oxide being activated.

2902
02:27:59,371 --> 02:28:03,208
So the red cell phenotype
is being manipulated

2903
02:28:03,208 --> 02:28:04,809
in a very sophisticated way

2904
02:28:04,809 --> 02:28:07,312
as the red cells
go through circulation.

2905
02:28:07,312 --> 02:28:11,950
And this is the glycolysis
and other features.

2906
02:28:11,950 --> 02:28:14,352
And this is just showing,
you know, you just don't see

2907
02:28:14,352 --> 02:28:16,955
that when you don't have
nitric oxide enzyme around.

2908
02:28:16,955 --> 02:28:19,391
So what's the consequence?

2909
02:28:20,225 --> 02:28:24,629
So first thing is the way
red cells use energy changes.

2910
02:28:24,629 --> 02:28:28,166
Red cells, ironically,
don't use oxygen, right?

2911
02:28:28,166 --> 02:28:30,935
So, they have no mitochondria,
but they burn glucose.

2912
02:28:30,935 --> 02:28:33,138
They burn glucose anaerobically.

2913
02:28:33,138 --> 02:28:36,107
And the way they route
the glucose changes.

2914
02:28:36,107 --> 02:28:40,378
And glucose is routed more
towards antioxidant systems

2915
02:28:40,912 --> 02:28:43,648
in deoxygenating red cells,

2916
02:28:43,648 --> 02:28:46,885
primarily because of this
nitric oxide signaling,

2917
02:28:46,885 --> 02:28:50,021
so that they can recycle
NADPH and glutathione,

2918
02:28:50,755 --> 02:28:54,659
which is very necessary for the
thiol-based antioxidant systems.

2919
02:28:54,659 --> 02:28:56,461
That makes perfect sense.

2920
02:28:56,461 --> 02:28:59,297
And then, when red cells
come back around, okay,

2921
02:28:59,297 --> 02:29:02,300
then glucose is routed
in a different way,

2922
02:29:02,300 --> 02:29:04,869
and you're making NADH and ATP,

2923
02:29:04,869 --> 02:29:08,807
which is reducing methemoglobin
and governing ion channel flux.

2924
02:29:10,141 --> 02:29:12,677
So, deformability.

2925
02:29:13,545 --> 02:29:18,383
The red cell cytoskeleton
is very, very well characterized

2926
02:29:18,383 --> 02:29:21,252
but has principally been thought
of as a static system --

2927
02:29:21,986 --> 02:29:24,322
that it's not that adaptive.

2928
02:29:24,322 --> 02:29:30,094
Now, take a neutrophil
or a macrophage

2929
02:29:30,094 --> 02:29:32,430
that is sort of moving
around like this.

2930
02:29:32,430 --> 02:29:37,268
I mean, you've got incredible
versatility in the cytoskeleton.

2931
02:29:37,268 --> 02:29:40,205
The cytoskeleton
can be a motor,

2932
02:29:40,972 --> 02:29:44,309
and red cell deformability
is changing

2933
02:29:44,309 --> 02:29:45,877
during circulatory transit.

2934
02:29:45,877 --> 02:29:48,046
But what's happening
with the cytoskeleton?

2935
02:29:48,847 --> 02:29:51,516
Well, it turns out
the cytoskeleton is assembling

2936
02:29:51,516 --> 02:29:54,752
and disassembling
every few seconds

2937
02:29:54,752 --> 02:29:57,755
as red cells traverse
our circulatory tree.

2938
02:29:58,389 --> 02:29:59,624
This is on the top.

2939
02:29:59,624 --> 02:30:03,895
We're looking at actin
at the bottom.

2940
02:30:03,895 --> 02:30:05,563
We're looking at spectrin.

2941
02:30:05,563 --> 02:30:11,035
You can see that there's
a diffuse cytoskeleton

2942
02:30:11,035 --> 02:30:13,605
that's complex going
throughout the cytosol

2943
02:30:13,605 --> 02:30:15,473
when the red cells
are oxygenated,

2944
02:30:15,473 --> 02:30:17,642
and it collapses
on deoxygenation.

2945
02:30:17,642 --> 02:30:19,944
This is happening
over and over again.

2946
02:30:20,945 --> 02:30:23,081
Turns out that doesn't happen

2947
02:30:23,081 --> 02:30:27,719
if you don't have nitric oxide
or nitric oxide synthase.

2948
02:30:27,719 --> 02:30:32,757
And you don't have that
if you prevent

2949
02:30:32,757 --> 02:30:35,894
this whole signaling system
that I was talking about before.

2950
02:30:36,895 --> 02:30:39,664
So, what does that mean
for deformability?

2951
02:30:39,664 --> 02:30:42,100
And so we had to figure out
a way to measure deformability

2952
02:30:42,100 --> 02:30:45,737
without deforming the cell.
So, if you deform the cell,

2953
02:30:46,304 --> 02:30:48,406
then you open
the calcium channel,

2954
02:30:48,406 --> 02:30:50,108
and now you've got a problem.

2955
02:30:50,108 --> 02:30:54,879
So, we're using something
called Brillouin spectroscopy,

2956
02:30:54,879 --> 02:30:58,216
which is a no-touch way
of measuring deformability

2957
02:30:58,216 --> 02:31:02,453
through photoacoustics
that is quite interesting.

2958
02:31:03,321 --> 02:31:07,892
But the bottom line
is that red cells --

2959
02:31:07,892 --> 02:31:09,294
and this is just validating it

2960
02:31:09,294 --> 02:31:13,598
with opening the calcium channel
causing deformability

2961
02:31:13,598 --> 02:31:16,234
and stiffening the red cell
with something called diamide

2962
02:31:16,234 --> 02:31:18,336
and showing that
we can measure this.

2963
02:31:18,336 --> 02:31:21,472
It turns out that when you
deoxygenate the red cells,

2964
02:31:22,006 --> 02:31:23,975
they have an increase
in deformability

2965
02:31:23,975 --> 02:31:26,511
because the cytoskeleton
is collapsing.

2966
02:31:26,511 --> 02:31:27,812
And this doesn't happen

2967
02:31:27,812 --> 02:31:30,148
if you don't have
nitric oxide synthase.

2968
02:31:32,684 --> 02:31:36,588
Just in the interest of time,
also the Bohr effect,

2969
02:31:36,588 --> 02:31:40,158
which is a complex control
of pH within red cells,

2970
02:31:40,158 --> 02:31:43,261
fails when you don't have
nitric oxide synthase.

2971
02:31:43,261 --> 02:31:45,930
And that's necessary
for O2 delivery homeostasis.

2972
02:31:46,564 --> 02:31:48,967
And the vasodilation
that I told you about

2973
02:31:48,967 --> 02:31:51,736
before that was the basis
of the Guyton experiment

2974
02:31:51,736 --> 02:31:55,239
also fails when you don't have
nitric oxide synthase.

2975
02:31:55,239 --> 02:31:57,976
And if you try to run mice
that don't have nitric oxide

2976
02:31:57,976 --> 02:32:01,679
synthase in their red cells,
they fall over.

2977
02:32:01,679 --> 02:32:05,283
So, basically, you need it
to scale your production.

2978
02:32:05,283 --> 02:32:07,485
Now, what happens
in sickle red cells?

2979
02:32:08,686 --> 02:32:11,255
So, we took a look,

2980
02:32:11,255 --> 02:32:14,859
and it turns out the regulatory
controls of the system

2981
02:32:14,859 --> 02:32:18,262
don't work in sickle red cells.
So, the sickle red cells,

2982
02:32:18,262 --> 02:32:21,866
which are supposed to have
an increase in calcium signaling

2983
02:32:21,866 --> 02:32:25,803
when you open Piezo
or when you close Piezol,

2984
02:32:25,803 --> 02:32:30,541
are insensitive to manipulation
of the Piezo1 channel.

2985
02:32:30,541 --> 02:32:34,545
So there's some other calcium
flux going on that

2986
02:32:34,545 --> 02:32:36,314
is interfering
with this system.

2987
02:32:36,848 --> 02:32:39,117
And therefore,
the nitric oxide synthase

2988
02:32:39,117 --> 02:32:41,352
is not responding
to normal controls,

2989
02:32:41,953 --> 02:32:44,722
and the regulation
of nitric oxide synthase --

2990
02:32:44,722 --> 02:32:47,425
the phosphorylation pattern --
is abnormal.

2991
02:32:47,425 --> 02:32:51,729
It's actually turned on all the
time, which was a surprise.

2992
02:32:51,729 --> 02:32:55,066
And it turns out the
cytoskeleton doesn't collapse

2993
02:32:55,066 --> 02:32:58,503
during circulatory
transit the way it should.

2994
02:32:59,070 --> 02:33:03,007
And because it doesn't collapse
during circulatory transit --

2995
02:33:03,007 --> 02:33:07,211
you can see these are red cells
where spectrin and actin

2996
02:33:07,211 --> 02:33:10,148
is not disappearing
when red cells deoxygenate.

2997
02:33:10,681 --> 02:33:15,586
These red cells, when we examine
them with Brillouin microscopy,

2998
02:33:15,586 --> 02:33:18,122
don't show
the deoxygenation-induced

2999
02:33:18,823 --> 02:33:20,091
increase in deformability.

3000
02:33:20,091 --> 02:33:22,493
In fact, as you all know,
it goes the other way.

3001
02:33:23,061 --> 02:33:27,365
So this is just the same thing
with sickled red cells.

3002
02:33:27,365 --> 02:33:32,070
So, it turns out that ENOS
is coordinating

3003
02:33:32,070 --> 02:33:35,406
a phenotype modulation
during circulatory transit

3004
02:33:35,406 --> 02:33:38,042
that supports
oxygen delivery homeostasis

3005
02:33:38,042 --> 02:33:39,877
whenever there's stress.

3006
02:33:40,411 --> 02:33:43,681
And that means, you know,
we, okay,

3007
02:33:43,681 --> 02:33:45,550
if you have normal red cells,

3008
02:33:45,550 --> 02:33:48,119
then you can run up and
downstairs and not fall over.

3009
02:33:48,119 --> 02:33:51,222
You can run up and downstairs
without getting claudication,

3010
02:33:51,222 --> 02:33:52,790
and you can have
a little asthma,

3011
02:33:52,790 --> 02:33:54,125
and you don't have a stroke,

3012
02:33:54,125 --> 02:33:56,561
and you don't have
all these problems

3013
02:33:56,561 --> 02:33:58,696
with oxygen delivery
in the periphery

3014
02:33:58,696 --> 02:34:01,766
that fail every time
there's a little bit of change

3015
02:34:01,766 --> 02:34:04,769
in oxygen delivery availability
or consumption.

3016
02:34:04,769 --> 02:34:08,005
And that this is
a complex system

3017
02:34:08,005 --> 02:34:10,641
with a lot of potential
druggable targets in it.

3018
02:34:11,342 --> 02:34:14,612
So, I apologize
for going through

3019
02:34:14,612 --> 02:34:16,013
a lot of that kind of fast,

3020
02:34:16,013 --> 02:34:19,584
but I wanted to give you an
overlay of an interesting system

3021
02:34:19,584 --> 02:34:21,452
that may improve
our understanding

3022
02:34:21,452 --> 02:34:24,489
of why patients
with sickle cell disease

3023
02:34:24,489 --> 02:34:27,825
can't seem to adapt
to hypoxia

3024
02:34:27,825 --> 02:34:30,361
in the way
that a normal person can.

3025
02:34:30,361 --> 02:34:34,265
And it's not just about
hemoglobin polymerization.

3026
02:34:34,265 --> 02:34:36,400
There's much more
to the disease than that.

3027
02:34:37,034 --> 02:34:40,204
The sickle red cells
just are metabolically different

3028
02:34:40,204 --> 02:34:42,106
even when they're not sickling.

3029
02:34:42,106 --> 02:34:44,942
So, I want to acknowledge the
people that did all this work --

3030
02:34:44,942 --> 02:34:47,445
principally, the two in red
there in the lab

3031
02:34:47,445 --> 02:34:49,247
who did all of the work,
in fact,

3032
02:34:49,747 --> 02:34:53,651
and the many colleagues
and support for the program.

3033
02:34:53,651 --> 02:34:55,253
Happy to take any questions.

3034
02:34:56,754 --> 02:35:03,661
[applause]

3035
02:35:03,661 --> 02:35:05,396
Female Speaker: Thank you
so much.

3036
02:35:05,396 --> 02:35:11,169
It was a really, for me,
you know, a real eye opener.

3037
02:35:11,736 --> 02:35:13,871
Actually, Manu has got
his hand up.

3038
02:35:16,707 --> 02:35:18,376
Manu Platt: Great. Thank you,
Manu Platt, NIH.

3039
02:35:18,376 --> 02:35:19,577
This was interesting.

3040
02:35:19,577 --> 02:35:22,547
So, I'm talking next,
but E, as you know,

3041
02:35:22,547 --> 02:35:24,482
the E in ENOS
is endothelial, right?

3042
02:35:24,482 --> 02:35:26,150
Because I come out
of a shear stress

3043
02:35:26,150 --> 02:35:27,819
endothelial cell
biology background

3044
02:35:27,819 --> 02:35:29,554
where we think it is one
of the genes quite unique

3045
02:35:29,554 --> 02:35:30,788
to endothelial cells.

3046
02:35:30,788 --> 02:35:33,624
So, all of this
is blowing to me,

3047
02:35:33,624 --> 02:35:36,027
and I've got to dig into
the literature you showed us.

3048
02:35:36,027 --> 02:35:37,995
But one of my things that
we know in endothelial cells

3049
02:35:37,995 --> 02:35:39,764
is ENOS
is shear stress-regulated

3050
02:35:39,764 --> 02:35:42,733
so that it gets phosphorylated
under high flow and high shear.

3051
02:35:42,733 --> 02:35:45,570
Endothelial cells being adhered
cells, so you can --

3052
02:35:45,570 --> 02:35:48,039
they are standing still while
the blood is moving over them.

3053
02:35:48,039 --> 02:35:50,441
How do you imagine
that looks in your RBCs

3054
02:35:50,441 --> 02:35:51,709
that are experiencing shear

3055
02:35:51,709 --> 02:35:54,045
while they're moving
with the blood flow,

3056
02:35:54,045 --> 02:35:56,847
but some of your activations
and localization

3057
02:35:56,847 --> 02:36:00,251
from internal to the cell
to the cell membrane?

3058
02:36:00,251 --> 02:36:01,786
And I'm just curious
how that plays

3059
02:36:01,786 --> 02:36:03,387
with these RBCs under flow.

3060
02:36:03,988 --> 02:36:06,224
Alan Docter: Yeah,
great question.

3061
02:36:06,224 --> 02:36:10,995
And so obviously what we're
doing here is trying to --

3062
02:36:11,596 --> 02:36:15,433
we were trying to dissect
or decouple something

3063
02:36:15,433 --> 02:36:19,136
that's going on
at the same time in real life.

3064
02:36:19,136 --> 02:36:22,840
So as the red cells are
deoxygenating and reoxygenating,

3065
02:36:22,840 --> 02:36:27,245
they're also deforming.
And the deformation is also --

3066
02:36:27,245 --> 02:36:30,948
the intensity of the deformation
is linked in part, obviously,

3067
02:36:30,948 --> 02:36:36,120
to the oxygen gradient
in that particular spot.

3068
02:36:36,120 --> 02:36:39,757
So, the -- I would think
the deformation signal

3069
02:36:39,757 --> 02:36:45,096
would be a change in tandem
with the deoxygenation signal.

3070
02:36:45,096 --> 02:36:47,798
Now, we haven't begun
to look at that yet.

3071
02:36:47,798 --> 02:36:49,500
We're only really been looking

3072
02:36:49,500 --> 02:36:52,136
at what's happening
with deoxygenation

3073
02:36:52,136 --> 02:36:55,573
and how Piezo is opening
just with deoxygenation,

3074
02:36:55,573 --> 02:36:57,408
which we thought
was kind of amazing

3075
02:36:57,408 --> 02:37:01,445
that there's a motor protein
that's kind of tickling it open

3076
02:37:02,246 --> 02:37:04,215
when the cells
are sitting still.

3077
02:37:04,215 --> 02:37:08,152
So, when we found that
when we were using, say,

3078
02:37:08,719 --> 02:37:10,988
an instrument that has --

3079
02:37:10,988 --> 02:37:13,824
say, you're familiar with
the Lorca instrument, right?

3080
02:37:13,824 --> 02:37:15,393
Which, when you try to deform,

3081
02:37:15,393 --> 02:37:18,229
when you are measuring
deformability

3082
02:37:18,229 --> 02:37:20,064
by deforming the cell,

3083
02:37:20,064 --> 02:37:22,366
we're interfering
with all this signaling.

3084
02:37:22,366 --> 02:37:25,970
So my suspicion is that these
things are acting in synergy,

3085
02:37:25,970 --> 02:37:28,839
but we haven't begun
to evaluate it.

3086
02:37:29,840 --> 02:37:31,208
But yes, good question.

3087
02:37:31,208 --> 02:37:34,445
And the E, you know,
it's a holdover.

3088
02:37:34,445 --> 02:37:38,049
It's really in more tissue types
than just the endothelium.

3089
02:37:40,184 --> 02:37:41,452
Female Speaker: That
was remarkable.

3090
02:37:41,452 --> 02:37:42,820
Thank you.

3091
02:37:42,820 --> 02:37:45,022
What do you think
the impact of medications

3092
02:37:45,022 --> 02:37:48,392
that delay conformational change
would have in this system?

3093
02:37:48,392 --> 02:37:49,994
Alan Docter: Yeah, great
question, right?

3094
02:37:51,862 --> 02:37:57,068
Okay. So if you,
so you might initially think,

3095
02:37:57,068 --> 02:37:58,703
"Oh, that's going
to be a problem," right?

3096
02:37:58,703 --> 02:38:04,375
Because we need that signal in
order to activate the program.

3097
02:38:04,375 --> 02:38:09,246
This is really about 10 percent
or less of the hemoglobin it,

3098
02:38:09,246 --> 02:38:12,450
so most of the hemoglobin
is nowhere near the membrane.

3099
02:38:12,450 --> 02:38:14,752
There's a special population
of hemoglobin

3100
02:38:14,752 --> 02:38:17,088
that's involved in this
type of regulation

3101
02:38:17,088 --> 02:38:19,323
that's in
the submembrane domain,

3102
02:38:19,323 --> 02:38:23,327
and it's the first hemoglobin
to deoxygenate.

3103
02:38:23,327 --> 02:38:26,464
So what -- there is
an interesting literature

3104
02:38:26,464 --> 02:38:30,368
on the cascade
of how much --

3105
02:38:30,368 --> 02:38:32,403
where in the red cell
is the hemoglobin,

3106
02:38:32,403 --> 02:38:33,871
is the oxygen
actually coming from,

3107
02:38:33,871 --> 02:38:36,207
and where the conformation
change is occurring.

3108
02:38:36,774 --> 02:38:41,278
So, there's a risk
that drugs like Voxelotor

3109
02:38:41,278 --> 02:38:43,748
or others that shift
the O2,

3110
02:38:45,683 --> 02:38:50,154
you know, affinity would be
retarding the signaling.

3111
02:38:50,721 --> 02:38:54,892
But we haven't even begun
to explore that.

3112
02:38:54,892 --> 02:38:57,995
There are ways to compensate
for that, perhaps,

3113
02:38:57,995 --> 02:39:02,500
but we haven't -- that's a good
question and probably relevant.

3114
02:39:03,434 --> 02:39:05,035
Male Speaker: Well, I was
wondering,

3115
02:39:06,237 --> 02:39:09,507
I was wondering,
have you done a comparison

3116
02:39:09,507 --> 02:39:16,147
between F cells and adult cells
and their ENOS content?

3117
02:39:18,716 --> 02:39:21,385
Alan Docter: Yes,
a long time ago,

3118
02:39:21,385 --> 02:39:25,389
but not here.
So we did it a long time ago

3119
02:39:25,389 --> 02:39:27,458
when we were looking
at sort of crude --

3120
02:39:28,025 --> 02:39:30,594
the amount of nitric oxide
that can be generated

3121
02:39:30,594 --> 02:39:34,999
to dilate a blood vessel --
and F cells generate more.

3122
02:39:35,599 --> 02:39:39,437
So, I don't know why.
And that's funny because

3123
02:39:39,437 --> 02:39:44,975
they have a right-shifted
oxygen dissociation curve,

3124
02:39:44,975 --> 02:39:49,680
but they generate more
NO than a non-F cell.

3125
02:39:50,381 --> 02:39:54,452
I don't know why, but we haven't
looked at those cells

3126
02:39:54,452 --> 02:39:56,253
with this particular system.

3127
02:39:56,253 --> 02:39:58,956
Male Speaker: Yeah. One thing
that interests me is how,

3128
02:39:58,956 --> 02:40:02,993
in patients who could easily
discriminate F cell content,

3129
02:40:03,627 --> 02:40:07,031
and I'm just wondering
if this is a way of doing

3130
02:40:07,031 --> 02:40:09,567
just that without
having using antibody.

3131
02:40:10,100 --> 02:40:16,040
I mean, can you just look
at a content of ENOS

3132
02:40:16,040 --> 02:40:18,909
or something else
just to see?

3133
02:40:18,909 --> 02:40:20,845
Alan Docter: Yeah, possibly.
I don't know that.

3134
02:40:20,845 --> 02:40:22,113
Female Speaker: Yeah.

3135
02:40:22,113 --> 02:40:23,981
So time's up,
but Marilyn [phonetic sp],

3136
02:40:23,981 --> 02:40:25,483
you've been dying
to ask a question.

3137
02:40:25,483 --> 02:40:29,453
I'll let you have the last
question before Dr. Dorff

3138
02:40:29,453 --> 02:40:30,721
[phonetic sp].

3139
02:40:30,721 --> 02:40:34,091
Female Speaker: So when patients
are treated with Voxelotor,

3140
02:40:34,625 --> 02:40:37,461
their deformability
of their red cells

3141
02:40:37,461 --> 02:40:39,830
as measured
by Lorca improves,

3142
02:40:39,830 --> 02:40:43,033
whereas it's reduced for
a lot of sickle cell patients.

3143
02:40:45,102 --> 02:40:50,975
Is there a technically
feasible way to measure

3144
02:40:50,975 --> 02:40:56,780
to what degree deformability
is helped or decreased

3145
02:40:56,780 --> 02:41:01,652
by the degree of kind
of reversible polymerization

3146
02:41:01,652 --> 02:41:03,621
of hemoglobin in the cell?

3147
02:41:03,621 --> 02:41:06,023
Or, for that matter,
what percent of hemoglobin

3148
02:41:06,023 --> 02:41:08,192
is proximal
to the membrane,

3149
02:41:08,192 --> 02:41:11,695
and what percent is it
so that you could say

3150
02:41:11,695 --> 02:41:15,032
what the percent contribution
is of what you've just

3151
02:41:15,032 --> 02:41:17,735
very beautifully presented
versus kind of --

3152
02:41:17,735 --> 02:41:19,236
I will call the traditional,

3153
02:41:19,236 --> 02:41:20,905
you know, it's all
about the hemoglobin?

3154
02:41:20,905 --> 02:41:22,673
Alan Docter: Yeah, yeah, yeah.

3155
02:41:22,673 --> 02:41:24,408
Well, there's a lot
to unpack in there,

3156
02:41:24,408 --> 02:41:29,580
but there is a technique
that is in development now

3157
02:41:31,415 --> 02:41:35,920
that involves something
called hyperspectral imaging,

3158
02:41:35,920 --> 02:41:41,859
which can monitor the degree
of protein polymerization

3159
02:41:41,859 --> 02:41:44,695
and whether --
and also whether --

3160
02:41:44,695 --> 02:41:47,698
that is cytoskeletal
or hemoglobin.

3161
02:41:49,166 --> 02:41:51,869
And it's not, you
know, it's not --

3162
02:41:52,403 --> 02:41:56,106
how can I put it,
to use Wilbur's language,

3163
02:41:56,106 --> 02:42:01,345
it's like TRL-2, so not ready
to be deployed by any stretch.

3164
02:42:02,379 --> 02:42:05,449
But there -- and it can
go through the skin.

3165
02:42:05,449 --> 02:42:09,853
So there are, there may be
approaches to monitoring

3166
02:42:09,853 --> 02:42:11,789
the degree of hemoglobin
polymerization

3167
02:42:11,789 --> 02:42:13,657
in a transcutaneous way,

3168
02:42:13,657 --> 02:42:17,728
but it's a few years --
more than a few years away.

3169
02:42:18,629 --> 02:42:19,863
Female Speaker: Thank you
so much.

3170
02:42:19,863 --> 02:42:22,866
So I will let you go
to give your other talk,

3171
02:42:22,866 --> 02:42:24,134
and I'll see you later.

3172
02:42:24,134 --> 02:42:25,803
I'll let you go,
and I will be back.

3173
02:42:25,803 --> 02:42:27,137
Alan Docter: [inaudible]

3174
02:42:27,137 --> 02:42:30,074
Female Speaker: So, yeah.

3175
02:42:30,074 --> 02:42:32,409
[applause]

3176
02:42:32,409 --> 02:42:35,012
So, it's my pleasure
to introduce Manu,

3177
02:42:35,779 --> 02:42:38,716
who I kind of know
very well and work with.

3178
02:42:38,716 --> 02:42:44,088
So Manu is the inaugural
director of the NIH White Center

3179
02:42:44,788 --> 02:42:48,325
for Biomedical Engineering
Technology Acceleration,

3180
02:42:48,859 --> 02:42:53,530
which is housed within the
National Institute of Bioimaging

3181
02:42:53,530 --> 02:42:55,466
and Bioengineering.
Did I get it right?

3182
02:42:57,401 --> 02:43:01,071
So, Manu, thank you very much.
So as I said, 25 minutes.

3183
02:43:01,605 --> 02:43:02,873
I know you've got
more than that.

3184
02:43:02,873 --> 02:43:04,475
Manu Platt: I've got my timer.

3185
02:43:04,475 --> 02:43:07,645
Okay. I'm really
looking forward to this.

3186
02:43:07,645 --> 02:43:08,846
Female Speaker: Thank you, Manu.

3187
02:43:08,846 --> 02:43:12,816
Manu Platt: Great. Thank you all
very much for having me.

3188
02:43:14,785 --> 02:43:16,353
And so many great people
here in the room

3189
02:43:16,353 --> 02:43:17,554
between today and tomorrow

3190
02:43:17,554 --> 02:43:19,623
whose work I've been building
on and reading for years.

3191
02:43:19,623 --> 02:43:22,259
I'm quite excited
to share my work with you all.

3192
02:43:22,259 --> 02:43:26,497
So, as mentioned,
I am at NIH at the NIBIB,

3193
02:43:26,497 --> 02:43:29,833
mentioned by Wilbur, but I just
moved there about 18 months ago.

3194
02:43:29,833 --> 02:43:31,468
I started my career
at Georgia Tech Emory

3195
02:43:31,468 --> 02:43:33,504
in their Department
of Biomedical Engineering

3196
02:43:33,504 --> 02:43:35,339
and actually got my PhD
at Georgia Tech Emory

3197
02:43:35,339 --> 02:43:38,709
in cardiovascular endothelial
cell and shear stress biology.

3198
02:43:38,709 --> 02:43:40,244
That then we shifted
to sickle cell

3199
02:43:40,244 --> 02:43:42,513
when I started
my own independent lab.

3200
02:43:42,513 --> 02:43:44,882
But I always, as the director
of this beta center,

3201
02:43:44,882 --> 02:43:47,851
I do have to plug it
everywhere I go because my job,

3202
02:43:47,851 --> 02:43:50,454
one of them, is to get people
in the extramural world

3203
02:43:50,454 --> 02:43:52,690
to be interested in working
and partnering with people

3204
02:43:52,690 --> 02:43:55,592
in the intramural
research program at NIH.

3205
02:43:55,592 --> 02:43:57,127
But one of the other goals
that we're doing

3206
02:43:57,127 --> 02:44:00,030
is to allow the other
intramural researchers at NIH

3207
02:44:00,030 --> 02:44:03,033
to access engineering tools,
analytical methods,

3208
02:44:03,033 --> 02:44:06,036
computational biology,
biomaterials, microfabrication.

3209
02:44:06,036 --> 02:44:08,505
So, again, also always
advertising that we are building

3210
02:44:08,505 --> 02:44:10,874
these internal capabilities
at the NIH,

3211
02:44:10,874 --> 02:44:13,444
but again, open
to working with others.

3212
02:44:13,444 --> 02:44:14,978
There's my wonderful
deputy director

3213
02:44:14,978 --> 02:44:16,680
who handles things
when I'm gone.

3214
02:44:16,680 --> 02:44:18,549
But again, one of the other
things that we do is, again,

3215
02:44:18,549 --> 02:44:19,883
to help build
these relationships.

3216
02:44:19,883 --> 02:44:23,520
We have a huge event coming up
at NIH on October 22nd,

3217
02:44:23,520 --> 02:44:24,955
building bridges across NIH

3218
02:44:24,955 --> 02:44:26,657
and with the broader
engineering community,

3219
02:44:26,657 --> 02:44:29,059
where we have an intramural
plenary talk

3220
02:44:29,059 --> 02:44:30,294
via Dr. John Tisdale
[phonetic sp]

3221
02:44:30,294 --> 02:44:32,730
here and an extramural plenary
talk by Dr. Rashid Bashir

3222
02:44:32,730 --> 02:44:33,931
[phonetic sp].

3223
02:44:33,931 --> 02:44:35,599
And there's multiple
talks happening on campus.

3224
02:44:35,599 --> 02:44:37,134
We'll be taking
over the campus,

3225
02:44:37,134 --> 02:44:38,569
networking,
bringing things together

3226
02:44:38,569 --> 02:44:41,372
so the engineers can meet with
the clinicians and researchers.

3227
02:44:41,372 --> 02:44:43,540
So if you'll be around Bethesda,
free registration

3228
02:44:43,540 --> 02:44:46,477
because your federal taxes
go towards our support.

3229
02:44:46,477 --> 02:44:48,011
So, thank you.
And we were fortunate

3230
02:44:48,011 --> 02:44:49,446
that Dr. Monica
Bertagnolli [phonetic sp]

3231
02:44:49,446 --> 02:44:51,715
will do a welcome for us
at the beginning.

3232
02:44:51,715 --> 02:44:55,619
But I do have a research lab.
My lab did move to NIH as well

3233
02:44:55,619 --> 02:44:57,855
and the NIBIB
intramural program.

3234
02:44:57,855 --> 02:45:00,557
A major focus of my work
is pediatric strokes

3235
02:45:00,557 --> 02:45:03,560
and sickle cell disease and some
of the underlying mechanisms,

3236
02:45:03,560 --> 02:45:05,062
which I'll be talking
to you about today.

3237
02:45:05,062 --> 02:45:08,365
And we use a number of different
techniques to assess this,

3238
02:45:08,365 --> 02:45:10,100
and I'll talk about
a few of those.

3239
02:45:11,702 --> 02:45:13,670
So, I say my lab studies
tissue remodeling.

3240
02:45:13,670 --> 02:45:14,872
And so, just to orient people,

3241
02:45:14,872 --> 02:45:16,874
what I think tissue
remodeling is,

3242
02:45:16,874 --> 02:45:19,743
I look at it as how do you go
from this diseased vessel

3243
02:45:20,410 --> 02:45:21,845
this healthy vessel
on the left

3244
02:45:21,845 --> 02:45:23,313
to this diseased vessel
on the right.

3245
02:45:23,313 --> 02:45:25,582
So that is a human
coronary artery,

3246
02:45:25,582 --> 02:45:27,050
and you can see
this cross-section.

3247
02:45:27,050 --> 02:45:28,852
So blood is coming
out of the board,

3248
02:45:29,419 --> 02:45:30,754
and it's nice
and happy and open --

3249
02:45:30,754 --> 02:45:32,189
minimally diseased,
we would say.

3250
02:45:32,189 --> 02:45:34,558
But you can see for that
atherosclerotic plaque to form,

3251
02:45:34,558 --> 02:45:36,860
where just that little
slick of white space

3252
02:45:36,860 --> 02:45:38,796
is where the blood
would now be moving.

3253
02:45:38,796 --> 02:45:41,799
That huge plaque has remodeled
that artery wall.

3254
02:45:41,799 --> 02:45:43,400
And so some of the initial
things that happen

3255
02:45:43,400 --> 02:45:45,803
there are degradation of some of
the structural proteins

3256
02:45:45,803 --> 02:45:48,505
that make up the artery wall --
the elastin and the collagen --

3257
02:45:48,505 --> 02:45:50,808
that leads to cells
receiving different cues.

3258
02:45:50,808 --> 02:45:53,277
They begin to migrate,
infiltrate that area,

3259
02:45:53,277 --> 02:45:54,812
deposit new proteins,

3260
02:45:54,812 --> 02:45:57,314
and there's a feedback
loop that continues.

3261
02:45:57,314 --> 02:45:59,817
So, what is happening?
But what's important is not only

3262
02:45:59,817 --> 02:46:02,486
is the biochemical environment
of that artery wall changing,

3263
02:46:02,486 --> 02:46:04,087
but the biomechanics change.

3264
02:46:04,087 --> 02:46:05,889
So I can appreciate Dr. Theon's
[phonetic sp]

3265
02:46:05,889 --> 02:46:08,225
opening about considering
the mechanics and the biology,

3266
02:46:08,225 --> 02:46:09,526
which is something that,

3267
02:46:09,526 --> 02:46:12,129
as biomedical engineers love
to bring together.

3268
02:46:12,129 --> 02:46:14,464
Another thing that people
understand is from osteoporosis.

3269
02:46:14,464 --> 02:46:17,868
You go from this normal, dense,
mineralized bone matrix to this.

3270
02:46:17,868 --> 02:46:19,369
You lose some of
the mineral calcium.

3271
02:46:19,369 --> 02:46:22,606
Again, loss of the biochemistry
changes the biomechanics,

3272
02:46:22,606 --> 02:46:25,709
and you see this predominantly
in postmenopausal women --

3273
02:46:25,709 --> 02:46:27,144
greater risk
of bone breaks, right?

3274
02:46:27,144 --> 02:46:29,646
But we also know in sickle cell,
the sickle bone disease

3275
02:46:29,646 --> 02:46:32,282
that also takes into account
this bone remodeling.

3276
02:46:32,282 --> 02:46:35,118
So really what my lab studies
is how things fall apart, okay?

3277
02:46:35,118 --> 02:46:36,687
And so we can understand
those mechanisms

3278
02:46:36,687 --> 02:46:39,089
so we can stop it
and hopefully keep it together

3279
02:46:39,089 --> 02:46:41,058
because some of these structures
aren't easily regenerated

3280
02:46:41,058 --> 02:46:42,726
or repaired, okay?

3281
02:46:42,726 --> 02:46:45,128
But these agents of destruction
that I really focus on

3282
02:46:45,128 --> 02:46:47,798
are these enzymes called
the cysteine cathepsins.

3283
02:46:47,798 --> 02:46:50,334
So, they were first
identified in lysosomes,

3284
02:46:50,334 --> 02:46:52,603
where they play key roles
in protein turnover.

3285
02:46:52,603 --> 02:46:54,104
But they're upregulated
in disease

3286
02:46:54,104 --> 02:46:56,006
and actually get released
and secreted,

3287
02:46:56,006 --> 02:46:58,642
where they can do damage
to a lot of matrix proteins.

3288
02:46:59,276 --> 02:47:01,745
Again, first there were we began
learning about them

3289
02:47:01,745 --> 02:47:04,047
in cardiovascular disease
and atherosclerosis,

3290
02:47:04,715 --> 02:47:06,516
where endothelial cells
begin to express them

3291
02:47:06,516 --> 02:47:08,252
under different
fluid environments.

3292
02:47:08,252 --> 02:47:10,454
Also, the smooth muscle cells
can express them

3293
02:47:10,454 --> 02:47:13,056
as they migrate and respond
to inflammatory cues.

3294
02:47:13,056 --> 02:47:15,259
All of this together
begins to remodel the milieu

3295
02:47:15,259 --> 02:47:17,060
of the artery wall.

3296
02:47:17,060 --> 02:47:20,397
And so also where mechanics come
into play are also blood flow.

3297
02:47:20,397 --> 02:47:22,165
So we think about,
I say, hemodynamics,

3298
02:47:22,165 --> 02:47:24,668
and I think some hematologists
do it differently.

3299
02:47:24,668 --> 02:47:26,737
So, I mean fluid shear stress

3300
02:47:26,737 --> 02:47:28,071
and the mechanical force
of blood

3301
02:47:28,071 --> 02:47:30,574
as it moves across
the blood vessel wall.

3302
02:47:31,174 --> 02:47:33,076
So, people knew for years,
back in the '50s,

3303
02:47:33,076 --> 02:47:35,379
they had identified that
were atherosclerotic plaques

3304
02:47:35,379 --> 02:47:37,514
were forming word regions
of bifurcations

3305
02:47:37,514 --> 02:47:39,583
or sharp turns
in the vascular tree.

3306
02:47:39,583 --> 02:47:41,485
So, a pathologist called
the aerospace engineer buddy,

3307
02:47:41,485 --> 02:47:42,753
and they were like,

3308
02:47:42,753 --> 02:47:44,388
"Oh, of course
they're happening here."

3309
02:47:44,388 --> 02:47:46,023
There are these regions
of flow separation.

3310
02:47:46,023 --> 02:47:48,225
There's not a laser thing
on here right now,

3311
02:47:48,225 --> 02:47:50,527
but they did the regions
of flow separation.

3312
02:47:50,527 --> 02:47:51,995
I'm sorry,
regions of bifurcations,

3313
02:47:51,995 --> 02:47:54,197
you get flow separation,
flow reversal,

3314
02:47:54,197 --> 02:47:55,933
and particularly with
the cardiac cycle of systole

3315
02:47:55,933 --> 02:47:57,167
and diastole.

3316
02:47:57,167 --> 02:47:58,969
You can actually get blood
moving backwards

3317
02:47:58,969 --> 02:48:01,772
depending on the geometries
of the artery wall.

3318
02:48:01,772 --> 02:48:02,973
And you can see here
where you see

3319
02:48:02,973 --> 02:48:04,675
these atherosclerotic plaques
forming --

3320
02:48:04,675 --> 02:48:07,110
sorry actually correlates
with where you have the regions

3321
02:48:07,110 --> 02:48:09,346
of flow reversal
in the artery wall.

3322
02:48:09,913 --> 02:48:11,815
And so, my PhD was all
about learning

3323
02:48:11,815 --> 02:48:14,117
how the mechanical forces
alone drive gene

3324
02:48:14,117 --> 02:48:16,720
and protein expression,
which really blew my mind.

3325
02:48:16,720 --> 02:48:18,689
From my undergrad degree
was biology,

3326
02:48:18,689 --> 02:48:20,991
where in biology, I think
you learn what happens, right?

3327
02:48:20,991 --> 02:48:22,859
This binds to this,
this does this.

3328
02:48:22,859 --> 02:48:24,928
But what I really appreciate
about biomedical engineering

3329
02:48:24,928 --> 02:48:27,064
is it told us more
about why it's happening.

3330
02:48:27,064 --> 02:48:30,100
Ourselves and our tissues obey
the same mechanical laws

3331
02:48:30,100 --> 02:48:31,702
that, like,
a brick does, right?

3332
02:48:31,702 --> 02:48:34,304
They also fall
with gravitational acceleration.

3333
02:48:34,304 --> 02:48:36,974
So, all of those things
are happening inside of cells.

3334
02:48:36,974 --> 02:48:39,242
And so that's where we found out
that the system could have

3335
02:48:39,242 --> 02:48:41,445
things that I mentioned
that are powerful collagenases

3336
02:48:41,445 --> 02:48:44,881
and elastases are actually
turned up at sites of disturbed

3337
02:48:44,881 --> 02:48:47,985
flow where you see plaques
and vascular remodeling,

3338
02:48:47,985 --> 02:48:49,886
and turned down
at the straighter parts

3339
02:48:49,886 --> 02:48:51,855
where you get
high unidirectional blood

3340
02:48:51,855 --> 02:48:53,924
flow or unidirectional
shear stress.

3341
02:48:53,924 --> 02:48:55,993
So, these are
mechano-sensitive proteins

3342
02:48:55,993 --> 02:48:57,861
that are regulated
based on blood flow.

3343
02:48:57,861 --> 02:48:59,162
Fast forward from then

3344
02:48:59,162 --> 02:49:01,832
to when I started
my independent lab in 2009

3345
02:49:01,832 --> 02:49:03,567
and really began
to have some mentors.

3346
02:49:03,567 --> 02:49:04,868
I was back in Atlanta

3347
02:49:04,868 --> 02:49:07,270
and started caring more
about sickle cell disease,

3348
02:49:07,270 --> 02:49:08,572
which we all know these facts,

3349
02:49:08,572 --> 02:49:10,474
so I don't have
to state them for you all.

3350
02:49:10,474 --> 02:49:12,376
But what really blew my mind
when I heard that children

3351
02:49:12,376 --> 02:49:14,478
with sickle cell disease
were having strokes.

3352
02:49:14,478 --> 02:49:15,979
I had been studying
cardiovascular disease

3353
02:49:15,979 --> 02:49:17,214
and atherosclerosis,

3354
02:49:17,214 --> 02:49:19,216
and we think about that
happening when people are 50,

3355
02:49:19,216 --> 02:49:21,318
60, 70,
80 years of age --

3356
02:49:21,318 --> 02:49:24,354
which was already terrible --
but kids having strokes?

3357
02:49:24,921 --> 02:49:27,858
Nobody was talking about this
about after a world,

3358
02:49:27,858 --> 02:49:29,292
and then again
the complication here,

3359
02:49:29,292 --> 02:49:30,527
I mean, at the complication,

3360
02:49:30,527 --> 02:49:32,462
the terrible part is 11 percent
of these children

3361
02:49:32,462 --> 02:49:35,198
will have a major stroke,
meaning there's some paralysis.

3362
02:49:35,198 --> 02:49:36,466
But then when you find out

3363
02:49:36,466 --> 02:49:38,502
that a third will have
a silent stroke,

3364
02:49:38,502 --> 02:49:40,370
where it's occurring
in a cognitive part of the brain

3365
02:49:40,370 --> 02:49:45,475
that isn't presenting, kids --
this makes no sense to me --

3366
02:49:46,076 --> 02:49:47,577
and understanding
that the red cell sickle

3367
02:49:47,577 --> 02:49:50,080
under deoxygenated conditions,
but strokes are happening

3368
02:49:50,080 --> 02:49:53,250
in the oxygenated
vascular conduits.

3369
02:49:53,250 --> 02:49:55,519
So, it really broke
a lot of the themes,

3370
02:49:55,519 --> 02:49:57,254
and paradoxes
started to really grow

3371
02:49:57,254 --> 02:49:59,222
for how we would think about it.

3372
02:49:59,222 --> 02:50:01,024
But some great work,
again from people in this room

3373
02:50:01,024 --> 02:50:04,161
and others, showed that
--I'm going to hypothesize about

3374
02:50:04,161 --> 02:50:05,762
what these mechanisms
could look like --

3375
02:50:05,762 --> 02:50:08,532
and they were shown to be
lasting in collagen degradation

3376
02:50:08,532 --> 02:50:11,134
in the artery walls
from autopsy specimens.

3377
02:50:11,134 --> 02:50:13,904
A lot of hypotheses, again,
you know, scavenging,

3378
02:50:13,904 --> 02:50:15,172
high shear, clotting,

3379
02:50:15,172 --> 02:50:16,473
and a number
of different hypotheses

3380
02:50:16,473 --> 02:50:18,008
about what could be happening.

3381
02:50:18,008 --> 02:50:19,843
But when I also read
about this STOP study

3382
02:50:19,843 --> 02:50:23,046
by Bob Adams at Medical
University South Carolina,

3383
02:50:23,680 --> 02:50:25,182
blew my mind because things
that I had learned

3384
02:50:25,182 --> 02:50:26,917
in my engineering training
was --

3385
02:50:26,917 --> 02:50:28,985
they said,
well, increase that --

3386
02:50:28,985 --> 02:50:32,389
increase velocities
in the cerebral arteries

3387
02:50:32,389 --> 02:50:33,723
a, middle cerebral ACA,

3388
02:50:33,723 --> 02:50:36,026
and the ICA,
which is the carotid artery.

3389
02:50:36,026 --> 02:50:37,994
Those are the children at
greatest risk of having strokes.

3390
02:50:37,994 --> 02:50:39,229
So, the STOP trial,

3391
02:50:39,229 --> 02:50:41,198
they put them on the placebo
or blood transfusions

3392
02:50:41,198 --> 02:50:42,999
--one of those trials
that had to be stopped early

3393
02:50:42,999 --> 02:50:45,435
because it was clear
those getting blood transfusions

3394
02:50:45,435 --> 02:50:47,637
were successful
and the others weren't.

3395
02:50:47,637 --> 02:50:49,473
Well, I had learned
in my fluid dynamics class

3396
02:50:49,473 --> 02:50:51,508
that where you get
increased velocities,

3397
02:50:51,508 --> 02:50:53,009
there could be some
narrowing of the lumen

3398
02:50:53,009 --> 02:50:55,479
in that location
or some other downstream

3399
02:50:55,479 --> 02:50:58,782
or upstream differences.
And we began to question,

3400
02:50:58,782 --> 02:51:00,851
well, we know that these red
cells in their white blood cells

3401
02:51:00,851 --> 02:51:02,319
and sickle cell
are quite adherent.

3402
02:51:02,319 --> 02:51:04,921
So, are there some
local transient accumulations

3403
02:51:04,921 --> 02:51:06,656
and aggregations
of red cells?

3404
02:51:06,656 --> 02:51:08,825
Again, Wilbur showed
those microfluidic images

3405
02:51:08,825 --> 02:51:12,295
of the cells coating the walls
of those vessels,

3406
02:51:12,295 --> 02:51:14,865
even though the blood
was still moving.

3407
02:51:14,865 --> 02:51:16,233
Or is there some luminal
narrowing

3408
02:51:16,233 --> 02:51:18,435
where the tissue itself
was being remodeled to close?

3409
02:51:18,435 --> 02:51:21,238
That would be more traditional
of an atherosclerotic plaque

3410
02:51:21,238 --> 02:51:23,173
but without the lipid core,
obviously.

3411
02:51:23,740 --> 02:51:26,276
But, well, either way, where you
get that increased blood flow,

3412
02:51:26,276 --> 02:51:28,211
downstream of that
you get disturbed blood flow

3413
02:51:28,211 --> 02:51:29,446
and flow reversal,

3414
02:51:29,446 --> 02:51:32,749
which then activates these
artery remodeling programs.

3415
02:51:32,749 --> 02:51:35,018
And again, we used to think
in atherosclerosis --

3416
02:51:35,018 --> 02:51:37,287
branches, bifurcation,
sharp curves.

3417
02:51:37,287 --> 02:51:38,555
But if you have regions

3418
02:51:38,555 --> 02:51:39,990
of accumulated
red cells throughout,

3419
02:51:39,990 --> 02:51:42,392
even the straight parts
of the artery wall,

3420
02:51:42,392 --> 02:51:44,594
are you now having
local pockets of disturbed

3421
02:51:44,594 --> 02:51:47,164
flow that could be
exacerbating this remodeling

3422
02:51:47,164 --> 02:51:49,766
while we're seeing such
accelerated artery damage

3423
02:51:49,766 --> 02:51:51,635
in people with sickle cell?

3424
02:51:51,635 --> 02:51:53,637
So these are the questions
we began to tackle.

3425
02:51:53,637 --> 02:51:54,838
And Russell [phonetic sp],

3426
02:51:54,838 --> 02:51:56,973
where actually met with
the Wilbur several years ago,

3427
02:51:56,973 --> 02:51:59,910
actually sent us some magnetic
resonance angiograms of children

3428
02:51:59,910 --> 02:52:02,979
with sickle cell so we could
actually take the MRIs,

3429
02:52:02,979 --> 02:52:05,682
we could reconstruct
the images in the computer

3430
02:52:05,682 --> 02:52:07,150
and reconstruct
the vasculature,

3431
02:52:07,150 --> 02:52:09,452
and then apply
computational fluid dynamics

3432
02:52:09,452 --> 02:52:11,988
to simulate how the blood
flow looks through this.

3433
02:52:11,988 --> 02:52:15,358
Because our question was, why is
the blood velocity increasing,

3434
02:52:15,992 --> 02:52:17,360
especially in certain MRIs?

3435
02:52:17,360 --> 02:52:19,262
You don't even see
a stenosis at the site

3436
02:52:19,262 --> 02:52:21,464
where the increased velocity
was being measured.

3437
02:52:21,464 --> 02:52:22,832
More paradoxes.

3438
02:52:22,832 --> 02:52:24,901
And so, in doing that,
the first thing my student found

3439
02:52:24,901 --> 02:52:26,770
when he first reconstructed
these arteries --

3440
02:52:26,770 --> 02:52:28,538
which I was really mad
at him at first --

3441
02:52:28,538 --> 02:52:32,108
the SS arteries are always way
more bumpier than the AA.

3442
02:52:32,108 --> 02:52:33,677
And I was like,
"Chris, what are you doing?

3443
02:52:33,677 --> 02:52:35,645
Are you not doing
the algorithms the same?"

3444
02:52:35,645 --> 02:52:37,514
Like, he was like,
"Dr. Platt, I'm following it

3445
02:52:37,514 --> 02:52:39,916
all the way I'm supposed to.
I've talked to our expert."

3446
02:52:39,916 --> 02:52:41,451
And so, this became
really important later

3447
02:52:41,451 --> 02:52:45,255
when we put through the same
inlet flow velocity profile

3448
02:52:45,255 --> 02:52:46,990
in the internal
carotid artery,

3449
02:52:46,990 --> 02:52:49,826
and just the geometries of
the individuals with sickle cell

3450
02:52:49,826 --> 02:52:52,329
led to increased
centerline velocities

3451
02:52:52,329 --> 02:52:55,665
above that 200 centimeters
per second target,

3452
02:52:55,665 --> 02:52:57,867
which we were shocked. Again,
the same inlet velocity --

3453
02:52:57,867 --> 02:53:00,070
we had asked him
for the patient's inlet flow.

3454
02:53:00,070 --> 02:53:02,639
They did vary.
But if we assume the same,

3455
02:53:02,639 --> 02:53:03,974
we saw these
increased velocities

3456
02:53:03,974 --> 02:53:06,409
showing just the geometry
was changing it.

3457
02:53:06,409 --> 02:53:08,311
That led us back
to those bumps again,

3458
02:53:08,311 --> 02:53:11,214
"Oh, maybe this is indicative
of something

3459
02:53:11,214 --> 02:53:13,316
because the MRI
is like the negative

3460
02:53:13,316 --> 02:53:15,585
of the blood vessel, right?
It's a space filling,

3461
02:53:15,585 --> 02:53:17,821
which could be some of
these aggregations, et cetera."

3462
02:53:17,821 --> 02:53:19,856
And if we looked
at flow recirculation,

3463
02:53:19,856 --> 02:53:21,858
which, again, is another
indicator of disturbed blood

3464
02:53:21,858 --> 02:53:24,894
flow that would cause those
altered remodeling pathways.

3465
02:53:24,894 --> 02:53:27,030
We could see those readings
of flow recirculation

3466
02:53:27,030 --> 02:53:29,566
in the cerebral arteries
of the sickle cell individuals

3467
02:53:29,566 --> 02:53:30,834
but not in wild type,

3468
02:53:30,834 --> 02:53:34,070
again with the same
input fluid velocity profiles.

3469
02:53:34,070 --> 02:53:36,106
We weren't biasing it there.

3470
02:53:36,106 --> 02:53:37,674
Again, so that's where we began
to develop

3471
02:53:37,674 --> 02:53:39,009
this kind of
multi-scale approach

3472
02:53:39,009 --> 02:53:40,744
of how does
the fluid shear stress --

3473
02:53:40,744 --> 02:53:42,445
the mechanical forces
of blood flow --

3474
02:53:42,445 --> 02:53:44,447
influence the gene
and protein expression

3475
02:53:44,447 --> 02:53:46,650
that caused the cells
to express these molecules

3476
02:53:46,650 --> 02:53:48,518
that will destroy
the artery wall.

3477
02:53:49,286 --> 02:53:52,022
So, we worked with the Sickle
Cell Foundation of Georgia

3478
02:53:52,022 --> 02:53:54,291
to ice or to collect
human blood from them --

3479
02:53:54,291 --> 02:53:56,359
which now we're going to start
working with sweet labor --

3480
02:53:56,359 --> 02:53:58,028
quite excited about.
And again,

3481
02:53:58,028 --> 02:54:00,730
I come from an endothelial cell
background and atherosclerosis.

3482
02:54:00,730 --> 02:54:04,234
The monocytes bind
to the endothelial cell

3483
02:54:04,234 --> 02:54:07,404
and the field is lining the wall
under sites of disturbed flow,

3484
02:54:07,404 --> 02:54:08,972
and then they could
enter the wall.

3485
02:54:08,972 --> 02:54:11,374
Well, we know with sickle cell
there's increased monocytosis

3486
02:54:11,374 --> 02:54:14,444
that's happening, and there's
increase in inflammation

3487
02:54:14,444 --> 02:54:16,313
and TNF-alpha circling
in the plasma.

3488
02:54:16,313 --> 02:54:17,914
All of these things
that could accelerate

3489
02:54:17,914 --> 02:54:19,482
this positive feed-forward

3490
02:54:19,482 --> 02:54:22,319
to get monocyte binding
and artery wall remodeling.

3491
02:54:22,319 --> 02:54:23,520
Love to show this picture.

3492
02:54:23,520 --> 02:54:25,422
This gentleman on the left
is Phil Keegan.

3493
02:54:25,422 --> 02:54:26,656
He was one of my first
grad students

3494
02:54:26,656 --> 02:54:28,325
who really led
this work off,

3495
02:54:28,325 --> 02:54:29,693
and that's me with
the lab technicians

3496
02:54:29,693 --> 02:54:31,194
at the Sickle Cell
Foundation of Georgia

3497
02:54:31,194 --> 02:54:32,962
who collected
the blood for us.

3498
02:54:32,962 --> 02:54:34,564
But I'm going to zoom
through this a bit.

3499
02:54:34,564 --> 02:54:37,133
But we found that, of course,
with SS PBMCs,

3500
02:54:37,133 --> 02:54:39,536
there was greater adhesion
to the endothelial cells.

3501
02:54:39,536 --> 02:54:41,938
We were doing this with
human aortic endothelial cells.

3502
02:54:41,938 --> 02:54:43,340
You all in this room
had shown this

3503
02:54:43,340 --> 02:54:45,008
before we did,
so nothing new.

3504
02:54:45,008 --> 02:54:47,344
We did ELISA to measure
the TNF-alpha levels

3505
02:54:47,344 --> 02:54:50,313
in the plasma --
elevated in the SS individuals.

3506
02:54:50,313 --> 02:54:52,649
But what we looked for was what
were the protease activities

3507
02:54:52,649 --> 02:54:54,851
that was turned on
after the monocytes

3508
02:54:54,851 --> 02:54:56,553
bound to the endothelium.

3509
02:54:56,553 --> 02:54:58,154
There's this assay
we developed in my group

3510
02:54:58,154 --> 02:54:59,356
called that zymography,

3511
02:54:59,356 --> 02:55:01,925
where you see increased
intensity of white bands --

3512
02:55:01,925 --> 02:55:04,461
that's where there's increased
amount of the active protease.

3513
02:55:04,461 --> 02:55:05,795
Okay
And what really --

3514
02:55:05,795 --> 02:55:08,231
we really thought
was going to happen to it,

3515
02:55:08,231 --> 02:55:11,234
that we knew that TNF-alpha
would turn on cathepsin K.

3516
02:55:11,768 --> 02:55:13,303
The cathepsins are denoted
by letters,

3517
02:55:13,303 --> 02:55:15,305
so each letter is
a different gene product.

3518
02:55:15,305 --> 02:55:17,941
Cathepsin K is the most powerful
human collagenase

3519
02:55:17,941 --> 02:55:19,809
and a very powerful elastase.

3520
02:55:19,809 --> 02:55:22,946
In fact, cathepsin K is used by
osteoclasts for bone resorption.

3521
02:55:22,946 --> 02:55:26,149
Okay, so we're seeing this being
expressed by endothelial cells

3522
02:55:26,149 --> 02:55:28,418
when they're stimulated
with TNF-alpha.

3523
02:55:28,418 --> 02:55:32,389
If we co-incubated the cells
with PBMCs isolated from people

3524
02:55:32,389 --> 02:55:34,724
with sickle cell,
again, you get greater adhesion,

3525
02:55:34,724 --> 02:55:36,926
and they turn on
cathepsin K themselves,

3526
02:55:36,926 --> 02:55:39,462
even without pre-stimulation
with TNF-alpha.

3527
02:55:39,462 --> 02:55:41,264
So, again, there's this
revved-up positive feedback

3528
02:55:41,264 --> 02:55:42,532
that's ready to happen --

3529
02:55:42,532 --> 02:55:44,367
greater monocytes,
greater adhesion,

3530
02:55:44,367 --> 02:55:46,469
and when they'd adhere,
they turn on this protease

3531
02:55:46,469 --> 02:55:48,071
to remodel that artery wall.

3532
02:55:48,738 --> 02:55:53,209
Cathepsin inhibitors have been
sought after by big pharma.

3533
02:55:53,209 --> 02:55:56,312
There have been about
16 cathepsin inhibitors

3534
02:55:56,312 --> 02:55:58,114
that have made it
to human clinical trials.

3535
02:55:58,114 --> 02:55:59,916
Sadly, 16 that have failed.

3536
02:56:01,051 --> 02:56:03,987
But the last eight --
it wasn't because of efficacy.

3537
02:56:03,987 --> 02:56:05,321
They actually were efficacious;

3538
02:56:05,321 --> 02:56:08,858
it was side effects that had
made them not able to be used.

3539
02:56:08,858 --> 02:56:10,660
So, we wanted to look at other
signaling pathways

3540
02:56:10,660 --> 02:56:11,995
that we could use to reduce

3541
02:56:11,995 --> 02:56:14,264
the expression
of these cysteine cathepsins.

3542
02:56:14,264 --> 02:56:15,932
And in other studies,
we found that JNK

3543
02:56:15,932 --> 02:56:17,767
and the C-gene
signaling cascade --

3544
02:56:17,767 --> 02:56:19,669
which we know
is downstream of TNF --

3545
02:56:19,669 --> 02:56:22,939
but also was able to turn
on cysteine cathepsins,

3546
02:56:22,939 --> 02:56:24,841
such that, with a JNK inhibitor,

3547
02:56:24,841 --> 02:56:26,810
we could reduce cathepsin
K activity

3548
02:56:26,810 --> 02:56:28,645
and cathepsin V
by about 50 percent.

3549
02:56:28,645 --> 02:56:30,079
So, you're going to see me
come back

3550
02:56:30,079 --> 02:56:31,915
to this JNK inhibition strategy.

3551
02:56:33,183 --> 02:56:35,552
Okay, so what can we do
with this flow information?

3552
02:56:35,552 --> 02:56:38,221
Well, we can also recreate these
flow environments in our lab

3553
02:56:38,221 --> 02:56:41,124
using a cone and plate
shear stress apparatus,

3554
02:56:41,124 --> 02:56:42,826
where we can grow
the endothelial cells

3555
02:56:42,826 --> 02:56:44,894
at the bottom
of a 10-centimeter dish,

3556
02:56:44,894 --> 02:56:46,129
put this cone on top,

3557
02:56:46,129 --> 02:56:48,865
and independently program
a fluid profile

3558
02:56:48,865 --> 02:56:50,200
to mimic
what it would look like

3559
02:56:50,200 --> 02:56:52,035
in certain parts
of the vascular tree.

3560
02:56:52,035 --> 02:56:54,904
And, again, very distinctly
study the mechanical influences

3561
02:56:54,904 --> 02:56:57,507
that drive gene
and protein expression.

3562
02:56:57,507 --> 02:56:58,808
And so, the endothelial cells --

3563
02:56:58,808 --> 02:57:00,944
they elongate and align
in the direction of flow,

3564
02:57:00,944 --> 02:57:02,712
so you know that
they're healthy, of course,

3565
02:57:02,712 --> 02:57:05,315
and that your flow regimes
are correct.

3566
02:57:05,315 --> 02:57:06,983
And this is one of those
big things that --

3567
02:57:06,983 --> 02:57:09,619
one of the things that I love
about putting mechanics

3568
02:57:09,619 --> 02:57:11,855
with biochemistry
is that there's this interplay

3569
02:57:11,855 --> 02:57:13,857
between the two
that must be considered.

3570
02:57:13,857 --> 02:57:16,226
So, as you see it, we grew
the cells under no flow

3571
02:57:16,226 --> 02:57:18,495
without any cytokine
stimulation.

3572
02:57:18,495 --> 02:57:20,363
You get cathepsin V expressed.

3573
02:57:20,363 --> 02:57:22,532
You increase -- with incubation
with TNF-alpha --

3574
02:57:22,532 --> 02:57:25,201
cathepsin K is turned on.
I'd shown you that earlier.

3575
02:57:25,201 --> 02:57:27,604
If we put that
under our pro-remodeling flow,

3576
02:57:27,604 --> 02:57:29,806
this is what we see.
At sites of disturbed flow,

3577
02:57:29,806 --> 02:57:31,908
cathepsin K is already turned
on a bit, right,

3578
02:57:31,908 --> 02:57:34,577
because it is a shear
stress-regulated gene itself.

3579
02:57:34,577 --> 02:57:38,515
With TNF, it turns up even more.
However, if they are put under

3580
02:57:38,515 --> 02:57:40,483
a vasoprotective shear
stress profile --

3581
02:57:40,483 --> 02:57:43,353
which you would see in
the straight parts of the artery

3582
02:57:43,353 --> 02:57:45,054
--vehicle, no cathepsin K.

3583
02:57:45,054 --> 02:57:50,360
But even in the presence of TNF,
under that fluid shear regime,

3584
02:57:50,360 --> 02:57:52,929
cathepsin K is not turned on.
This is crazy, right?

3585
02:57:52,929 --> 02:57:55,031
The same cytokines of --
your biologists are like,

3586
02:57:55,031 --> 02:57:56,566
"Well, the signals
bind at the receptor,

3587
02:57:56,566 --> 02:57:58,234
and all these things
should be turning it on."

3588
02:57:58,234 --> 02:58:00,069
But the flow is turning it off.

3589
02:58:00,069 --> 02:58:02,005
And so, we began to investigate
those mechanisms.

3590
02:58:02,005 --> 02:58:03,273
Again, I'll skip to the point,

3591
02:58:03,273 --> 02:58:05,441
and Betty Pace helped us
with this study.

3592
02:58:05,441 --> 02:58:08,778
And there's this dual pathway of
AP1 as a transcription factor,

3593
02:58:08,778 --> 02:58:12,181
regulated by the biochemistry,
that turns on cathepsin K.

3594
02:58:12,181 --> 02:58:13,483
And then, through NF-kappa B,

3595
02:58:13,483 --> 02:58:15,385
is the shear
stress-modulated pathway.

3596
02:58:15,952 --> 02:58:19,222
That both need to be present
for the enzyme to be turned up.

3597
02:58:19,222 --> 02:58:23,326
So, that was all our work with
human cells and in vitro work.

3598
02:58:23,326 --> 02:58:25,795
So, then we began to use the
Townes sickle cell mouse model

3599
02:58:25,795 --> 02:58:27,764
to see if we could see
some of these same things

3600
02:58:27,764 --> 02:58:30,633
in a preclinical trial model,
or preclinical model.

3601
02:58:30,633 --> 02:58:31,935
And because we were worried

3602
02:58:31,935 --> 02:58:34,137
or wondering
about these young children

3603
02:58:34,137 --> 02:58:36,506
showing up with these
artery damages and strokes,

3604
02:58:36,506 --> 02:58:37,707
we first sacrificed --

3605
02:58:37,707 --> 02:58:39,409
or euthanized
--our mice at one month,

3606
02:58:39,409 --> 02:58:41,578
isolated their common
carotid arteries,

3607
02:58:41,578 --> 02:58:44,147
and did a van Gieson
staining looking for elastin.

3608
02:58:44,147 --> 02:58:46,049
And just at one month --
no other interventions,

3609
02:58:46,049 --> 02:58:47,350
just having sickle cell --

3610
02:58:47,350 --> 02:58:50,520
we see these elastin breaks
in this degraded elastic lamina

3611
02:58:50,520 --> 02:58:52,388
in the artery wall
one month of age.

3612
02:58:52,922 --> 02:58:55,458
And we could quantify
the elastin breaks over time.

3613
02:58:56,225 --> 02:58:59,729
Then we did immunohistochemical
staining for cathepsin K.

3614
02:58:59,729 --> 02:59:02,632
And you could see here
there's a fact where the SS mice

3615
02:59:02,632 --> 02:59:05,301
are expressing a lot of
cathepsin K in the artery wall.

3616
02:59:05,301 --> 02:59:07,237
Remind you -- an elastase
and a collagenase --

3617
02:59:07,237 --> 02:59:09,973
right around all that elastin
and collagen there.

3618
02:59:09,973 --> 02:59:12,075
And so, Betty Pace is also
my student's committee

3619
02:59:12,075 --> 02:59:13,509
and she knew about the JNK data.

3620
02:59:13,509 --> 02:59:15,111
She was like, "Why don't you
inject that in the mice?"

3621
02:59:15,111 --> 02:59:16,579
I was like,
"That'll never work clinically.

3622
02:59:16,579 --> 02:59:18,548
Well, we need something --
just go for it and let's see."

3623
02:59:18,548 --> 02:59:22,418
So, Phil wonderfully did daily
injections of this JNK inhibitor

3624
02:59:22,418 --> 02:59:24,721
in our sickle mice
from one month to three months.

3625
02:59:24,721 --> 02:59:26,522
No, they did not like it.

3626
02:59:26,522 --> 02:59:28,324
But we looked for
what are the systemic

3627
02:59:28,324 --> 02:59:31,027
what are the effects
with the systemic inhibition.

3628
02:59:31,027 --> 02:59:32,629
And what we saw was, like,

3629
02:59:32,629 --> 02:59:34,230
so now from one
to three months of age.

3630
02:59:34,230 --> 02:59:36,666
So, by three months,
we see that expansive outward

3631
02:59:36,666 --> 02:59:39,602
remodeling of the carotid artery
in the SS mice.

3632
02:59:39,602 --> 02:59:43,339
But the JNK inhibition actually
stops that morphology changes.

3633
02:59:44,073 --> 02:59:45,642
We looked at cathepsin K, again.

3634
02:59:45,642 --> 02:59:47,944
Three months -- cathepsin K
is up in the artery wall,

3635
02:59:47,944 --> 02:59:49,278
but with the JNK inhibition,

3636
02:59:49,278 --> 02:59:52,015
we had severely reduced
the signal of that enzyme.

3637
02:59:52,015 --> 02:59:53,683
We also then looked
at mechanical testing

3638
02:59:53,683 --> 02:59:54,917
of these arteries.

3639
02:59:54,917 --> 02:59:58,788
Would that play?
If I punch it -- so we can play.

3640
02:59:58,788 --> 03:00:01,424
But as you can tie cannulate
the carotid artery,

3641
03:00:01,424 --> 03:00:03,192
increase the pressure through --
the video's not playing,

3642
03:00:03,192 --> 03:00:05,628
but you'll see the artery
wall expand, right?

3643
03:00:05,628 --> 03:00:08,564
So, the stiffer the artery is,

3644
03:00:08,564 --> 03:00:11,567
the less expansion you see
as you increase pressure.

3645
03:00:11,567 --> 03:00:13,302
So, we look at these
pressure-diameter curves,

3646
03:00:13,302 --> 03:00:14,604
and our hypothesis was that

3647
03:00:14,604 --> 03:00:16,305
if the elastin is being
degraded --

3648
03:00:16,305 --> 03:00:18,441
that confers compliance
to the artery wall --

3649
03:00:18,441 --> 03:00:19,942
then we would see
stiffer vessels

3650
03:00:19,942 --> 03:00:21,878
in the sickle cell arteries.

3651
03:00:21,878 --> 03:00:24,313
But we actually didn't at
one month, nor at three months.

3652
03:00:24,313 --> 03:00:26,683
It's actually the sickle
arteries were more compliant.

3653
03:00:26,683 --> 03:00:27,917
So, what does that tell us?

3654
03:00:27,917 --> 03:00:29,385
Well, there's more
than just elastin

3655
03:00:29,385 --> 03:00:32,488
that is conferring mechanical
properties to the artery wall.

3656
03:00:32,488 --> 03:00:35,024
So, my wonderful research
scientist, Hannah Song,

3657
03:00:35,024 --> 03:00:37,527
actually then looked at collagen
in the artery wall.

3658
03:00:37,527 --> 03:00:39,796
So, we went and did
Mason trichrome staining.

3659
03:00:39,796 --> 03:00:42,398
And what's really shocking
is that top image on the right

3660
03:00:42,398 --> 03:00:44,067
with Mason trichrome,
where you see blue,

3661
03:00:44,067 --> 03:00:45,802
is where collagen is present.

3662
03:00:45,802 --> 03:00:47,770
And then that SS artery --
these are now at five months.

3663
03:00:47,770 --> 03:00:49,038
So, we did the drug treatment

3664
03:00:49,038 --> 03:00:50,707
from three months
to five months.

3665
03:00:50,707 --> 03:00:53,743
Five months, that elastin
is gone in that artery wall,

3666
03:00:53,743 --> 03:00:55,278
and you can see it's all red.

3667
03:00:55,278 --> 03:00:58,314
Plus, you can see the expansive,
and it almost looks aneurysmal.

3668
03:00:58,314 --> 03:01:00,316
But again, with our
JNK inhibitor treatment,

3669
03:01:00,316 --> 03:01:02,685
we can actually retain
some of the collagen

3670
03:01:02,685 --> 03:01:04,754
in that artery wall.
Collagen, remember,

3671
03:01:04,754 --> 03:01:07,156
confers tensile strength
to the artery wall,

3672
03:01:07,156 --> 03:01:08,491
which now we're understanding

3673
03:01:08,491 --> 03:01:11,194
why we're seeing more blown-out
compliant arteries

3674
03:01:11,194 --> 03:01:12,595
in the SS mice.

3675
03:01:12,595 --> 03:01:14,397
So, as we look at these things
happening over time,

3676
03:01:14,397 --> 03:01:15,631
at the early stages,

3677
03:01:15,631 --> 03:01:17,600
we're seeing early
elastic lamina damage,

3678
03:01:17,600 --> 03:01:19,102
which we might put there.

3679
03:01:19,102 --> 03:01:21,804
And then at three months, we're
seeing greater elastin breaks.

3680
03:01:21,804 --> 03:01:23,940
And by five months, we're seeing
this loss of collagen.

3681
03:01:23,940 --> 03:01:25,575
So, we're seeing these enzymes
that can degrade

3682
03:01:25,575 --> 03:01:29,112
both of these structures
be increased over time.

3683
03:01:29,779 --> 03:01:32,215
How we relate that to the
human condition is that, again,

3684
03:01:32,215 --> 03:01:33,816
it's known that
at the earlier ages,

3685
03:01:33,816 --> 03:01:35,785
children are at greater risk
of a thrombotic

3686
03:01:35,785 --> 03:01:38,387
or an infarctive stroke,
versus at the later ages,

3687
03:01:38,387 --> 03:01:40,289
people have a greater risk
of hemorrhagic stroke.

3688
03:01:40,289 --> 03:01:42,525
So, if you're reducing
the mechanical integrity

3689
03:01:42,525 --> 03:01:43,726
of that artery wall,

3690
03:01:43,726 --> 03:01:45,762
greater susceptibility
to rupture.

3691
03:01:47,463 --> 03:01:49,432
Lots of variability,
as has been mentioned.

3692
03:01:49,432 --> 03:01:51,400
And we think about that --
I do -- for other work.

3693
03:01:51,400 --> 03:01:53,836
I do personalized medicine
and other things.

3694
03:01:53,836 --> 03:01:55,138
And even in our mouse models,

3695
03:01:55,138 --> 03:01:58,174
there is great variability
of the disease severity, right?

3696
03:01:58,174 --> 03:02:00,276
In the humans, you see
11 percent get a major stroke.

3697
03:02:00,276 --> 03:02:02,178
So, it's still variability
with all.

3698
03:02:02,178 --> 03:02:04,680
So, my wonderful scientist,
I found a protocol

3699
03:02:04,680 --> 03:02:07,150
for label-free magnetic
resonance angiograms,

3700
03:02:07,150 --> 03:02:09,218
so we could actually
track the same mouse

3701
03:02:09,218 --> 03:02:11,754
over time versus
these endpoint analyses

3702
03:02:11,754 --> 03:02:13,589
and averaging it all together.

3703
03:02:13,589 --> 03:02:15,925
So, we began to do MRA --
a wonderful grad student

3704
03:02:15,925 --> 03:02:17,860
who started about
three years ago now --

3705
03:02:17,860 --> 03:02:19,662
where we could do
a label-free MRA

3706
03:02:19,662 --> 03:02:22,465
on these sickled mice and track
the same mice as they grew one,

3707
03:02:22,465 --> 03:02:23,933
three, five, seven months.

3708
03:02:23,933 --> 03:02:26,903
Reconstruct the arteries, again,
in computer,

3709
03:02:26,903 --> 03:02:29,005
and then make
morphometric measurements

3710
03:02:29,005 --> 03:02:31,474
to watch it change
in a mouse over time,

3711
03:02:31,474 --> 03:02:34,143
with or without sickle cell.
And what we did see at first

3712
03:02:34,143 --> 03:02:36,646
was what we found histologically
was supported,

3713
03:02:36,646 --> 03:02:38,181
in that in the SS mice,

3714
03:02:38,181 --> 03:02:41,217
you do see expansion of these
lumens as these mice grow.

3715
03:02:41,217 --> 03:02:43,252
There actually is a bit
of a sex-specific difference.

3716
03:02:43,252 --> 03:02:45,188
The males steadily get worse,

3717
03:02:45,188 --> 03:02:47,323
whereas the females
kind of narrow off

3718
03:02:47,323 --> 03:02:49,091
by three to between three
and five months.

3719
03:02:49,091 --> 03:02:50,326
Which again, in the humans,

3720
03:02:50,326 --> 03:02:52,662
the males have a lower life
expectancy than women.

3721
03:02:52,662 --> 03:02:54,664
So, we're seeing
some of that reflected.

3722
03:02:55,364 --> 03:02:58,801
But what really was nice
with the MRA allows us to see

3723
03:02:58,801 --> 03:03:01,304
is you actually can see
in one artery in a mouse

3724
03:03:01,304 --> 03:03:04,574
a development of a stenosis
between one of our time points.

3725
03:03:04,574 --> 03:03:07,276
And why that's interesting
is when we look at measuring

3726
03:03:07,276 --> 03:03:08,678
the way we get this measurement,

3727
03:03:08,678 --> 03:03:11,480
we measure the artery diameter
along the full length.

3728
03:03:11,480 --> 03:03:13,216
You can actually see it looks
like the arteries

3729
03:03:13,216 --> 03:03:15,551
shrink over time,
but it's not that.

3730
03:03:15,551 --> 03:03:17,353
There are now stenosed regions
in the middle that,

3731
03:03:17,353 --> 03:03:18,554
as you average it out,

3732
03:03:18,554 --> 03:03:20,823
make it seem like
the vessel's getting smaller.

3733
03:03:20,823 --> 03:03:23,893
So, we're looking at better ways
to analyze this morphometry.

3734
03:03:24,660 --> 03:03:26,496
But again, taking into account
the variability,

3735
03:03:26,496 --> 03:03:28,464
this now allows us to now look
at how are

3736
03:03:28,464 --> 03:03:30,499
these things different,
though they all have SS.

3737
03:03:30,499 --> 03:03:33,302
And so, one of my talented
post-bacs at NIH

3738
03:03:33,302 --> 03:03:34,737
has been analyzing these.

3739
03:03:34,737 --> 03:03:36,806
And we see that
in some of the SS mice,

3740
03:03:36,806 --> 03:03:38,241
this one here,
there's variability.

3741
03:03:38,241 --> 03:03:40,409
One of these mice
at three months, no stenosis.

3742
03:03:40,409 --> 03:03:42,445
And at five months,
you can see a stenosis

3743
03:03:42,445 --> 03:03:43,713
in the carotid artery.

3744
03:03:43,713 --> 03:03:46,849
Versus a separate SS mouse
at three months,

3745
03:03:46,849 --> 03:03:50,219
had a significant stenosis
that persisted at five months

3746
03:03:50,219 --> 03:03:52,255
and didn't resolve itself.

3747
03:03:52,255 --> 03:03:55,157
Versus AA, we never were able
to visualize that.

3748
03:03:55,758 --> 03:03:57,059
So, we now put up a new workflow

3749
03:03:57,059 --> 03:03:58,494
because, again,
I told you earlier,

3750
03:03:58,494 --> 03:04:01,163
with a stenosis, you get changes
in the blood flow patterns

3751
03:04:01,163 --> 03:04:02,965
and regions of flow circulation.

3752
03:04:02,965 --> 03:04:05,935
We want to now model that with
computational fluid dynamics.

3753
03:04:05,935 --> 03:04:08,871
So, this is our workflow there
after we get the MR,

3754
03:04:08,871 --> 03:04:10,873
a series of softwares.

3755
03:04:10,873 --> 03:04:12,875
And we can then --
it's going to play by itself,

3756
03:04:12,875 --> 03:04:15,044
it's going to skip,
but we're good --

3757
03:04:15,044 --> 03:04:17,680
and so, we can recreate
these for multiple vessels.

3758
03:04:17,680 --> 03:04:19,548
And again, what's unique
about sickle cell,

3759
03:04:19,548 --> 03:04:20,883
we are looking at disturbed flow

3760
03:04:20,883 --> 03:04:23,052
in the straight parts
of the carotid artery.

3761
03:04:23,052 --> 03:04:25,121
We know we're going to see it
in the bifurcations,

3762
03:04:25,121 --> 03:04:27,690
but it's that straight part
that makes sickle cell unique.

3763
03:04:27,690 --> 03:04:29,926
And we are able to localize
these regions.

3764
03:04:29,926 --> 03:04:32,929
Also, I guess I'll play with --
push it -- I'll push it.

3765
03:04:32,929 --> 03:04:35,564
I'm scared to push it because
I don't want to go, okay.

3766
03:04:35,564 --> 03:04:38,734
Where we can also then calculate
what are these areas

3767
03:04:38,734 --> 03:04:41,203
of low
or oscillatory shear stress,

3768
03:04:41,203 --> 03:04:43,306
which occurs as these sites
of disturbed flow.

3769
03:04:43,306 --> 03:04:44,874
And those are then subject

3770
03:04:44,874 --> 03:04:46,976
to the upregulation
of these proteases

3771
03:04:46,976 --> 03:04:48,678
that will remodel
the artery wall.

3772
03:04:50,646 --> 03:04:53,616
Right, now that's a beautiful
image, as you can see.

3773
03:04:53,616 --> 03:04:56,185
I'm not this fancy; they made
these wonderful things for me.

3774
03:04:56,185 --> 03:04:57,787
But what we found
in the SS arteries

3775
03:04:57,787 --> 03:05:00,122
is that you actually get
this variability around --

3776
03:05:00,122 --> 03:05:01,490
or this asymmetry around --

3777
03:05:01,490 --> 03:05:04,293
even the straighter parts
of the common carotid artery.

3778
03:05:04,293 --> 03:05:05,595
And we can then --

3779
03:05:05,595 --> 03:05:08,965
you can see the greater
asymmetry in SS versus AA.

3780
03:05:09,498 --> 03:05:12,301
But we also then now have able
to match the MRA.

3781
03:05:12,301 --> 03:05:14,203
Then when we sacrifice
or euthanize the mouse,

3782
03:05:14,203 --> 03:05:16,205
we can then look
at the histology

3783
03:05:16,205 --> 03:05:18,674
on that exact artery
of which we did the CFD.

3784
03:05:18,674 --> 03:05:21,544
Because, again, to reduce that
subject-to-subject variability

3785
03:05:21,544 --> 03:05:24,013
by looking at one subject
at a time.

3786
03:05:24,013 --> 03:05:26,449
And what we see
with the asymmetry, you see --

3787
03:05:26,449 --> 03:05:27,984
again, I'm sorry
about the laser pointer --

3788
03:05:27,984 --> 03:05:29,185
but you see at this part

3789
03:05:29,185 --> 03:05:32,655
where you have these straighter
parts of the elastic lamina,

3790
03:05:32,655 --> 03:05:34,423
that's where you have
the elastic lamina breaks

3791
03:05:34,423 --> 03:05:36,092
and the nicks
that straighten it out.

3792
03:05:36,092 --> 03:05:37,426
But where you get
that nice wavy part,

3793
03:05:37,426 --> 03:05:39,595
that's the intact
elastic lamina.

3794
03:05:39,595 --> 03:05:41,664
And where we get the regions
of disturbed flow

3795
03:05:41,664 --> 03:05:42,965
and low oscillatory shear,

3796
03:05:42,965 --> 03:05:44,834
which is asymmetric
to the artery wall,

3797
03:05:44,834 --> 03:05:47,470
that's where we're seeing
these uniform breaks

3798
03:05:47,470 --> 03:05:49,071
in the elastic lamina.

3799
03:05:50,139 --> 03:05:52,074
And then we then wanted to match
it up with genes

3800
03:05:52,074 --> 03:05:53,743
that we know
are shear-stress regulated

3801
03:05:53,743 --> 03:05:55,978
to confirm
where we get the elastin breaks.

3802
03:05:55,978 --> 03:05:58,848
We are now seeing the genes
that have been established

3803
03:05:58,848 --> 03:06:01,150
to be regulated by flow.
We haven't done ENOS yet.

3804
03:06:01,150 --> 03:06:03,886
But cystatin C was one that
I also did during my PhD.

3805
03:06:03,886 --> 03:06:06,889
It's elevated under
unidirectional healthy flow.

3806
03:06:06,889 --> 03:06:08,624
It is actually the inhibitor
of the cysteine

3807
03:06:08,624 --> 03:06:10,593
cathepsins that the cells make.

3808
03:06:10,593 --> 03:06:12,061
So, the inhibitor
is highly present

3809
03:06:12,061 --> 03:06:14,864
in the curlicue part
of the elastic lamina

3810
03:06:14,864 --> 03:06:16,399
and is actually not
as much expressed

3811
03:06:16,399 --> 03:06:18,034
in the straighter nicked part.

3812
03:06:18,034 --> 03:06:19,802
And so, again, just validating
that where

3813
03:06:19,802 --> 03:06:22,171
we're seeing shear-stress gene
protein expression

3814
03:06:22,171 --> 03:06:23,873
is where we're seeing the low
and oscillatory wall

3815
03:06:23,873 --> 03:06:25,141
shear stress,

3816
03:06:25,141 --> 03:06:27,977
which is where we're seeing
the CFD that indicated it.

3817
03:06:27,977 --> 03:06:30,012
So, just to close all that up,

3818
03:06:30,012 --> 03:06:32,248
these anatomical changes
we've been seeing in the carotid

3819
03:06:32,248 --> 03:06:34,984
and cerebral arteries
do change the fluid dynamics

3820
03:06:34,984 --> 03:06:37,486
and induce flow-mediated
arterial remodeling.

3821
03:06:37,486 --> 03:06:39,221
And if we can look
at some of these other disturbed

3822
03:06:39,221 --> 03:06:40,423
flow-mediated proteins

3823
03:06:40,423 --> 03:06:42,625
that we know can remodel
the artery wall,

3824
03:06:42,625 --> 03:06:44,794
it opens up new
therapeutic possibilities

3825
03:06:44,794 --> 03:06:47,863
to protect these arteries
for children with sickle cell.

3826
03:06:48,531 --> 03:06:50,266
Again, the mechanics
of blood flow integrates

3827
03:06:50,266 --> 03:06:52,168
with the inflammatory
and biochemical cues,

3828
03:06:52,168 --> 03:06:54,136
which make it a wonderful
challenging problem,

3829
03:06:54,136 --> 03:06:55,404
along with all
the other challenges

3830
03:06:55,404 --> 03:06:57,573
that we struggle with
with sickle cell.

3831
03:06:57,573 --> 03:06:59,575
And again, this
patient-to-patient variability

3832
03:06:59,575 --> 03:07:01,510
is also reflected
in artery damage.

3833
03:07:01,510 --> 03:07:03,279
And we'd love to partner
with clinicians

3834
03:07:03,279 --> 03:07:05,214
with longitudinal MRA data

3835
03:07:05,214 --> 03:07:07,016
as we can take
what we were doing in mice --

3836
03:07:07,016 --> 03:07:08,250
can we transfer
this to humans --

3837
03:07:08,250 --> 03:07:10,486
and you all would have
the outcomes that would be,

3838
03:07:10,486 --> 03:07:12,822
again, a better validation
of what we might be seeing.

3839
03:07:12,822 --> 03:07:14,023
Thank you for your time,

3840
03:07:14,023 --> 03:07:17,226
the initiative I allowed
[laughs].

3841
03:07:17,226 --> 03:07:18,427
[applause]

3842
03:07:18,427 --> 03:07:19,695
I want to thank
my funding sources

3843
03:07:19,695 --> 03:07:20,863
from before I moved to NIH.

3844
03:07:20,863 --> 03:07:22,932
Now, my funding
is all from NIBIB.

3845
03:07:22,932 --> 03:07:25,868
I've got a great group
that has now been grown --

3846
03:07:25,868 --> 03:07:27,670
sorry, grown --
there at the NIH.

3847
03:07:27,670 --> 03:07:29,371
And I love this picture
at the bottom.

3848
03:07:29,371 --> 03:07:31,273
That's us at
the Sickle Cell Walk Run

3849
03:07:31,273 --> 03:07:33,809
for the Sickle Cell Foundation
of Georgia two years ago.

3850
03:07:33,809 --> 03:07:35,144
And appreciate them
for all their help.

3851
03:07:35,144 --> 03:07:36,545
All right, thank you.

3852
03:07:36,545 --> 03:07:41,217
[applause]

3853
03:07:41,217 --> 03:07:43,786
Female Speaker: Thank you, Manu,
I'm sorry I have to compete.

3854
03:07:43,786 --> 03:07:45,187
I don't know what's going on.

3855
03:07:45,187 --> 03:07:46,822
Manu Platt: That's all right,

3856
03:07:46,822 --> 03:07:48,991
as long as I don't hear it
on this video.

3857
03:07:48,991 --> 03:07:54,163
Female Speaker: We do have five
minutes for questions, Scott.

3858
03:07:57,633 --> 03:07:58,901
Scott Pestelak: Scott Pestelak
[phonetic sp],

3859
03:07:58,901 --> 03:08:00,202
UPenn.
Really great talk.

3860
03:08:00,202 --> 03:08:03,072
And I too am shocked
at how early patients

3861
03:08:03,072 --> 03:08:04,740
with sickle cell disease develop

3862
03:08:04,740 --> 03:08:07,643
cerebral vascular
malformations and stroke.

3863
03:08:07,643 --> 03:08:12,081
It's really impressive
from a biological perspective,

3864
03:08:12,081 --> 03:08:13,482
and your work
was really interesting

3865
03:08:13,482 --> 03:08:15,351
from that perspective
to be able to figure that out.

3866
03:08:15,351 --> 03:08:16,585
Do you think, you know,

3867
03:08:16,585 --> 03:08:18,187
the only way we know
how to treat patients

3868
03:08:18,187 --> 03:08:19,755
who have had stroke
with sickle cell disease

3869
03:08:19,755 --> 03:08:22,725
is by longitudinal transfusions
and exchange transfusion?

3870
03:08:22,725 --> 03:08:24,193
Do you think any of the work
you're doing

3871
03:08:24,193 --> 03:08:25,427
or there's any evidence

3872
03:08:25,427 --> 03:08:27,463
that we could be able
to use this to understand

3873
03:08:27,463 --> 03:08:31,200
how to remodel in some way
to reduce long-term risk?

3874
03:08:31,734 --> 03:08:34,603
And if we could use that
to be able to risk

3875
03:08:34,603 --> 03:08:36,405
stratify patients as well?

3876
03:08:36,405 --> 03:08:37,940
Manu Platt: That is
a really interesting question.

3877
03:08:37,940 --> 03:08:40,342
We have thought about,
in our mouse models,

3878
03:08:40,342 --> 03:08:42,244
that we want to try
transfusion protocols

3879
03:08:42,244 --> 03:08:44,647
just to see if we can also
prevent this arterial

3880
03:08:44,647 --> 03:08:46,215
remodeling with
the transfusion protocol

3881
03:08:46,215 --> 03:08:48,250
that would match up
to what's in humans.

3882
03:08:48,250 --> 03:08:49,919
And we don't have that answer,

3883
03:08:50,686 --> 03:08:52,254
but it's something
that we could think about

3884
03:08:52,254 --> 03:08:54,523
because we have now shifted --
I don't show this here --

3885
03:08:54,523 --> 03:08:56,725
we started looking
at transplantation.

3886
03:08:56,725 --> 03:09:00,029
And even after BMT,
is the artery wall

3887
03:09:00,029 --> 03:09:01,764
still protected
from further remodeling?

3888
03:09:01,764 --> 03:09:04,934
And from that aspect, we have
seen that early transplantation

3889
03:09:04,934 --> 03:09:07,169
does prevent further
artery remodeling.

3890
03:09:07,169 --> 03:09:09,538
But if we wait too late,
the artery's already damaged,

3891
03:09:09,538 --> 03:09:10,973
and there was
no protective effect,

3892
03:09:10,973 --> 03:09:13,509
which I would imagine
would transfer the transfusions.

3893
03:09:13,509 --> 03:09:14,910
Scott Pestelak: Yeah,
interesting. Thank you.

3894
03:09:14,910 --> 03:09:16,512
Manu Platt: All right,
thank you.

3895
03:09:18,547 --> 03:09:19,848
Female Speaker: Bob has
a question.

3896
03:09:19,848 --> 03:09:22,551
Male Speaker: Hi, I was
just fascinated

3897
03:09:22,551 --> 03:09:25,621
by the anatomical changes.

3898
03:09:25,621 --> 03:09:31,393
And I'm wondering about
monocytes, macrophages,

3899
03:09:31,393 --> 03:09:34,897
and their role.
Lenzon [phonetic sp]

3900
03:09:34,897 --> 03:09:38,801
just recently had an article
in Science dealing with dooming

3901
03:09:38,801 --> 03:09:41,537
and grooming of hematopoietic
stem cells.

3902
03:09:41,537 --> 03:09:43,772
I don't know if you saw
that article or not,

3903
03:09:44,373 --> 03:09:48,544
but it's a mechanism
by which senescent hematopoietic

3904
03:09:49,311 --> 03:09:54,950
stem cells
are removed early on.

3905
03:09:55,718 --> 03:09:59,989
And I'm wondering,
in sickle cell patients,

3906
03:10:00,823 --> 03:10:03,425
there's a lot of red
cell removal

3907
03:10:03,425 --> 03:10:05,027
because of the sickle cell.

3908
03:10:05,794 --> 03:10:09,732
Is there an association
between your plaque formation

3909
03:10:09,732 --> 03:10:11,433
and red cell removal?

3910
03:10:12,868 --> 03:10:15,404
John, for example,
has done studies

3911
03:10:15,404 --> 03:10:21,277
looking at the pharmacokinetics
of red cell clearance

3912
03:10:21,277 --> 03:10:23,412
and found that
the sickle cell patients

3913
03:10:23,412 --> 03:10:26,448
had a very rapid loss
of red cells.

3914
03:10:26,448 --> 03:10:28,150
And I'm just wondering

3915
03:10:28,150 --> 03:10:33,889
if that's the mechanism
that's occurring --

3916
03:10:33,889 --> 03:10:36,692
is that the macrophages
are getting activated

3917
03:10:36,692 --> 03:10:38,560
and causing
the endothelial damage?

3918
03:10:39,061 --> 03:10:40,396
Another question would be,

3919
03:10:40,396 --> 03:10:44,333
do you see increases
of C-reactive protein

3920
03:10:44,333 --> 03:10:46,969
in these patients
that develop stroke?

3921
03:10:46,969 --> 03:10:48,837
That's an athero question --
the C-reactive protein.

3922
03:10:48,837 --> 03:10:50,072
Manu Platt: Another
thing, maybe --

3923
03:10:50,072 --> 03:10:51,940
we have not yet translated
that to sickle cell.

3924
03:10:51,940 --> 03:10:53,542
So, not looked at CRP yet.

3925
03:10:54,176 --> 03:10:56,912
As far as red cell clearance,
we don't address that.

3926
03:10:56,912 --> 03:10:58,681
I'm happy to talk after this

3927
03:10:58,681 --> 03:11:00,983
about how maybe there's
some collaboration

3928
03:11:00,983 --> 03:11:02,184
that we can do there.

3929
03:11:02,184 --> 03:11:03,953
But one thing we
do care about --

3930
03:11:03,953 --> 03:11:06,689
we expected, actually, that once
we opened up these arteries,

3931
03:11:06,689 --> 03:11:10,659
we would see monocytes adhered
all along the endothelial layer,

3932
03:11:10,659 --> 03:11:14,430
which we have not seen
in the way that we perfuse

3933
03:11:14,430 --> 03:11:18,667
and process our samples
post-euthanization.

3934
03:11:18,667 --> 03:11:20,336
So, one way we are trying
to look at then

3935
03:11:20,336 --> 03:11:22,671
the monocyte interactions
in the artery walls,

3936
03:11:22,671 --> 03:11:24,440
there's trying some new
imaging modalities.

3937
03:11:24,440 --> 03:11:26,008
But one thing we are
going to do directly --

3938
03:11:26,008 --> 03:11:28,344
we now have approval
for animal studies

3939
03:11:28,344 --> 03:11:31,213
to put in cranial
chambers in these mice.

3940
03:11:31,213 --> 03:11:32,748
And we've been crossing
the Townes mouse

3941
03:11:32,748 --> 03:11:35,017
with the GFP monocyte mouse

3942
03:11:35,017 --> 03:11:36,518
so that now we can have
the two together

3943
03:11:36,518 --> 03:11:38,454
and actually then look
at monocyte attachment

3944
03:11:38,454 --> 03:11:41,390
rolling to look
at the amounts of monocytes

3945
03:11:41,390 --> 03:11:44,159
and how long they actually stay
attached to that artery wall.

3946
03:11:44,159 --> 03:11:45,494
But there's some
complications --

3947
03:11:45,494 --> 03:11:47,363
or there's, let me
say, controversy --

3948
03:11:47,363 --> 03:11:49,331
about does the shear stress
in the arteries

3949
03:11:49,331 --> 03:11:51,266
allow the monocytes
to stick or adhere?

3950
03:11:51,266 --> 03:11:53,635
But I'm like, they do that
under an atherosclerotic regime.

3951
03:11:53,635 --> 03:11:55,604
Why would they not
under these conditions,

3952
03:11:55,604 --> 03:11:57,673
even with greater activation
of the endothelium?

3953
03:11:57,673 --> 03:11:59,141
So, that's where I can
try to get back to you

3954
03:11:59,141 --> 03:12:00,376
and see what those
monocytes do.

3955
03:12:00,376 --> 03:12:01,577
Male Speaker: Well, that's
really a good way

3956
03:12:01,577 --> 03:12:02,778
of approaching it

3957
03:12:02,778 --> 03:12:05,014
because you're comparing
what you normally see

3958
03:12:05,014 --> 03:12:06,749
with what you'll see
in the sickle.

3959
03:12:06,749 --> 03:12:08,283
Right, thank you.

3960
03:12:08,283 --> 03:12:11,086
Female Speaker: Okay, I think
we will close this session.

3961
03:12:11,086 --> 03:12:12,421
Thank you so much, Manu.
Manu Platt: Thank you.

3962
03:12:12,421 --> 03:12:13,622
[applause]

3963
03:12:13,622 --> 03:12:16,191
Female Speaker: So, I know

3964
03:12:16,191 --> 03:12:18,160
it's going to cut
into your lunch break,

3965
03:12:18,160 --> 03:12:20,796
but we have to try to
catch up in the meantime.

3966
03:12:20,796 --> 03:12:24,299
So, please come back at 12:45.
It's on the program.

3967
03:12:24,666 --> 03:12:26,101
Female Speaker: We
are about to start,

3968
03:12:26,101 --> 03:12:27,669
and Dr. Ramsay
is going to take over.

3969
03:12:27,669 --> 03:12:30,973
But I just wanted to say,
while you're eating,

3970
03:12:30,973 --> 03:12:33,542
just to bring your attention

3971
03:12:33,542 --> 03:12:38,013
to two tables to the side
of hardworking people.

3972
03:12:38,013 --> 03:12:41,350
One is a display from the
Sickle Cell Unit in Jamaica,

3973
03:12:41,350 --> 03:12:43,318
just because you're
here in Jamaica.

3974
03:12:43,318 --> 03:12:44,753
It's a pity that
you couldn't all come

3975
03:12:44,753 --> 03:12:46,321
and visit us at our unit,

3976
03:12:47,222 --> 03:12:52,728
but we have some resources here
that we use at the unit.

3977
03:12:52,728 --> 03:12:57,199
So, if you have any time after
lunch, or during a break time,

3978
03:12:57,199 --> 03:12:59,768
or at the end of the day,
please do go and take a look.

3979
03:12:59,768 --> 03:13:01,236
And I just want to say
one more thing,

3980
03:13:01,236 --> 03:13:03,038
that the University
of the Western Days,

3981
03:13:03,038 --> 03:13:04,940
the Sickle Cell Unit,
is very grateful

3982
03:13:05,507 --> 03:13:08,510
for some really
important support

3983
03:13:08,510 --> 03:13:10,379
we have gotten
from four sponsors

3984
03:13:11,547 --> 03:13:13,081
that enabled the
Sickle Cell Unit

3985
03:13:13,081 --> 03:13:16,485
to do our little bit to bring
this conference together,

3986
03:13:17,052 --> 03:13:19,254
and one is represented here.

3987
03:13:19,254 --> 03:13:23,992
Zachary is here from Pemex,
and we are really very excitedly

3988
03:13:23,992 --> 03:13:26,161
looking at the demonstration
of the Gazelle.

3989
03:13:26,795 --> 03:13:30,466
And our other sponsors
who have supported the unit

3990
03:13:30,466 --> 03:13:31,767
for this conference

3991
03:13:31,767 --> 03:13:37,372
are Fulcrum Therapeutics,
Adios, and Bluebird Bio.

3992
03:13:37,372 --> 03:13:39,441
Really grateful for their
support, thank you.

3993
03:13:39,441 --> 03:13:42,010
So, do go and visit
the two setups

3994
03:13:42,010 --> 03:13:43,946
whenever you get a
minute, thank you.

3995
03:13:47,816 --> 03:13:49,885
Zachary Ramsay: Hi,
good afternoon, everybody.

3996
03:13:49,885 --> 03:13:53,789
I'm Dr. Zachary Ramsay,
and I'm happy to be chairing

3997
03:13:53,789 --> 03:13:55,791
the third session
for this afternoon.

3998
03:13:56,925 --> 03:14:00,028
So, the third session
will be on the complexities

3999
03:14:00,028 --> 03:14:02,698
of the common complications
in sickle cell disease.

4000
03:14:03,398 --> 03:14:06,702
And our first presentation
will be on insomnia

4001
03:14:06,702 --> 03:14:09,638
and sleep health
by Dr. Monica Hack.

4002
03:14:10,372 --> 03:14:13,475
Now, Dr. Hack is an Associate
Professor of Neurology

4003
03:14:14,076 --> 03:14:16,011
at Harvard Medical School,

4004
03:14:16,011 --> 03:14:19,047
and she leads the Sleep
and Pain Laboratory

4005
03:14:19,047 --> 03:14:23,519
at Beth Israel Deaconess
Medical Center in Boston.

4006
03:14:24,419 --> 03:14:25,954
So, Dr. Hack.

4007
03:14:25,954 --> 03:14:27,222
Monica Hack: Thank you.

4008
03:14:27,222 --> 03:14:28,790
Zachary Ramsey: I was
telling you that this is

4009
03:14:28,790 --> 03:14:30,092
to change the slides.

4010
03:14:30,092 --> 03:14:32,561
Okay. And then there's a
pointer here if you want.

4011
03:14:36,431 --> 03:14:37,666
Monica Hack: Well,
thank you very much.

4012
03:14:37,666 --> 03:14:41,403
I'm so happy to be here and
talk about sleep and insomnia.

4013
03:14:42,037 --> 03:14:47,209
And I hope you stay all
with me after this, after --

4014
03:14:47,209 --> 03:14:49,811
during this nap time,
post-lunch nap time.

4015
03:14:50,646 --> 03:14:54,283
So, I first would like -- so,
I will talk about insomnia

4016
03:14:54,283 --> 03:14:57,319
and sleep health. And
we'll focus on pain.

4017
03:14:58,387 --> 03:15:04,226
So, what I would like to do
is touch base on four topics.

4018
03:15:04,226 --> 03:15:06,662
What is sleep health?
Why is it important?

4019
03:15:06,662 --> 03:15:08,130
How do we measure it?

4020
03:15:08,130 --> 03:15:10,632
Insomnia -- what is
the prevalence of insomnia?

4021
03:15:11,700 --> 03:15:14,870
I would like to concentrate
on this perpetuating cycle

4022
03:15:14,870 --> 03:15:18,106
between insomnia and pain,
talk about mechanisms.

4023
03:15:18,807 --> 03:15:20,642
What are the systems
and mediators

4024
03:15:20,642 --> 03:15:23,712
through which poor sleep
can exacerbate pain?

4025
03:15:23,712 --> 03:15:25,280
Then, how can we treat it?

4026
03:15:26,915 --> 03:15:28,984
So, how do we define
sleep health?

4027
03:15:29,851 --> 03:15:33,622
And sleep health is
a multi-dimensional

4028
03:15:33,622 --> 03:15:38,093
construct with all dimensions
associated with outcomes.

4029
03:15:38,093 --> 03:15:40,095
And just to give
you some examples:

4030
03:15:40,095 --> 03:15:42,998
Sleep health is important
for optimal brain function,

4031
03:15:42,998 --> 03:15:46,335
metabolic clearance,
as well as cognitive function,

4032
03:15:46,969 --> 03:15:49,938
adaptive and innate
immune system.

4033
03:15:49,938 --> 03:15:52,808
So, it's important
for infections,

4034
03:15:53,475 --> 03:15:56,111
to control infections,

4035
03:15:56,111 --> 03:15:59,081
inflammatory
homeostasis, metabolism.

4036
03:15:59,715 --> 03:16:02,918
Sleep health is associated with
the cardiovascular system.

4037
03:16:02,918 --> 03:16:05,153
That probably has
been most studied.

4038
03:16:05,153 --> 03:16:09,458
And, for example, there
is arterial regeneration

4039
03:16:09,458 --> 03:16:13,428
during sleep that's related
to the blood pressure dipping

4040
03:16:13,428 --> 03:16:15,163
that we see during sleep.

4041
03:16:15,163 --> 03:16:18,433
And also, it's important for
somatosensory processing,

4042
03:16:18,433 --> 03:16:20,102
in particular pain.

4043
03:16:20,102 --> 03:16:22,070
So, when we look
at sleep health,

4044
03:16:22,070 --> 03:16:24,072
many people think
about sleep duration,

4045
03:16:24,072 --> 03:16:27,376
and that probably has
been most studied.

4046
03:16:27,943 --> 03:16:30,512
We do know that sleep
that is too little --

4047
03:16:30,512 --> 03:16:32,114
as sleep that is too long --

4048
03:16:33,015 --> 03:16:35,717
is associated with
increased mortality risk.

4049
03:16:36,451 --> 03:16:39,988
It's about six to eight hours
is the optimal amount

4050
03:16:39,988 --> 03:16:41,690
for the majority of adults.

4051
03:16:42,257 --> 03:16:46,094
And then another independent
aspect is regularity of sleep.

4052
03:16:46,094 --> 03:16:47,763
So, this means going to bed,

4053
03:16:47,763 --> 03:16:50,799
getting up out of bed
at the same time,

4054
03:16:50,799 --> 03:16:55,537
plus minus 30 minutes.
This is an increasing problem,

4055
03:16:55,537 --> 03:16:59,207
irregular sleep
patterns in society,

4056
03:16:59,207 --> 03:17:02,477
which is an independent
risk factor for mortality

4057
03:17:02,477 --> 03:17:05,514
and all kinds of other
health outcomes.

4058
03:17:05,514 --> 03:17:07,683
And then we also
have timing of sleep.

4059
03:17:07,683 --> 03:17:11,520
So, sleep should fall
into the sleep window,

4060
03:17:11,520 --> 03:17:15,023
and that's disturbed,
for example, in shift workers.

4061
03:17:15,023 --> 03:17:17,092
And also, satisfaction
with sleep.

4062
03:17:17,092 --> 03:17:20,762
So, how is sleep perceived?
How is sleep quality perceived?

4063
03:17:21,663 --> 03:17:24,533
Do I feel that I'm
refreshed in the morning?

4064
03:17:24,533 --> 03:17:27,102
Is an important dimension,

4065
03:17:27,969 --> 03:17:30,172
and it's, for example,
for mental health,

4066
03:17:30,172 --> 03:17:33,008
it's more important
than the duration of sleep.

4067
03:17:33,008 --> 03:17:35,510
And then we have oxygen.

4068
03:17:35,510 --> 03:17:38,513
Good breathing is important
for sleep health,

4069
03:17:39,081 --> 03:17:43,618
and oxygen saturations of lower
than 90 percent at night

4070
03:17:44,553 --> 03:17:47,622
is the most predictive
measure of mortality.

4071
03:17:48,590 --> 03:17:54,930
We have efficiency,
so this means continuously

4072
03:17:54,930 --> 03:17:57,099
sleeping through
the sleep period.

4073
03:17:57,099 --> 03:18:00,535
So, without having
problems falling asleep,

4074
03:18:01,436 --> 03:18:05,307
sleep can be maintained without
frequent awakenings at night,

4075
03:18:05,307 --> 03:18:07,976
which are classical symptoms
in insomnia disorder.

4076
03:18:09,177 --> 03:18:11,012
And, of course, there's
then also alertness

4077
03:18:11,012 --> 03:18:12,914
and sleepiness during the day,

4078
03:18:12,914 --> 03:18:15,784
which is often one of
the very first indicators

4079
03:18:15,784 --> 03:18:18,353
that something is
wrong with sleep.

4080
03:18:18,353 --> 03:18:20,455
So, how do we measure
sleep health and sleep?

4081
03:18:20,455 --> 03:18:22,290
Of course, there are
several questionnaires

4082
03:18:22,290 --> 03:18:24,159
--that's probably
the easiest way.

4083
03:18:24,159 --> 03:18:26,595
There are sleep health
screening questionnaires

4084
03:18:26,595 --> 03:18:30,799
that cover all these dimensions.
In the United States,

4085
03:18:30,799 --> 03:18:34,069
the PROMIS Sleep Disturbance
Scale is very popular

4086
03:18:34,069 --> 03:18:35,637
because it gives you a T-score

4087
03:18:35,637 --> 03:18:38,707
that can determine
whether a person is below

4088
03:18:38,707 --> 03:18:43,645
the population average or above.
And then, we have also sleep

4089
03:18:43,645 --> 03:18:45,580
disorder-specific
questionnaires,

4090
03:18:45,580 --> 03:18:48,450
such as the Stop-Bang
for Apnea Screening

4091
03:18:48,450 --> 03:18:50,218
or the Insomnia Severity Index.

4092
03:18:50,752 --> 03:18:52,888
And then, of course,
we have sleep diaries.

4093
03:18:53,688 --> 03:18:56,591
And with electronic versions,

4094
03:18:56,591 --> 03:19:00,462
it's very easy to
get a very precise

4095
03:19:00,462 --> 03:19:05,066
or more precise idea of
these various sleep dimensions.

4096
03:19:05,767 --> 03:19:10,772
Sleep diaries are generally
filled out every day,

4097
03:19:10,772 --> 03:19:13,542
and you can really
see what happens

4098
03:19:13,542 --> 03:19:15,143
within a longer time period.

4099
03:19:15,744 --> 03:19:17,579
And what's getting
more and more popular

4100
03:19:17,579 --> 03:19:19,281
are wearable sleep monitors.

4101
03:19:20,215 --> 03:19:23,618
They can objectively assess
the duration of sleep,

4102
03:19:23,618 --> 03:19:25,153
regularity, efficiency,

4103
03:19:25,153 --> 03:19:27,355
breathing, heart
rate variability.

4104
03:19:27,355 --> 03:19:29,224
So, they're
multi-sensor devices,

4105
03:19:29,224 --> 03:19:30,792
they're getting
better and better.

4106
03:19:30,792 --> 03:19:33,161
And here, you have
these ring devices,

4107
03:19:33,161 --> 03:19:35,831
such as the Aura
Ring or Fitbits.

4108
03:19:36,765 --> 03:19:39,401
And there's also -- these
are commercial devices --

4109
03:19:39,401 --> 03:19:44,306
but there's more and more
research on research devices

4110
03:19:44,973 --> 03:19:46,508
that can be used for research

4111
03:19:46,508 --> 03:19:49,344
and where data can be
customized better.

4112
03:19:49,344 --> 03:19:52,414
And, of course, then we have,
what I wanted to mention

4113
03:19:52,414 --> 03:19:55,650
is that really shows the
popularity in the United States.

4114
03:19:55,650 --> 03:19:58,787
It's about 35 percent
who track their sleep

4115
03:19:58,787 --> 03:20:00,288
through these devices,

4116
03:20:00,288 --> 03:20:02,991
and about two-thirds
who change their sleep

4117
03:20:02,991 --> 03:20:04,593
based on what they
have learned.

4118
03:20:05,327 --> 03:20:07,596
And then, of course, we
have polysomnography,

4119
03:20:08,163 --> 03:20:11,900
sleep apnea tests that can
be done not only in facility,

4120
03:20:11,900 --> 03:20:13,101
but also at home.

4121
03:20:13,101 --> 03:20:15,103
And there are lots
of devices now

4122
03:20:15,103 --> 03:20:18,807
where you can measure sleep
in the at-home environment.

4123
03:20:18,807 --> 03:20:21,877
And these are indicated
for certain sleep disorders

4124
03:20:21,877 --> 03:20:24,045
to quantify
breathing-related disorders,

4125
03:20:24,045 --> 03:20:27,782
restless leg syndrome, nightmare
disorders, and other disorders.

4126
03:20:29,517 --> 03:20:32,420
So, as I said, insomnia
is highly prevalent,

4127
03:20:32,420 --> 03:20:36,658
and it's about 22
percent of individuals

4128
03:20:36,658 --> 03:20:38,793
in the United States,
Europe, Asia,

4129
03:20:38,793 --> 03:20:42,297
Africa meeting diagnostic
criteria for insomnia.

4130
03:20:42,297 --> 03:20:44,533
So this is diagnostic criteria.

4131
03:20:44,533 --> 03:20:49,471
This is not just having one
or two insomnia symptoms.

4132
03:20:49,971 --> 03:20:54,042
Diagnostic criteria include
dissatisfaction with sleep.

4133
03:20:54,042 --> 03:20:57,646
And these are associated with
difficulties initiating sleep,

4134
03:20:57,646 --> 03:21:00,515
maintaining sleep, and
early morning awakenings.

4135
03:21:00,515 --> 03:21:04,719
And these problems have to cause
clinically significant distress

4136
03:21:04,719 --> 03:21:09,291
or impairment of function,
such as in social, occupational.

4137
03:21:09,291 --> 03:21:11,192
And there's also
frequency criteria.

4138
03:21:11,192 --> 03:21:13,461
So, the sleep
problem has to occur

4139
03:21:13,461 --> 03:21:16,264
at least three times per week
for at least three months

4140
03:21:16,865 --> 03:21:19,734
and can, of course,
not better explained

4141
03:21:19,734 --> 03:21:24,472
by a coexisting
disorder or drug abuse.

4142
03:21:25,473 --> 03:21:28,043
And, but as I said, these
are diagnostic criteria.

4143
03:21:28,043 --> 03:21:32,714
22 percent -- there's many, many
more people who do not fulfill,

4144
03:21:32,714 --> 03:21:34,883
who have insomnia symptoms,

4145
03:21:34,883 --> 03:21:38,186
do not fulfill the
diagnostic criteria.

4146
03:21:39,321 --> 03:21:41,890
So, insomnia is common in
a wide range of disorders

4147
03:21:41,890 --> 03:21:43,124
involving pain.

4148
03:21:43,124 --> 03:21:46,761
It's 72 percent of
chronic pain population

4149
03:21:46,761 --> 03:21:50,932
that also suffers from insomnia,
comorbid with insomnia.

4150
03:21:51,833 --> 03:21:54,436
Autoimmune diseases are
very common with insomnia.

4151
03:21:55,103 --> 03:21:57,572
Post-virus syndromes
such as long COVID --

4152
03:21:57,572 --> 03:21:58,807
sleep disturbances,

4153
03:21:58,807 --> 03:22:02,310
pain are among the top
five symptoms in general.

4154
03:22:02,310 --> 03:22:04,079
Infectious respiratory illnesses

4155
03:22:04,079 --> 03:22:06,181
and also in blood
cell conditions,

4156
03:22:06,181 --> 03:22:08,583
comorbidity between
insomnia and complaints

4157
03:22:09,384 --> 03:22:11,186
and sickle cell estimated

4158
03:22:11,186 --> 03:22:14,856
between 47 percent
and 57 percent.

4159
03:22:14,856 --> 03:22:16,691
There's unfortunately
not that many studies,

4160
03:22:16,691 --> 03:22:18,293
so I found three studies.

4161
03:22:19,661 --> 03:22:22,530
So, but what I would
like to concentrate on

4162
03:22:22,530 --> 03:22:24,799
is really this
perpetuating relationship

4163
03:22:24,799 --> 03:22:27,202
between insomnia
and disease burden.

4164
03:22:27,869 --> 03:22:31,840
And insomnia in itself
can increase disease burden.

4165
03:22:31,840 --> 03:22:33,708
I will here focus on pain.

4166
03:22:33,708 --> 03:22:36,611
And, of course, pain
increases insomnia.

4167
03:22:36,611 --> 03:22:39,347
I mean, pain is a powerful
disruptor of sleep.

4168
03:22:40,215 --> 03:22:44,386
And the question is that I
would like to focus on here is,

4169
03:22:44,386 --> 03:22:46,588
how does insomnia
contribute to disease

4170
03:22:46,588 --> 03:22:48,923
risk and greater symptom burden?

4171
03:22:48,923 --> 03:22:51,993
And can we make it better
if we treat insomnia?

4172
03:22:52,994 --> 03:22:56,331
So, one thing that I
would like to go into

4173
03:22:56,331 --> 03:22:58,933
is that I think
is very important,

4174
03:22:58,933 --> 03:23:02,203
is considering sex as a
modulator in the association

4175
03:23:02,203 --> 03:23:04,005
between insomnia
and symptom burden.

4176
03:23:05,440 --> 03:23:08,743
What we do see is symptom
burden in many diseases

4177
03:23:08,743 --> 03:23:11,913
is much more common
in females than in males.

4178
03:23:12,614 --> 03:23:14,949
They also have more
persistent symptoms.

4179
03:23:14,949 --> 03:23:18,453
And this also has been reported
for sickle cell disease.

4180
03:23:19,454 --> 03:23:22,190
And that can have many
reasons: chromosomal changes,

4181
03:23:22,190 --> 03:23:24,292
cultural changes,
social changes.

4182
03:23:24,292 --> 03:23:28,663
But also insomnia seems to
be a contributing factor.

4183
03:23:28,663 --> 03:23:33,201
So, insomnia seems to be
strongly associated with symptom

4184
03:23:33,201 --> 03:23:36,704
burden, greater symptom burden
in females than in males.

4185
03:23:36,704 --> 03:23:40,442
That has been shown in various
epidemiological studies.

4186
03:23:40,442 --> 03:23:42,043
And I would also
like to show you

4187
03:23:42,043 --> 03:23:45,413
some experimental studies
where this has been shown.

4188
03:23:45,413 --> 03:23:50,518
So, to better really understand
the effects of insomnia on pain,

4189
03:23:50,518 --> 03:23:54,122
on inflammation, on
cardiovascular system,

4190
03:23:54,122 --> 03:23:57,292
we can simulate insomnia
in the laboratory setting.

4191
03:23:57,826 --> 03:23:59,394
And in the very beginning,

4192
03:23:59,394 --> 03:24:02,197
people have used acute
sleep deficiency models

4193
03:24:02,764 --> 03:24:05,967
of total sleep deprivation,
one night of sleep restriction.

4194
03:24:05,967 --> 03:24:09,237
And I'm not going into
that, but more recently,

4195
03:24:10,138 --> 03:24:13,141
people have used more chronic
sleep deficiency models.

4196
03:24:13,875 --> 03:24:16,377
And they have a higher
ecological validity.

4197
03:24:16,377 --> 03:24:20,381
So, for example, so the blue
basically is the sleep.

4198
03:24:20,381 --> 03:24:23,551
So, we can mimic patterns
of sleeping very little

4199
03:24:23,551 --> 03:24:24,819
during those workdays

4200
03:24:24,819 --> 03:24:26,921
and then catching up
on sleep on the weekend,

4201
03:24:26,921 --> 03:24:28,823
which I think many people do.

4202
03:24:28,823 --> 03:24:31,326
And see what kind of
consequences does this have

4203
03:24:31,826 --> 03:24:36,030
for pain, for inflammation,
for cardiovascular regulation.

4204
03:24:36,030 --> 03:24:37,465
And then also --

4205
03:24:37,465 --> 03:24:40,235
and I will focus a little
bit more on that model

4206
03:24:40,235 --> 03:24:45,240
is we can repeatedly
disturb sleep

4207
03:24:47,642 --> 03:24:50,044
with intermittent
recovery periods.

4208
03:24:50,044 --> 03:24:54,582
So, and the nice thing
with these models

4209
03:24:54,582 --> 03:24:57,852
is we can really understand
the symptom responses:

4210
03:24:57,852 --> 03:25:00,488
pain, fatigue,
biological responses.

4211
03:25:00,488 --> 03:25:01,956
Can they actually
adapt to those?

4212
03:25:01,956 --> 03:25:04,359
Can we adapt to
sleep disruption?

4213
03:25:04,359 --> 03:25:09,397
And also, do we recover from
these sleep disruption models?

4214
03:25:10,465 --> 03:25:12,233
So, this is basically a model

4215
03:25:12,233 --> 03:25:14,068
I would like to show you
some more data from.

4216
03:25:14,068 --> 03:25:15,537
This is a 19-day model.

4217
03:25:15,537 --> 03:25:18,673
So, people stay in the clinical
research center for 19 days.

4218
03:25:19,274 --> 03:25:20,675
And what you can see,

4219
03:25:20,675 --> 03:25:22,810
it starts with three nights
of undisturbed sleep.

4220
03:25:22,810 --> 03:25:25,880
So, people can sleep
eight hours per night,

4221
03:25:25,880 --> 03:25:28,783
and they have then these three
days of sleep disruption.

4222
03:25:28,783 --> 03:25:31,819
So, they have 40
minutes of sleep,

4223
03:25:31,819 --> 03:25:33,821
nurse comes in,
20 minutes of awake,

4224
03:25:33,821 --> 03:25:36,491
40 minutes of sleep,
20 minutes awake.

4225
03:25:36,491 --> 03:25:39,260
And then they have
a recovery night,

4226
03:25:39,260 --> 03:25:42,197
and then they do this again,
recovery night, do this again.

4227
03:25:43,264 --> 03:25:46,134
And then they come back
and have every day,

4228
03:25:46,134 --> 03:25:49,204
every night, eight hours
of sleep undisturbed sleep.

4229
03:25:49,204 --> 03:25:50,572
So, this is the environment.

4230
03:25:50,572 --> 03:25:53,141
So, they stay in the
clinical research center.

4231
03:25:53,141 --> 03:25:56,945
They have a nice room
with view of Boston.

4232
03:25:56,945 --> 03:26:01,049
And outside,
you can see the control.

4233
03:26:01,049 --> 03:26:04,652
So, we do PSG, blood draws
can be done through the wall.

4234
03:26:05,220 --> 03:26:07,322
And these environments
are very controlled.

4235
03:26:07,322 --> 03:26:10,725
So, food is controlled,
fluid, lights is controlled.

4236
03:26:10,725 --> 03:26:16,331
But we try to keep it still
not like isolating people,

4237
03:26:16,331 --> 03:26:19,534
so they can have visitors,
access to email and phone,

4238
03:26:19,534 --> 03:26:21,135
and so on.

4239
03:26:21,669 --> 03:26:26,207
So, this is basically
a hypnogram of such a night.

4240
03:26:26,207 --> 03:26:28,009
So, if you haven't seen this --

4241
03:26:30,812 --> 03:26:34,382
so basically, what you see
here is there is wake,

4242
03:26:34,382 --> 03:26:36,184
and then you see the
different sleep stages.

4243
03:26:36,184 --> 03:26:39,254
"R" stands for REM,
and then you have N1, N2, N3.

4244
03:26:39,254 --> 03:26:40,855
N3 is the deep sleep.

4245
03:26:41,356 --> 03:26:43,391
So, they stay awake,
they stay in bed,

4246
03:26:43,391 --> 03:26:47,128
they stay awake for an hour.
And then they go into sleep,

4247
03:26:47,128 --> 03:26:48,529
and then they have
a wake period.

4248
03:26:48,529 --> 03:26:51,766
20 minutes awake, they go into
sleep again, 20 minutes awake.

4249
03:26:51,766 --> 03:26:55,603
And this is very common
in the general population,

4250
03:26:55,603 --> 03:26:57,905
and especially
in chronic pain population.

4251
03:26:57,905 --> 03:27:00,275
This discontinuity of sleep,

4252
03:27:01,109 --> 03:27:03,311
I mean, what we cannot model
is the problem,

4253
03:27:04,145 --> 03:27:06,914
but we can model
the sleep phenotype.

4254
03:27:08,983 --> 03:27:14,522
So, I just want to first show
you how people respond

4255
03:27:14,522 --> 03:27:15,923
with respect to fatigue.

4256
03:27:15,923 --> 03:27:20,728
So, every four hours, we ask
on computerized rating scales

4257
03:27:20,728 --> 03:27:22,864
how they feel with respect
to fatigue,

4258
03:27:22,864 --> 03:27:24,632
pain, sleepiness, and so on.

4259
03:27:25,199 --> 03:27:27,435
And here you can see
the fatigue responses.

4260
03:27:28,136 --> 03:27:29,570
The red is the disturbed,

4261
03:27:29,570 --> 03:27:31,973
and, of course,
people are more fatigued.

4262
03:27:31,973 --> 03:27:35,810
And then the shaded areas,
that are the recovery periods.

4263
03:27:35,810 --> 03:27:39,480
So, you can see, after one
night of recovery sleep,

4264
03:27:39,480 --> 03:27:40,915
fatigue goes down.

4265
03:27:40,915 --> 03:27:44,986
What I would like to show you
is that females and males,

4266
03:27:46,220 --> 03:27:49,190
they have the same
level of fatigue.

4267
03:27:49,190 --> 03:27:52,493
But what you can see in females,
they just don't recover.

4268
03:27:52,493 --> 03:27:55,596
So, even after three nights
of sleeping eight hours,

4269
03:27:55,596 --> 03:27:57,765
they're still fatigued.
And I think that's important,

4270
03:27:57,765 --> 03:28:00,401
because fatigue
is such a big problem

4271
03:28:00,401 --> 03:28:02,003
in many chronic diseases.

4272
03:28:02,537 --> 03:28:06,341
And these diseases are often
over-represented in females.

4273
03:28:07,342 --> 03:28:09,177
So, when we look
at spontaneous pain,

4274
03:28:09,977 --> 03:28:12,080
so this is a composite score.

4275
03:28:12,613 --> 03:28:14,315
What I would like
to show you here

4276
03:28:14,315 --> 03:28:17,952
is that the pain
during the nighttime

4277
03:28:17,952 --> 03:28:21,789
is much higher
than during the daytime, right?

4278
03:28:21,789 --> 03:28:25,526
And that's something that
we can see for all localized

4279
03:28:25,526 --> 03:28:27,395
and non-localized pain items.

4280
03:28:27,395 --> 03:28:29,530
So, here you can
see stomach pain,

4281
03:28:29,530 --> 03:28:32,200
headache, back pain,
muscular pain,

4282
03:28:32,200 --> 03:28:34,068
joint pain,
generalized body pain.

4283
03:28:35,103 --> 03:28:38,806
And this may mean
that pain management

4284
03:28:38,806 --> 03:28:42,110
may specifically
target nighttime pain.

4285
03:28:42,110 --> 03:28:44,912
For example, through timing
of energetic medications.

4286
03:28:46,247 --> 03:28:48,916
So, we can ask for
spontaneous pain,

4287
03:28:48,916 --> 03:28:50,985
but we also can look
at evoked pain.

4288
03:28:50,985 --> 03:28:53,855
So, we use stimuli,
pressure pain,

4289
03:28:53,855 --> 03:28:57,024
or heat pain here
through an algometer.

4290
03:28:57,558 --> 03:29:00,228
And what we do see here,
this is now sex differences.

4291
03:29:00,228 --> 03:29:03,664
So, pressure pain thresholds
in general go down,

4292
03:29:03,664 --> 03:29:05,700
but here it's only in females.

4293
03:29:05,700 --> 03:29:08,703
And then when we look
at heat pain,

4294
03:29:09,771 --> 03:29:12,607
it's only affected in males.

4295
03:29:12,607 --> 03:29:15,343
So, the point that I
wanted to make here

4296
03:29:15,343 --> 03:29:16,711
is that we always have,

4297
03:29:16,711 --> 03:29:20,047
if we want to find
better mechanisms,

4298
03:29:20,681 --> 03:29:24,051
better therapeutics,
more precise therapeutics,

4299
03:29:24,051 --> 03:29:27,221
I think we always have to
take into account

4300
03:29:27,221 --> 03:29:29,457
that there might be
sex differential effects.

4301
03:29:29,991 --> 03:29:31,292
So, and, of course,

4302
03:29:31,292 --> 03:29:33,861
we also see this
in insomnia disorder, right?

4303
03:29:33,861 --> 03:29:38,733
This is a very young group
of people with insomnia disorder

4304
03:29:38,733 --> 03:29:41,269
that have not yet developed pain

4305
03:29:41,269 --> 03:29:45,373
or are not comorbid with any
disorders, not on medications.

4306
03:29:45,373 --> 03:29:48,943
And even here you can see
there's higher pain frequency,

4307
03:29:48,943 --> 03:29:51,379
and there's much
lower pain thresholds.

4308
03:29:53,381 --> 03:29:56,117
So, there's good evidence
that insomnia itself

4309
03:29:56,117 --> 03:29:57,718
can increase symptom burden,

4310
03:29:58,820 --> 03:30:01,389
and it might be stronger
in females than in males.

4311
03:30:01,389 --> 03:30:07,361
But what are the mechanisms and
potential mechanistic pathways?

4312
03:30:07,361 --> 03:30:15,236
So, what I would like to show
you is the various systems

4313
03:30:15,236 --> 03:30:18,372
and mediators that have
analgesic properties

4314
03:30:18,372 --> 03:30:21,075
on the very left,
hybrid properties --

4315
03:30:21,075 --> 03:30:23,544
analgesic as well
as hyperalgesic --

4316
03:30:23,544 --> 03:30:26,013
as well as hyperalgesic
properties.

4317
03:30:26,013 --> 03:30:28,349
And the point
that I want to make here

4318
03:30:28,349 --> 03:30:31,352
is that all these systems
are affected by sleep.

4319
03:30:32,887 --> 03:30:34,489
For example, opioid system.

4320
03:30:35,189 --> 03:30:38,626
Opioid system in a
sleep-disturbed person,

4321
03:30:38,626 --> 03:30:42,163
the responsivity to
exogenous opioids is reduced,

4322
03:30:42,163 --> 03:30:45,533
meaning they need
more opioid consumption.

4323
03:30:48,736 --> 03:30:50,938
Melatonin has
analgesic properties,

4324
03:30:50,938 --> 03:30:53,708
and it also has
sleep-promoting properties.

4325
03:30:53,708 --> 03:30:56,010
So, there's lots of
studies -- not lots,

4326
03:30:56,010 --> 03:30:58,446
but there are more
and more studies out there --

4327
03:30:58,446 --> 03:31:01,249
really looking at
whether through melatonin

4328
03:31:01,249 --> 03:31:03,951
we really can target
this association

4329
03:31:03,951 --> 03:31:05,920
between insomnia and pain.

4330
03:31:05,920 --> 03:31:07,955
And, of course,
the immune system

4331
03:31:07,955 --> 03:31:09,891
probably has been best studied.

4332
03:31:09,891 --> 03:31:14,061
There's a clear upregulation
of pro-inflammatory mediators,

4333
03:31:14,061 --> 03:31:15,663
as well as prostaglandins.

4334
03:31:16,464 --> 03:31:18,633
And I would like to talk
a little bit more

4335
03:31:18,633 --> 03:31:20,434
about two
promising mechanisms,

4336
03:31:20,434 --> 03:31:23,671
and that's central pain
modulation and inflammation.

4337
03:31:24,705 --> 03:31:27,642
So, central pain
modulation has been --

4338
03:31:28,676 --> 03:31:31,546
these two mechanisms have been
probably best studied

4339
03:31:31,546 --> 03:31:34,282
in the context of insomnia
and sleep disturbances.

4340
03:31:35,116 --> 03:31:37,585
So, central pain
modulation, basically,

4341
03:31:37,585 --> 03:31:39,954
there is a network
of cortical structures

4342
03:31:40,788 --> 03:31:44,125
that project to
the dorsal horn

4343
03:31:44,125 --> 03:31:49,263
where a sensation can be
inhibited or facilitated

4344
03:31:49,263 --> 03:31:51,032
before it reaches
consciousness.

4345
03:31:52,266 --> 03:31:57,438
So, it has been shown
that these descending pathways

4346
03:31:57,438 --> 03:32:00,441
are dysregulated in many
chronic pain conditions.

4347
03:32:00,441 --> 03:32:02,143
And they are involved
in the transition

4348
03:32:02,143 --> 03:32:04,178
from acute to chronic pain.

4349
03:32:04,178 --> 03:32:07,281
And when we look at the effects
of sleep disturbances,

4350
03:32:07,281 --> 03:32:09,784
there are less effective
pain inhibitory circuits,

4351
03:32:10,918 --> 03:32:12,520
in particular in women,

4352
03:32:12,520 --> 03:32:15,623
and more active pain
facilitatory circuits.

4353
03:32:16,123 --> 03:32:17,959
And then we also have
inflammation.

4354
03:32:17,959 --> 03:32:23,364
As I just mentioned, there's
various inflammatory markers

4355
03:32:23,364 --> 03:32:26,601
that are released
in sleep-disturbed people

4356
03:32:26,601 --> 03:32:30,938
that are able to sensitize
peripheral nociceptors,

4357
03:32:30,938 --> 03:32:34,041
as well as central
pain transmission neurons,

4358
03:32:34,041 --> 03:32:37,011
and then lead to
an exaggerated pain response.

4359
03:32:39,046 --> 03:32:42,683
And these include, basically,
all kinds of pro-

4360
03:32:42,683 --> 03:32:45,086
and counter-inflammatory
pathways:

4361
03:32:45,086 --> 03:32:48,022
NF-kappa B pathway with
a production of cytokines,

4362
03:32:48,856 --> 03:32:50,591
cyclooxygenase pathway,

4363
03:32:51,158 --> 03:32:53,361
hypothalamus-pituitary-adrenal
axis

4364
03:32:53,361 --> 03:32:55,663
with a factor hormone cortisol,

4365
03:32:55,663 --> 03:32:58,332
and also the so-called --
that's pretty new --

4366
03:32:58,332 --> 03:33:01,936
the so-called specialized
pro-resolving mediators.

4367
03:33:02,870 --> 03:33:05,273
That there's very little
human research out there.

4368
03:33:05,273 --> 03:33:08,175
They are derived
from omega-3 fatty acids.

4369
03:33:08,175 --> 03:33:11,112
But they have shown
in pre-clinical animal models

4370
03:33:11,112 --> 03:33:15,016
that they have
high energetic efficacy

4371
03:33:15,016 --> 03:33:16,417
in various clinical models.

4372
03:33:16,417 --> 03:33:18,152
But we are not there
yet in humans.

4373
03:33:18,152 --> 03:33:23,190
So, okay, and, of course,

4374
03:33:23,190 --> 03:33:24,925
there is, like,
there are interactions

4375
03:33:24,925 --> 03:33:29,397
of these inflammatory
and neuronal pain pathways.

4376
03:33:29,397 --> 03:33:32,900
But they also determine
what kind of pain we then have:

4377
03:33:32,900 --> 03:33:35,903
nociplastic type of pain
that's more regulated to --

4378
03:33:36,671 --> 03:33:41,575
that's more associated
with the processing of pain --

4379
03:33:41,575 --> 03:33:43,944
or more nociceptive
type of pain.

4380
03:33:43,944 --> 03:33:46,514
That then also can,
if we know this,

4381
03:33:47,248 --> 03:33:51,719
that can inform
treatment decisions.

4382
03:33:51,719 --> 03:33:54,055
So, how do we break
the perpetuating cycle

4383
03:33:54,055 --> 03:33:56,057
between sleep
and disturbances and pain?

4384
03:33:56,057 --> 03:33:58,926
Of course, we can target
mechanisms such as inflammation.

4385
03:33:59,960 --> 03:34:02,396
There's very little data
out there

4386
03:34:02,396 --> 03:34:06,300
that really looked at insomnia
and pain in parallel.

4387
03:34:06,300 --> 03:34:07,935
We can target pain through
NSAIDs,

4388
03:34:07,935 --> 03:34:09,670
corticosteroids, opioids.

4389
03:34:10,371 --> 03:34:14,341
But here, we'd like to more
focus on, can we target sleep?

4390
03:34:14,341 --> 03:34:19,413
And if we target sleep,
can we improve pain?

4391
03:34:19,413 --> 03:34:21,982
There are various
pharmacological approaches --

4392
03:34:21,982 --> 03:34:23,918
non-benzodiazepine approaches
that,

4393
03:34:23,918 --> 03:34:26,620
in general,
have a better safety profile,

4394
03:34:26,620 --> 03:34:29,990
less dependency than compared
to benzodiazepines.

4395
03:34:30,558 --> 03:34:34,395
There are orexin receptor
antagonists, melatonin,

4396
03:34:34,395 --> 03:34:42,803
as I said, has both analgesic
and sleep-promoting properties.

4397
03:34:42,803 --> 03:34:44,171
And also cannabinoids.

4398
03:34:44,171 --> 03:34:47,408
And I think we hear
later more on cannabinoids.

4399
03:34:47,408 --> 03:34:49,744
What I would like to focus
on a little bit

4400
03:34:49,744 --> 03:34:52,079
is non-pharmacological
approaches,

4401
03:34:52,079 --> 03:34:54,014
cognitive behavioral
therapy for insomnia,

4402
03:34:54,014 --> 03:34:58,052
or hybrid therapies that target
both insomnia and pain.

4403
03:34:59,086 --> 03:35:02,056
And then what's also coming
more and more

4404
03:35:02,056 --> 03:35:04,492
is integrative
mind-body therapies,

4405
03:35:04,492 --> 03:35:06,761
such as mindful movement,
yoga, tai chi,

4406
03:35:06,761 --> 03:35:09,230
qigong, that just have --

4407
03:35:09,230 --> 03:35:11,699
they have a lot of these
non-behavioral therapies

4408
03:35:11,699 --> 03:35:14,902
have a lot of acceptance
because they have a very,

4409
03:35:14,902 --> 03:35:17,404
you know, they just come
with less side effects.

4410
03:35:18,105 --> 03:35:21,876
So, does treatment of insomnia
with CBT-I improve chronic pain?

4411
03:35:22,510 --> 03:35:24,378
Cognitive behavioral
therapy for insomnia

4412
03:35:24,378 --> 03:35:26,881
is the first line
of treatment for insomnia,

4413
03:35:26,881 --> 03:35:28,849
and it outperforms
pharmacotherapy

4414
03:35:28,849 --> 03:35:30,785
because it has
longer-lasting effects.

4415
03:35:31,385 --> 03:35:32,787
And then there are different --

4416
03:35:32,787 --> 03:35:36,557
so, the traditional delivery
method is face-to-face,

4417
03:35:36,557 --> 03:35:40,561
but there's now many
digital apps, such as Sleepio,

4418
03:35:40,561 --> 03:35:42,763
ShutEye,
or CBT-I Coach,

4419
03:35:42,763 --> 03:35:45,699
that have been validated
in clinical trials.

4420
03:35:45,699 --> 03:35:48,602
And it has various components
that I will not go into it.

4421
03:35:48,602 --> 03:35:52,606
It's sleep hygiene --
so, avoiding screen time

4422
03:35:52,606 --> 03:35:55,242
before bedtime,
stimulus control.

4423
03:35:55,242 --> 03:35:56,911
There are sleep
restriction components

4424
03:35:56,911 --> 03:35:59,313
to increase sleep efficiency
at night.

4425
03:36:00,080 --> 03:36:03,384
They have relaxation components,
and also cognitive components,

4426
03:36:03,384 --> 03:36:07,054
such as restructuring
of undesired thinking patterns.

4427
03:36:08,722 --> 03:36:11,659
So, this was the title
of an editorial,

4428
03:36:11,659 --> 03:36:13,260
is Cognitive Behavioral Therapy

4429
03:36:13,260 --> 03:36:15,629
for Insomnia
the New Best Painkiller?

4430
03:36:15,629 --> 03:36:20,401
And that was an editorial
on a study on a meta-analysis

4431
03:36:20,401 --> 03:36:23,337
of 14 high-quality randomized
clinical trials

4432
03:36:24,872 --> 03:36:28,108
in people comorbid with insomnia
and chronic pain:

4433
03:36:28,108 --> 03:36:30,644
fibromyalgia, osteoarthritis,
shoulder pain,

4434
03:36:30,644 --> 03:36:32,479
back pain,
and other pains.

4435
03:36:32,479 --> 03:36:37,351
And they showed that there is a
significantly higher probability

4436
03:36:37,351 --> 03:36:39,420
of having better sleep
at post-treatment

4437
03:36:39,420 --> 03:36:41,021
as well as at follow-up.

4438
03:36:41,956 --> 03:36:45,426
When we then look at pain,
when we compare baseline pain

4439
03:36:45,426 --> 03:36:48,929
with post-treatment,
58 percent probability

4440
03:36:48,929 --> 03:36:50,865
of having less pain
at post-treatment.

4441
03:36:50,865 --> 03:36:52,933
But then, when we look
at follow-up,

4442
03:36:52,933 --> 03:36:54,568
this is not significant
anymore.

4443
03:36:55,469 --> 03:36:59,440
So, this also shows
that we probably need --

4444
03:37:00,674 --> 03:37:04,144
for targeting chronic pain
comorbid with insomnia --

4445
03:37:04,144 --> 03:37:07,648
we need combination therapies.
And I also would like --

4446
03:37:07,648 --> 03:37:09,984
sleep intervention
has been frequently studied

4447
03:37:11,118 --> 03:37:14,655
in the context of surgery,
because post-operative pain

4448
03:37:14,655 --> 03:37:16,523
is such a major
healthcare challenge

4449
03:37:17,191 --> 03:37:21,328
that remains under-managed.
And also, what we can see here,

4450
03:37:21,328 --> 03:37:24,398
they actually used
pharmacological interventions,

4451
03:37:24,398 --> 03:37:26,667
and we see that with
the improvement in sleep,

4452
03:37:26,667 --> 03:37:28,702
we have a reduction in pain

4453
03:37:28,702 --> 03:37:32,740
and also decrease
in the amount of analgesic drugs

4454
03:37:34,174 --> 03:37:35,910
in these surgery patients.

4455
03:37:38,445 --> 03:37:39,980
So, what are the clinical
implications?

4456
03:37:39,980 --> 03:37:42,449
You might think,
why did I not present anything

4457
03:37:42,449 --> 03:37:44,785
on interventions
in sickle cell disease?

4458
03:37:46,253 --> 03:37:48,455
There are no studies
out there yet.

4459
03:37:49,757 --> 03:37:51,959
Unless -- I don't --
I think there is, like,

4460
03:37:52,726 --> 03:37:55,663
there's great awareness
of the importance,

4461
03:37:55,663 --> 03:37:57,898
but so far --
and I hope this will come soon.

4462
03:37:58,666 --> 03:38:00,968
So, what are
the clinical implications

4463
03:38:00,968 --> 03:38:03,337
in this perpetuating
relationship

4464
03:38:03,337 --> 03:38:05,439
between insomnia and pain?

4465
03:38:05,439 --> 03:38:08,108
And one, of course, is
monitoring sleep health through,

4466
03:38:08,108 --> 03:38:10,878
you know, it's pretty easy --
to wearable devices

4467
03:38:10,878 --> 03:38:13,881
that often give feedback
on sleep-wake patterns.

4468
03:38:13,881 --> 03:38:16,417
And it's important
to promote sleep health

4469
03:38:16,417 --> 03:38:19,853
early on through behavioral and/
or pharmacological interventions

4470
03:38:19,853 --> 03:38:23,958
or combinations of interventions
to protect from pain development

4471
03:38:23,958 --> 03:38:25,859
and better manage pain.

4472
03:38:25,859 --> 03:38:27,895
And that's not also
true for pain.

4473
03:38:27,895 --> 03:38:31,198
That is also true
for many other health outcomes.

4474
03:38:32,533 --> 03:38:35,869
And I think what I also
would like to say

4475
03:38:35,869 --> 03:38:40,841
is that sleep problems
have often treatment priority

4476
03:38:40,841 --> 03:38:44,345
in individuals
with chronic pain.

4477
03:38:44,345 --> 03:38:50,718
So, they are much more
determine quality of life

4478
03:38:50,718 --> 03:38:52,453
than other aspects of pain.

4479
03:38:52,453 --> 03:38:55,356
Of course, healthcare providers
may screen for insomnia symptoms

4480
03:38:55,356 --> 03:38:58,392
in pain clinics
on a regular basis.

4481
03:38:58,392 --> 03:39:01,161
We have to be careful with
sleep-disturbing medications

4482
03:39:01,161 --> 03:39:03,163
and analgesics
such as opioids.

4483
03:39:03,163 --> 03:39:06,667
They can, by itself,
form like a vicious cycle.

4484
03:39:08,268 --> 03:39:12,206
And I didn't talk about this --
considering timing of medication

4485
03:39:12,206 --> 03:39:14,041
to minimize
sleep-disturbing effects,

4486
03:39:14,608 --> 03:39:18,445
considering sex to really have
more precise

4487
03:39:18,445 --> 03:39:21,048
intervention methods,
better understand mechanisms

4488
03:39:21,782 --> 03:39:24,551
that link insomnia
and chronic pain --

4489
03:39:25,386 --> 03:39:28,922
that would then be the basis
to really develop more novel

4490
03:39:28,922 --> 03:39:30,190
and more targeted

4491
03:39:30,190 --> 03:39:32,626
and personalized
therapeutic targets.

4492
03:39:33,260 --> 03:39:35,529
So, thank you very much
for listening.

4493
03:39:35,529 --> 03:39:37,164
I'm still in time.

4494
03:39:37,164 --> 03:39:42,736
[applause]

4495
03:39:42,736 --> 03:39:44,204
We have questions now.

4496
03:39:44,204 --> 03:39:45,439
Male Speaker: Yes.

4497
03:39:45,439 --> 03:39:47,641
So, thank you very much
for that great talk.

4498
03:39:48,308 --> 03:39:50,944
Welcoming questions.
Five minutes of questions.

4499
03:39:53,113 --> 03:39:54,748
Male Speaker: So, thank you.
That was really interesting.

4500
03:39:54,748 --> 03:39:57,718
I'm wondering if you could
unpack the recommendation

4501
03:39:57,718 --> 03:40:02,456
about screen time
and sleep hygiene.

4502
03:40:02,456 --> 03:40:05,859
So, it's a recommendation
that we make all the time,

4503
03:40:05,859 --> 03:40:07,828
but a lot of patients
will tell you,

4504
03:40:07,828 --> 03:40:10,130
you know, I like to read
before I sleep.

4505
03:40:10,130 --> 03:40:11,432
So, I read on my screen.

4506
03:40:11,432 --> 03:40:16,070
I don't recall us recommending
decreasing book time

4507
03:40:16,070 --> 03:40:18,072
before there were screens.

4508
03:40:18,072 --> 03:40:20,574
So, is there a way
to unpack that?

4509
03:40:21,208 --> 03:40:24,945
Is there a healthy way to use
your screen to help you sleep?

4510
03:40:24,945 --> 03:40:28,248
Because many patients do use
their screen to help them sleep.

4511
03:40:28,882 --> 03:40:31,919
Monica Hack: So, there is,
I think, one option is to have,

4512
03:40:31,919 --> 03:40:37,925
I think many phones and many
screens have filters, right?

4513
03:40:37,925 --> 03:40:41,395
So, you filter out blue light
and other wavelengths

4514
03:40:42,062 --> 03:40:44,364
that will help you to not,

4515
03:40:45,499 --> 03:40:48,635
to keep circadian rhythms
in place.

4516
03:40:48,635 --> 03:40:51,171
So, that would be one option.
But I completely agree.

4517
03:40:51,171 --> 03:40:54,508
It's not -- it's not --
because this is also

4518
03:40:54,508 --> 03:40:57,044
for many people
a relaxation method, right?

4519
03:40:57,044 --> 03:41:01,048
So, they, before they go to bed,
they just read for 30 minutes

4520
03:41:01,048 --> 03:41:03,417
or watch a relaxing show
or something.

4521
03:41:04,118 --> 03:41:06,053
But that's probably
the best option that's out now.

4522
03:41:06,053 --> 03:41:07,254
Male Speaker: [inaudible]

4523
03:41:07,254 --> 03:41:08,856
Monica Hack: And.
Yeah.

4524
03:41:09,423 --> 03:41:13,794
Yes. That has been shown.
If you really reduce, use those.

4525
03:41:13,794 --> 03:41:16,296
That has been shown to,
you know,

4526
03:41:16,296 --> 03:41:19,666
to less interfere
with circadian rhythmicity.

4527
03:41:24,104 --> 03:41:26,874
Female Speaker: Hi.
Thank you so much for your talk.

4528
03:41:26,874 --> 03:41:28,475
I was wondering
if you could give us

4529
03:41:28,475 --> 03:41:31,879
a little more of the background
of the participants of the study

4530
03:41:31,879 --> 03:41:33,447
that you mentioned
that were on

4531
03:41:33,447 --> 03:41:35,682
for 19 days
with disrupted sleep.

4532
03:41:36,216 --> 03:41:39,186
We're very curious in learning,
at least for me,

4533
03:41:39,186 --> 03:41:41,655
if any of these patients
had sickle cell disease.

4534
03:41:41,655 --> 03:41:45,092
We saw that they were
distributed female and male,

4535
03:41:46,059 --> 03:41:47,494
but a little bit more
of the background

4536
03:41:47,494 --> 03:41:48,695
and how they were enrolled.

4537
03:41:48,695 --> 03:41:50,831
And the second aspect
of my question,

4538
03:41:50,831 --> 03:41:53,800
since we don't have studies
in sickle cell related to sleep,

4539
03:41:55,035 --> 03:41:56,870
do you have any --

4540
03:41:56,870 --> 03:41:58,505
there's so many things
that we can study --

4541
03:41:58,505 --> 03:42:00,374
but is there anything that,
in particular,

4542
03:42:00,374 --> 03:42:02,809
interests you that
we could start looking at?

4543
03:42:03,810 --> 03:42:07,447
Monica Hack: So, with respect
to the study that I showed

4544
03:42:07,447 --> 03:42:10,751
on these experimental
in-laboratory designs,

4545
03:42:10,751 --> 03:42:13,720
these are healthy individuals.
They're healthy individuals.

4546
03:42:13,720 --> 03:42:16,990
And the reason for that
is to really understand --

4547
03:42:17,658 --> 03:42:19,693
you start with
a healthy individual

4548
03:42:19,693 --> 03:42:22,396
to see what sleep
disturbances in itself

4549
03:42:22,396 --> 03:42:25,032
are doing without
the confounding effects.

4550
03:42:25,666 --> 03:42:27,768
You know, that's now --
that's getting complicated.

4551
03:42:27,768 --> 03:42:30,571
If you have real patient,
you have medications,

4552
03:42:30,571 --> 03:42:32,439
you have so many
other comorbidities,

4553
03:42:32,973 --> 03:42:35,542
you need a huge sample size
to really figure out

4554
03:42:35,542 --> 03:42:37,177
what's the contribution
of sleep.

4555
03:42:37,177 --> 03:42:38,512
So that's the reason.

4556
03:42:38,512 --> 03:42:41,648
But of course, there is very
limited generalizability, right?

4557
03:42:41,648 --> 03:42:44,651
I mean, you know, okay, sleep
is doing this in this context,

4558
03:42:45,652 --> 03:42:47,721
but now it really
needs to go out.

4559
03:42:47,721 --> 03:42:51,658
What do we actually see
in much more complex people

4560
03:42:51,658 --> 03:42:53,961
who are sick, right?
What can we do?

4561
03:42:54,962 --> 03:42:56,897
So, with respect to sickle cell,

4562
03:42:56,897 --> 03:43:00,067
I think I'm not aware that
there are currently any studies

4563
03:43:00,968 --> 03:43:05,739
on any kind of CBTI treatment.

4564
03:43:06,707 --> 03:43:08,709
I think what would be
important to really --

4565
03:43:08,709 --> 03:43:13,447
and I think there's also
very limited literature I found

4566
03:43:13,447 --> 03:43:16,750
on what kind of sleep disorders
are actually prevalent.

4567
03:43:16,750 --> 03:43:19,253
I mean, everybody,
there is a lot

4568
03:43:19,253 --> 03:43:23,423
on sleep-disordered breathing;
there's much known there.

4569
03:43:24,024 --> 03:43:28,195
But on insomnia,
what kind of insomnia there is,

4570
03:43:28,195 --> 03:43:33,367
how many are actually affected,
who fulfill insomnia disorder --

4571
03:43:33,367 --> 03:43:36,036
I think there needs to be
more base research out there

4572
03:43:36,036 --> 03:43:39,873
before we can really then target
and design therapies

4573
03:43:39,873 --> 03:43:42,376
that might be not
just CBTI, that.

4574
03:43:42,376 --> 03:43:44,811
I think there's a lot
of combination therapies out now

4575
03:43:44,811 --> 03:43:47,614
with CBTI plus light,
plus pharmacotherapy,

4576
03:43:47,614 --> 03:43:50,951
plus melatonin
that can be very effective,

4577
03:43:50,951 --> 03:43:53,620
but I think we need to know
what's actually there.

4578
03:43:53,620 --> 03:43:55,222
And I think there are still --

4579
03:43:56,056 --> 03:43:59,359
I hope this research will come,
and maybe I can help with that.

4580
03:44:00,060 --> 03:44:01,628
Monica Hack: Thank you.

4581
03:44:01,628 --> 03:44:07,401
[applause]

4582
03:44:07,401 --> 03:44:08,802
Male Speaker: All right,
thank you again

4583
03:44:08,802 --> 03:44:10,570
for that great talk.

4584
03:44:10,570 --> 03:44:14,708
So, our second presentation
is on Pain,

4585
03:44:14,708 --> 03:44:19,880
Many Mechanisms, and Mysteries,
and it is by Dr. Cheryl Stucky.

4586
03:44:20,614 --> 03:44:24,751
So, Dr. Stucky is the director
of the Pain Division

4587
03:44:24,751 --> 03:44:26,687
of the Neuroscience
Research Center

4588
03:44:27,220 --> 03:44:29,823
at the Medical College
of Wisconsin.

4589
03:44:40,467 --> 03:44:42,102
Cheryl Stucky: All right,
thank you so much

4590
03:44:42,102 --> 03:44:45,405
for that very kind introduction.
I really appreciate it.

4591
03:44:45,405 --> 03:44:48,208
Yeah, and you even said
my last name right.

4592
03:44:48,208 --> 03:44:51,845
Stucky rhymes with cookie
in my case. Good job.

4593
03:44:52,446 --> 03:44:55,882
Yeah, so it's a real
pleasure to be here.

4594
03:44:55,882 --> 03:44:57,718
I'm from beautiful Milwaukee.

4595
03:44:57,718 --> 03:45:00,620
It's not quite as warm as here,
but it's lovely.

4596
03:45:01,688 --> 03:45:05,659
And I'm here to talk about pain
in sickle cell disease.

4597
03:45:06,560 --> 03:45:11,064
So this, I feel like,
is a really cool --

4598
03:45:11,064 --> 03:45:13,433
does this work, this pointer?

4599
03:45:13,433 --> 03:45:18,672
There we go. It won't work.
Sorry, does it work?

4600
03:45:18,672 --> 03:45:20,240
Male Speaker: So this is
to change the slides,

4601
03:45:20,240 --> 03:45:21,508
but you can use the pointer.

4602
03:45:21,508 --> 03:45:22,776
Cheryl Stucky: This is to
change the slides?

4603
03:45:22,776 --> 03:45:24,010
Oh.

4604
03:45:24,010 --> 03:45:25,445
Male Speaker: The red button
goes backwards.

4605
03:45:25,445 --> 03:45:27,047
Cheryl Stucky: Oh, very good.
Okay, great.

4606
03:45:28,615 --> 03:45:30,884
All right,
so this is a painting.

4607
03:45:30,884 --> 03:45:34,688
Have you seen this before?
Yes. Who is it by?

4608
03:45:35,655 --> 03:45:39,726
It's Hertz Nazaire.
It's a self-portrait of himself

4609
03:45:39,726 --> 03:45:44,798
when he is
in a acute pain episode.

4610
03:45:45,599 --> 03:45:48,935
And it is called 10 Redefined,

4611
03:45:48,935 --> 03:45:51,271
because on a scale
of zero to 10,

4612
03:45:51,972 --> 03:45:54,641
with 10 being the worst pain
that you ever feel,

4613
03:45:55,208 --> 03:45:57,844
it's worse than that.
And you can see.

4614
03:45:58,445 --> 03:46:00,547
Unfortunately, Dr. --
or Mr. --

4615
03:46:00,547 --> 03:46:02,749
Nazaire passed away
about three years ago

4616
03:46:02,749 --> 03:46:05,685
from complications
of sickle cell disease

4617
03:46:05,685 --> 03:46:08,488
at the age of 48.

4618
03:46:10,924 --> 03:46:12,993
Okay, there we go.

4619
03:46:12,993 --> 03:46:15,529
So, as you know,
sickled red blood cells are --

4620
03:46:16,897 --> 03:46:19,566
when they sickle,
they cause vaso-occlusion.

4621
03:46:20,367 --> 03:46:24,004
That occurs when the hemoglobin
molecules form polymers

4622
03:46:24,004 --> 03:46:25,605
when they're deoxygenated.

4623
03:46:26,673 --> 03:46:31,311
And sickle hemoglobin,
this causes vaso-occlusion,

4624
03:46:31,311 --> 03:46:35,515
repeat tissue ischemia,
and reperfusion injury.

4625
03:46:36,516 --> 03:46:40,654
This also leads to a shortened
red blood cell lifespan,

4626
03:46:40,654 --> 03:46:41,922
shortened survival.

4627
03:46:41,922 --> 03:46:44,191
They lyse their contents
into the blood,

4628
03:46:44,191 --> 03:46:49,095
dumping heme and other kinds
of things into the bloodstream.

4629
03:46:49,095 --> 03:46:54,701
And there's also chronic
microvascular inflammation.

4630
03:46:57,037 --> 03:47:01,575
And a huge hallmark,
let us be clear,

4631
03:47:02,242 --> 03:47:06,246
is the acute
and the chronic pain.

4632
03:47:06,246 --> 03:47:11,852
It is horrible, and it plagues
patients for their entire lives.

4633
03:47:12,786 --> 03:47:19,426
So, this is a painting by artist
Ellen Weinstein.

4634
03:47:19,426 --> 03:47:20,627
It's The Sickle Boy.

4635
03:47:20,627 --> 03:47:24,531
And this is how one patient
describes how he feels,

4636
03:47:24,531 --> 03:47:28,301
with the snakes coming out
of his body all over.

4637
03:47:28,869 --> 03:47:30,804
And when you ask a patient,

4638
03:47:30,804 --> 03:47:33,139
"How do you describe
your sickle pain?"

4639
03:47:34,307 --> 03:47:35,909
What do they say?

4640
03:47:36,676 --> 03:47:39,813
"I feel like knives are
stabbing me from the inside.

4641
03:47:40,780 --> 03:47:44,150
I feel a radiating
deep pain from inside.

4642
03:47:44,985 --> 03:47:47,120
I feel like my bones
are breaking.

4643
03:47:47,754 --> 03:47:51,258
I feel like there's broken glass
flowing through my veins.

4644
03:47:51,925 --> 03:47:53,393
And I feel like
a heart attack

4645
03:47:53,393 --> 03:47:55,262
is happening through
my entire body."

4646
03:47:57,797 --> 03:48:02,269
So, with sickle pain,
we have acute episodic pain

4647
03:48:02,269 --> 03:48:09,843
that is triggered by cold,
stress, exercise, illness.

4648
03:48:09,843 --> 03:48:12,779
So what can these kids do?
What can these people do?

4649
03:48:12,779 --> 03:48:15,815
Not a lot of normal things
that other people do.

4650
03:48:16,316 --> 03:48:19,419
Can't go swimming.
Can't stand in the cold.

4651
03:48:19,419 --> 03:48:20,820
You can't really exercise.

4652
03:48:20,820 --> 03:48:22,622
You can't do what
the other kids do.

4653
03:48:23,757 --> 03:48:25,492
Many of them also
have chronic pain.

4654
03:48:25,492 --> 03:48:27,160
In fact, about 40
to 50 percent

4655
03:48:27,160 --> 03:48:30,764
of these patients ultimately
suffer from chronic pain,

4656
03:48:31,464 --> 03:48:35,969
perhaps after these repeated
vaso-occlusive events

4657
03:48:35,969 --> 03:48:39,806
that prime the nervous and other
systems to have chronic pain.

4658
03:48:40,440 --> 03:48:43,910
Then there's acute pain
on top of the chronic pain.

4659
03:48:45,145 --> 03:48:47,080
Now we know --
and we'll hear more

4660
03:48:47,080 --> 03:48:50,250
about this next
from Dr. Darberry [phonetic sp]

4661
03:48:50,250 --> 03:48:52,986
-- opioids are still
the first line of treatments

4662
03:48:52,986 --> 03:48:56,523
for especially the acute pain
because they do work.

4663
03:48:57,357 --> 03:49:02,395
But we all know they have a host
of unpleasant side effects.

4664
03:49:03,496 --> 03:49:06,433
They cause dependence.

4665
03:49:06,433 --> 03:49:08,768
And for many patients,
unfortunately,

4666
03:49:08,768 --> 03:49:11,171
because opioids
are the only thing

4667
03:49:11,171 --> 03:49:13,873
maybe that works in their case
for acute pain,

4668
03:49:13,873 --> 03:49:16,443
when they go to the emergency
room in the hospital,

4669
03:49:16,443 --> 03:49:19,713
they're thought of sometimes
as -- or maybe often --

4670
03:49:19,713 --> 03:49:22,916
as drug seekers.
That's really unfortunate.

4671
03:49:24,651 --> 03:49:27,554
So, we've been studying
sickle cell pain

4672
03:49:27,554 --> 03:49:29,789
from the mouse perspective.

4673
03:49:29,789 --> 03:49:32,759
And I'm so delighted
that Manu has opened us up

4674
03:49:32,759 --> 03:49:35,662
with describing what
these mouse models are like.

4675
03:49:35,662 --> 03:49:38,131
We use both the Townes model
that he described

4676
03:49:38,131 --> 03:49:39,933
and also the Berkeley
mouse model.

4677
03:49:39,933 --> 03:49:41,768
They're a little different
in their genetics.

4678
03:49:41,768 --> 03:49:43,336
I won't get into that.

4679
03:49:43,336 --> 03:49:45,005
But we've been using
the Townes model

4680
03:49:45,005 --> 03:49:46,539
because we think
it's a little better

4681
03:49:46,539 --> 03:49:51,444
for actually recapitulating what
actually happens in a patient.

4682
03:49:51,444 --> 03:49:54,714
So, how do these mice
recapitulate what happens

4683
03:49:54,714 --> 03:49:56,316
in a patient?
Do they?

4684
03:49:57,484 --> 03:50:00,420
So, the patients
have sickled red cells.

4685
03:50:00,420 --> 03:50:03,523
The mice do as well.
Patients have vaso-occlusion.

4686
03:50:03,523 --> 03:50:04,791
So do the mice.

4687
03:50:04,791 --> 03:50:07,293
Patients have anemia,
as do the mice.

4688
03:50:07,293 --> 03:50:09,229
Patients have
severe organ damage.

4689
03:50:09,229 --> 03:50:11,131
So do the mice.

4690
03:50:11,131 --> 03:50:14,434
But do they have
chronic touch-evoked pain?

4691
03:50:14,434 --> 03:50:16,169
Do they have cold pain?

4692
03:50:16,169 --> 03:50:18,672
Do they have
vaso-occlusive pain?

4693
03:50:18,672 --> 03:50:20,674
Do they have spontaneous pain?

4694
03:50:20,674 --> 03:50:23,610
So, these are all questions
that my lab and others,

4695
03:50:23,610 --> 03:50:26,713
like Kalpana Gupta's lab,
have been asking.

4696
03:50:29,215 --> 03:50:32,018
So, we know that about
40 percent of patients

4697
03:50:32,018 --> 03:50:33,453
with sickle cell disease

4698
03:50:33,453 --> 03:50:36,523
experience
chronic touch-evoked pain.

4699
03:50:36,523 --> 03:50:39,092
Touch-evoked pain
all over their body.

4700
03:50:39,092 --> 03:50:40,794
So, we started by asking, well,

4701
03:50:40,794 --> 03:50:43,496
do the mice experience
touch-evoked pain?

4702
03:50:44,698 --> 03:50:47,367
Here, what we did
is we put the mice

4703
03:50:47,367 --> 03:50:51,137
on a platform where we could --

4704
03:50:51,137 --> 03:50:52,872
and a plexiglass box
over them --

4705
03:50:52,872 --> 03:50:55,408
and we can poke the bottom
of the animal's paw

4706
03:50:55,408 --> 03:50:57,010
with a von Frey filament.

4707
03:50:57,010 --> 03:51:00,547
Those of you that are MDs
or serve

4708
03:51:00,547 --> 03:51:03,183
in a neurology clinic know
what a von Frey filament is.

4709
03:51:03,183 --> 03:51:07,721
It's used for touching or
determining thresholds for pain.

4710
03:51:08,588 --> 03:51:12,492
And when you do this,
in this case,

4711
03:51:12,492 --> 03:51:14,461
and you test the animal's
bottom of the paw,

4712
03:51:14,461 --> 03:51:17,230
each filament bends
at a certain force.

4713
03:51:17,230 --> 03:51:23,369
And you can see that over here
-- paw withdrawal thresholds.

4714
03:51:23,369 --> 03:51:28,341
So, the lower the threshold,
the more sensitive they are.

4715
03:51:28,341 --> 03:51:31,411
The higher the threshold,
the less sensitive they are.

4716
03:51:31,411 --> 03:51:35,815
So, compared to controls,
sickle animals are chronically

4717
03:51:35,815 --> 03:51:38,985
very, very sensitive
to mechanical stimuli.

4718
03:51:41,688 --> 03:51:45,158
We see the same thing
if we poke the bottom animal,

4719
03:51:45,158 --> 03:51:47,427
the bottom of the animal's paw
with a needle --

4720
03:51:47,427 --> 03:51:52,298
a frankly noxious needle poke.
So, in this case,

4721
03:51:52,298 --> 03:51:55,935
the animals have more responses
to the needle stick.

4722
03:51:55,935 --> 03:51:58,404
The sickle animals
chronically do.

4723
03:51:58,404 --> 03:52:01,374
And if we just swipe
the bottom of the animal's paw

4724
03:52:01,374 --> 03:52:02,909
with a light paintbrush,

4725
03:52:02,909 --> 03:52:06,212
the animals with sickle cell
disease have more responses.

4726
03:52:06,212 --> 03:52:08,248
They just don't like
being touched.

4727
03:52:09,449 --> 03:52:13,319
And so, mice have chronic
mechanical allodynia

4728
03:52:13,319 --> 03:52:15,288
or hypersensitivity
to light touch.

4729
03:52:16,589 --> 03:52:21,795
But as our last speaker, Monica,
brought up,

4730
03:52:21,795 --> 03:52:23,730
what about spontaneous pain?

4731
03:52:24,230 --> 03:52:26,633
And that's really important
in the pain field now.

4732
03:52:26,633 --> 03:52:30,737
Everybody's interested
in what do these pain phenotypes

4733
03:52:30,737 --> 03:52:33,072
look like when you're looking
at spontaneous pain

4734
03:52:33,072 --> 03:52:36,309
because the patients have pain
when they're just sitting there,

4735
03:52:36,309 --> 03:52:39,712
pain when they're moving around.
They don't have to be touched.

4736
03:52:39,712 --> 03:52:43,883
So, we have begun looking at --
sorry,

4737
03:52:43,883 --> 03:52:46,186
I'm getting my pointers
confused --

4738
03:52:47,554 --> 03:52:51,624
we have begun looking, using AI,
Artificial intelligence,

4739
03:52:51,624 --> 03:52:56,329
to look at pain behaviors
by looking at the animal's face.

4740
03:52:56,329 --> 03:52:57,997
This is called facial grimace.

4741
03:52:58,565 --> 03:53:02,168
And so, what you can see
in an animal that is in pain --

4742
03:53:02,168 --> 03:53:04,537
and this is verified
by veterinarians --

4743
03:53:04,537 --> 03:53:06,773
you will see that they pull
their eyes back,

4744
03:53:06,773 --> 03:53:08,041
they pull their ears back,

4745
03:53:08,041 --> 03:53:10,243
they push
their whiskers forward,

4746
03:53:10,243 --> 03:53:11,811
they have a nose bulge.

4747
03:53:11,811 --> 03:53:14,447
And these are all elements
and evidence

4748
03:53:14,447 --> 03:53:19,118
that the animal is in pain.
So, we did this grimace test

4749
03:53:19,118 --> 03:53:21,020
with this artificial
intelligence,

4750
03:53:21,020 --> 03:53:24,958
and what we see is, indeed,
the sickle animals,

4751
03:53:24,958 --> 03:53:27,527
shown in red,
have higher grimace scores

4752
03:53:27,527 --> 03:53:31,798
chronically than the age-matched
control littermates.

4753
03:53:33,132 --> 03:53:34,300
And we're doing a variety

4754
03:53:34,300 --> 03:53:37,570
of other spontaneous
pain tests now,

4755
03:53:37,570 --> 03:53:40,406
but this suggests
that sickle mice also exhibit

4756
03:53:40,406 --> 03:53:43,042
this chronic,
ongoing-like pain behavior.

4757
03:53:44,444 --> 03:53:47,881
Now, where is that pain
coming from?

4758
03:53:48,414 --> 03:53:52,752
Well, we know that pain
receptors, called nociceptors,

4759
03:53:52,752 --> 03:53:55,054
in the body
that are all over the body

4760
03:53:55,054 --> 03:53:57,957
are what respond
to painful stimuli.

4761
03:53:57,957 --> 03:53:59,592
So, my lab asked a question:

4762
03:53:59,592 --> 03:54:01,294
well, are
these pain receptors --

4763
03:54:01,294 --> 03:54:03,129
are they actually sensitized?

4764
03:54:03,129 --> 03:54:05,064
Do they actually fire
more impulses

4765
03:54:05,064 --> 03:54:08,868
or more action potentials
in response to a touch stimulus?

4766
03:54:09,535 --> 03:54:13,539
And so, we took our mice --
sickle animals,

4767
03:54:13,539 --> 03:54:15,508
sickle and control animals --

4768
03:54:15,508 --> 03:54:19,913
and what we did is we took
this hindpaw skin and the nerve,

4769
03:54:19,913 --> 03:54:22,448
the saphenous nerve
that innervates that skin,

4770
03:54:22,448 --> 03:54:26,019
took it out of the animal,
kept it happy in a tissue bath,

4771
03:54:26,019 --> 03:54:29,155
and then recorded
from single primary

4772
03:54:29,155 --> 03:54:31,824
afferent sensory neuron
nociceptors.

4773
03:54:31,824 --> 03:54:33,626
And this right here,
as you can see,

4774
03:54:33,626 --> 03:54:37,931
the action potentials that you
get in a single pain receptor

4775
03:54:37,931 --> 03:54:40,366
when you stimulate it
with mechanical stimuli.

4776
03:54:42,235 --> 03:54:44,170
And so, what you can see

4777
03:54:44,170 --> 03:54:49,876
is both the C-fiber
unmyelinated nociceptors

4778
03:54:49,876 --> 03:54:55,248
and also the myelinated
nociceptors respond more,

4779
03:54:55,248 --> 03:54:58,685
with higher frequency
of action potential firing,

4780
03:54:58,685 --> 03:55:00,853
than the control animals --

4781
03:55:00,853 --> 03:55:03,022
the age-matched
littermate controls.

4782
03:55:04,223 --> 03:55:07,627
So, the nociceptors all over
the body are sensitized,

4783
03:55:07,627 --> 03:55:11,230
and they're sending
more input into the body.

4784
03:55:11,230 --> 03:55:14,233
Now, question we asked,

4785
03:55:14,233 --> 03:55:19,138
can we reverse this pain
with TRPV1 inhibition?

4786
03:55:19,138 --> 03:55:22,508
Okay, so who knows?
Tell me about what this is.

4787
03:55:22,508 --> 03:55:24,110
Who knows what these are?

4788
03:55:25,678 --> 03:55:27,547
How many of you like hot,
spicy food?

4789
03:55:29,282 --> 03:55:32,151
A lot of you? Okay, cool.
Yeah, hot, spicy food.

4790
03:55:32,151 --> 03:55:36,122
Does anybody know what the
chemical in hot, spicy food is?

4791
03:55:36,923 --> 03:55:39,258
Capsaicin, you guys know.

4792
03:55:39,258 --> 03:55:42,996
Okay, do you know why
the capsaicin was made famous

4793
03:55:42,996 --> 03:55:49,502
in the last three years?
Think Nobel. Nobel, Nobel Prize.

4794
03:55:51,904 --> 03:55:57,243
Yeah, Nobel Prize was won
by this gentleman, David Julius,

4795
03:55:57,810 --> 03:56:02,148
for discovery of the capsaicin
receptor, the TRPV1 --

4796
03:56:02,148 --> 03:56:05,451
transient receptor potential
vanilloid 1 -- receptor.

4797
03:56:06,185 --> 03:56:09,989
He won the Nobel Prize in 2021.
So, this is a really big deal.

4798
03:56:09,989 --> 03:56:14,560
It's hot stuff.
So, it is hot stuff.

4799
03:56:14,560 --> 03:56:17,597
So, just trying
to wake you up, right?

4800
03:56:18,965 --> 03:56:24,971
So, hot stuff, locally, through
patches, does alleviate pain.

4801
03:56:24,971 --> 03:56:28,274
So, you've known for many years
that you can use capsaicin

4802
03:56:28,274 --> 03:56:30,376
as a patch,
as a cream, and so forth.

4803
03:56:30,376 --> 03:56:36,816
You can inject it into the knee.
It causes -- it alleviates pain.

4804
03:56:36,816 --> 03:56:39,519
And we can talk about
the mechanisms for that later.

4805
03:56:39,519 --> 03:56:44,791
Okay, but the point is that
if you try to inject capsaicin

4806
03:56:44,791 --> 03:56:47,994
inhibitors systemically,
systemically, it's a problem.

4807
03:56:47,994 --> 03:56:49,629
Many, many people
have tried to.

4808
03:56:49,629 --> 03:56:51,564
Drug companies
have tried to do this.

4809
03:56:51,564 --> 03:56:56,636
What? So, these local analgesics
are effective,

4810
03:56:56,636 --> 03:57:01,607
but systemically, the inhibitors
induce hyperthermia --

4811
03:57:01,607 --> 03:57:04,811
so, fevers in patients
and in rodents.

4812
03:57:04,811 --> 03:57:06,813
We can talk
about mechanisms later.

4813
03:57:06,813 --> 03:57:09,849
And they also dampen the
individual's protective pain.

4814
03:57:09,849 --> 03:57:12,251
So, if they put their hand
on a hot stove,

4815
03:57:12,251 --> 03:57:13,519
they won't feel it,

4816
03:57:13,519 --> 03:57:15,555
and that's bad
because they get burnt.

4817
03:57:15,555 --> 03:57:20,893
Okay, so the question is,
can we target upstream of TRPV1?

4818
03:57:20,893 --> 03:57:22,662
Can we target mechanisms
that are involved

4819
03:57:22,662 --> 03:57:25,431
in sickle cell disease
upstream to TRPV1?

4820
03:57:26,332 --> 03:57:30,002
Here's where we started
bridging the translational gap.

4821
03:57:30,737 --> 03:57:35,374
Because there are basic
science investigators like me,

4822
03:57:35,374 --> 03:57:37,844
there are clinical investigators
in this room,

4823
03:57:37,844 --> 03:57:41,514
and then there are these
wonderful clinical individuals

4824
03:57:41,514 --> 03:57:43,816
who are treating the patients.

4825
03:57:44,383 --> 03:57:47,253
And I feel like a lot of times,
we're on our own islands,

4826
03:57:47,787 --> 03:57:50,857
and then in the sea
are all the patients

4827
03:57:50,857 --> 03:57:52,592
trying to find help somehow.

4828
03:57:53,526 --> 03:57:56,963
And so, what I think we need
to do a lot more of

4829
03:57:56,963 --> 03:58:01,033
is bridging the gap together --
bridging the islands together --

4830
03:58:01,033 --> 03:58:04,770
and I hope that meetings
like this will help us do that.

4831
03:58:08,141 --> 03:58:11,043
So, what we have done in my lab

4832
03:58:11,043 --> 03:58:14,514
is partner up with a fantastic
sickle cell clinician.

4833
03:58:14,514 --> 03:58:17,750
She's named Amanda Brandow.
She's fabulous.

4834
03:58:18,885 --> 03:58:21,420
And this is my lab, and we are
really trying very hard

4835
03:58:21,420 --> 03:58:25,057
to make this bridge
of translational research.

4836
03:58:25,057 --> 03:58:28,661
How are we doing that?
How's our first endeavor?

4837
03:58:29,495 --> 03:58:31,898
So, let's let patients
guide our research.

4838
03:58:31,898 --> 03:58:36,202
So, Amanda treats kids and
adults with sickle cell disease,

4839
03:58:36,769 --> 03:58:40,039
and she said, let's let
the patients guide our research.

4840
03:58:40,039 --> 03:58:42,074
Well, how will we do that?

4841
03:58:42,074 --> 03:58:47,613
Multiple Speaker: [inaudible]

4842
03:58:47,613 --> 03:58:51,117
Cheryl Stucky: Oh, yeah, sorry.
I keep getting confused.

4843
03:58:51,117 --> 03:58:52,451
There we go.

4844
03:58:52,451 --> 03:58:56,289
So, what Amanda did is
she took plasma from patients

4845
03:58:56,289 --> 03:59:00,693
with sickle cell disease
during an acute pain episode

4846
03:59:01,460 --> 03:59:04,864
and compared it
to healthy baseline plasma,

4847
03:59:05,398 --> 03:59:08,568
and then she did
a gene-associated array

4848
03:59:09,735 --> 03:59:13,105
and looked at
pain-relevant molecules.

4849
03:59:13,105 --> 03:59:15,241
And these are the hot things
that came up.

4850
03:59:15,241 --> 03:59:16,809
This is not published yet,

4851
03:59:16,809 --> 03:59:18,678
but she's allowing me
to present it.

4852
03:59:18,678 --> 03:59:22,748
The number one top molecule
was tumor necrosis factor,

4853
03:59:22,748 --> 03:59:25,151
and we heard about
that from Manu already.

4854
03:59:25,685 --> 03:59:28,187
So, tumor necrosis factor
is a hot one.

4855
03:59:28,187 --> 03:59:32,291
Here are a couple of others:
CCL2, CCR5, and so forth.

4856
03:59:33,492 --> 03:59:37,129
And so, we know
from past literature

4857
03:59:37,129 --> 03:59:42,201
that tumor necrosis factor
sensitizes TRPV1 channels.

4858
03:59:42,702 --> 03:59:48,641
So, maybe TNF
is upstream to TRPV1,

4859
03:59:48,641 --> 03:59:51,043
and a really interesting thing

4860
03:59:51,043 --> 03:59:55,181
is that TNF-alpha inhibitors
are already FDA-approved,

4861
03:59:55,181 --> 03:59:59,385
like infliximab and some
other things like etanercept.

4862
04:00:00,052 --> 04:00:04,624
So, we started
testing infliximab,

4863
04:00:04,624 --> 04:00:06,626
and this is now back
to our mouse model.

4864
04:00:07,326 --> 04:00:09,762
So we asked, does TNF inhibition
affect

4865
04:00:09,762 --> 04:00:14,767
mechanical hypersensitivity
after a induction

4866
04:00:14,767 --> 04:00:17,536
of an acute
vaso-occlusive event?

4867
04:00:18,604 --> 04:00:21,941
So how we did this is
the protocol is on the left,

4868
04:00:22,541 --> 04:00:27,413
we infused the animals
with infliximab for several days

4869
04:00:27,413 --> 04:00:31,217
and then induced an acute
vaso-occlusive event

4870
04:00:31,217 --> 04:00:34,053
with putting the animals
in a hypoxia chamber.

4871
04:00:34,620 --> 04:00:38,324
And then we tested
their mechanical thresholds.

4872
04:00:38,324 --> 04:00:40,993
And so what you see
on the left here --

4873
04:00:40,993 --> 04:00:45,264
again, I want to remind you that
the lower end is actually --

4874
04:00:46,265 --> 04:00:50,736
the lower end is going to be
more sensitive down here,

4875
04:00:51,737 --> 04:00:54,106
and then the higher end
is less sensitive.

4876
04:00:54,674 --> 04:00:56,809
And so our wild type animals

4877
04:00:56,809 --> 04:00:59,278
that do not have sickle
cell disease are in blue,

4878
04:00:59,912 --> 04:01:03,616
and the animals with sickle
cell disease are in pink.

4879
04:01:03,616 --> 04:01:07,486
And the animals that are treated
with infliximab are in solids.

4880
04:01:08,387 --> 04:01:13,225
So before any treatments,
just with infliximab itself,

4881
04:01:13,225 --> 04:01:14,660
you can see our baseline.

4882
04:01:14,660 --> 04:01:17,496
These sickle animals
are quite sensitive.

4883
04:01:18,230 --> 04:01:21,100
Then with the gray stripe there,

4884
04:01:21,100 --> 04:01:26,672
that's where we induced
the vaso-occlusive event.

4885
04:01:26,672 --> 04:01:29,542
So induced
a vaso-occlusive event.

4886
04:01:29,542 --> 04:01:31,977
And the sickle animals
that were treated with vehicle

4887
04:01:31,977 --> 04:01:33,679
are in the open circles.

4888
04:01:33,679 --> 04:01:36,382
They not only remain really,
really sensitive,

4889
04:01:36,382 --> 04:01:39,752
but they get even worse,
even more sensitive as --

4890
04:01:39,752 --> 04:01:41,487
after this
vasal occlusive event.

4891
04:01:41,487 --> 04:01:44,290
And they continue to be very,
very sensitive.

4892
04:01:44,290 --> 04:01:45,558
On the other hand,

4893
04:01:45,558 --> 04:01:47,927
the animals that
were treated with infliximab,

4894
04:01:47,927 --> 04:01:51,764
those in the dark pink circles,
the filled circles,

4895
04:01:51,764 --> 04:01:55,968
they get a complete reversal
of this hypersensitivity,

4896
04:01:55,968 --> 04:01:58,037
which is pretty interesting.

4897
04:01:58,037 --> 04:02:02,208
Then we redid the vasal
occlusive event again

4898
04:02:02,208 --> 04:02:03,809
with that gray stripe.

4899
04:02:03,809 --> 04:02:07,880
The animals
with sickle cell vehicle,

4900
04:02:07,880 --> 04:02:09,448
they get even worse
down there at the bottom.

4901
04:02:09,448 --> 04:02:10,716
Those open circles,

4902
04:02:10,716 --> 04:02:13,219
they're going to be even more
and more sensitive,

4903
04:02:13,219 --> 04:02:17,189
whereas the animals treated
with infliximab have, again,

4904
04:02:17,189 --> 04:02:20,126
a reversal of the pain
hypersensitivity,

4905
04:02:20,126 --> 04:02:21,927
touch hypersensitivity.

4906
04:02:21,927 --> 04:02:24,997
And again, that happened
again a third time.

4907
04:02:26,232 --> 04:02:28,701
So then, we asked, well, what --

4908
04:02:28,701 --> 04:02:31,237
what's happening
at a cellular level?

4909
04:02:31,237 --> 04:02:33,406
Can we take out the pain
receptors,

4910
04:02:33,406 --> 04:02:36,442
the nociceptors that are
in the dorsal root ganglia

4911
04:02:36,442 --> 04:02:40,212
by the spinal cord,
put them in a culture and record

4912
04:02:40,212 --> 04:02:42,882
from those pain
receptor nociceptors?

4913
04:02:42,882 --> 04:02:45,251
So here's what we do
on the left here,

4914
04:02:45,251 --> 04:02:49,388
that's a cell on a cover slip
that we're going to target,

4915
04:02:49,388 --> 04:02:50,623
and we're going to do whole cell

4916
04:02:50,623 --> 04:02:53,659
patch clamp electrophysiology
on that cell.

4917
04:02:54,527 --> 04:02:58,063
And we simply look at
the resting membrane potential.

4918
04:02:58,864 --> 04:03:00,633
For example, and on the left,

4919
04:03:00,633 --> 04:03:04,270
what you can see is compared
to the blue animals,

4920
04:03:04,270 --> 04:03:08,174
the control animals,
the resting memory potentials

4921
04:03:08,174 --> 04:03:11,544
of the sickle animals
are depolarized.

4922
04:03:11,544 --> 04:03:13,112
So they're more sensitive,

4923
04:03:13,112 --> 04:03:16,048
they're more likely to fire
an action potential.

4924
04:03:16,048 --> 04:03:18,651
And if you take neurons
out of animals

4925
04:03:18,651 --> 04:03:21,520
that were treated
in vivo with infliximab

4926
04:03:21,520 --> 04:03:23,889
and do these ex-vivo recordings,

4927
04:03:23,889 --> 04:03:27,793
the infliximab reverses
this elevation

4928
04:03:27,793 --> 04:03:29,395
in resting membrane potential.

4929
04:03:30,029 --> 04:03:33,933
Then if you look at spontaneous
action potential firing,

4930
04:03:33,933 --> 04:03:37,703
the top is --
the top trace is a neuron

4931
04:03:37,703 --> 04:03:40,306
just from a sickle animal
treated with vehicle.

4932
04:03:40,306 --> 04:03:42,141
You see those lines,
those are spikes,

4933
04:03:42,141 --> 04:03:45,744
those are firings of action
potentials in that neuron.

4934
04:03:45,744 --> 04:03:48,948
The infliximab treated-animal
neuron is below.

4935
04:03:48,948 --> 04:03:51,283
There are
fewer action potentials,

4936
04:03:51,283 --> 04:03:52,885
and if you quantify those,

4937
04:03:52,885 --> 04:03:55,387
the number of action potentials
on the right side,

4938
04:03:56,622 --> 04:04:00,192
compared to the blue control,
the sickle animals have way more

4939
04:04:00,192 --> 04:04:02,394
spontaneous action
potential firing,

4940
04:04:02,394 --> 04:04:05,965
and it's brought back
down close to baseline

4941
04:04:05,965 --> 04:04:07,233
if you take animals

4942
04:04:07,233 --> 04:04:10,503
or if you take neurons
from the animal sickle animals

4943
04:04:10,503 --> 04:04:12,571
or that were
treated with infliximab.

4944
04:04:14,473 --> 04:04:17,042
So -- and then we asked, okay,

4945
04:04:17,042 --> 04:04:21,247
is this happening through TRPV1,
the capsaicin receptor?

4946
04:04:21,247 --> 04:04:23,849
So in this case
we did calcium imaging

4947
04:04:23,849 --> 04:04:27,853
where you can basically use
a calcium sensitive Fluo-4

4948
04:04:27,853 --> 04:04:31,123
and look at neuronal responses
with this Fluo-4.

4949
04:04:31,624 --> 04:04:33,425
And hopefully
what you can see

4950
04:04:33,425 --> 04:04:37,263
is this is we're now stimulating
those neurons with capsaicin.

4951
04:04:37,763 --> 04:04:40,032
And what I think you can see

4952
04:04:40,032 --> 04:04:43,335
is that the sickle animals
treated with vehicle,

4953
04:04:43,335 --> 04:04:48,307
those isolated neurons are
more responsive to capsaicin.

4954
04:04:48,307 --> 04:04:52,177
And if you take neurons out of
the infliximab-treated animals,

4955
04:04:53,178 --> 04:04:57,316
that's returned back to normal
capsaicin responsiveness.

4956
04:04:57,316 --> 04:05:02,388
And the same is true with
the amount of calcium influx

4957
04:05:02,388 --> 04:05:04,423
when you stimulate them
with capsaicin.

4958
04:05:04,423 --> 04:05:08,561
So it seems like infliximab
reverses the sensitization

4959
04:05:08,561 --> 04:05:14,266
of TRPV1 in pain receptors
at the cellular level as well.

4960
04:05:14,867 --> 04:05:18,437
And again, we did this
with whole cell patch clamping

4961
04:05:18,437 --> 04:05:21,473
and you can see
that the infliximab again

4962
04:05:21,473 --> 04:05:24,476
reverses that responsive --

4963
04:05:24,476 --> 04:05:27,646
enhanced responsiveness
to capsaicin.

4964
04:05:27,646 --> 04:05:30,549
And it's similar to
if you use a TRPV1

4965
04:05:30,549 --> 04:05:32,651
inhibitor on those neurons.

4966
04:05:32,651 --> 04:05:35,120
So we think this mechanism
is occurring ultimately

4967
04:05:35,120 --> 04:05:36,388
through TRPV1,

4968
04:05:36,388 --> 04:05:39,558
this TNF sensitization
during sickle cell disease.

4969
04:05:40,426 --> 04:05:44,163
So we're wondering whether
we could possibly think

4970
04:05:44,163 --> 04:05:48,133
about repurposing FDA-approved
TNF inhibitors

4971
04:05:48,133 --> 04:05:52,538
for the acute pain events
that tend to be associated

4972
04:05:52,538 --> 04:05:55,874
with a vaso-occlusive event
in sickle cell patients,

4973
04:05:55,874 --> 04:05:57,576
patients with
sickle cell disease.

4974
04:05:59,612 --> 04:06:02,915
And I'm almost done.
We have a lot of mysteries.

4975
04:06:02,915 --> 04:06:06,185
We understand so far
the tip of the iceberg

4976
04:06:06,185 --> 04:06:10,255
for what's causing the pain
in sickle cell disease.

4977
04:06:10,923 --> 04:06:14,059
And what are the things
we don't know?

4978
04:06:14,059 --> 04:06:17,630
This is my last slide, but there
are many things we don't know.

4979
04:06:17,630 --> 04:06:19,965
What are the underlying
mechanisms for acute

4980
04:06:19,965 --> 04:06:22,134
and chronic pain
and sickle cell disease?

4981
04:06:22,134 --> 04:06:23,702
We're starting to
understand them,

4982
04:06:23,702 --> 04:06:25,671
but we still have
a long way to go.

4983
04:06:25,671 --> 04:06:29,141
How do these account
for the individual variability

4984
04:06:29,141 --> 04:06:32,444
between patients
and their different phenotypes?

4985
04:06:33,412 --> 04:06:35,014
What are the risk factors,

4986
04:06:35,014 --> 04:06:37,483
but also what are
the protective factors

4987
04:06:37,483 --> 04:06:42,955
for developing pain over the
lifespan from babies to adults?

4988
04:06:45,357 --> 04:06:48,427
Well, we have existing therapies
and Dr. Darbari

4989
04:06:48,427 --> 04:06:50,195
is going to be talking
about this next.

4990
04:06:50,195 --> 04:06:53,799
So, which of these are the
most effective for acute pain

4991
04:06:53,799 --> 04:06:57,536
and a chronic pain and then
acute on top of chronic pain?

4992
04:06:58,804 --> 04:07:02,174
Will early therapy as babies
or young children --

4993
04:07:02,174 --> 04:07:05,544
will that actually prevent
the development of chronic pain?

4994
04:07:05,544 --> 04:07:07,680
We still don't know that.

4995
04:07:08,247 --> 04:07:11,316
Will bone marrow transplant
or gene therapy

4996
04:07:11,316 --> 04:07:15,020
reverse chronic pain
that's already established?

4997
04:07:15,020 --> 04:07:16,321
Will it?

4998
04:07:16,321 --> 04:07:18,357
And if it will,
at what time and point?

4999
04:07:19,725 --> 04:07:21,694
We don't know that.

5000
04:07:21,694 --> 04:07:26,632
Can we identify novel
ideological targets for acute

5001
04:07:26,632 --> 04:07:29,068
and chronic pain?
Novel targets?

5002
04:07:29,068 --> 04:07:32,171
And that's one thing my love
is really, really interested in.

5003
04:07:32,171 --> 04:07:35,708
And with that, I just want to
thank the members of my lab.

5004
04:07:35,708 --> 04:07:38,210
This is the Stucky Lab
on the left.

5005
04:07:39,478 --> 04:07:44,216
I want to thank my funding
sources largely from NIH,

5006
04:07:44,216 --> 04:07:47,019
especially NINDS and NHLBI.

5007
04:07:47,619 --> 04:07:50,155
And then I really,
really want to shout out

5008
04:07:50,155 --> 04:07:54,093
and thank my fabulous clinical
partner, Amanda Brandow.

5009
04:07:54,093 --> 04:07:58,597
And I hope that you all will
partner up with a clinician

5010
04:07:58,597 --> 04:08:01,667
if you're a basic scientist
or a basic scientist

5011
04:08:01,667 --> 04:08:02,901
if you're a clinician,

5012
04:08:02,901 --> 04:08:06,739
and really try to go bench
to bedside and backwards

5013
04:08:07,306 --> 04:08:10,476
because I think this is
a really strong pathway forward.

5014
04:08:10,476 --> 04:08:12,611
And thank you very much
for your attention.

5015
04:08:20,018 --> 04:08:21,620
Zachary Ramsay: Well, don't go
too far.

5016
04:08:22,154 --> 04:08:24,490
Yes, thanks very much
for that talk.

5017
04:08:24,490 --> 04:08:27,793
I actually do a lot of work with
quantitative sensory testing.

5018
04:08:28,794 --> 04:08:30,496
So this is very exciting

5019
04:08:30,496 --> 04:08:33,799
and certainly a lot
of the papers that you've --

5020
04:08:33,799 --> 04:08:37,336
you know, you're discussing
particularly from Dr. Brandow,

5021
04:08:38,504 --> 04:08:41,173
you know, they've been very,
you know,

5022
04:08:41,173 --> 04:08:43,375
useful in guiding
a lot of that research.

5023
04:08:43,976 --> 04:08:46,712
So I'm going to welcome
two short questions.

5024
04:08:47,379 --> 04:08:49,014
Just trying to keep up
with time.

5025
04:08:51,116 --> 04:08:52,351
Male Speaker: Yeah.
That was very nice.

5026
04:08:52,351 --> 04:08:53,552
And I'll keep it quick.

5027
04:08:53,552 --> 04:08:56,255
At what age did you do these
pain studies with your mice?

5028
04:08:56,255 --> 04:08:59,124
And you hinted at this,
at your final conclusions,

5029
04:08:59,124 --> 04:09:01,660
and did you see
any age-related differences

5030
04:09:01,660 --> 04:09:03,395
in their pain responses
into the medicine?

5031
04:09:03,395 --> 04:09:04,696
Cheryl Stucky: Excellent
question.

5032
04:09:04,696 --> 04:09:09,868
So we've seen the pain phenotype
and chronically by two week,

5033
04:09:09,868 --> 04:09:12,838
or sorry,
by two months of age,

5034
04:09:12,838 --> 04:09:17,810
it gets worse and worse
as the animals age to a year.

5035
04:09:17,810 --> 04:09:19,645
So it gets worse with age.

5036
04:09:19,645 --> 04:09:23,148
We are now conducting studies to
look at earlier than two months.

5037
04:09:23,949 --> 04:09:26,718
It is kind of difficult
because the myelination

5038
04:09:26,718 --> 04:09:29,788
doesn't develop after birth
for a few weeks

5039
04:09:29,788 --> 04:09:31,423
and the myelination
is really important

5040
04:09:31,423 --> 04:09:34,092
for how they withdraw
from the stimulus.

5041
04:09:34,092 --> 04:09:39,064
But it's a great question.
Thank you. Yes, please.

5042
04:09:39,064 --> 04:09:40,332
Swee Thein: I have a quick one.

5043
04:09:40,332 --> 04:09:42,334
So I'm really interested,
you know,

5044
04:09:43,001 --> 04:09:46,905
I'm fascinated by this pain.
So you mentioned about TRPV1.

5045
04:09:46,905 --> 04:09:48,106
Cheryl Stucky: [affirmative]

5046
04:09:48,106 --> 04:09:50,876
Swee Thein: And in fact,
I just kind of happened

5047
04:09:50,876 --> 04:09:54,713
to look to all this,
you know, about the thing.

5048
04:09:54,713 --> 04:09:57,950
You know, new --
using a new approach

5049
04:09:58,851 --> 04:10:03,455
and I didn't realize that
there's so many TRPV1 inhibitors

5050
04:10:03,455 --> 04:10:05,023
that are under
clinical trials or pain.

5051
04:10:05,023 --> 04:10:06,225
Cheryl Stucky: Yes. Yes.

5052
04:10:06,225 --> 04:10:07,459
Swee Thein: And so many of them

5053
04:10:07,459 --> 04:10:08,760
have been
prematurely terminated.

5054
04:10:08,760 --> 04:10:09,962
Cheryl Stucky: Yes.

5055
04:10:09,962 --> 04:10:14,266
Swee Thein: Presumably for
this hyper variant.

5056
04:10:14,266 --> 04:10:15,968
Cheryl Stucky: That's exactly
why they've been terminated.

5057
04:10:15,968 --> 04:10:17,202
Swee Thein: Hyper variant.

5058
04:10:17,202 --> 04:10:18,704
Cheryl Stucky: That's
exactly why.

5059
04:10:18,704 --> 04:10:20,305
Swee Thein: One thing I want
to ask you,

5060
04:10:21,073 --> 04:10:23,075
why you mentioned
the patient variability.

5061
04:10:23,075 --> 04:10:24,309
Cheryl Stucky: Yeah.

5062
04:10:24,309 --> 04:10:27,179
Swee Thein: And assuming TRPV1
is so important

5063
04:10:28,313 --> 04:10:29,915
are they genetic variants?

5064
04:10:30,983 --> 04:10:32,284
Cheryl Stucky: Yeah.

5065
04:10:32,284 --> 04:10:35,454
There are -- in other
populations of humans,

5066
04:10:35,454 --> 04:10:38,690
there are -- to my knowledge,
it has not been looked at

5067
04:10:38,690 --> 04:10:40,993
in patients
with sickle cell disease.

5068
04:10:40,993 --> 04:10:44,196
I think it's a great question.
Great question.

5069
04:10:45,163 --> 04:10:46,598
Male Speaker: I have just
a quick question.

5070
04:10:46,598 --> 04:10:48,567
I -- you know, the TNF-alpha
is very interesting

5071
04:10:48,567 --> 04:10:49,801
that you see this emerge.

5072
04:10:49,801 --> 04:10:51,937
And I'm curious
if there's any role

5073
04:10:51,937 --> 04:10:53,972
of kind of
microvascular thrombosis

5074
04:10:53,972 --> 04:10:55,407
or platelet activation
in any way,

5075
04:10:55,407 --> 04:10:58,644
both in terms of pain
and in terms of say,

5076
04:10:58,644 --> 04:11:00,245
a risk of thrombosis
more broadly too.

5077
04:11:00,245 --> 04:11:01,480
Cheryl Stucky: So if you --

5078
04:11:01,480 --> 04:11:02,948
you mean
with TNF alpha inhibition?

5079
04:11:02,948 --> 04:11:04,149
Male Speaker: Yeah.

5080
04:11:04,149 --> 04:11:06,518
Cheryl Stucky: That is
a fantastic question.

5081
04:11:06,518 --> 04:11:11,123
I am not a hematologist.
I should start looking at that,

5082
04:11:11,123 --> 04:11:14,259
and I welcome your advice
on how to do that.

5083
04:11:14,259 --> 04:11:15,494
I would love to do that.

5084
04:11:15,494 --> 04:11:17,663
We haven't really looked
at any other body parts.

5085
04:11:17,663 --> 04:11:19,765
It's actually a shame
because we sacked the animals.

5086
04:11:19,765 --> 04:11:22,034
We only took the one --
the things we knew about.

5087
04:11:22,034 --> 04:11:24,703
We could have taken
all kinds of things.

5088
04:11:25,370 --> 04:11:26,571
Male Speaker: Thanks.

5089
04:11:26,571 --> 04:11:27,806
Cheryl Stucky: Yeah. Sure.

5090
04:11:27,806 --> 04:11:29,308
Swee Thein: One last question.
Cheryl Stucky: Sure.

5091
04:11:29,308 --> 04:11:31,109
Swee Thein: So now
that we have AI,

5092
04:11:31,843 --> 04:11:33,178
can we actually use AI

5093
04:11:33,178 --> 04:11:37,482
to actually target
just the part that you want,

5094
04:11:37,482 --> 04:11:43,088
but you know, avoiding
the hyper hyperthermia,

5095
04:11:44,156 --> 04:11:45,357
you know, communication?

5096
04:11:45,357 --> 04:11:47,092
Cheryl Stucky: Yeah.
Hypothermia.

5097
04:11:47,092 --> 04:11:48,627
Swee Thein: And hyperalgesia?

5098
04:11:48,627 --> 04:11:51,396
Cheryl Stucky: Hyperalgesia.
Yeah. Yeah. Fabulous question.

5099
04:11:51,396 --> 04:11:53,966
AI is getting more
and more developed by the --

5100
04:11:53,966 --> 04:11:57,502
by the minute.
And so yes, your answer is yes.

5101
04:11:58,804 --> 04:12:00,872
We are working on that
with other groups

5102
04:12:00,872 --> 04:12:04,376
to look at pain behaviors
and nuances in pain behaviors.

5103
04:12:04,376 --> 04:12:06,979
There's also things
like black box recording

5104
04:12:06,979 --> 04:12:10,415
where you use AI to look
at the gate of the animal

5105
04:12:10,415 --> 04:12:12,584
and how much pressure
it puts on different parts

5106
04:12:12,584 --> 04:12:14,386
and how much it rears up
and all.

5107
04:12:14,386 --> 04:12:16,154
And you know,
the angle of its body.

5108
04:12:16,154 --> 04:12:18,523
We're just about to install
one of those in our lab.

5109
04:12:18,523 --> 04:12:21,994
So the answer is yes, and I
think that's going to explode.

5110
04:12:23,962 --> 04:12:25,163
Thank you.

5111
04:12:25,163 --> 04:12:26,765
Swee Thein: Thank you.

5112
04:12:30,135 --> 04:12:31,470
Zachary Ramsay: All right.

5113
04:12:31,470 --> 04:12:36,608
And our third presentation is
on managing pain beyond opioids.

5114
04:12:37,142 --> 04:12:42,180
So looking on cannabinoids,
buprenorphine --

5115
04:12:42,180 --> 04:12:44,449
I'm sure I pronounced
that incorrectly.

5116
04:12:44,449 --> 04:12:46,251
And ketamine.

5117
04:12:46,251 --> 04:12:50,689
And this is
by Dr. Deepika Darbari.

5118
04:12:50,689 --> 04:12:55,127
And Dr. Darbari is a pediatric
hematologist oncologist

5119
04:12:55,127 --> 04:12:57,295
at the Children's
National Hospital,

5120
04:12:57,829 --> 04:13:00,132
and also the professor
of pediatrics

5121
04:13:00,132 --> 04:13:03,702
at the George Washington
University in Washington D.C.

5122
04:13:11,143 --> 04:13:12,744
Deepika Darbari: All right.

5123
04:13:16,581 --> 04:13:18,083
All right.
Thank you everyone,

5124
04:13:18,083 --> 04:13:20,052
and thank you for
the organizing committee

5125
04:13:20,052 --> 04:13:22,154
for giving me
this opportunity.

5126
04:13:22,154 --> 04:13:24,756
And as we know, pain is
the most common complication

5127
04:13:24,756 --> 04:13:27,526
of sickle cell disease.
And as we heard earlier,

5128
04:13:27,526 --> 04:13:31,029
opioids are pretty much
the treatment right now,

5129
04:13:31,029 --> 04:13:32,664
but that has
many side effects.

5130
04:13:32,664 --> 04:13:35,801
So it's important that we learn
about some of the other things,

5131
04:13:35,801 --> 04:13:38,904
other agents, that are coming up
for managing pain

5132
04:13:38,904 --> 04:13:40,372
in sickle cell disease.

5133
04:13:40,372 --> 04:13:42,674
Just a disclaimer,
my first name is spelled

5134
04:13:42,674 --> 04:13:45,410
Deepika and Darbari
is my last name [laughs].

5135
04:13:45,410 --> 04:13:48,914
All right. All right.
So these are my disclosures.

5136
04:13:49,681 --> 04:13:51,516
So first of all,
as I mentioned,

5137
04:13:51,516 --> 04:13:53,452
pain is the most
common complication.

5138
04:13:53,452 --> 04:13:54,853
And as Cheryl mentioned,

5139
04:13:54,853 --> 04:13:58,190
it's important to understand
their different mechanism.

5140
04:13:58,190 --> 04:14:01,426
So when -- whenever we say pain,
it could be acute pain,

5141
04:14:01,426 --> 04:14:02,928
it could be chronic pain,

5142
04:14:02,928 --> 04:14:04,896
or it could be acute
episode of pain

5143
04:14:04,896 --> 04:14:06,798
on the background
of chronic pain.

5144
04:14:06,798 --> 04:14:08,500
And the mechanisms are different

5145
04:14:08,500 --> 04:14:12,370
and sometimes these mechanism
may be present at the same time.

5146
04:14:13,038 --> 04:14:15,407
And limitation right now
for managing

5147
04:14:15,407 --> 04:14:18,677
is our treatments are
just opioid centric or NSAIDs.

5148
04:14:18,677 --> 04:14:20,712
Those are the one we use.

5149
04:14:20,712 --> 04:14:23,682
But all of us you know,
who have managed the patient,

5150
04:14:23,682 --> 04:14:26,651
we see we can go up
on the doses of opioid,

5151
04:14:26,651 --> 04:14:27,886
but there's no response.

5152
04:14:27,886 --> 04:14:29,821
So patients
are treatment refractory

5153
04:14:30,322 --> 04:14:33,892
and it's and especially
when you have chronic pain.

5154
04:14:33,892 --> 04:14:36,728
And we also know that more than
50 percent of the adults

5155
04:14:36,728 --> 04:14:37,963
have chronic pain.

5156
04:14:37,963 --> 04:14:39,197
So we really have --

5157
04:14:39,197 --> 04:14:42,267
don't have many treatment
options for those individuals.

5158
04:14:43,935 --> 04:14:46,905
So -- and other thing is,
if you look at the opioid --

5159
04:14:46,905 --> 04:14:49,407
so first of all,
opioid is the only choice.

5160
04:14:49,407 --> 04:14:52,511
And chronic opioid therapy
has become very common,

5161
04:14:52,511 --> 04:14:54,646
but that has many side effects.

5162
04:14:54,646 --> 04:14:57,716
And the -- you know,
some of the mechanism we are --

5163
04:14:57,716 --> 04:15:01,853
heard in during the sleep-talk,
central sensitization

5164
04:15:01,853 --> 04:15:05,590
is one of the very important
mechanism for contributing --

5165
04:15:05,590 --> 04:15:07,959
of contributing to chronic pain.

5166
04:15:07,959 --> 04:15:10,729
So even if you can correct
sickle cell disease

5167
04:15:10,729 --> 04:15:12,464
with some of the treatments,

5168
04:15:12,464 --> 04:15:14,833
you may not be able
to reverse chronic pain.

5169
04:15:14,833 --> 04:15:17,302
So it's important that opioid
can contribute

5170
04:15:17,302 --> 04:15:19,171
to central sensitization.

5171
04:15:19,171 --> 04:15:22,040
Also poor quality of life,
depression.

5172
04:15:22,040 --> 04:15:23,708
So all I'm trying to say here

5173
04:15:23,708 --> 04:15:26,244
is it's important we look
at the other agents.

5174
04:15:27,012 --> 04:15:29,548
So these are the three agents
I'm going to talk about.

5175
04:15:29,548 --> 04:15:33,018
First is cannabinoid,
buprenorphine and ketamine.

5176
04:15:33,618 --> 04:15:36,588
So first cannabinoid,
which has been in news

5177
04:15:36,588 --> 04:15:40,225
and has been approved
in many of the states in U.S.

5178
04:15:40,225 --> 04:15:42,594
So humans have used it
for centuries.

5179
04:15:42,594 --> 04:15:44,663
Like more than many
thousands of years,

5180
04:15:45,430 --> 04:15:47,265
this plant has been used.

5181
04:15:47,265 --> 04:15:51,670
But in 1960, that was the first
time the active compound

5182
04:15:51,670 --> 04:15:54,806
or the THC was identified
from this plant.

5183
04:15:54,806 --> 04:15:57,909
And that led to identification
of these receptors.

5184
04:15:57,909 --> 04:15:59,578
And these receptors
are important

5185
04:15:59,578 --> 04:16:03,248
because we'll talk about those.
So cannabinoid receptor 1

5186
04:16:03,248 --> 04:16:06,551
and cannabinoid receptor
2 were identified.

5187
04:16:06,551 --> 04:16:09,187
And at the same time,
the whole cannabinoid system

5188
04:16:09,187 --> 04:16:12,023
was identified in the body,
which is present.

5189
04:16:12,023 --> 04:16:15,193
And it's -- the action
is through endocannabinoid.

5190
04:16:15,193 --> 04:16:19,231
So these endocannabinoids
are of two kinds.

5191
04:16:19,231 --> 04:16:22,334
And the first one
is AEA and 2-AG.

5192
04:16:22,334 --> 04:16:24,336
And I want to mention anandamine

5193
04:16:24,336 --> 04:16:25,971
because that kind of
indicates --

5194
04:16:25,971 --> 04:16:28,006
so ananda is the Sanskrit word,

5195
04:16:28,006 --> 04:16:31,810
a language, ancient India,
that means joy.

5196
04:16:31,810 --> 04:16:34,913
So people knew that, you know,
cannabis and joy

5197
04:16:34,913 --> 04:16:37,482
kind of go hand in hand,
[laughs].

5198
04:16:37,482 --> 04:16:39,985
But recently --
so people have --

5199
04:16:39,985 --> 04:16:41,786
and I'm trying to understand

5200
04:16:41,786 --> 04:16:44,723
like what are the therapeutic
potential of this medication?

5201
04:16:45,624 --> 04:16:48,260
So if you have not seen
the plant looks like this,

5202
04:16:48,893 --> 04:16:51,997
and there are some of the things
which are here,

5203
04:16:51,997 --> 04:16:55,767
[laughs], so now next time
you see, you know what it is,

5204
04:16:55,767 --> 04:16:57,502
[laughs].
So these are the parts.

5205
04:16:57,502 --> 04:17:00,538
So one is flowers.
So flowers are mostly the one.

5206
04:17:00,538 --> 04:17:04,142
Those are used for many forms
of edibles or you know,

5207
04:17:04,142 --> 04:17:06,411
different ways,
but also leaves.

5208
04:17:06,411 --> 04:17:08,747
So I learned that leaves
are of two kind.

5209
04:17:08,747 --> 04:17:11,082
The more potent ones
are the small ones,

5210
04:17:11,082 --> 04:17:15,086
are the sugar leaves and the fan
leaves are important,

5211
04:17:15,086 --> 04:17:16,554
but not that important.

5212
04:17:16,554 --> 04:17:19,858
And then your stem is also used
for many, you know,

5213
04:17:19,858 --> 04:17:21,993
like making ropes
and stuff like that.

5214
04:17:21,993 --> 04:17:24,229
But seeds for the next crop.
So plant --

5215
04:17:24,229 --> 04:17:27,032
I mean really all the parts
of the plants are used.

5216
04:17:28,300 --> 04:17:30,702
So the way cannabinoids act

5217
04:17:31,603 --> 04:17:33,938
is through two receptors
as I mentioned.

5218
04:17:33,938 --> 04:17:37,976
So CBR1, cannabinoid receptor 1
and cannabinoid receptor 2.

5219
04:17:38,643 --> 04:17:40,078
So the 1 is -- has --

5220
04:17:40,078 --> 04:17:43,915
and these receptors are present
in our central nervous system.

5221
04:17:43,915 --> 04:17:46,418
So important for management
of pain because pain

5222
04:17:46,418 --> 04:17:48,787
is also felt
in our nervous system.

5223
04:17:48,787 --> 04:17:52,190
So important thing to know here
is that 1 is really --

5224
04:17:53,391 --> 04:17:54,893
contributes to a lot of things.

5225
04:17:54,893 --> 04:17:58,196
So it's important for pain,
anxiety, sleep and appetite.

5226
04:17:58,196 --> 04:18:01,666
And that's why we see
some of the patients report

5227
04:18:01,666 --> 04:18:05,003
that they benefit
from using cannabinoid.

5228
04:18:05,003 --> 04:18:08,440
But the problem is it also
has psychoactive effect.

5229
04:18:08,440 --> 04:18:10,575
So that is the downside
of cannabinoid.

5230
04:18:10,575 --> 04:18:15,113
If we are using or targeting
only cannabinoid receptor 1.

5231
04:18:15,113 --> 04:18:18,850
Receptor 2 is localized
in immune cells.

5232
04:18:18,850 --> 04:18:23,121
So the way it works for the pain
is by acting on the --

5233
04:18:23,121 --> 04:18:26,124
so we also heard in the sleep
talk the mechanism

5234
04:18:26,124 --> 04:18:27,859
or how the pain is felt.

5235
04:18:27,859 --> 04:18:31,796
So it works at different levels.
So it acts presynaptically.

5236
04:18:31,796 --> 04:18:35,066
So you are -- inhibits the
release of neurotransmitter,

5237
04:18:35,066 --> 04:18:38,970
changes the uptake
and also the activation of DNIC.

5238
04:18:38,970 --> 04:18:42,374
DNIC is the --
our natural pathway in our body

5239
04:18:42,374 --> 04:18:45,143
that inhibits pain.
So it activates pain.

5240
04:18:45,143 --> 04:18:47,212
So there are many ways
it works in pain

5241
04:18:47,846 --> 04:18:49,914
and also in neuroinflammation.

5242
04:18:49,914 --> 04:18:51,783
So these are all important
thing we know

5243
04:18:51,783 --> 04:18:53,685
in sickle cell that's important.

5244
04:18:53,685 --> 04:18:55,453
So it can help
in sickle cell pain.

5245
04:18:56,321 --> 04:18:58,523
But the problem has been
the side effect,

5246
04:18:58,523 --> 04:19:00,558
the psychoactive side effects.

5247
04:19:00,558 --> 04:19:04,095
If we are targeting
only cannabinoid receptor 1.

5248
04:19:04,095 --> 04:19:05,697
So it's important recently,

5249
04:19:05,697 --> 04:19:09,634
CBD or cannabinoid
has been used more commonly

5250
04:19:09,634 --> 04:19:14,472
and that acts on cannabinoid
receptor 2 and not on 1.

5251
04:19:14,472 --> 04:19:16,708
And that may have
some beneficial effect.

5252
04:19:17,242 --> 04:19:19,644
So the -- right now,
there are only in sickle cell,

5253
04:19:19,644 --> 04:19:23,148
only the mouse model studies
that showed that --

5254
04:19:23,148 --> 04:19:28,052
as Cheryl showed hyperalgesia.
So it can decrease hyperalgesia

5255
04:19:28,052 --> 04:19:31,389
and also inflammation
important in pain.

5256
04:19:31,389 --> 04:19:33,158
So those are the things
that have been shown

5257
04:19:33,158 --> 04:19:37,595
in sickle cell models so far.
How about in humans?

5258
04:19:37,595 --> 04:19:39,931
So there are --
some of the studies experienced

5259
04:19:39,931 --> 04:19:42,200
from the patients
have been reported.

5260
04:19:42,200 --> 04:19:46,771
And so really not great benefit
at this point,

5261
04:19:46,771 --> 04:19:47,972
as you can see here.

5262
04:19:47,972 --> 04:19:50,442
So I have listed full study
and some --

5263
04:19:50,442 --> 04:19:52,477
most of them were like looking
at the data

5264
04:19:52,477 --> 04:19:55,680
from the medical record
or hospitalization

5265
04:19:55,680 --> 04:19:57,248
and patient report,

5266
04:19:57,248 --> 04:19:59,951
but not really significant
difference in patients

5267
04:19:59,951 --> 04:20:03,421
who were taking medical
marijuana or not taking it.

5268
04:20:03,421 --> 04:20:07,392
Only -- there's only one pilot
randomized control trial

5269
04:20:07,392 --> 04:20:11,896
that looked at
the vaporized cannabis

5270
04:20:11,896 --> 04:20:14,032
and it did not show any effect.

5271
04:20:14,032 --> 04:20:16,201
So that was the only
randomized trial

5272
04:20:16,201 --> 04:20:19,637
and it actually did not reduce
pain or associated symptoms.

5273
04:20:19,637 --> 04:20:23,675
So that was the only study.
So what can we say?

5274
04:20:23,675 --> 04:20:25,977
So American Society
of Hematology

5275
04:20:25,977 --> 04:20:27,512
came up with the guidelines

5276
04:20:27,512 --> 04:20:29,881
on management of pain
few years ago,

5277
04:20:30,381 --> 04:20:32,884
and their comment
on medical cannabis is,

5278
04:20:32,884 --> 04:20:37,755
so cannabis at federal level
in U.S. is still illegal.

5279
04:20:37,755 --> 04:20:41,793
Although states have approved
the, you know, medical use

5280
04:20:41,793 --> 04:20:44,295
and recreational use,
you can use cannabis,

5281
04:20:44,295 --> 04:20:48,733
but as a physician you need like
special things to prescribe.

5282
04:20:48,733 --> 04:20:51,503
So they did not make
a comment of like,

5283
04:20:51,503 --> 04:20:54,472
would cannabis would work
for sickle cell pain or not,

5284
04:20:54,472 --> 04:20:56,241
but they did identify it.

5285
04:20:56,241 --> 04:20:58,843
So since many of
our patients take it,

5286
04:20:58,843 --> 04:21:00,778
so it's important
that we understand

5287
04:21:00,778 --> 04:21:04,449
and we look at does it --
is it beneficial or not?

5288
04:21:04,449 --> 04:21:07,352
And especially important
not only the efficacy,

5289
04:21:07,352 --> 04:21:08,953
but also the side effect

5290
04:21:08,953 --> 04:21:13,892
and what are the downsides of
using med marijuana or cannabis?

5291
04:21:16,060 --> 04:21:20,999
So right now the cannabis status
in U.S. is it's schedule 1 drug.

5292
04:21:20,999 --> 04:21:22,367
And I have put --
what are --

5293
04:21:22,367 --> 04:21:25,003
what is the definition
of schedule 1 drug?

5294
04:21:25,003 --> 04:21:28,973
So schedule 1 has no currently
accepted medical use.

5295
04:21:28,973 --> 04:21:31,342
And this is again
as the federal level,

5296
04:21:31,342 --> 04:21:33,511
so high potential for abuse.

5297
04:21:33,511 --> 04:21:36,648
And some of these things
you can see here.

5298
04:21:36,648 --> 04:21:39,784
But that has not stopped
the industry.

5299
04:21:39,784 --> 04:21:42,620
So the sales for --
cannabis-related sales

5300
04:21:42,620 --> 04:21:46,090
are in billions now,
and use has increased.

5301
04:21:46,090 --> 04:21:48,693
Other problem is that
if you buy those product

5302
04:21:48,693 --> 04:21:51,963
from different dispensary,
the product may be different.

5303
04:21:51,963 --> 04:21:54,332
So there's no consistency
and some of that

5304
04:21:54,332 --> 04:21:56,801
there will be combination
of dangerous substances

5305
04:21:56,801 --> 04:21:59,103
that can contribute
to side effects.

5306
04:21:59,103 --> 04:22:01,105
So it's really -- you know,
so some of the --

5307
04:22:01,105 --> 04:22:03,041
this research is undergoing,

5308
04:22:03,041 --> 04:22:06,544
but we also know many of
our patients use this substance.

5309
04:22:06,544 --> 04:22:09,881
It's important to educate them
about the risk and benefit.

5310
04:22:10,982 --> 04:22:12,483
So risk and benefit, the --

5311
04:22:12,483 --> 04:22:14,886
these are the side effects,
those are listed.

5312
04:22:14,886 --> 04:22:17,889
So you can see here
pretty much affect many organs.

5313
04:22:17,889 --> 04:22:20,191
So paranoia,
impaired memory, fatigue,

5314
04:22:20,191 --> 04:22:23,428
and some of the things
are already present in patients

5315
04:22:23,428 --> 04:22:25,029
with sickle cell disease.

5316
04:22:25,029 --> 04:22:28,833
One of the biggest concern
has been used in adolescent.

5317
04:22:28,833 --> 04:22:31,703
So almost like one
in three teenagers by age --

5318
04:22:32,337 --> 04:22:34,839
by 12th grade
they have used marijuana.

5319
04:22:34,839 --> 04:22:37,075
And that can lead
to multiple problems.

5320
04:22:37,075 --> 04:22:39,944
So that has been recently like
one of the bigger problem.

5321
04:22:40,545 --> 04:22:42,981
And also vaping.

5322
04:22:42,981 --> 04:22:45,583
So not only our patients
have acute chest syndrome

5323
04:22:45,583 --> 04:22:47,085
and involvement of lung,

5324
04:22:47,085 --> 04:22:48,920
so it becomes
even more important.

5325
04:22:49,420 --> 04:22:52,223
And also another thing when
teenagers or young adults

5326
04:22:52,223 --> 04:22:55,927
are driving while under
the influence that can lead to,

5327
04:22:55,927 --> 04:22:59,097
you know, harm to them
and also people around them.

5328
04:22:59,097 --> 04:23:01,299
So it's really important
that we think about

5329
04:23:01,299 --> 04:23:04,068
and look at the benefits
and side effects.

5330
04:23:05,436 --> 04:23:08,039
Next, I'm going to move on
to buprenorphine.

5331
04:23:09,207 --> 04:23:13,511
So buprenorphine is -- it's a --
it's like a opioid,

5332
04:23:13,511 --> 04:23:16,547
but it's partial agonist
and antagonist.

5333
04:23:16,547 --> 04:23:19,250
So it acts on the opioid
receptor.

5334
04:23:19,250 --> 04:23:21,185
So I have put them up here,

5335
04:23:21,185 --> 04:23:22,987
as you can see
on the right side.

5336
04:23:24,088 --> 04:23:26,257
So the opioid receptor,
there are new opioid

5337
04:23:26,257 --> 04:23:31,596
receptor kappa and delta.
So this buprenorphine acts on --

5338
04:23:31,596 --> 04:23:34,365
it's a partial agonist
on the new opioid receptor.

5339
04:23:34,365 --> 04:23:36,668
So by that virtue
it causes pain relief.

5340
04:23:36,668 --> 04:23:39,804
So, which is a good thing and,
but it doesn't have the --

5341
04:23:39,804 --> 04:23:43,441
since it's not full agonist,
it doesn't cause those problems

5342
04:23:43,441 --> 04:23:47,345
that we can see with
the morphine or other opioid.

5343
04:23:47,345 --> 04:23:50,948
So like, you know, they don't
have dysphoria, sedation.

5344
04:23:50,948 --> 04:23:52,850
Potential for addiction is low

5345
04:23:52,850 --> 04:23:56,654
because there's not that much
of high with buprenorphine.

5346
04:23:56,654 --> 04:23:58,056
Depression and other things

5347
04:23:58,056 --> 04:24:00,391
are also less common
with buprenorphine.

5348
04:24:01,793 --> 04:24:06,631
So it has been approved by FDA
for management of chronic pain.

5349
04:24:06,631 --> 04:24:07,932
It can be used alone.

5350
04:24:07,932 --> 04:24:11,102
So buprenorphine alone or
buprenorphine with naloxone

5351
04:24:11,102 --> 04:24:12,336
has been used.

5352
04:24:12,336 --> 04:24:14,072
So this is the picture
I have put in,

5353
04:24:14,072 --> 04:24:17,041
what's the difference
between full opioid agonist

5354
04:24:17,041 --> 04:24:19,143
or partial opioid agonist?

5355
04:24:19,143 --> 04:24:20,812
So people generally
think that --

5356
04:24:20,812 --> 04:24:23,081
does that mean
it would not help in pain?

5357
04:24:23,081 --> 04:24:27,452
But that's not true. It is --
the NLG effects are there,

5358
04:24:27,452 --> 04:24:29,220
but the side effects
are not there.

5359
04:24:29,220 --> 04:24:30,588
So it has become really like --

5360
04:24:30,588 --> 04:24:34,125
the use has been coming up
for this condition.

5361
04:24:34,726 --> 04:24:37,028
Other things are,
since the impact,

5362
04:24:37,028 --> 04:24:39,764
the respiratory depression
and some of the other things

5363
04:24:39,764 --> 04:24:43,501
are less, the --
you know, it would not cause --

5364
04:24:43,501 --> 04:24:46,003
hopefully it would not cause
that much of, you know,

5365
04:24:46,003 --> 04:24:48,005
death or overdose death

5366
04:24:48,005 --> 04:24:50,775
as the other opioids
can do that.

5367
04:24:50,775 --> 04:24:53,111
Other important thing
is it's hepatically

5368
04:24:53,111 --> 04:24:54,779
or it's cleared by liver.

5369
04:24:54,779 --> 04:24:57,148
So if individuals have renal
impairment,

5370
04:24:57,148 --> 04:24:59,117
it can be used for them as well.

5371
04:25:00,918 --> 04:25:03,421
So how about --
so buprenorphine has not --

5372
04:25:03,421 --> 04:25:07,258
has been used in other painful
condition as you can see here,

5373
04:25:07,258 --> 04:25:09,694
and also for
sickle cell disease.

5374
04:25:09,694 --> 04:25:11,329
So how do we do that?

5375
04:25:11,329 --> 04:25:14,098
So there are different protocols
and you can look up.

5376
04:25:14,098 --> 04:25:16,701
So I have put some
of the studies up here.

5377
04:25:16,701 --> 04:25:18,035
So this can be done,

5378
04:25:18,035 --> 04:25:21,839
this transition from opioid
or morphine or oxycodone

5379
04:25:21,839 --> 04:25:25,710
and things like that can be
changed to buprenorphine.

5380
04:25:25,710 --> 04:25:29,881
It can be done inpatient
outpatient or even at home.

5381
04:25:29,881 --> 04:25:33,084
The principle is such that,
you know, the solid line

5382
04:25:33,084 --> 04:25:34,685
is the opioid agonist.

5383
04:25:34,685 --> 04:25:37,822
So it could be long-acting
opioid or things like that.

5384
04:25:37,822 --> 04:25:42,059
So they -- this person is on
high MME or morphine equivalent.

5385
04:25:42,059 --> 04:25:45,163
So what you do
is this dose comes down

5386
04:25:45,163 --> 04:25:48,299
and the buprenorphine
dose comes up.

5387
04:25:48,299 --> 04:25:50,234
So at some point the patient
would be fully

5388
04:25:50,234 --> 04:25:52,403
transitioned to buprenorphine

5389
04:25:52,403 --> 04:25:55,606
while they are monitored
for the withdrawal symptom.

5390
04:25:55,606 --> 04:25:58,242
So this -- so this is just
the general principle

5391
04:25:58,242 --> 04:26:00,344
and there are many path --
many --

5392
04:26:00,344 --> 04:26:02,713
there are many protocols
that can be used

5393
04:26:02,713 --> 04:26:04,682
and the references are in here.

5394
04:26:04,682 --> 04:26:06,484
So I'm in pediatrics and what --

5395
04:26:06,484 --> 04:26:08,452
how we have been using
at our center

5396
04:26:08,452 --> 04:26:11,389
is we are gradually
coming down on opioid

5397
04:26:11,389 --> 04:26:13,324
and slowly going up
on buprenorphine

5398
04:26:13,324 --> 04:26:16,494
rather than just stopping
the drug totally at one time.

5399
04:26:18,296 --> 04:26:20,498
So is this beneficial?

5400
04:26:20,498 --> 04:26:23,434
So this is some of the data
as you can see on the left side.

5401
04:26:23,434 --> 04:26:25,469
This is the pre-induction.

5402
04:26:25,469 --> 04:26:28,639
As you can see, the patients
were admitted or acute care

5403
04:26:28,639 --> 04:26:32,243
visit multiple visits.
And this is the post-induction.

5404
04:26:32,243 --> 04:26:35,346
So you can see the difference
was significant.

5405
04:26:35,346 --> 04:26:37,448
And so average number from 10

5406
04:26:38,182 --> 04:26:40,551
in past six months
reduced to three.

5407
04:26:40,551 --> 04:26:43,354
So this was like, you know,
significant reduction

5408
04:26:43,354 --> 04:26:46,257
in acute visit
for acute pain.

5409
04:26:46,257 --> 04:26:49,327
And patients who continued
longer beyond six months,

5410
04:26:49,327 --> 04:26:51,162
they continue to have
similar effects.

5411
04:26:51,162 --> 04:26:53,831
So these were really
clear benefit

5412
04:26:53,831 --> 04:26:55,433
of buprenorphine therapy.

5413
04:26:56,033 --> 04:27:00,004
And listed here is again
continuing with the similar,

5414
04:27:00,004 --> 04:27:02,440
you know, buprenorphine
in sickle cell disease.

5415
04:27:02,440 --> 04:27:04,609
So as you can see,
the acute care visits,

5416
04:27:04,609 --> 04:27:06,544
ED visit, infusion visit,

5417
04:27:06,544 --> 04:27:09,013
acute care visit
and hospitalization,

5418
04:27:09,013 --> 04:27:12,683
they all reduced significantly
as you can see pre-induction

5419
04:27:12,683 --> 04:27:14,285
and here post-induction.

5420
04:27:14,819 --> 04:27:17,755
Other interesting thing
that I thought was not

5421
04:27:17,755 --> 04:27:20,391
only that acute care
visit went down,

5422
04:27:20,391 --> 04:27:24,462
but non-acute care visit
came up, which is really good

5423
04:27:24,462 --> 04:27:26,964
because our patients
were not coming to the ER

5424
04:27:26,964 --> 04:27:30,668
or coming for pain medication
but coming to the clinic more

5425
04:27:30,668 --> 04:27:32,470
for their health
maintenance visit.

5426
04:27:34,472 --> 04:27:37,575
So what -- what was the American
Society of Hematology

5427
04:27:37,575 --> 04:27:39,911
guidelines set
about buprenorphine?

5428
04:27:39,911 --> 04:27:43,614
They commented that there is
experience with buprenorphine

5429
04:27:43,614 --> 04:27:45,716
and other chronic
pain condition.

5430
04:27:45,716 --> 04:27:48,152
And these studies
are research priority,

5431
04:27:48,152 --> 04:27:50,288
so it should be studied further,

5432
04:27:50,288 --> 04:27:53,591
so can be done safely
in our patient population.

5433
04:27:55,092 --> 04:27:58,129
So also it's important
when we offer a treatment

5434
04:27:58,129 --> 04:27:59,363
to our patients,

5435
04:27:59,363 --> 04:28:02,199
how would they decide,
should I take this medication,

5436
04:28:02,199 --> 04:28:04,502
should I give up
my opioids or not?

5437
04:28:04,502 --> 04:28:06,904
So I thought this was
really nice paper.

5438
04:28:06,904 --> 04:28:09,540
Looking at this paper
interviewed --

5439
04:28:09,540 --> 04:28:11,208
the author
interviewed individuals

5440
04:28:11,208 --> 04:28:12,443
who had sickle cell disease

5441
04:28:12,443 --> 04:28:15,680
and transitioned from opioid
to buprenorphine

5442
04:28:15,680 --> 04:28:18,482
to see what did
they think about it.

5443
04:28:18,482 --> 04:28:21,352
So they classified this
into three themes.

5444
04:28:21,352 --> 04:28:23,955
So first of all, patient has
to decide like, okay,

5445
04:28:23,955 --> 04:28:26,824
I want to do it
because as we may say things,

5446
04:28:26,824 --> 04:28:29,827
but unless they hear from --
you know,

5447
04:28:29,827 --> 04:28:32,663
unless they do their research
and decide to do that,

5448
04:28:32,663 --> 04:28:35,733
it's not going to happen.
Second important thing is here

5449
04:28:35,733 --> 04:28:37,601
because if there is
some uncertainty,

5450
04:28:37,601 --> 04:28:40,805
I'd switch to this medication,
would it help in my pain?

5451
04:28:40,805 --> 04:28:44,375
And how do our patients
get their information?

5452
04:28:44,375 --> 04:28:47,745
So obviously personal decision,
do their own research,

5453
04:28:47,745 --> 04:28:50,514
but also important to hear
from other patients

5454
04:28:50,514 --> 04:28:51,782
who have sickle cell disease.

5455
04:28:51,782 --> 04:28:54,552
So that's important that we
educate the whole community,

5456
04:28:54,552 --> 04:28:57,788
not just one patient.
And also look at the other --

5457
04:28:57,788 --> 04:29:01,192
so patients reported the --
their symptoms improved.

5458
04:29:01,192 --> 04:29:03,861
So importance of patient
reported outcome,

5459
04:29:03,861 --> 04:29:06,630
the improved social function,
personal function,

5460
04:29:06,630 --> 04:29:08,966
and also changes
with the pain medication.

5461
04:29:08,966 --> 04:29:11,602
They looked at opioid
differently and,

5462
04:29:11,602 --> 04:29:14,138
but also they identified
some of the problems.

5463
04:29:14,138 --> 04:29:16,741
And we have faced this
in our clinic as well.

5464
04:29:17,475 --> 04:29:19,510
Barriers related to like stigma

5465
04:29:19,510 --> 04:29:23,014
because the suboxone
or buprenorphine is listed

5466
04:29:23,014 --> 04:29:25,416
as opioid use disorder drug.

5467
04:29:25,416 --> 04:29:27,985
So if you see that medication
was prescribed to you,

5468
04:29:27,985 --> 04:29:31,622
people may think they may feel
stigmatized for that.

5469
04:29:31,622 --> 04:29:35,593
And also coverage by insurance.
And this has happened to me

5470
04:29:35,593 --> 04:29:37,862
because suddenly insurance
would decide like,

5471
04:29:37,862 --> 04:29:39,497
oh, they need
prior authorization

5472
04:29:39,497 --> 04:29:42,466
and they had to stop medication,
which you cannot do that.

5473
04:29:42,466 --> 04:29:44,135
So these are some
of the challenges

5474
04:29:44,135 --> 04:29:46,570
and some of the benefits
that came out from that.

5475
04:29:47,872 --> 04:29:50,608
Last but not the least,
I'll talk about ketamine.

5476
04:29:51,876 --> 04:29:56,480
So ketamine also has been
first synthesized in 1960s

5477
04:29:56,480 --> 04:30:00,618
and it was tested for --
because it was a fast anesthetic

5478
04:30:00,618 --> 04:30:04,822
and a short half-life
and relatively safe drug.

5479
04:30:04,822 --> 04:30:08,259
So it was used
quite a bit in war setting.

5480
04:30:08,259 --> 04:30:11,228
So like a battlefield anesthesia
and things like that.

5481
04:30:11,228 --> 04:30:12,463
But at the same time,

5482
04:30:12,463 --> 04:30:15,232
people learned
about the side effects.

5483
04:30:15,232 --> 04:30:18,502
So delirium, dysphoria, some
of these things were identified.

5484
04:30:18,502 --> 04:30:21,772
So that kind of, you know,
it was not used as much.

5485
04:30:21,772 --> 04:30:24,875
In recent year, we have started
to think more, you know,

5486
04:30:24,875 --> 04:30:28,879
about ketamine because of the --
some of the analgesic property

5487
04:30:28,879 --> 04:30:31,649
and things like that,
and especially refractory pain.

5488
04:30:32,516 --> 04:30:35,453
So it's
a dissociative anesthetic.

5489
04:30:35,453 --> 04:30:39,623
And the important thing is that
it acts on the NMDA receptor.

5490
04:30:39,623 --> 04:30:43,160
So NMDA receptor is very
important in chronic pain.

5491
04:30:43,694 --> 04:30:46,063
And so it's -- that --

5492
04:30:46,063 --> 04:30:48,499
this is the population
and our clinic also,

5493
04:30:48,499 --> 04:30:51,402
we use quite a bit patients
who have chronic pain

5494
04:30:51,402 --> 04:30:53,571
and develop acute pain
on chronic pain.

5495
04:30:53,571 --> 04:30:55,573
So that is, it can be used.

5496
04:30:55,573 --> 04:30:58,642
Not only it acts
on NMDA receptor,

5497
04:30:58,642 --> 04:31:01,212
but other receptors or --

5498
04:31:01,212 --> 04:31:03,514
and other pathways,
it's also effective.

5499
04:31:03,514 --> 04:31:07,518
So that's the benefit of that.
So it works on opioid pathways

5500
04:31:07,518 --> 04:31:09,620
and some of these,
as you are listed here.

5501
04:31:11,555 --> 04:31:13,691
So ketamine
and sickle cell disease.

5502
04:31:13,691 --> 04:31:16,894
So keta, if you look up the --
do the search of ketamine

5503
04:31:16,894 --> 04:31:20,397
and sickle cell disease,
you would see lot of papers.

5504
04:31:20,397 --> 04:31:23,134
The problem is everyone
has done their own thing,

5505
04:31:23,134 --> 04:31:25,803
including our group,
looking at like --

5506
04:31:25,803 --> 04:31:28,272
you know, so sometimes
we all would use it in clinic,

5507
04:31:28,272 --> 04:31:31,876
sometimes in ED,
sometimes inpatient or ICU.

5508
04:31:31,876 --> 04:31:34,211
So really we cannot look
at the data together.

5509
04:31:35,412 --> 04:31:37,615
And it's --
and also same thing, dosage.

5510
04:31:37,615 --> 04:31:41,452
So dose has been variable
and root has been a variable.

5511
04:31:41,452 --> 04:31:44,054
So intranasal versus IV,
et cetera.

5512
04:31:44,755 --> 04:31:47,491
Also, then most of the time,
how do we decide

5513
04:31:47,491 --> 04:31:51,028
when is it time to use?
Ketamine is typically left

5514
04:31:51,028 --> 04:31:52,963
to the patient
physician's discretion.

5515
04:31:52,963 --> 04:31:55,799
So first the physician
has to decide, now,

5516
04:31:55,799 --> 04:31:58,369
my patient has chronic pain,
refractory pain,

5517
04:31:58,369 --> 04:32:00,204
and they may benefit from that.

5518
04:32:00,871 --> 04:32:02,873
We do should not --
we should not forget

5519
04:32:02,873 --> 04:32:05,176
that there are associated
side effects.

5520
04:32:05,176 --> 04:32:09,213
So they're psychotomimetic, and
as you can read all these here,

5521
04:32:09,213 --> 04:32:10,814
these are some of
the side effects

5522
04:32:10,814 --> 04:32:12,416
that can happen with ketamine.

5523
04:32:12,983 --> 04:32:16,987
So it's important that --
it's a useful drug,

5524
04:32:16,987 --> 04:32:19,156
but people need to be familiar
with the drug

5525
04:32:19,156 --> 04:32:22,092
and we cannot use just randomly.

5526
04:32:22,660 --> 04:32:26,163
And if -- it has received
a lot of attention recently.

5527
04:32:26,163 --> 04:32:28,732
So if you do just ketamine
and pain,

5528
04:32:28,732 --> 04:32:30,701
I tried to do that
and I got like,

5529
04:32:30,701 --> 04:32:32,836
you know,
I could buy ketamine here,

5530
04:32:32,836 --> 04:32:35,773
so you can buy for anxiety
or depression

5531
04:32:35,773 --> 04:32:40,277
or anything like that online.
And you can get it.

5532
04:32:40,277 --> 04:32:42,880
But also people like
to make money and it's --

5533
04:32:42,880 --> 04:32:45,816
it has become really
a big industry

5534
04:32:45,816 --> 04:32:47,218
with lot of side effects.

5535
04:32:47,218 --> 04:32:50,354
So as you can see it here,
it has been on news.

5536
04:32:50,354 --> 04:32:52,489
So like initially,
if you look at --

5537
04:32:52,489 --> 04:32:55,192
it's kind of interesting
to see the timeline.

5538
04:32:55,192 --> 04:32:58,095
You would -- first you'll see
all the benefits of ketamine,

5539
04:32:58,095 --> 04:33:02,733
then FDA issue of misuse of you
know, ketamine and other thing.

5540
04:33:02,733 --> 04:33:06,537
And after Matthew Perry's death,
it has become --

5541
04:33:06,537 --> 04:33:08,739
gained, like,
a lot of attention on ketamine

5542
04:33:08,739 --> 04:33:13,811
and how to do it safely.
So again, going back

5543
04:33:13,811 --> 04:33:16,780
to the American Society
of Hematology guidelines.

5544
04:33:16,780 --> 04:33:19,650
So they gave it conditional
recommendation.

5545
04:33:19,650 --> 04:33:21,318
And the reason for that is --

5546
04:33:21,318 --> 04:33:25,122
so they suggested it can be used
for acute or chronic pain

5547
04:33:25,122 --> 04:33:27,324
in patients
with sickle cell disease.

5548
04:33:27,324 --> 04:33:30,027
And the -- and here
they also give the dose.

5549
04:33:30,027 --> 04:33:33,364
So it's used in the
sub-anesthetic or small dose.

5550
04:33:34,064 --> 04:33:38,435
So it's generally 0.1, to 0.3
milligram per kilo per hour

5551
04:33:38,435 --> 04:33:39,637
and up to 1.

5552
04:33:39,637 --> 04:33:41,272
So that's, like,
the maximum dose.

5553
04:33:41,272 --> 04:33:45,676
So Azure guidelines gives us
that dose and again,

5554
04:33:45,676 --> 04:33:48,846
leaves some of the room
for like physician discretion.

5555
04:33:48,846 --> 04:33:52,016
And those are acute pain
that is refractory

5556
04:33:52,016 --> 04:33:53,384
in the treating
physician's opinion.

5557
04:33:53,384 --> 04:33:54,618
So there are no --

5558
04:33:54,618 --> 04:33:57,821
and we don't have
a definition of refractory pain.

5559
04:33:57,821 --> 04:33:59,790
So it kind of ends
with the physician

5560
04:33:59,790 --> 04:34:01,625
when they want to try that.

5561
04:34:01,625 --> 04:34:04,561
They also make comment,
it's important to do

5562
04:34:04,561 --> 04:34:08,532
safe administration
of the medication,

5563
04:34:08,532 --> 04:34:13,103
and also only if the expertise
is available at a institution

5564
04:34:13,103 --> 04:34:14,705
to do it safely.

5565
04:34:15,973 --> 04:34:19,810
So in conclusion, we all know
that acute and chronic pain

5566
04:34:19,810 --> 04:34:22,079
is common
in sickle cell disease.

5567
04:34:22,079 --> 04:34:24,381
Current treatment
is opioid centric,

5568
04:34:24,381 --> 04:34:26,917
which is associated
with many side effects

5569
04:34:26,917 --> 04:34:29,019
and may not be effective.

5570
04:34:29,019 --> 04:34:32,056
Cannabinoids are often
used by our patients.

5571
04:34:32,056 --> 04:34:34,892
However, we don't have data
on efficacy

5572
04:34:34,892 --> 04:34:37,294
and we don't know the risk
and adverse effect

5573
04:34:37,294 --> 04:34:40,497
and especially its impact
on the developing teen brains,

5574
04:34:40,497 --> 04:34:41,732
which are where the --

5575
04:34:41,732 --> 04:34:44,134
in this population,
the use is increasing.

5576
04:34:44,835 --> 04:34:48,005
Buprenorphine, a mixed agonist
and agonist

5577
04:34:48,005 --> 04:34:50,007
opioid receptor modulator,

5578
04:34:50,007 --> 04:34:53,444
it was shown to be effective
in sickle cell population.

5579
04:34:53,444 --> 04:34:56,313
It was effective
in reducing pain,

5580
04:34:56,313 --> 04:34:57,981
reduced acute care visit,

5581
04:34:57,981 --> 04:35:00,317
and also opioid use
in small studies.

5582
04:35:00,317 --> 04:35:01,819
So all the studies I showed,

5583
04:35:01,819 --> 04:35:04,221
these are like small studies,
open label.

5584
04:35:05,389 --> 04:35:07,591
Use is increasing
in sickle cell disease,

5585
04:35:07,591 --> 04:35:10,027
but barriers still exist
for its use.

5586
04:35:11,128 --> 04:35:13,864
Ketamine is --
can be used for chronic

5587
04:35:13,864 --> 04:35:16,500
or refractory pain
and conditionally --

5588
04:35:16,500 --> 04:35:18,836
right now it's approved
conditionally.

5589
04:35:19,737 --> 04:35:21,839
Recommended because
of the limited data.

5590
04:35:21,839 --> 04:35:24,541
So we may need to have more data
so that it can get --

5591
04:35:25,142 --> 04:35:28,912
and I talked about mostly, like,
the pharmaceutical agent,

5592
04:35:28,912 --> 04:35:31,014
but as we heard earlier
in the talk,

5593
04:35:31,014 --> 04:35:34,118
they're like whole area of the
non-pharmacologic approaches

5594
04:35:34,118 --> 04:35:37,154
also that can be integrated
in the care,

5595
04:35:37,154 --> 04:35:40,124
so we can avoid the side
effect of different things.

5596
04:35:40,724 --> 04:35:43,260
That's it. Thank you so much
for your attention.

5597
04:35:49,466 --> 04:35:51,201
Zachary Ramsay: All right.
So thanks for that talk,

5598
04:35:51,201 --> 04:35:53,070
which is the last one
for the session,

5599
04:35:53,070 --> 04:35:57,241
but we're going to welcome two
quick questions if anybody has.

5600
04:36:04,615 --> 04:36:07,818
Male Speaker: Hi. Great talk.
Thank you for the review.

5601
04:36:07,818 --> 04:36:11,121
So regarding cannabis,
to the best of our knowledge,

5602
04:36:11,889 --> 04:36:15,159
does use --
how does use affect perhaps

5603
04:36:15,159 --> 04:36:17,561
the incidences
of acute chest syndrome, right?

5604
04:36:17,561 --> 04:36:19,696
It's a type of smoking,

5605
04:36:19,696 --> 04:36:21,365
but at the same time
you might be treating pain

5606
04:36:21,365 --> 04:36:24,334
that you could argue it can go
almost back and forth

5607
04:36:24,334 --> 04:36:26,703
and obviously we're still
at the research level.

5608
04:36:26,703 --> 04:36:28,205
So I'd love your thoughts
on that.

5609
04:36:28,205 --> 04:36:31,208
And then number two,
what are your thoughts?

5610
04:36:31,208 --> 04:36:35,179
Again, it's still -- we're still
in the investigation stages,

5611
04:36:35,179 --> 04:36:37,981
but the different
formulations of cannabis,

5612
04:36:37,981 --> 04:36:41,452
whether it's the synthetic forms
or the derivatives

5613
04:36:41,452 --> 04:36:45,289
or even the different ways
to deliver the --

5614
04:36:45,289 --> 04:36:46,957
I think there's different
formulations these days,

5615
04:36:46,957 --> 04:36:48,192
so I'd love
your thoughts on that.

5616
04:36:48,192 --> 04:36:49,460
Deepika Darbari: Okay.

5617
04:36:49,460 --> 04:36:52,296
So first of all, disclosure,
I'm a pediatrician [laughs],

5618
04:36:52,296 --> 04:36:54,231
so I don't prescribe
any cannabis

5619
04:36:54,231 --> 04:36:56,700
to any of my patient [laughs].

5620
04:36:56,700 --> 04:36:59,203
And second thing,
I do want to say, like,

5621
04:36:59,203 --> 04:37:02,573
you know, my approach has been
more like whole person care

5622
04:37:02,573 --> 04:37:05,342
because as a pediatrician,
my goal is to make our patients

5623
04:37:05,342 --> 04:37:08,412
independent and in future
they can support themselves.

5624
04:37:08,412 --> 04:37:11,381
So when I counsel them,
I said, if I'm taking marijuana,

5625
04:37:11,381 --> 04:37:13,817
do you think my hospital
will keep me employed?

5626
04:37:13,817 --> 04:37:15,152
And answer is no.

5627
04:37:15,152 --> 04:37:17,321
So what makes you think
that you would be using?

5628
04:37:17,321 --> 04:37:19,156
But that's not your question.

5629
04:37:19,156 --> 04:37:21,859
So your question is like,
you know, of what kind of --

5630
04:37:22,559 --> 04:37:24,261
how can we use it?

5631
04:37:24,261 --> 04:37:25,863
So the one trial
that was used --

5632
04:37:25,863 --> 04:37:28,599
that used the inhaled vaporized,

5633
04:37:28,599 --> 04:37:32,402
but there was a side effect
of like in that study of acute

5634
04:37:32,402 --> 04:37:33,737
and in the case --

5635
04:37:33,737 --> 04:37:35,572
so there were certain
side effects,

5636
04:37:35,572 --> 04:37:38,809
smoking in general, marijuana
or something else

5637
04:37:38,809 --> 04:37:40,811
we don't recommend
for our patients

5638
04:37:40,811 --> 04:37:44,648
just because, you know
risk of acute chest syndrome.

5639
04:37:44,648 --> 04:37:46,783
Because smoking is just bad.

5640
04:37:46,783 --> 04:37:51,021
So if our patients, if they are
taking the compound or any --

5641
04:37:51,021 --> 04:37:52,823
so we would suggest
like it's better

5642
04:37:52,823 --> 04:37:55,993
to take maybe edible
than smoking.

5643
04:37:56,793 --> 04:37:58,862
So those are
the really main thing.

5644
04:37:58,862 --> 04:38:01,031
And I don't think
we have enough information

5645
04:38:01,031 --> 04:38:03,600
on synthetic versus you know,

5646
04:38:03,600 --> 04:38:07,237
natural forms of marijuana
or any other drug.

5647
04:38:07,237 --> 04:38:09,573
And there was a article,
I want to say maybe New York

5648
04:38:09,573 --> 04:38:12,075
Times,
but they said if you think about

5649
04:38:12,075 --> 04:38:15,512
what people smoked maybe 30
or 40 years ago,

5650
04:38:15,512 --> 04:38:19,149
it's very different from
what's available in market now.

5651
04:38:19,149 --> 04:38:21,818
So maybe the compound
which was smoked by,

5652
04:38:21,818 --> 04:38:24,555
you know, older generation
that was much more pure

5653
04:38:24,555 --> 04:38:27,357
and didn't have
all these additive.

5654
04:38:27,357 --> 04:38:29,393
So it's kind of has become
very dangerous

5655
04:38:29,393 --> 04:38:31,228
because they have certain
other things

5656
04:38:31,228 --> 04:38:33,230
added to it for more effect,

5657
04:38:33,230 --> 04:38:35,666
and that's contributing
to more of a problem.

5658
04:38:35,666 --> 04:38:38,735
So hopefully there'll be
more research in this area,

5659
04:38:38,735 --> 04:38:40,671
but we don't have
a lot of answer.

5660
04:38:40,671 --> 04:38:42,272
Yes.

5661
04:38:45,976 --> 04:38:48,645
Male Speaker: So do you know
the number of recorded

5662
04:38:49,780 --> 04:38:52,716
overdoses of marijuana use?

5663
04:38:54,851 --> 04:38:56,153
Deepika Darbari:
No, I don't know.

5664
04:38:56,153 --> 04:38:58,655
I mean, I can guess it's high,
but I don't know.

5665
04:38:58,655 --> 04:38:59,890
Male Speaker: No, it's
actually zero.

5666
04:38:59,890 --> 04:39:01,124
There are --

5667
04:39:01,124 --> 04:39:04,161
there are no recorded
overdoses of marijuana use.

5668
04:39:04,161 --> 04:39:05,362
Deepika Darbari: Okay.

5669
04:39:05,362 --> 04:39:06,863
Male Speaker: And opioids
are now at,

5670
04:39:06,863 --> 04:39:09,666
what, like, 110,000 deaths
in the U.S. last year?

5671
04:39:09,666 --> 04:39:10,867
Deepika Darbari: Yeah.
No, absolutely.

5672
04:39:10,867 --> 04:39:14,171
I'm not suggesting opioids
are better or, you know --

5673
04:39:14,838 --> 04:39:16,673
you know, marijuana,
which one is better,

5674
04:39:16,673 --> 04:39:20,877
but I'm just suggesting that we
should think about side effect

5675
04:39:20,877 --> 04:39:24,548
and what's the person's goal is.
You know, pain control,

5676
04:39:24,548 --> 04:39:27,451
there are other things that can
be used for controlling pain.

5677
04:39:27,451 --> 04:39:29,953
That would be my --
especially for pediatrics.

5678
04:39:30,754 --> 04:39:33,090
Cheryl Stucky: Well, and I think
specific to pediatrics,

5679
04:39:33,090 --> 04:39:37,227
so in our state
where products were legalized,

5680
04:39:37,227 --> 04:39:40,297
we've seen in pediatrics
an increase in toxicity

5681
04:39:40,297 --> 04:39:43,000
in like very young children
who found the products.

5682
04:39:43,567 --> 04:39:47,471
So there are overdoses
in that regard. So --

5683
04:39:48,705 --> 04:39:49,973
Deepika Darbari: Yeah,
and that was the one

5684
04:39:49,973 --> 04:39:52,943
of the things like, for example,
Colorado and other states,

5685
04:39:52,943 --> 04:39:55,846
they said if the stuff
is legalized,

5686
04:39:55,846 --> 04:39:59,816
it'll reduce the use
and mortality and accident.

5687
04:39:59,816 --> 04:40:02,119
So you may not die
from overdose,

5688
04:40:02,119 --> 04:40:04,354
but you may be driving
under the influence

5689
04:40:04,354 --> 04:40:06,189
and may get killed
and kill others as well.

5690
04:40:06,189 --> 04:40:07,391
So --

5691
04:40:07,391 --> 04:40:08,625
Jane Little: Hey, Dipaki,
that was great.

5692
04:40:08,625 --> 04:40:09,626
Deepika Darbari: Thank you.

5693
04:40:09,626 --> 04:40:10,861
Jane Little: It's
Jane over here.

5694
04:40:10,861 --> 04:40:12,095
Jane Little.
Deepika Darbari: Yes.

5695
04:40:12,095 --> 04:40:13,497
Jane Little: How do you
integrate mental health

5696
04:40:13,497 --> 04:40:18,301
into this kind of view
of different medications

5697
04:40:18,301 --> 04:40:20,270
that you use?
Like do you bring it --

5698
04:40:20,871 --> 04:40:22,239
we try to bring it
in very early,

5699
04:40:22,239 --> 04:40:24,174
but I don't know
if that's universal.

5700
04:40:24,174 --> 04:40:26,643
Deepika Darbari: Yeah,
so we have a --

5701
04:40:26,643 --> 04:40:28,979
we have this clinic
called integrative clinic

5702
04:40:28,979 --> 04:40:32,816
or whole-person care where all
the medications are discussed.

5703
04:40:32,816 --> 04:40:35,485
Obviously the first treatment
is like sickle cell disease

5704
04:40:35,485 --> 04:40:38,822
modifying therapy
along like hydroxyurea.

5705
04:40:38,822 --> 04:40:40,891
But all these things
are offered.

5706
04:40:40,891 --> 04:40:43,160
So if, for example,
ketamine is --

5707
04:40:43,160 --> 04:40:45,228
we use often in ketamine,

5708
04:40:45,228 --> 04:40:47,698
and mostly it's like patients
who may have chronic pain

5709
04:40:47,698 --> 04:40:50,967
and admitted only
in inpatient setting,

5710
04:40:50,967 --> 04:40:53,403
and there's a limit
on how much can you use.

5711
04:40:53,403 --> 04:40:55,906
So not more than once a month,
for example.

5712
04:40:55,906 --> 04:40:57,240
So those are the patient --

5713
04:40:57,240 --> 04:40:59,309
and not ketamine
doesn't work for everyone.

5714
04:40:59,309 --> 04:41:01,011
So there are some patients
who would like it,

5715
04:41:01,011 --> 04:41:02,779
but others don't want to try it.

5716
04:41:03,547 --> 04:41:06,883
Then for buprenorphine,
we are using more now,

5717
04:41:06,883 --> 04:41:08,852
and those are typically
the patients

5718
04:41:08,852 --> 04:41:11,555
who have been
on high doses of opioid

5719
04:41:11,555 --> 04:41:14,324
and more like chronic
opioid therapy.

5720
04:41:14,324 --> 04:41:17,194
But it's -- it --
mental health is so important

5721
04:41:17,194 --> 04:41:19,363
because many times pain is --

5722
04:41:19,363 --> 04:41:20,697
you know,
because of the anxiety,

5723
04:41:20,697 --> 04:41:22,833
depression and some of
the other things.

5724
04:41:22,833 --> 04:41:25,535
So if you don't correct those,
then you know, it's --

5725
04:41:25,535 --> 04:41:26,737
it may not work.

5726
04:41:26,737 --> 04:41:29,239
So our approach has been
a comprehensive approach.

5727
04:41:29,239 --> 04:41:32,109
We are lucky to have
a psychologist in our --

5728
04:41:32,109 --> 04:41:35,212
in our clinic as well
as working with a psychiatrist

5729
04:41:35,212 --> 04:41:37,347
who has this interest
in buprenorphine

5730
04:41:37,347 --> 04:41:39,049
in sickle cell disease.

5731
04:41:39,049 --> 04:41:41,651
So we have been kind of
bring it together, give --

5732
04:41:41,651 --> 04:41:43,720
educate our families
and hopefully,

5733
04:41:43,720 --> 04:41:46,623
you know, they'll get better.
Thank you.

5734
04:41:48,792 --> 04:41:50,394
Okay. Thank you so much.

5735
04:41:55,565 --> 04:41:57,501
Haydar Frangoul: Well,
thank you everybody.

5736
04:41:57,501 --> 04:42:00,604
I have the pleasure of be
chairing the next session

5737
04:42:00,604 --> 04:42:04,141
on the mechanism based therapies
for sickle cell disease.

5738
04:42:04,141 --> 04:42:06,643
I would like to commend
the previous session

5739
04:42:06,643 --> 04:42:07,978
because they stayed on time.

5740
04:42:07,978 --> 04:42:09,813
So my goal is
to stay on time here.

5741
04:42:10,514 --> 04:42:13,216
So this session is
what's keeping you guys away

5742
04:42:13,216 --> 04:42:15,051
from happy hour
and dinner, by the way.

5743
04:42:15,051 --> 04:42:16,586
So we just need
to keep it on time.

5744
04:42:16,586 --> 04:42:20,690
So it is my pleasure
to introduce Dr. Daniel Bauer

5745
04:42:21,925 --> 04:42:24,094
who is the
Donald Frederickson Associate

5746
04:42:24,094 --> 04:42:27,364
Professor of pediatrics
at Harvard Medical School

5747
04:42:27,364 --> 04:42:29,065
and the director
of the gene therapy program

5748
04:42:29,065 --> 04:42:31,201
at Boston Children's Hospital.

5749
04:42:31,201 --> 04:42:33,703
Dr. Bauer was not able
to attend the meeting,

5750
04:42:33,703 --> 04:42:37,440
so he's going to deliver
his talk virtually.

5751
04:42:37,440 --> 04:42:39,609
So I think they are
going to queue it in.

5752
04:42:57,027 --> 04:42:58,628
Daniel Bauer: Hi,
can you hear me?

5753
04:43:00,463 --> 04:43:04,134
Great. Here.
Let me share.

5754
04:43:11,541 --> 04:43:18,715
All right.
It's a bit of an echo for me.

5755
04:43:21,551 --> 04:43:25,489
Okay.
Well, please let me know

5756
04:43:25,489 --> 04:43:27,991
if there's any problem
technically,

5757
04:43:27,991 --> 04:43:34,264
and thanks Swee Lay and John
and all for the opportunity

5758
04:43:34,264 --> 04:43:37,033
to participate
in this terrific meeting.

5759
04:43:37,033 --> 04:43:39,703
I'm really sorry
I couldn't be there in person.

5760
04:43:40,971 --> 04:43:49,279
I -- okay, great.
I'm just looking at the chat.

5761
04:43:50,513 --> 04:43:53,550
Yeah. So anyway,
I just came off hematology

5762
04:43:53,550 --> 04:43:55,151
inpatient service this morning.

5763
04:43:56,419 --> 04:43:59,256
And I think many of us
are facing cognitive dissonance

5764
04:43:59,256 --> 04:44:02,826
where on the one hand we have
this remarkable opportunity

5765
04:44:02,826 --> 04:44:05,595
to offer sickle cell
disease patients

5766
04:44:05,595 --> 04:44:08,698
approved genetic
medicine service.

5767
04:44:08,698 --> 04:44:10,667
We discussed
and consider gene

5768
04:44:10,667 --> 04:44:13,470
therapy options role
of our patients.

5769
04:44:13,470 --> 04:44:15,171
And actually we got input
from Jane

5770
04:44:15,171 --> 04:44:16,773
Little whose voice I just heard.

5771
04:44:17,274 --> 04:44:22,646
On the other hand, the therapies
are complex, costly, toxic,

5772
04:44:22,646 --> 04:44:25,115
and cannot scale to address
the unmet clinical

5773
04:44:25,115 --> 04:44:28,551
need of an underestimated
300,000 babies

5774
04:44:28,551 --> 04:44:31,187
born around the world each year
with sickle cell disease.

5775
04:44:31,187 --> 04:44:32,722
And so I would argue this means

5776
04:44:32,722 --> 04:44:35,358
we still need to develop
better approaches

5777
04:44:35,358 --> 04:44:38,495
that are simpler, safer,
and more effective.

5778
04:44:43,600 --> 04:44:45,268
Here's my disclosures.

5779
04:44:46,970 --> 04:44:50,240
So clinical observations
dating back to those

5780
04:44:50,807 --> 04:44:54,244
from Janet Watson in the 1940s
indicate that newborns

5781
04:44:54,244 --> 04:44:56,746
with sickle cell disease
are protected

5782
04:44:56,746 --> 04:44:59,816
due to the high level
expression of fetal hemoglobin.

5783
04:45:01,718 --> 04:45:04,955
Disease only begins once,
fetal gamma globin,

5784
04:45:05,789 --> 04:45:09,693
the paralogue and genomic
neighbor of adult beta globin

5785
04:45:09,693 --> 04:45:12,262
has been transcriptionally
silenced after birth.

5786
04:45:13,096 --> 04:45:15,265
A longstanding goal
of hematology

5787
04:45:15,265 --> 04:45:17,233
has been to deeply
understand hemoglobin

5788
04:45:17,233 --> 04:45:21,471
switching to enable therapeutic
induction of fetal hemoglobin.

5789
04:45:23,106 --> 04:45:26,242
When I joined Stuart Orkin's Lab
as a hematology fellow,

5790
04:45:26,242 --> 04:45:28,845
I became interested in how
common genetic variation

5791
04:45:29,446 --> 04:45:32,716
at BCL11A
influenced fetal hemoglobin.

5792
04:45:33,616 --> 04:45:36,953
We observed that the disease
associated in chronic

5793
04:45:36,953 --> 04:45:39,756
SNPs identified in Swee Lay's

5794
04:45:39,756 --> 04:45:44,527
pioneering study and validated
many times since overlapped

5795
04:45:44,527 --> 04:45:47,197
an erythroid enhancer
cloning signature.

5796
04:45:48,632 --> 04:45:52,402
We use gene editing to disrupt
the autologous regulatory

5797
04:45:52,402 --> 04:45:54,671
sequences
in a mouse erythroid cell

5798
04:45:55,505 --> 04:45:58,975
and observe that the erythroid
BCL11A enhancers

5799
04:45:58,975 --> 04:46:02,846
were selectively essential
for erythroid BCL11A expression.

5800
04:46:05,415 --> 04:46:07,217
Our CRISPR dense mutagenesis

5801
04:46:08,218 --> 04:46:10,153
where each dot shows
an individual guide

5802
04:46:10,153 --> 04:46:14,657
RNA, identified critical minimal
sequences at the BCL11A

5803
04:46:14,657 --> 04:46:17,527
enhancers that could serve
as therapeutic targets.

5804
04:46:18,395 --> 04:46:21,665
We found GATA-1 binding sites
at the plus 58

5805
04:46:21,665 --> 04:46:24,634
and plus 55 enhancers
that were required

5806
04:46:24,634 --> 04:46:26,836
for robust fetal hemoglobin
silencing.

5807
04:46:28,772 --> 04:46:31,307
So this led to a simple
therapeutic vision to disrupt

5808
04:46:31,307 --> 04:46:33,209
the BCL11A enhancer

5809
04:46:33,810 --> 04:46:37,280
in hematopoietic stem cells
leading to reduction of BCL11A

5810
04:46:37,280 --> 04:46:40,517
specifically in erythroid
precursors and subsequent,

5811
04:46:40,517 --> 04:46:42,252
the repression
of fetal hemoglobin.

5812
04:46:43,353 --> 04:46:47,357
Ex-vivo modified HSCs could
serve in an autonomous graft

5813
04:46:47,357 --> 04:46:48,958
for hematopoietic transplant.

5814
04:46:51,394 --> 04:46:54,330
Recent clinical trials by CRISPR
therapeutics

5815
04:46:54,330 --> 04:46:58,968
and Vertex have shown that in
43 sickle cell disease patients,

5816
04:46:59,502 --> 04:47:03,440
ex-vivo gene editing can produce
efficient indels in blood cells

5817
04:47:03,440 --> 04:47:04,707
with about

5818
04:47:04,707 --> 04:47:09,479
70 fives edited potent
fetal hemoglobin induction

5819
04:47:09,479 --> 04:47:12,949
comprising about 40 percent
of total hemoglobin

5820
04:47:13,850 --> 04:47:15,719
improvement
in hemolysis

5821
04:47:15,719 --> 04:47:18,521
and reduction in vaso-occlusive
episode frequency,

5822
04:47:19,222 --> 04:47:23,827
leading to the FDA approval
of CASGEVY in December, 2023.

5823
04:47:25,895 --> 04:47:29,399
Nonetheless, patients had
some residual hemolysis

5824
04:47:29,399 --> 04:47:33,369
and six out of 43 had
two episodes after therapy.

5825
04:47:34,170 --> 04:47:36,673
Long-term outcomes,
including the impact

5826
04:47:36,673 --> 04:47:40,510
on the insidious deterioration
characteristic of sickle cell

5827
04:47:40,510 --> 04:47:43,613
disease organ function
remain unknown.

5828
04:47:45,849 --> 04:47:48,184
This study from Belisario
et al.

5829
04:47:48,184 --> 04:47:52,889
reports a Brazilian cohort
of Hb S/HPFH compound,

5830
04:47:52,889 --> 04:47:56,559
heterozygous children with mean
hemoglobin about 12

5831
04:47:56,559 --> 04:47:59,929
and a half grams per deciliter
and fetal hemoglobin

5832
04:47:59,929 --> 04:48:02,966
around 42 percent,
which are similar values

5833
04:48:02,966 --> 04:48:04,968
as reported in the recent
clinical trial

5834
04:48:05,835 --> 04:48:09,172
and revealed great amelioration
of sickle cell disease,

5835
04:48:09,172 --> 04:48:12,208
but still some episodes
of acute chest syndrome.

5836
04:48:12,208 --> 04:48:15,545
Acute pain episodes
and transfusion requirements

5837
04:48:15,545 --> 04:48:17,380
suggesting
clinical manifestations

5838
04:48:17,380 --> 04:48:21,050
of sickle cell disease
were not completely reversed,

5839
04:48:22,819 --> 04:48:25,355
meaning individuals
with sickle cell trait

5840
04:48:25,355 --> 04:48:28,558
with heterozygous HBS mutation
are largely healthy.

5841
04:48:29,793 --> 04:48:32,795
Under venous oxygen tension
of about 4 percent,

5842
04:48:32,795 --> 04:48:36,766
it takes about 65 percent adult
hemoglobin to prevent sickling,

5843
04:48:37,333 --> 04:48:39,602
which is the precise
distribution of adult hemoglobin

5844
04:48:39,602 --> 04:48:41,204
found in sickle cell trait.

5845
04:48:41,738 --> 04:48:44,207
50 percent hemoglobin
will be expected

5846
04:48:44,207 --> 04:48:47,143
to achieve a similar degree
of sickling protection,

5847
04:48:47,143 --> 04:48:49,379
suggesting that slightly
more robust fetal

5848
04:48:49,379 --> 04:48:52,115
hemoglobin induction
might yield clinical outcomes,

5849
04:48:52,115 --> 04:48:53,883
non-inferior
to sickle cell trait.

5850
04:48:56,019 --> 04:48:58,621
Recent work from my lab
led by Jing Zang

5851
04:48:58,621 --> 04:49:00,957
has shown that combined
targeting of the two major

5852
04:49:00,957 --> 04:49:04,627
BCL11A erythroid enhancers
plus 58

5853
04:49:04,627 --> 04:49:08,998
and plus 55 reduces
superior enhancer disruption

5854
04:49:10,800 --> 04:49:14,037
compared to single enhancer
disruption or alternative

5855
04:49:14,037 --> 04:49:18,208
approaches like BCL11A
knockdown or gene

5856
04:49:18,208 --> 04:49:23,012
editing targeting the gamma
globin promoter minus 115 site.

5857
04:49:23,847 --> 04:49:27,050
The combined BCL11A
enhancer editing approach

5858
04:49:27,050 --> 04:49:29,552
produced the greatest fetal
hemoglobin induction

5859
04:49:29,552 --> 04:49:30,753
and prevention

5860
04:49:30,753 --> 04:49:34,691
of in vitro erythrocyte sickling
attributable to disruption

5861
04:49:34,691 --> 04:49:38,728
of both GATA-1 binding sites
at both major enhancers up

5862
04:49:38,728 --> 04:49:41,731
to four total binding sites
disrupted per cell.

5863
04:49:44,033 --> 04:49:48,204
With our colleagues John Tisdale
and Selami Demirci at NHLBI,

5864
04:49:48,204 --> 04:49:50,907
we tested this combined
enhancer gene

5865
04:49:50,907 --> 04:49:52,542
editing protocol
in the rhesus macaque,

5866
04:49:52,542 --> 04:49:56,512
non-human primate where we could
follow many of the same steps

5867
04:49:56,512 --> 04:49:59,015
as would be done in patients
including mobilizing,

5868
04:49:59,015 --> 04:50:01,818
collecting and purify
hematopoietic stem cells.

5869
04:50:01,818 --> 04:50:05,321
Prior to gene editing,
ex vivo and autologous infusion,

5870
04:50:06,155 --> 04:50:07,790
we tested cohorts.

5871
04:50:07,790 --> 04:50:10,493
One was treated with
standard busalan chemotherapy

5872
04:50:10,493 --> 04:50:12,962
and the other treated
with an anti-CD45

5873
04:50:12,962 --> 04:50:14,530
antibody drug conjugate.

5874
04:50:15,298 --> 04:50:17,700
We observed similar
high level gene edits

5875
04:50:17,700 --> 04:50:19,502
in the engrafting blood cells

5876
04:50:19,502 --> 04:50:22,372
and similarly robust fetal
hemoglobin induction

5877
04:50:22,372 --> 04:50:24,073
with or without chemotherapy

5878
04:50:24,707 --> 04:50:26,409
over at least a year
of follow-up,

5879
04:50:27,043 --> 04:50:29,045
providing proof of concept
that chemotherapy

5880
04:50:29,045 --> 04:50:33,449
is not required for effective
hematopoietic reconstitution

5881
04:50:33,449 --> 04:50:35,051
by the gene edited cells.

5882
04:50:37,153 --> 04:50:40,256
One possible risk of gene
editing is off-target effects.

5883
04:50:40,256 --> 04:50:41,724
With our bioinformatic
colleagues,

5884
04:50:41,724 --> 04:50:45,561
we built a computational tool
called CRISPRme to predict

5885
04:50:45,561 --> 04:50:48,831
the impact of genetic variation
on off-target risk.

5886
04:50:48,831 --> 04:50:51,234
We predicted that the most
likely off-target effect

5887
04:50:51,234 --> 04:50:52,802
of the gene editing approach

5888
04:50:52,802 --> 04:50:56,105
is due to a genetic variant
shown on the left in blue,

5889
04:50:56,105 --> 04:51:00,310
which creates a PAM sequence
that allows Cas9 to bind

5890
04:51:00,310 --> 04:51:02,378
in an adjacent site
at the CPS1

5891
04:51:02,378 --> 04:51:04,580
locus with
just three mismatches.

5892
04:51:04,580 --> 04:51:07,684
This variant is found at about
5 percent allele frequency

5893
04:51:07,684 --> 04:51:08,985
in African ancestry.

5894
04:51:08,985 --> 04:51:12,255
Individuals suggest to one
in 10 sickle cell

5895
04:51:12,255 --> 04:51:14,357
disease patients
might carry this variant.

5896
04:51:16,225 --> 04:51:18,861
Since the off-target sites
on the Q arm of chromosome

5897
04:51:18,861 --> 04:51:24,767
2 more than 150 megabases from
the BCL11A target site, a P arm,

5898
04:51:24,767 --> 04:51:27,003
we hypothesized
that simultaneous cleavage

5899
04:51:27,003 --> 04:51:30,773
of the sites could result
in pericentric inversions,

5900
04:51:30,773 --> 04:51:33,209
which indeed we confirmed
were present at about 1

5901
04:51:33,209 --> 04:51:35,111
in 600 allele frequency

5902
04:51:35,111 --> 04:51:38,081
after gene editing
in donor hematopoietic cells

5903
04:51:38,081 --> 04:51:39,949
carrying a heterozygous
risk variant.

5904
04:51:40,984 --> 04:51:44,454
We think genetic variant
associated off-target editing

5905
04:51:44,454 --> 04:51:46,622
is a generic risk
of gene editing

5906
04:51:46,622 --> 04:51:48,791
and should be considered
in editing design,

5907
04:51:49,425 --> 04:51:51,961
patient screening
and clinical follow-up.

5908
04:51:53,896 --> 04:51:57,834
Alongside its approval
of cevy in December, 2023,

5909
04:51:57,834 --> 04:52:01,371
the FDA mandated a post-
marketing surveillance study

5910
04:52:01,371 --> 04:52:04,607
to screen patients
for this CPS1 variant

5911
04:52:04,607 --> 04:52:08,378
and assess for genetic variant
associated off-target editing.

5912
04:52:10,780 --> 04:52:13,883
Many potential genetic variant
associated off-target effects

5913
04:52:13,883 --> 04:52:17,253
are due to much rarer variants
than the CPS1 variant,

5914
04:52:17,253 --> 04:52:19,956
which might make it infeasible
to find donors

5915
04:52:19,956 --> 04:52:21,624
for experimental testing.

5916
04:52:21,624 --> 04:52:23,493
Here I'm showing
the minor allele frequency

5917
04:52:23,493 --> 04:52:26,329
of 72 candidate variant
off-targets

5918
04:52:26,329 --> 04:52:29,465
based on cutting frequency
determination or at least 0.4.

5919
04:52:30,032 --> 04:52:32,602
Most associated with very rare
genetic variants.

5920
04:52:33,302 --> 04:52:37,073
It would not be feasible
to obtain CD34 cells from donors

5921
04:52:37,073 --> 04:52:38,574
carrying each of these variants

5922
04:52:38,574 --> 04:52:40,710
for direct off-target
assessment.

5923
04:52:40,710 --> 04:52:43,312
So to address this challenge,
we've developed an assay

5924
04:52:43,312 --> 04:52:45,848
that can assess
these variant off-target edits

5925
04:52:45,848 --> 04:52:48,050
while maintaining
clinically relevant cellular

5926
04:52:48,050 --> 04:52:50,186
and gene editing
delivery context.

5927
04:52:50,186 --> 04:52:55,591
The experimental design of our
so-called ABSOLVE-seq assay

5928
04:52:55,591 --> 04:52:58,561
involves using lentivirus
to introduce alternative

5929
04:52:58,561 --> 04:53:01,464
allele sequences
into the 34 cells

5930
04:53:01,464 --> 04:53:03,232
and then performing
editing following

5931
04:53:03,232 --> 04:53:06,869
clinically relevant protocols.
We include unique molecular

5932
04:53:06,869 --> 04:53:09,772
identifiers to detect
single editing events

5933
04:53:09,772 --> 04:53:12,809
and we test a pool of targets
together in a single experiment

5934
04:53:13,309 --> 04:53:15,611
within an accompanying
computational pipeline.

5935
04:53:17,013 --> 04:53:18,948
Here are the results
of our pooled experiment.

5936
04:53:18,948 --> 04:53:20,883
I'll summarize a lot of data

5937
04:53:20,883 --> 04:53:23,152
that we do find
the three expected targets,

5938
04:53:23,152 --> 04:53:25,054
the two on targets
in this experiment,

5939
04:53:25,054 --> 04:53:27,390
and one variant
associated off-target.

5940
04:53:27,957 --> 04:53:29,926
And with unprecedented
sensitivity,

5941
04:53:29,926 --> 04:53:31,794
we do not detect
off-target editing

5942
04:53:31,794 --> 04:53:33,763
at each of the other
72 candidates

5943
04:53:34,263 --> 04:53:37,233
providing reassurance of
the sensitivity of our approach.

5944
04:53:38,968 --> 04:53:41,771
So these data helps support
our clinical trial application,

5945
04:53:41,771 --> 04:53:43,639
which has now been FDA cleared

5946
04:53:43,639 --> 04:53:46,075
and anticipate
beginning enrollment

5947
04:53:46,075 --> 04:53:48,811
at Boston Children's Hospital
in early 2025.

5948
04:53:49,679 --> 04:53:52,882
More broadly, this demonstrates
a scalable strategy

5949
04:53:52,882 --> 04:53:54,617
to tackle off-target assessment

5950
04:53:54,617 --> 04:53:56,552
for novel candidate
gene editors.

5951
04:53:58,754 --> 04:54:01,424
So we have great opportunities
ahead for sickle cell disease

5952
04:54:01,424 --> 04:54:03,226
therapeutic gene editing.

5953
04:54:03,226 --> 04:54:06,629
With genetic medicine, we can
aspire to make a large impact

5954
04:54:06,629 --> 04:54:08,598
on the clinical unmet need.

5955
04:54:08,598 --> 04:54:10,433
And due to
the unique accessibility

5956
04:54:10,433 --> 04:54:11,701
of the blood system,

5957
04:54:11,701 --> 04:54:13,469
we can expect
to deeply understand

5958
04:54:13,469 --> 04:54:15,838
the impact of gene
editing at molecular,

5959
04:54:15,838 --> 04:54:19,542
cellular and physiologic levels.
With indefinite follow-up.

5960
04:54:19,542 --> 04:54:22,078
I think we have a responsibility
to our patients

5961
04:54:22,078 --> 04:54:24,780
to follow their outcomes
closely and to develop

5962
04:54:24,780 --> 04:54:27,350
improved therapies to provide
a safe,

5963
04:54:27,350 --> 04:54:30,086
effective and accessible
therapies as possible.

5964
04:54:31,721 --> 04:54:33,689
I'm extremely grateful
to current

5965
04:54:33,689 --> 04:54:37,059
and former lab members, mentors,
colleagues, collaborators.

5966
04:54:37,059 --> 04:54:39,562
There's -- and especially sickle
cell disease patients

5967
04:54:39,562 --> 04:54:41,297
and families.
Thank you.

5968
04:54:45,134 --> 04:54:46,402
Haydar Frangoul: Thank you
so much.

5969
04:54:46,402 --> 04:54:49,038
We have a time
for a couple of questions.

5970
04:54:52,542 --> 04:54:58,614
Any questions for Dan? No?
All right. Okay.

5971
04:54:58,614 --> 04:55:00,416
Well thank you so much
for the presentation.

5972
04:55:00,416 --> 04:55:02,852
You did a lot of legwork
for my presentation.

5973
04:55:02,852 --> 04:55:04,453
Thank you.

5974
04:55:06,589 --> 04:55:07,890
Daniel Bauer: Thank you.

5975
04:55:07,890 --> 04:55:09,659
Swee Thein: So, Haydar --
oh, there you go.

5976
04:55:10,393 --> 04:55:11,661
Let me introduce you.

5977
04:55:11,661 --> 04:55:13,062
Haydar Frangoul: Okay,
that's fine.

5978
04:55:13,062 --> 04:55:15,298
Swee Thein: So I'm really
delighted

5979
04:55:15,298 --> 04:55:18,568
that Haydar Frangoul
could join us today

5980
04:55:19,202 --> 04:55:23,306
and he's going to talk to us
about induction

5981
04:55:23,306 --> 04:55:25,875
of fetal hemoglobin
using genetic approaches.

5982
04:55:26,742 --> 04:55:29,712
Haydar is the director
of the pediatric stem

5983
04:55:29,712 --> 04:55:33,950
cell transplant program
at the Sarah Cannon Research

5984
04:55:33,950 --> 04:55:37,920
Institute and Tristar
Centennial Children's Hospital

5985
04:55:37,920 --> 04:55:42,158
in Nashville, Tennessee.
So thank you so much for coming.

5986
04:55:42,158 --> 04:55:43,893
Haydar Frangoul: Thank you
so much for inviting me.

5987
04:55:43,893 --> 04:55:45,695
Thank you for
the organizing committee

5988
04:55:45,695 --> 04:55:47,296
to invite me
to give this talk.

5989
04:55:49,031 --> 04:55:54,237
I think this is --
is this how you --

5990
04:55:57,373 --> 04:55:59,442
the other -- the other one.

5991
04:55:59,442 --> 04:56:02,211
Okay, perfect. Okay.
These are my disclosures.

5992
04:56:03,512 --> 04:56:06,816
So again, as mentioned
by Dan earlier,

5993
04:56:06,816 --> 04:56:09,285
that symptoms
of sickle cell disease

5994
04:56:09,285 --> 04:56:12,054
start after the switching
in the main type

5995
04:56:12,054 --> 04:56:15,024
from hemoglobin F
in the prenatal life

5996
04:56:15,024 --> 04:56:18,227
to adult hemoglobin in patients
with sickle cell disease.

5997
04:56:18,227 --> 04:56:20,096
The onset of symptoms

5998
04:56:20,096 --> 04:56:23,532
occurs as hemoglobin
F switches to hemoglobin

5999
04:56:23,532 --> 04:56:27,470
A, which is affected
by disease-causing mutation.

6000
04:56:27,470 --> 04:56:29,505
I'm not going to spend
a lot of time on this

6001
04:56:29,505 --> 04:56:31,974
because this is very well
known to everybody.

6002
04:56:31,974 --> 04:56:35,244
So this is a paper
by oral plat in 1994

6003
04:56:35,244 --> 04:56:40,249
following 3,700 patients in the
NIH cohort for several decades.

6004
04:56:40,249 --> 04:56:42,985
And the observation in that
paper was that individuals

6005
04:56:42,985 --> 04:56:47,857
who maintain a fetal hemoglobin
of over 8.6 percent over time

6006
04:56:47,857 --> 04:56:50,960
have almost doubled
the survival by age 50

6007
04:56:50,960 --> 04:56:53,829
as compared to those
who do not maintain high levels

6008
04:56:53,829 --> 04:56:56,232
of fetal hemoglobin
long-term.

6009
04:56:57,366 --> 04:57:00,169
So a subset of patients
with sickle cell disease

6010
04:57:00,169 --> 04:57:02,872
who continue to express
fetal hemoglobin into adulthood,

6011
04:57:02,872 --> 04:57:06,175
a condition known as persistent
fetal hemoglobin experience

6012
04:57:06,175 --> 04:57:07,476
less symptoms.

6013
04:57:07,476 --> 04:57:10,312
And usually by the time
you reach a fetal hemoglobin

6014
04:57:10,312 --> 04:57:12,281
of around 30 to 40 percent,

6015
04:57:12,281 --> 04:57:14,483
the patients become
relatively asymptomatic.

6016
04:57:16,352 --> 04:57:18,988
So genetic studies
as mentioned by then earlier,

6017
04:57:18,988 --> 04:57:21,157
this described
the genetic variation

6018
04:57:21,157 --> 04:57:24,493
leading to decrease expression
of BCL11A results

6019
04:57:24,493 --> 04:57:26,829
in increased
hemoglobin F expression.

6020
04:57:26,829 --> 04:57:31,067
So BCL11A became
a very important target

6021
04:57:32,334 --> 04:57:35,705
in designing genetic therapies
to induce fetal hemoglobin.

6022
04:57:37,640 --> 04:57:40,376
So there are multiple trials
which I'm going to go through

6023
04:57:40,376 --> 04:57:42,278
within the limitation
of time we have.

6024
04:57:42,278 --> 04:57:46,148
There is the paper reported
using a antiviral approach

6025
04:57:46,148 --> 04:57:47,550
by the Boston Children Group.

6026
04:57:47,550 --> 04:57:50,686
There is the CRISPR-9 gene
editing of the HBG1,

6027
04:57:50,686 --> 04:57:53,222
HBG2 promoter
that was run by Novartis.

6028
04:57:54,023 --> 04:57:56,559
I'm going to go into more
details in the two trials,

6029
04:57:56,559 --> 04:57:57,893
which is the exa-cel trial

6030
04:57:57,893 --> 04:57:59,462
leading to CRISPR
being approved.

6031
04:57:59,462 --> 04:58:00,930
And I'm going to show you
new data

6032
04:58:00,930 --> 04:58:05,601
that we just presented
in IHA June and reni-cel,

6033
04:58:05,601 --> 04:58:10,740
which uses Cas12A editing
of the HBG1 and HBG2 promoter.

6034
04:58:10,740 --> 04:58:13,242
And also there is data
that was recently presented

6035
04:58:13,242 --> 04:58:15,845
a couple of months ago
that I'm going to present here.

6036
04:58:15,845 --> 04:58:18,881
And there is another trial
ongoing, which is the BEAM-101,

6037
04:58:18,881 --> 04:58:20,983
which uses a totally
different approach,

6038
04:58:20,983 --> 04:58:23,953
which is base editing
to introduce naturally occurring

6039
04:58:23,953 --> 04:58:28,824
A-to-G substitution into
the promoter of HBG1 and HBG2.

6040
04:58:28,824 --> 04:58:31,861
Now, BEAM-101 does not have
any publicly available data,

6041
04:58:31,861 --> 04:58:34,029
so I'm going to limit
my presentation

6042
04:58:34,029 --> 04:58:35,631
to the top four studies.

6043
04:58:36,198 --> 04:58:38,901
So this is the paper
by Dave Williams Group

6044
04:58:38,901 --> 04:58:40,202
from Boston Children

6045
04:58:40,202 --> 04:58:43,906
and they use
BCH-BB694 antiviral vector,

6046
04:58:43,906 --> 04:58:46,609
which encodes
a short hairpin RNA

6047
04:58:46,609 --> 04:58:48,878
targeting the BCL11A
messenger RNA,

6048
04:58:48,878 --> 04:58:51,046
embedded in the micro RNA,

6049
04:58:51,046 --> 04:58:54,450
allowing erythroid
lineage specific breakdown.

6050
04:58:54,450 --> 04:58:56,685
The paper reported on six
individuals

6051
04:58:56,685 --> 04:58:58,687
with sickle cell disease treated

6052
04:58:58,687 --> 04:59:00,990
and all of them achieved
the fetal hemoglobin

6053
04:59:00,990 --> 04:59:04,660
between 20 and 41 percent
with only three patients

6054
04:59:04,660 --> 04:59:08,631
having fetal hemoglobin greater
than 30 percent with F cells

6055
04:59:08,631 --> 04:59:11,367
ranging between
58 to 93 percent.

6056
04:59:11,367 --> 04:59:12,768
And following this therapy,

6057
04:59:12,768 --> 04:59:15,604
none of the patients experienced
any vaso-occlusive crisis.

6058
04:59:15,604 --> 04:59:17,306
This paper came out in 2021.

6059
04:59:18,641 --> 04:59:22,878
The next paper came out in 2023,
which is by Akshay Sharma

6060
04:59:22,878 --> 04:59:26,682
is the study using CRISPR-Cas9,
editing of the HBG1,

6061
04:59:26,682 --> 04:59:31,020
HBG2 gene promoter
that treats sickle cell disease.

6062
04:59:31,020 --> 04:59:32,955
This is based
on basic science work

6063
04:59:32,955 --> 04:59:36,859
that showed that targeting
this promoter region

6064
04:59:36,859 --> 04:59:41,263
can increase fetal hemoglobin in
animal love in animal studies.

6065
04:59:41,263 --> 04:59:43,165
And they screened multiple
guide RNA

6066
04:59:43,165 --> 04:59:44,433
and ended up with a guide,

6067
04:59:44,433 --> 04:59:47,803
RNA number 68
that they used for this study.

6068
04:59:47,803 --> 04:59:49,338
And there were
three subjects treated,

6069
04:59:49,338 --> 04:59:51,807
reported in New England
Journal of Medicine last year,

6070
04:59:51,807 --> 04:59:54,076
a total hemoglobin
at last follow-up range

6071
04:59:54,076 --> 04:59:56,679
between 10.4 and 11.9.

6072
04:59:56,679 --> 04:59:59,548
And the fetal hemoglobin
at last follow-up was 19

6073
04:59:59,548 --> 05:00:02,985
to 25 percent
of the total hemoglobin.

6074
05:00:02,985 --> 05:00:05,488
So the patients continued
to be slightly anemic

6075
05:00:05,488 --> 05:00:08,324
and the fetal hemoglobin
was less than 30 percent,

6076
05:00:08,324 --> 05:00:10,392
and all patients had some
clinical benefit

6077
05:00:10,392 --> 05:00:11,861
from this therapy.

6078
05:00:11,861 --> 05:00:14,663
My understanding is this trial
is not accruing anymore.

6079
05:00:16,365 --> 05:00:18,901
I want to spend some time
talking about the exa-cell data,

6080
05:00:18,901 --> 05:00:21,203
which then refer to --

6081
05:00:21,203 --> 05:00:24,139
resulting in the approval
of CRISPR last December.

6082
05:00:24,840 --> 05:00:29,044
So exa-cel mechanism is grounded
in human genetics.

6083
05:00:29,778 --> 05:00:33,382
It is basically targets
the BCL11A

6084
05:00:33,382 --> 05:00:34,750
erythroid enhanced region,

6085
05:00:34,750 --> 05:00:37,453
resulting a reactivation
of hemoglobin F

6086
05:00:37,453 --> 05:00:39,622
and the infusion of exa-cel,
as I'm going to show you,

6087
05:00:39,622 --> 05:00:42,825
resulted in pancellular
hemoglobin F production

6088
05:00:42,825 --> 05:00:45,761
with a fetal hemoglobin
of around 40 percent

6089
05:00:45,761 --> 05:00:48,063
resulting in
significant reduction

6090
05:00:48,063 --> 05:00:49,965
or elimination of VOCs.

6091
05:00:50,833 --> 05:00:53,903
So the patient journey
is relatively complicated.

6092
05:00:53,903 --> 05:00:57,273
This is not easy studies to do,
or easy therapy to deliver.

6093
05:00:57,273 --> 05:00:58,707
It takes a long time.

6094
05:00:58,707 --> 05:01:00,910
Patients are --
usually undergo --

6095
05:01:00,910 --> 05:01:03,746
exchange transfusions
for around four to eight weeks

6096
05:01:03,746 --> 05:01:06,482
prior to peripheral blood
stem cell collection

6097
05:01:06,482 --> 05:01:08,617
stem cell
collected using plerixafor.

6098
05:01:09,518 --> 05:01:12,221
And because we use
plerixafor the mobilization

6099
05:01:12,221 --> 05:01:14,323
is not as robust
as when you use GCSF,

6100
05:01:14,323 --> 05:01:17,526
which you cannot use in patients
with sickle cell disease cells,

6101
05:01:17,526 --> 05:01:20,095
and then manufactured
and then shipped back

6102
05:01:20,095 --> 05:01:21,730
to the transplant center

6103
05:01:21,730 --> 05:01:24,199
where the patient undergo
myeloablative chemotherapy

6104
05:01:24,199 --> 05:01:27,336
with busulfan which is
pharmacokinetically adjusted.

6105
05:01:27,336 --> 05:01:28,570
The cells are infused

6106
05:01:28,570 --> 05:01:30,873
and the patients
are followed for two years.

6107
05:01:30,873 --> 05:01:33,676
This was a phase
three multicenter trial,

6108
05:01:34,276 --> 05:01:37,713
that enrolled patients
between the ages of 12 to 35.

6109
05:01:38,514 --> 05:01:40,082
And they define severe disease

6110
05:01:40,082 --> 05:01:42,318
as having two vaso-occlusive
crisis per year

6111
05:01:42,318 --> 05:01:43,652
in the last two years.

6112
05:01:43,652 --> 05:01:46,989
So basically four
in the last two years.

6113
05:01:47,623 --> 05:01:50,626
The primary endpoint
was being hospitalization.

6114
05:01:50,626 --> 05:01:54,863
The primary endpoint was being
VOC3 for 12 consecutive months.

6115
05:01:54,863 --> 05:01:56,865
And a secondary --
key secondary endpoint

6116
05:01:56,865 --> 05:02:00,803
was being hospitalization
3,4,12 consecutive months.

6117
05:02:00,803 --> 05:02:04,807
And that's HF12.
And because of the trial,

6118
05:02:04,807 --> 05:02:06,508
met the primary
and secondary endpoint,

6119
05:02:06,508 --> 05:02:07,910
which I'm going to show you
a little bit later.

6120
05:02:07,910 --> 05:02:10,479
It was as mentioned
previously,

6121
05:02:10,479 --> 05:02:12,715
the product was commercially
now available

6122
05:02:12,715 --> 05:02:14,616
and approved
in the United States,

6123
05:02:14,616 --> 05:02:17,720
the EU,
the United, Kingdom,

6124
05:02:17,720 --> 05:02:19,521
Kingdom of Saudi Arabia
and Bahrain.

6125
05:02:20,756 --> 05:02:24,760
So the full dataset
is for all 46 patients.

6126
05:02:24,760 --> 05:02:27,429
Now the primary efficacy
is the 39 patients

6127
05:02:27,429 --> 05:02:29,465
that have long
enough follow-up.

6128
05:02:29,465 --> 05:02:31,333
The mean age
was 21 years of age.

6129
05:02:31,333 --> 05:02:32,601
They were equally divided

6130
05:02:32,601 --> 05:02:34,837
between male
and female subjects.

6131
05:02:34,837 --> 05:02:37,573
The majority had beta
as beta as genotype.

6132
05:02:37,573 --> 05:02:39,875
And of note,
around 40 percent of the patient

6133
05:02:39,875 --> 05:02:42,478
had one or two alpha
gene deletions.

6134
05:02:42,478 --> 05:02:45,114
And the number of historic VOCs
were four per year

6135
05:02:45,114 --> 05:02:46,515
in the last two years.

6136
05:02:46,515 --> 05:02:49,084
And the median number
of hospitalization

6137
05:02:49,084 --> 05:02:51,487
was almost three per year
in the last two years.

6138
05:02:52,888 --> 05:02:56,692
So the patients required
the median mobilizations of two,

6139
05:02:56,692 --> 05:02:58,727
but ranging from one to six.

6140
05:02:58,727 --> 05:03:02,498
The number of CD34 cells
infused was 4.7 million,

6141
05:03:02,498 --> 05:03:04,366
CD34 per kilogram,

6142
05:03:04,366 --> 05:03:06,902
and the median duration
of follow-up was 28 months.

6143
05:03:07,636 --> 05:03:09,872
All patients engrafted,
neutrophil and platelets

6144
05:03:09,872 --> 05:03:13,208
at a median of 27
and 34 days respectively.

6145
05:03:13,208 --> 05:03:14,543
And of note, for those of you

6146
05:03:14,543 --> 05:03:16,211
who have used
single agent busulfan

6147
05:03:16,211 --> 05:03:20,282
and there is really around nine
days after infusing that cells,

6148
05:03:20,282 --> 05:03:21,917
the patients have normal counts.

6149
05:03:21,917 --> 05:03:24,753
So the duration of neutropenia
was only 17 days.

6150
05:03:25,587 --> 05:03:27,156
And the time to the last
red blood cell

6151
05:03:27,156 --> 05:03:28,891
transfusion was 19 days,

6152
05:03:28,891 --> 05:03:31,193
and the hospital stay
was 30 days.

6153
05:03:32,294 --> 05:03:34,229
So this is
a complicated graph here.

6154
05:03:34,229 --> 05:03:35,497
I just want to orient you.

6155
05:03:35,497 --> 05:03:37,933
This is a swim plot
looking at the number

6156
05:03:37,933 --> 05:03:41,470
of vaso-occlusive crisis
pre and postsl infusion.

6157
05:03:42,304 --> 05:03:44,973
I think I have a pointer here,
maybe.

6158
05:03:46,408 --> 05:03:49,778
Yes. So the area here
in gray represent two years

6159
05:03:49,778 --> 05:03:52,047
prior to the exa-cel infusion,

6160
05:03:52,047 --> 05:03:56,351
and each diamond here represent
a VOC vaso-occlusive crisis.

6161
05:03:56,351 --> 05:03:58,187
The red dark bars are the times

6162
05:03:58,187 --> 05:04:01,156
when the patients were receiving
red blood cell transfusion,

6163
05:04:01,156 --> 05:04:03,659
and the dark gray
is 60-day washout.

6164
05:04:03,659 --> 05:04:06,728
So the clock starts
for the efficacy from 60 days

6165
05:04:06,728 --> 05:04:08,697
after the last transfusion.

6166
05:04:08,697 --> 05:04:12,301
So 36 of the 39 individuals
on this trial,

6167
05:04:12,301 --> 05:04:15,270
or 92.3 percent achieved
the primary endpoint

6168
05:04:15,270 --> 05:04:18,674
of being vaso-occlusive 3
for 12 consecutive months.

6169
05:04:18,674 --> 05:04:21,143
And the average duration range
from 12 months

6170
05:04:21,143 --> 05:04:22,811
to around five years.

6171
05:04:23,445 --> 05:04:25,647
Seven participants
who are in the bottom,

6172
05:04:25,647 --> 05:04:28,417
who are not included
in the primary efficacy,

6173
05:04:28,417 --> 05:04:31,286
these are patients who don't
have long enough follow up.

6174
05:04:31,286 --> 05:04:33,956
There are seven of them
and five are still eligible

6175
05:04:33,956 --> 05:04:35,824
to meet the VF12 definition.

6176
05:04:36,725 --> 05:04:39,995
Pain events happened
after infusion of exa-cel,

6177
05:04:39,995 --> 05:04:42,598
and it usually was associated
with either infection

6178
05:04:42,598 --> 05:04:46,001
like parvovirus B19,
influenza B or COVID-19,

6179
05:04:46,001 --> 05:04:48,070
or a procedure
like a bone marrow biopsy

6180
05:04:48,070 --> 05:04:50,139
or the use of corticosteroids.

6181
05:04:50,139 --> 05:04:52,808
More importantly, the patients
who experienced VOCs

6182
05:04:52,808 --> 05:04:56,979
after exa-cel also had robust
increase in fetal hemoglobin.

6183
05:04:59,081 --> 05:05:04,019
This is the secondary --
this is -- this figure here

6184
05:05:04,019 --> 05:05:07,055
divides the patient
between adults and adolescents.

6185
05:05:07,055 --> 05:05:10,392
Adolescent defined at 12
to 18 years of age

6186
05:05:10,392 --> 05:05:12,161
and 92 percent
of the adults

6187
05:05:12,161 --> 05:05:15,030
and 90 percent of
the adolescent patients

6188
05:05:15,030 --> 05:05:18,567
achieved the vaso-occlusive
3,4,12 consecutive months.

6189
05:05:20,235 --> 05:05:22,171
This is the key
secondary endpoint

6190
05:05:22,171 --> 05:05:24,072
looking at hospitalizations,
again,

6191
05:05:24,072 --> 05:05:26,308
to orient you the area
here on the left

6192
05:05:26,308 --> 05:05:27,910
to present
the hospital admission.

6193
05:05:27,910 --> 05:05:30,312
Each dot is
one hospital admission

6194
05:05:30,312 --> 05:05:33,248
and 38 of the 39
evaluable patients,

6195
05:05:33,248 --> 05:05:37,085
or 97.4 percent met
the secondary endpoint

6196
05:05:37,085 --> 05:05:39,922
of being hospital free
for 12 consecutive months.

6197
05:05:39,922 --> 05:05:41,456
And the mean duration
of hospital

6198
05:05:41,456 --> 05:05:44,193
free ranges from 12 months
to almost five years.

6199
05:05:45,627 --> 05:05:49,598
This, on the left here shows
the hemoglobin percent,

6200
05:05:49,598 --> 05:05:53,135
and this is divided
between adolescent and adults.

6201
05:05:53,135 --> 05:05:55,771
The adolescents are in black,
the adults are in blue.

6202
05:05:55,771 --> 05:05:57,039
And as you can see,

6203
05:05:57,039 --> 05:06:01,276
the mean hemoglobin
F was 45 percent at one year

6204
05:06:01,276 --> 05:06:03,579
and 42 percent at two years
in the adolescent.

6205
05:06:03,579 --> 05:06:05,881
And very similar
in the adult cohort.

6206
05:06:05,881 --> 05:06:08,951
The graph on the right represent
the total hemoglobin,

6207
05:06:08,951 --> 05:06:11,620
and again, the mean
hemoglobin in adult at --

6208
05:06:11,620 --> 05:06:18,627
in adolescent at one year was 13
and at two years was 13.2.

6209
05:06:18,627 --> 05:06:22,497
And the mean hemoglobin
in adults was 12.7 and 13.2

6210
05:06:22,497 --> 05:06:24,566
at one
and two years respectively.

6211
05:06:24,566 --> 05:06:27,102
So the majority of the patients
had normal

6212
05:06:27,102 --> 05:06:28,704
or near normal hemoglobin.

6213
05:06:30,105 --> 05:06:32,708
When you look at the
distribution of fetal cells

6214
05:06:32,708 --> 05:06:34,643
red blood cells
containing fetal hemoglobin,

6215
05:06:34,643 --> 05:06:37,512
the F cells, more than
95 percent of the cells

6216
05:06:37,512 --> 05:06:39,948
contained fetal hemoglobin
by month three.

6217
05:06:39,948 --> 05:06:41,450
And this was sustained
over time.

6218
05:06:41,450 --> 05:06:44,319
Actually, those dots represent
a standard deviation,

6219
05:06:44,319 --> 05:06:47,122
which is very tight, so that's
why you can see the bars.

6220
05:06:48,090 --> 05:06:51,026
We evaluated the editing
percentage

6221
05:06:51,026 --> 05:06:53,061
in peripheral blood
and bone marrow.

6222
05:06:53,061 --> 05:06:55,130
The top panel represents
the bone marrow.

6223
05:06:55,898 --> 05:06:58,834
We looked at CD34 cells
and looked at the percent

6224
05:06:58,834 --> 05:07:01,436
editing in stem cells
in the bone marrow,

6225
05:07:01,436 --> 05:07:04,439
and we looked at whole blood
nucleated cells in the bottom.

6226
05:07:04,439 --> 05:07:06,575
The green lines represent

6227
05:07:06,575 --> 05:07:10,012
those who achieved
the primary endpoint.

6228
05:07:10,012 --> 05:07:13,515
The red bars took about
the patients

6229
05:07:13,515 --> 05:07:15,017
who have not achieved it,

6230
05:07:15,017 --> 05:07:16,685
and you can see
the editing percentage

6231
05:07:16,685 --> 05:07:18,620
was very stable
and durable over time,

6232
05:07:18,620 --> 05:07:20,889
both in the bone marrow
and peripheral blood.

6233
05:07:22,124 --> 05:07:23,425
When you look at hemolysis,

6234
05:07:23,425 --> 05:07:26,061
which is very important
in sickle cell disease,

6235
05:07:26,061 --> 05:07:28,997
intravascular hemolysis
looking at LDH and haptoglobin,

6236
05:07:28,997 --> 05:07:33,302
LDH was elevated and haptoglobin
was very low at screening.

6237
05:07:33,302 --> 05:07:35,070
And both of those
either normalized

6238
05:07:35,070 --> 05:07:38,440
or became very close to normal
after infusion of exa-cel.

6239
05:07:38,440 --> 05:07:41,977
The reticulocyte count dropped
and the indirect bilirubin

6240
05:07:41,977 --> 05:07:44,680
improved quite dramatically
after exa-cel infusion.

6241
05:07:46,448 --> 05:07:48,450
We have done patient
reported outcome.

6242
05:07:48,450 --> 05:07:50,018
It's not only important to see

6243
05:07:50,018 --> 05:07:51,953
if we have elevation
in fetal hemoglobin,

6244
05:07:51,953 --> 05:07:54,156
it's also very important
to see if we actually --

6245
05:07:54,156 --> 05:07:56,358
that resulted in patient benefit

6246
05:07:56,358 --> 05:07:58,627
and we looked at patient
reported outcomes.

6247
05:07:58,627 --> 05:08:00,962
This data was presented
at EHA in 2024.

6248
05:08:00,962 --> 05:08:02,831
I'm just going to show you
a few graphs from it

6249
05:08:02,831 --> 05:08:04,299
for the sake of time.

6250
05:08:04,299 --> 05:08:07,669
This is looking at a tool called
FACT-G,

6251
05:08:07,669 --> 05:08:09,738
which looks at
the total scores in adults.

6252
05:08:09,738 --> 05:08:10,939
And as you can see,

6253
05:08:10,939 --> 05:08:13,542
there was dramatic
improvement from baseline

6254
05:08:13,542 --> 05:08:15,577
to last follow-up 36 months.

6255
05:08:16,311 --> 05:08:19,715
Similarly in the another tool
called BMT scores in adult

6256
05:08:19,715 --> 05:08:21,083
in primary efficacy point,

6257
05:08:21,083 --> 05:08:23,185
and then there was
significant improvement

6258
05:08:23,185 --> 05:08:24,786
in quality of life
over time.

6259
05:08:25,654 --> 05:08:27,022
When you look at the pain scale,

6260
05:08:27,022 --> 05:08:30,926
there was a significant drop
in reported pain from baseline

6261
05:08:30,926 --> 05:08:35,597
to last follow-up.
So the side effects.

6262
05:08:35,597 --> 05:08:37,432
So this therapy is not
without side effect.

6263
05:08:37,432 --> 05:08:39,501
I keep telling John
he needs to find a way

6264
05:08:39,501 --> 05:08:41,136
to treat patients
without busulfan.

6265
05:08:41,136 --> 05:08:43,305
So all the side effects
you see here are related

6266
05:08:43,305 --> 05:08:45,741
to the conditioning
regimen with busulfan.

6267
05:08:45,741 --> 05:08:48,176
So, as you expect with high dose
chemotherapy

6268
05:08:48,176 --> 05:08:49,478
and autologous transplant,

6269
05:08:49,478 --> 05:08:52,781
patients experienced dermatitis,
nausea, fever neutropenia.

6270
05:08:52,781 --> 05:08:55,650
More importantly, there were
no secondary malignancies

6271
05:08:55,650 --> 05:08:59,054
and no serious adverse events
related to exa-cel.

6272
05:08:59,054 --> 05:09:00,756
Unfortunately,
one of the individuals

6273
05:09:00,756 --> 05:09:02,357
enrolled on this trial

6274
05:09:02,357 --> 05:09:04,860
passed away related
to COVID-19 infection

6275
05:09:04,860 --> 05:09:06,261
and respiratory failure.

6276
05:09:06,261 --> 05:09:08,797
Just of note, this patient
was not immunized

6277
05:09:08,797 --> 05:09:11,133
and the trial was performed
during the COVID era.

6278
05:09:11,133 --> 05:09:14,636
We were very careful trying
to protect patients from COVID,

6279
05:09:14,636 --> 05:09:16,338
but this was
an unfortunate event.

6280
05:09:17,839 --> 05:09:19,674
So in conclusion,
for the exa-cell data

6281
05:09:19,674 --> 05:09:21,042
is the first
and only approved

6282
05:09:21,042 --> 05:09:23,812
CRISPR-Cas9 gene
editing therapy.

6283
05:09:23,812 --> 05:09:27,015
It resulted in 92.3 percent VOC

6284
05:09:27,015 --> 05:09:30,752
free rate and 97 percent
hospital free rates.

6285
05:09:30,752 --> 05:09:34,823
There was durable hemoglobin F
that lasted now up to five years

6286
05:09:34,823 --> 05:09:36,258
with the longest follow-up.

6287
05:09:36,258 --> 05:09:40,729
There is stable allelic editing
in the bone marrow

6288
05:09:40,729 --> 05:09:43,532
and peripheral blood
that was also durable.

6289
05:09:43,532 --> 05:09:45,700
And the safety profile
is very consistent

6290
05:09:45,700 --> 05:09:47,436
with what we expect
with busulfan.

6291
05:09:48,036 --> 05:09:50,038
And again, this could be have
the potential

6292
05:09:50,038 --> 05:09:51,306
to be a functional cure

6293
05:09:51,306 --> 05:09:52,808
for patients
with sickle cell disease.

6294
05:09:52,808 --> 05:09:54,776
I want to profess here,

6295
05:09:54,776 --> 05:09:57,078
although I am the lead
investigator on this trial,

6296
05:09:57,078 --> 05:10:00,816
is that we still don't have real
long enough data,

6297
05:10:00,816 --> 05:10:02,150
as Dan mentioned earlier,

6298
05:10:02,150 --> 05:10:04,519
to determine if this therapy
will affect

6299
05:10:04,519 --> 05:10:06,822
really the end organ damage
15 years down the road.

6300
05:10:06,822 --> 05:10:09,491
So that's why the patients
are all enrolled

6301
05:10:09,491 --> 05:10:12,160
on the long-term study
for up to 15 years.

6302
05:10:13,295 --> 05:10:16,364
Now, switching gears
to the editors clinical trial,

6303
05:10:16,364 --> 05:10:20,635
which is reni-cel
which uses a proprietary Cas12A

6304
05:10:21,269 --> 05:10:26,508
and they're editing the HBG1
and HBG2 promoter region.

6305
05:10:26,508 --> 05:10:29,177
You saw data in the Novo
Nordisk data using CAS9.

6306
05:10:29,177 --> 05:10:30,412
This is used as CAS12,

6307
05:10:30,412 --> 05:10:34,049
which is more specific
to that site and more effective.

6308
05:10:34,583 --> 05:10:39,621
And the idea is to induce fetal
hemoglobin similar inclusion

6309
05:10:39,621 --> 05:10:41,756
and exclusion criteria
to the exa-cel trial.

6310
05:10:41,756 --> 05:10:45,527
Except this trial includes
patients up to 50 years of age

6311
05:10:45,527 --> 05:10:47,896
while exa-cel stopped at age 35.

6312
05:10:48,663 --> 05:10:51,800
They defined VOC again
as severe VOC

6313
05:10:51,800 --> 05:10:54,269
as two events per year
in the last two years.

6314
05:10:55,537 --> 05:10:57,873
This -- there was
screening mobilization,

6315
05:10:57,873 --> 05:11:00,275
apheresis, manufacturing,
and infusion

6316
05:11:00,275 --> 05:11:03,211
identical to the trial,
I presented earlier.

6317
05:11:04,012 --> 05:11:06,748
There were 18 patients
reported this June and IHA.

6318
05:11:06,748 --> 05:11:09,117
And this is the data
that was provided to me

6319
05:11:09,117 --> 05:11:10,886
by Dr. Hanna and the sponsor.

6320
05:11:11,453 --> 05:11:14,556
Most of them had a beta,
as beta as genotype,

6321
05:11:14,556 --> 05:11:16,725
and the median age was 27 years.

6322
05:11:16,725 --> 05:11:20,195
And the median number of VOEs in
the previous two years was five.

6323
05:11:21,062 --> 05:11:23,832
And the number of mobilizations
were similar to exa-cel of two,

6324
05:11:23,832 --> 05:11:25,834
ranging from one to four.

6325
05:11:25,834 --> 05:11:30,038
The number of CD34 infused
were 4.6 million per kilogram.

6326
05:11:30,038 --> 05:11:32,274
And the follow-up
was seven months.

6327
05:11:32,274 --> 05:11:34,809
At the time, all patients
engrafted neutrophil

6328
05:11:34,809 --> 05:11:38,113
and platelets at 23
and 24 days respectively.

6329
05:11:38,847 --> 05:11:41,550
Looking at the outcome here,
although we don't have

6330
05:11:41,550 --> 05:11:43,285
a lot of patients
on long follow-up

6331
05:11:43,952 --> 05:11:48,056
all patients after infusion
of reni-cel remained VOC

6332
05:11:48,056 --> 05:11:51,059
free for up to 22.8 months.

6333
05:11:51,059 --> 05:11:53,762
And the study continues
to enroll and accrue patients.

6334
05:11:55,363 --> 05:11:58,466
This is data describing
the total hemoglobin

6335
05:11:58,466 --> 05:12:00,101
as well as the fetal hemoglobin.

6336
05:12:00,101 --> 05:12:01,703
You can see by month four,

6337
05:12:02,337 --> 05:12:04,673
the fetal hemoglobin
was over 40 percent

6338
05:12:04,673 --> 05:12:06,274
and it was sustained over time.

6339
05:12:06,841 --> 05:12:09,844
The hemoglobin reached normal
levels by month three

6340
05:12:09,844 --> 05:12:11,446
and was sustained over time.

6341
05:12:12,013 --> 05:12:14,516
All hemolysis markers,
including reticulocyte,

6342
05:12:14,516 --> 05:12:16,818
indirect bilirubin,
LDH and haptoglobin,

6343
05:12:16,818 --> 05:12:19,721
either improved or normalized
after infusion of reni-cel.

6344
05:12:21,089 --> 05:12:24,092
Again, the F cells
are quite high indicating

6345
05:12:24,092 --> 05:12:28,263
a very uniform distribution
of the fetal hemoglobin

6346
05:12:28,263 --> 05:12:31,166
and red blood cells,
which was over 95 percent.

6347
05:12:31,166 --> 05:12:33,802
And they also performed
editing evaluation

6348
05:12:33,802 --> 05:12:36,638
in the bone marrow and blood,
which was sustained over time

6349
05:12:36,638 --> 05:12:39,975
and high in the stem cells
in the bone marrow.

6350
05:12:42,110 --> 05:12:44,479
When you look at side effects,
again, all the side effects

6351
05:12:44,479 --> 05:12:46,982
are related
to the high dose chemotherapy

6352
05:12:46,982 --> 05:12:50,685
and autologous stem cell
infusion basically stomatitis,

6353
05:12:51,419 --> 05:12:53,288
and fever neutropenia.

6354
05:12:53,288 --> 05:12:56,124
So all of them
were related to busulfan.

6355
05:12:56,124 --> 05:12:58,860
There were no serious side
effects related to reni-cel.

6356
05:13:00,261 --> 05:13:02,263
So in conclusion, reni-cel again

6357
05:13:02,263 --> 05:13:05,133
is another product
investigational autologous gene

6358
05:13:05,133 --> 05:13:08,536
editing medicine that
demonstrate promising results.

6359
05:13:08,536 --> 05:13:12,641
In gene editing, it showed that
the patient remained VOE free,

6360
05:13:12,641 --> 05:13:15,744
all patients experienced in
early correction of the anemia

6361
05:13:15,744 --> 05:13:18,580
with sustained high
fetal hemoglobin over time.

6362
05:13:19,114 --> 05:13:22,283
And the treatment for reni-cel
showed favorable safety profile

6363
05:13:22,283 --> 05:13:24,519
and promising
preliminary efficacy

6364
05:13:24,519 --> 05:13:26,321
supporting the further
investigation.

6365
05:13:26,321 --> 05:13:28,957
The trial now is,
actually accruing

6366
05:13:28,957 --> 05:13:30,659
and treating
adolescent cohort.

6367
05:13:32,027 --> 05:13:34,029
I just wanted to show you
a couple of things.

6368
05:13:34,029 --> 05:13:37,132
This is a smear since
everybody was showing pictures,

6369
05:13:37,132 --> 05:13:39,067
so I like to do that too here.
I was jealous.

6370
05:13:39,067 --> 05:13:41,703
So this is a smear
from one of our subjects

6371
05:13:41,703 --> 05:13:43,838
that enrolled in our site
and the exa-cel trial.

6372
05:13:43,838 --> 05:13:47,108
This was actually a patient
who was not having any crisis

6373
05:13:47,108 --> 05:13:48,410
when I screened them.

6374
05:13:48,410 --> 05:13:50,845
And this is their peripheral
smear at enrollment.

6375
05:13:50,845 --> 05:13:53,248
This is their smear
at one year post transplant.

6376
05:13:54,482 --> 05:13:57,952
Then I would like to show
that one of our patients,

6377
05:13:57,952 --> 05:13:59,587
this was reported yesterday
in the news.

6378
05:13:59,587 --> 05:14:01,356
So I modified my slides today.

6379
05:14:02,157 --> 05:14:04,693
This is our patient, Jimmy,
that was reported in the news.

6380
05:14:04,693 --> 05:14:07,529
He was the first sickle cell
patient to climb Kilimanjaro

6381
05:14:07,529 --> 05:14:09,397
and make it there
and come down.

6382
05:14:09,397 --> 05:14:13,368
He just texted me and he is back
in Atlanta doing very well,

6383
05:14:13,368 --> 05:14:14,969
and he was able to do it.

6384
05:14:15,603 --> 05:14:18,006
He'll be the first patient
to climb Kilimanjaro.

6385
05:14:19,741 --> 05:14:22,577
I would like to thank first
and foremost the patients.

6386
05:14:22,577 --> 05:14:25,447
This is Victoria Gray, which
made a lot of news nationally.

6387
05:14:25,447 --> 05:14:27,382
She is the first patient
to enroll.

6388
05:14:27,382 --> 05:14:28,850
When I consented her, I said,

6389
05:14:28,850 --> 05:14:30,885
we are giving you a CRISPR
modified stem cells

6390
05:14:30,885 --> 05:14:33,755
that nobody has ever received.
We don't know if it works.

6391
05:14:33,755 --> 05:14:37,058
I have no clue if this is going
to even help you long-term.

6392
05:14:37,058 --> 05:14:38,426
And she said, sign me up.

6393
05:14:38,426 --> 05:14:40,061
So she was the first one
to do it,

6394
05:14:40,061 --> 05:14:42,797
and thankfully I just saw her
for her five year follow-up

6395
05:14:42,797 --> 05:14:45,400
and she's doing extremely well.
She was not able to work.

6396
05:14:45,400 --> 05:14:48,203
Now she's working full time
and taking care of her kids.

6397
05:14:49,404 --> 05:14:52,574
This is -- I would like
to thank our team.

6398
05:14:52,574 --> 05:14:54,642
This is January of 2024, we --

6399
05:14:54,642 --> 05:14:56,711
when we celebrated
our 40th infusion

6400
05:14:57,746 --> 05:14:59,381
of genetically modified,

6401
05:14:59,381 --> 05:15:01,282
genetically edited stem cells
in patients

6402
05:15:01,282 --> 05:15:03,618
with sickle cell disease
and beta thalassemia.

6403
05:15:03,618 --> 05:15:06,755
This study would not have been
able to be conducted in our site

6404
05:15:06,755 --> 05:15:08,923
without an entire village.
Thank you.

6405
05:15:08,923 --> 05:15:10,525
I'm happy to take
any questions.

6406
05:15:15,363 --> 05:15:18,900
Swee Thein: Thank you so much.
That was a really good overview.

6407
05:15:19,701 --> 05:15:24,472
So I see one hand raised.
In fact two.

6408
05:15:24,472 --> 05:15:26,374
Maybe let's start
with Mark Walters.

6409
05:15:26,374 --> 05:15:27,976
Haydar Frangoul: Oh,
I'm in trouble.

6410
05:15:27,976 --> 05:15:29,577
Mark Walters: Hi, Haydar.
That was really --

6411
05:15:30,612 --> 05:15:34,449
I think both those approaches
using the CRISPR technology

6412
05:15:34,449 --> 05:15:37,252
clearly established the efficacy
of the treatment

6413
05:15:38,987 --> 05:15:41,222
certainly in the short term,
if not the long term.

6414
05:15:41,222 --> 05:15:46,261
So my question has more to do
with safety and we know that,

6415
05:15:46,995 --> 05:15:50,098
that double strand of breaks
in true hematopoietic

6416
05:15:50,098 --> 05:15:54,369
stem cells elicit untoward
effects and cell death.

6417
05:15:54,369 --> 05:15:58,773
And from David Kent's careful
work

6418
05:16:00,275 --> 05:16:03,011
characterizing six patients
in David Williams' trial,

6419
05:16:03,812 --> 05:16:07,615
that reconstitution
of hematopoiesis can --

6420
05:16:07,615 --> 05:16:11,319
occurs in as few as several
thousand true hematopoietic

6421
05:16:11,319 --> 05:16:14,055
stem cells in
the lentiviral approach.

6422
05:16:14,055 --> 05:16:17,692
I predict it's even fewer
after CRISPR disruption.

6423
05:16:17,692 --> 05:16:22,163
So what can you tell us
about clonal hematopoiesis

6424
05:16:22,163 --> 05:16:24,699
after these treatments?
Have you --

6425
05:16:24,699 --> 05:16:29,003
been have you been following
the natural history

6426
05:16:29,003 --> 05:16:30,738
of this post-infusion?

6427
05:16:30,738 --> 05:16:32,240
Haydar Frangoul: The short
answer is no.

6428
05:16:32,240 --> 05:16:35,109
None of these studies
really did clonal hematopoiesis.

6429
05:16:35,643 --> 05:16:38,746
And this was a decision
made by the sponsors.

6430
05:16:38,746 --> 05:16:41,483
Now we are performing
bone marrows routinely

6431
05:16:41,483 --> 05:16:43,885
and we are storing
bone marrows for testing

6432
05:16:43,885 --> 05:16:45,787
if something is to arise
in the future.

6433
05:16:45,787 --> 05:16:47,455
But clonal hematopoiesis,

6434
05:16:47,455 --> 05:16:49,490
I think the point you're raising
is very important.

6435
05:16:49,490 --> 05:16:52,827
And this has not been studied
very well in this setting.

6436
05:16:54,929 --> 05:16:56,731
Female Speaker: Yeah.
It's over here.

6437
05:16:56,731 --> 05:16:58,433
Yeah, that was
a fascinating talk.

6438
05:16:59,067 --> 05:17:01,769
In the exa-cel trial,
you measured pain

6439
05:17:02,303 --> 05:17:05,240
and you saw that
that went down in the patients.

6440
05:17:05,240 --> 05:17:07,575
Was that presumably
that was chronic pain

6441
05:17:08,076 --> 05:17:10,111
because they're not --

6442
05:17:10,111 --> 05:17:12,547
are they not having
any acute pain whatsoever

6443
05:17:12,547 --> 05:17:17,418
because they don't have VOEs
and then -- yeah.

6444
05:17:17,418 --> 05:17:19,153
How did you measure the pain?

6445
05:17:19,153 --> 05:17:20,555
Haydar Frangoul: Yeah.
Well, this is a great question.

6446
05:17:20,555 --> 05:17:23,124
So the majority -- actually two
thirds of the patients

6447
05:17:23,124 --> 05:17:25,126
in the exa-cel trial
were adults.

6448
05:17:25,126 --> 05:17:27,896
And I can speak on which
a lot of the patients

6449
05:17:27,896 --> 05:17:29,297
were from our side.

6450
05:17:29,297 --> 05:17:31,766
A lot of patients came to us
as adults with, you know,

6451
05:17:31,766 --> 05:17:33,902
AVN in the shoulder,
AVN in the hip,

6452
05:17:33,902 --> 05:17:35,436
that they were on
chronic opioids.

6453
05:17:35,436 --> 05:17:37,272
I can tell you
within our side data,

6454
05:17:37,272 --> 05:17:38,973
which we have not yet really,

6455
05:17:38,973 --> 05:17:41,109
truly looked back
at the pain scale

6456
05:17:41,109 --> 05:17:42,443
and looking at which is chronic,

6457
05:17:42,443 --> 05:17:44,979
which is acute,
is everybody in our site

6458
05:17:44,979 --> 05:17:47,115
was able to come off
their chronic opioids.

6459
05:17:47,115 --> 05:17:49,384
Now, several individuals
had to go back

6460
05:17:49,384 --> 05:17:51,319
and get their hips
and shoulders replaced,

6461
05:17:51,319 --> 05:17:52,687
which they were planning pre,

6462
05:17:52,687 --> 05:17:54,789
but they postponed it
until after

6463
05:17:54,789 --> 05:17:57,492
and they were able to
come off the medications.

6464
05:17:57,492 --> 05:18:01,062
But as you can tell -- that,
you know, sickle cell disease,

6465
05:18:01,062 --> 05:18:02,997
as you know,
is a chronic disease

6466
05:18:02,997 --> 05:18:05,199
that leads to a lot
of long-term complications.

6467
05:18:05,199 --> 05:18:07,802
So a lot of those damage joints

6468
05:18:07,802 --> 05:18:09,237
are not going to get
miraculously better

6469
05:18:09,237 --> 05:18:10,838
because we infused exa-cel.
Correct.

6470
05:18:10,838 --> 05:18:13,308
So I think there is
a component of chronic pain.

6471
05:18:13,308 --> 05:18:15,510
And in fact,
I think also what is --

6472
05:18:15,510 --> 05:18:18,246
was an eyeopener
is even with Victoria

6473
05:18:18,246 --> 05:18:19,914
in the first
six months afterwards,

6474
05:18:19,914 --> 05:18:22,784
she calls me and says, doc,
I think my sickle cell is back.

6475
05:18:22,784 --> 05:18:24,552
It's like, okay, so Victoria,
what's happening?

6476
05:18:24,552 --> 05:18:26,087
It's like, well, my legs hurt.

6477
05:18:26,087 --> 05:18:28,289
What did you do?
I cleaned house all day.

6478
05:18:28,289 --> 05:18:30,692
I worked,
I took my kids to school

6479
05:18:30,692 --> 05:18:32,160
and what is a baseball game.

6480
05:18:32,160 --> 05:18:34,395
Well, I'm hearing
that I am hurting. Correct.

6481
05:18:34,395 --> 05:18:36,965
So I think there is also
a lot of anxiety

6482
05:18:36,965 --> 05:18:38,599
in the patients about pain

6483
05:18:38,599 --> 05:18:40,635
and attributing pain
from daily life.

6484
05:18:40,635 --> 05:18:43,538
Also, I think that issue
really needs to be addressed

6485
05:18:43,538 --> 05:18:46,841
not only in the gene therapy
but in the transplant setting

6486
05:18:46,841 --> 05:18:49,010
to see what happens
to pain afterwards.

6487
05:18:49,010 --> 05:18:50,612
I think this is a huge need
in the field.

6488
05:18:50,612 --> 05:18:51,846
Female Speaker: That's
fascinating.

6489
05:18:51,846 --> 05:18:53,581
Thank you so much.

6490
05:18:53,581 --> 05:18:54,983
Swee Thein: So you have
one comment

6491
05:18:54,983 --> 05:18:59,821
from one of the people
listening hybrid online.

6492
05:18:59,821 --> 05:19:02,223
It's a groundbreaking
innovation. Congratulations.

6493
05:19:02,223 --> 05:19:03,458
Haydar Frangoul: Well,
thank you.

6494
05:19:03,458 --> 05:19:06,461
This is a team effort.
This is not only me. Thank you.

6495
05:19:06,461 --> 05:19:08,029
Swee Thein: I want to
ask you one last question.

6496
05:19:08,029 --> 05:19:09,797
Yes, sure.
In one of your slides,

6497
05:19:10,398 --> 05:19:11,833
the person we followed,

6498
05:19:11,833 --> 05:19:16,771
I think the longest,
hemoglobin reached 17.6 total.

6499
05:19:16,771 --> 05:19:18,072
Haydar Frangoul: In the
reni-cel?

6500
05:19:18,072 --> 05:19:19,307
Swee Thein: That's the reni-cel.
Yes.

6501
05:19:19,307 --> 05:19:20,508
Haydar Frangoul: The reni-cel.
Yes.

6502
05:19:20,508 --> 05:19:23,211
The hemoglobin was high
and actually it had --

6503
05:19:23,211 --> 05:19:25,213
it's having no adverse event
on the patient.

6504
05:19:25,213 --> 05:19:27,015
The patient is doing very well,
but you are right,

6505
05:19:27,015 --> 05:19:30,218
there were occasional patients
even on the exa-cel trial

6506
05:19:30,218 --> 05:19:32,987
that reached the hemoglobin
in the 16 year range.

6507
05:19:32,987 --> 05:19:35,523
Swee Thein: So, and there
are no issues.

6508
05:19:35,523 --> 05:19:37,258
Haydar Frangoul: No. No issues,
no clinical issues

6509
05:19:37,258 --> 05:19:39,994
at least that we can see
from the increased hemoglobin.

6510
05:19:42,096 --> 05:19:43,331
Male Speaker: Oh, yep.

6511
05:19:43,331 --> 05:19:44,532
Swee Thein: You are
going to take over.

6512
05:19:44,532 --> 05:19:45,733
Haydar Frangoul: Yep.
I am going to take over.

6513
05:19:45,733 --> 05:19:47,468
Thank you.
So I'm going to --

6514
05:19:47,468 --> 05:19:49,470
I'm going to introduce
our next speaker.

6515
05:19:50,371 --> 05:19:51,672
Oh, there's another question.
Yes.

6516
05:19:51,672 --> 05:19:52,874
Male Speaker: Sorry,
I just had --

6517
05:19:52,874 --> 05:19:54,075
Haydar Frangoul: Yeah, sure.

6518
05:19:54,075 --> 05:19:55,309
Male Speaker: Yeah.
So thank you for your talk.

6519
05:19:55,309 --> 05:19:58,112
So similar to Mark's question
in double strand breaks,

6520
05:19:58,112 --> 05:20:00,448
comparing the reni-cel
and exa-cel data, right?

6521
05:20:00,448 --> 05:20:01,916
There are some differences
in media

6522
05:20:01,916 --> 05:20:03,518
and neutrophil engraftment times

6523
05:20:03,518 --> 05:20:05,053
and you're looking
at the ranges.

6524
05:20:05,053 --> 05:20:07,155
Can you comment all that?
We don't have any --

6525
05:20:07,155 --> 05:20:09,424
at least I don't think
public data on GCSF

6526
05:20:09,424 --> 05:20:10,658
use post-transplant.

6527
05:20:10,658 --> 05:20:13,094
Right. Just trying to compare
those engraftment times.

6528
05:20:13,094 --> 05:20:15,596
Can you speak to GCSF use?

6529
05:20:15,596 --> 05:20:17,432
Haydar Frangoul: I don't know
the GCSF use

6530
05:20:17,432 --> 05:20:18,633
for individual patients.

6531
05:20:18,633 --> 05:20:21,736
I know that the studies
allow GCSF use

6532
05:20:21,736 --> 05:20:23,237
if there is no engraftment

6533
05:20:23,237 --> 05:20:26,407
at the discretion
of the investigator

6534
05:20:26,407 --> 05:20:30,111
by day 21 with consultation
with the medical monitor.

6535
05:20:30,111 --> 05:20:32,847
So I know that some patients
received GCSF

6536
05:20:32,847 --> 05:20:35,349
just because they had an ASC
of 400 and they were bored.

6537
05:20:35,349 --> 05:20:36,951
They wanted to leave
the hospital,

6538
05:20:36,951 --> 05:20:38,453
so they needed
to meet engraftment.

6539
05:20:38,453 --> 05:20:40,788
So they received GCSF
to engraft.

6540
05:20:40,788 --> 05:20:42,490
But I don't have
the exact data,

6541
05:20:43,024 --> 05:20:46,694
but I know both studies allowed
the use of GCSF after day 21.

6542
05:20:46,694 --> 05:20:48,029
Male Speaker: Thank you.

6543
05:20:48,029 --> 05:20:49,630
Haydar Frangoul: Oh, you're
welcome.

6544
05:20:50,665 --> 05:20:54,102
All right. It's my pleasure
to introduce the next speaker.

6545
05:20:55,103 --> 05:20:57,405
The talk is the induction
of fetal hemoglobin,

6546
05:20:57,405 --> 05:20:59,907
small molecule
and pharmacological approaches.

6547
05:21:00,741 --> 05:21:03,578
It is Dr. Scott Peslak.

6548
05:21:03,578 --> 05:21:05,646
Dr. Peslak is
a physician scientist

6549
05:21:05,646 --> 05:21:07,949
and an assistant professor
of medicine

6550
05:21:07,949 --> 05:21:09,383
at the University
of Pennsylvania

6551
05:21:09,383 --> 05:21:10,618
and cares for patients

6552
05:21:10,618 --> 05:21:13,287
at UPenn Comprehensive
Sickle Cell Program

6553
05:21:13,287 --> 05:21:15,723
and comprehensive adult
thalassemia program.

6554
05:21:15,723 --> 05:21:17,291
Thank you.

6555
05:21:21,662 --> 05:21:22,930
Scott Peslak: Great. Thank you.

6556
05:21:22,930 --> 05:21:24,465
I'd love to thank the organizers
for inviting me

6557
05:21:24,465 --> 05:21:26,400
to speak here today.
It's my first time in Jamaica.

6558
05:21:26,400 --> 05:21:28,503
It's really lovely and
it's really fantastic to hear

6559
05:21:28,503 --> 05:21:31,472
all this wonderful research
going on here in the field.

6560
05:21:31,472 --> 05:21:32,940
So as Dr. Frangoul said,

6561
05:21:32,940 --> 05:21:34,976
I'm an adult hematologist
at UPenn

6562
05:21:34,976 --> 05:21:36,711
and I see sickle cell disease
and thalassemia patients.

6563
05:21:36,711 --> 05:21:39,313
I'll be talking today
about small molecules

6564
05:21:39,313 --> 05:21:42,316
and pharmacological approaches
to inducing fetal hemoglobin.

6565
05:21:42,316 --> 05:21:44,118
And these are my disclosures.

6566
05:21:45,453 --> 05:21:47,321
So we all know --
what we're all here for

6567
05:21:47,321 --> 05:21:48,623
is a study
of sickle cell disease.

6568
05:21:48,623 --> 05:21:50,558
And the point I wanted
to make with this slide

6569
05:21:50,558 --> 05:21:55,062
is that we not only want
to treat acute complications

6570
05:21:55,062 --> 05:21:56,864
from sickle cell disease,
but really to prevent these

6571
05:21:56,864 --> 05:21:59,167
from happening in
the first place by using disease

6572
05:21:59,167 --> 05:22:02,403
modifying therapies to prevent
occlusive pain episodes

6573
05:22:02,403 --> 05:22:03,838
and prevent
chronic complications,

6574
05:22:03,838 --> 05:22:05,273
which can really occur
in any organ system

6575
05:22:05,273 --> 05:22:06,507
throughout the entire body.

6576
05:22:06,507 --> 05:22:08,075
And we'll hear a lot
about this tomorrow

6577
05:22:08,075 --> 05:22:09,310
in a whole series of talks

6578
05:22:09,310 --> 05:22:10,845
involving specific
organ complications

6579
05:22:10,845 --> 05:22:12,446
in sickle cell disease.

6580
05:22:12,980 --> 05:22:14,715
There's been a tremendous
amount of progress

6581
05:22:14,715 --> 05:22:17,518
on the pediatric side
in improving mortality.

6582
05:22:17,518 --> 05:22:20,655
We heard this morning in
sickle cell pediatric patients,

6583
05:22:21,322 --> 05:22:23,958
and this coincides
with disease

6584
05:22:23,958 --> 05:22:25,726
directed therapy
like hydroxyurea

6585
05:22:25,726 --> 05:22:28,796
as well as early treatment
of infection and vaccination.

6586
05:22:28,796 --> 05:22:30,665
But we really haven't made
a tremendous amount of progress

6587
05:22:30,665 --> 05:22:33,100
in the adult side.
And so we --

6588
05:22:33,100 --> 05:22:35,169
and this is a study done
by Lanzkron a few years ago,

6589
05:22:35,169 --> 05:22:36,637
and many others have looked
at this as well,

6590
05:22:36,637 --> 05:22:37,972
that we need to move the needle

6591
05:22:37,972 --> 05:22:41,342
more in improving morbidity
and mortality

6592
05:22:41,342 --> 05:22:43,778
and lengthening life
and improving quality of life

6593
05:22:43,778 --> 05:22:45,646
in our adult
sickle cell population.

6594
05:22:46,881 --> 05:22:48,482
So as you just heard
from Dr. Frangoul,

6595
05:22:48,482 --> 05:22:50,017
there's been a tremendous
amount of excitement

6596
05:22:50,017 --> 05:22:53,154
involving gene therapy as well
as bone marrow transplant

6597
05:22:53,154 --> 05:22:54,755
[laughs].
Thank you.

6598
05:22:56,290 --> 05:22:59,260
And these really are
transformative therapies

6599
05:22:59,260 --> 05:23:00,928
for the treatment
of sickle cell disease.

6600
05:23:00,928 --> 05:23:02,964
However, there are
some limitations.

6601
05:23:02,964 --> 05:23:04,665
This is challenging
to deploy worldwide,

6602
05:23:04,665 --> 05:23:06,067
not only because of cost,

6603
05:23:06,067 --> 05:23:07,401
which we is a barrier
we can overcome,

6604
05:23:07,401 --> 05:23:09,604
but also the expertise that's
needed to actually be able

6605
05:23:09,604 --> 05:23:12,506
to deliver an autologous stem
cell transplant to patients.

6606
05:23:13,040 --> 05:23:14,375
As Dr. Frangoul
mentioned as well,

6607
05:23:14,375 --> 05:23:16,277
busulfan is not really
a great conditioning regimen.

6608
05:23:16,277 --> 05:23:18,312
We need better conditioning
regimens since this does

6609
05:23:18,312 --> 05:23:21,315
potentially result in things
like secondary malignancies

6610
05:23:21,315 --> 05:23:23,451
as well as infertility
in our patients.

6611
05:23:23,451 --> 05:23:25,486
So there's been
a tremendous amount of efforts

6612
05:23:25,486 --> 05:23:27,188
trying to find
new pharmacologic therapies

6613
05:23:27,188 --> 05:23:28,456
for the treatment
of sickle cell disease.

6614
05:23:28,456 --> 05:23:30,658
And in the United States
there's four FDA approved

6615
05:23:30,658 --> 05:23:33,160
therapies, hydroxyurea,
which I won't talk about today

6616
05:23:33,160 --> 05:23:34,829
because there's
a whole session tomorrow

6617
05:23:34,829 --> 05:23:37,231
focusing on hydroxyurea
as well as Crizanlizumab,

6618
05:23:37,231 --> 05:23:39,100
which is a P selected
inhibitor, Voxelotor,

6619
05:23:39,100 --> 05:23:40,501
which binds high oxygen
and affinity

6620
05:23:40,501 --> 05:23:41,902
binding hemoglobin state

6621
05:23:41,902 --> 05:23:44,405
and now L-glutamine,
which reduces oxidative stress.

6622
05:23:44,405 --> 05:23:46,140
And these work well
for many patients,

6623
05:23:46,140 --> 05:23:47,441
but they don't work
well for all patients,

6624
05:23:47,441 --> 05:23:48,976
particularly on the adult side.

6625
05:23:48,976 --> 05:23:51,512
So we need more effective
pharmacologic options

6626
05:23:51,512 --> 05:23:53,981
for treatment of our sickle
cell disease patients.

6627
05:23:53,981 --> 05:23:55,349
And what I'll talk about today

6628
05:23:55,349 --> 05:23:56,751
is the induction
of fetal hemoglobin

6629
05:23:56,751 --> 05:23:58,386
from a pharmacologic
perspective.

6630
05:23:58,953 --> 05:24:01,155
So you heard from Dr. Bauer
and Dr. Frangoul

6631
05:24:01,155 --> 05:24:03,357
about this hemoglobin switch
that occurs in --

6632
05:24:03,357 --> 05:24:06,394
during the perinatal period
in which you have a switch

6633
05:24:06,394 --> 05:24:08,963
from fetal hemoglobin
to adult hemoglobin.

6634
05:24:08,963 --> 05:24:10,531
And if we can reverse
this switch,

6635
05:24:10,531 --> 05:24:13,334
the idea is that we can reverse
a lot of the pathophysiology

6636
05:24:13,334 --> 05:24:14,769
and the complications
that happen

6637
05:24:14,769 --> 05:24:16,871
in sickle cell
disease patients.

6638
05:24:16,871 --> 05:24:18,873
And the reason
this is the same figure

6639
05:24:18,873 --> 05:24:20,708
that we know from
a few years ago now,

6640
05:24:20,708 --> 05:24:23,678
that either if you see induction
of fetal hemoglobin

6641
05:24:23,678 --> 05:24:26,881
by hydroxyurea or by naturally
occurring genetic variants

6642
05:24:26,881 --> 05:24:29,417
termed hereditary persistence
of fetal hemoglobin,

6643
05:24:29,417 --> 05:24:31,085
these patients live longer
and they do better

6644
05:24:31,085 --> 05:24:32,286
and have fewer complications.

6645
05:24:32,286 --> 05:24:34,622
And this is because cells
that express fetal hemoglobin

6646
05:24:34,622 --> 05:24:37,825
that termed F cells are less
likely to undergo vaso occlusion

6647
05:24:37,825 --> 05:24:39,060
and also less likely
to hemolyze.

6648
05:24:39,060 --> 05:24:41,996
So if we could increase F cells,
we really could reverse

6649
05:24:41,996 --> 05:24:44,065
all the underlying
cellular pathophysiology

6650
05:24:44,065 --> 05:24:45,333
of sickle cell disease

6651
05:24:45,333 --> 05:24:47,034
and all organ systems
can benefit.

6652
05:24:48,035 --> 05:24:49,603
There's been a tremendous
amount of work

6653
05:24:49,603 --> 05:24:51,205
in the last 20
to 30 years,

6654
05:24:51,739 --> 05:24:54,008
involving trying to understand
how this switch works

6655
05:24:54,008 --> 05:24:56,644
and the direct transcriptional
repressors of fetal hemoglobin.

6656
05:24:56,644 --> 05:24:59,814
And again, Dr. Bauer explained
this earlier work

6657
05:24:59,814 --> 05:25:01,382
that was originally described
by Swee Lay Thein

6658
05:25:01,382 --> 05:25:02,750
and subsequently
by Stuart Orkins

6659
05:25:02,750 --> 05:25:04,852
Lab, Dan Bauer, [unintelligible]
and many others,

6660
05:25:04,852 --> 05:25:07,988
identifying BC11A as a
direct transcription repressor

6661
05:25:07,988 --> 05:25:09,890
of fetal hemoglobin
in addition to LRF

6662
05:25:09,890 --> 05:25:12,326
or ZBTB7A and NF1A and X,

6663
05:25:12,326 --> 05:25:15,196
which is identified by Garrett
Lobo's Lab a few years ago.

6664
05:25:15,196 --> 05:25:17,264
And ideally, we'd like to be
able to target these directly.

6665
05:25:17,264 --> 05:25:20,201
And this is what the therapy
for -- gene therapy for --

6666
05:25:20,201 --> 05:25:23,037
as we just heard for BC11A
is the target for.

6667
05:25:23,037 --> 05:25:25,539
However, from a therapeutic
and pharmacologic perspective,

6668
05:25:25,539 --> 05:25:27,575
this is very challenging
to target these transcription

6669
05:25:27,575 --> 05:25:29,744
factors
directly with small molecules.

6670
05:25:30,244 --> 05:25:33,347
Thus my goal since I've been
working in the lab,

6671
05:25:33,347 --> 05:25:35,616
first in Garrett Lobo's Lab
as a postdoc and now my own lab

6672
05:25:35,616 --> 05:25:37,651
as well as others in the field
to try to understand

6673
05:25:37,651 --> 05:25:39,553
what are the upstream
of these regulators?

6674
05:25:39,553 --> 05:25:41,956
What can we target to be able
to modulate fetal hemoglobin

6675
05:25:41,956 --> 05:25:43,290
in a positive way?

6676
05:25:43,290 --> 05:25:46,460
And we've had a tremendous
amount of success

6677
05:25:46,460 --> 05:25:48,129
doing this with
the collaboration with Junwe Shi

6678
05:25:48,129 --> 05:25:49,597
at the University
of Pennsylvania,

6679
05:25:49,597 --> 05:25:51,599
in which we use CRISPR
domain focus,

6680
05:25:51,599 --> 05:25:53,801
CRISPR knockout screens,
where we take either two cells

6681
05:25:53,801 --> 05:25:55,102
which are erythroid cell lines

6682
05:25:55,102 --> 05:25:57,438
that are really good for you
doing genetic studies

6683
05:25:57,438 --> 05:25:59,940
and infect them with specific
guide RNA libraries

6684
05:25:59,940 --> 05:26:02,610
that target specific kinds
of functions in the cell.

6685
05:26:03,177 --> 05:26:04,745
We can then differentiate
and sort these

6686
05:26:04,745 --> 05:26:07,181
into fetal hemoglobin high
and low populations

6687
05:26:07,181 --> 05:26:09,683
and identify which genes
when depleted lead

6688
05:26:09,683 --> 05:26:11,752
to higher levels
of fetal hemoglobin.

6689
05:26:11,752 --> 05:26:12,987
And these are some of the kinase

6690
05:26:12,987 --> 05:26:15,523
or some of the libraries
we've targeted here,

6691
05:26:15,523 --> 05:26:16,891
I'll talk about today,

6692
05:26:16,891 --> 05:26:18,426
identifying many
different targets

6693
05:26:18,426 --> 05:26:20,594
that have really expanded
our knowledge

6694
05:26:20,594 --> 05:26:22,229
of how fetal hemoglobin
is regulated,

6695
05:26:22,229 --> 05:26:24,698
not just at
a direct transcriptional level,

6696
05:26:24,698 --> 05:26:26,767
but upstream of this as well.

6697
05:26:26,767 --> 05:26:29,570
And this really has broadened
our idea of how switching works.

6698
05:26:29,570 --> 05:26:31,372
This is a really nice review,

6699
05:26:31,372 --> 05:26:33,607
written by my colleague
Eugene Khandros,

6700
05:26:33,607 --> 05:26:35,409
in the Children's Hospital
of Philadelphia

6701
05:26:35,409 --> 05:26:37,912
and Garrett Lobo
that looks at both gamma globin,

6702
05:26:37,912 --> 05:26:39,713
repressors and activators.
And this all,

6703
05:26:39,713 --> 05:26:42,183
there's a lot of lines
in this thing in this graph.

6704
05:26:42,183 --> 05:26:43,918
So I'm not going to go through
every one of these.

6705
05:26:43,918 --> 05:26:46,053
But I'm going to talk about
a subset of these

6706
05:26:46,053 --> 05:26:48,022
that I think are important to
highlight some of the advances

6707
05:26:48,022 --> 05:26:51,358
that have been made in the last
five to 10 years or so here.

6708
05:26:51,358 --> 05:26:52,593
So the first I'll talk about

6709
05:26:52,593 --> 05:26:54,095
is something that came
out of Garrett Lobo

6710
05:26:54,095 --> 05:26:55,830
and work that I've done as well,

6711
05:26:55,830 --> 05:26:58,098
identifying a regulator
of fetal hemoglobin

6712
05:26:58,098 --> 05:27:00,301
called Heme-regulated
inhibitor, HRI.

6713
05:27:00,301 --> 05:27:02,069
And this is one of the first
libraries we've screened.

6714
05:27:02,069 --> 05:27:03,804
We looked at kinase
screens libraries

6715
05:27:03,804 --> 05:27:06,807
because they're purportedly
the most easiest

6716
05:27:06,807 --> 05:27:08,476
to be able to target.

6717
05:27:08,476 --> 05:27:11,946
And we depleted HRI and we saw
increases in fetal hemoglobin

6718
05:27:11,946 --> 05:27:13,581
in our in vitro systems.

6719
05:27:14,181 --> 05:27:16,851
And we -- I'd elucidated
the mechanism of this proceeding

6720
05:27:16,851 --> 05:27:18,686
via intermediate called ATF4.

6721
05:27:18,686 --> 05:27:22,223
So ATF four is translationally
regulated by HRI.

6722
05:27:22,223 --> 05:27:24,892
ATF4, we showed binds
to the minor enhancer,

6723
05:27:24,892 --> 05:27:26,360
the plus 55 enhancer,
as you heard

6724
05:27:26,360 --> 05:27:29,196
from Dr. Bauer of BC11A
and drives the transcription.

6725
05:27:29,196 --> 05:27:31,432
So if we deplete HRI,
we can decrease

6726
05:27:31,432 --> 05:27:34,068
ATF4 and decrease transcription
to BC11A

6727
05:27:34,068 --> 05:27:36,604
and thus increase levels
of fetal hemoglobin.

6728
05:27:37,338 --> 05:27:40,641
And I showed subsequently that
we can combine HRI depletion

6729
05:27:40,641 --> 05:27:43,277
with other modulators
of fetal hemoglobin inducers,

6730
05:27:43,277 --> 05:27:45,079
including several
I'll talk about today,

6731
05:27:45,079 --> 05:27:48,749
such as pomalidomide
and UNC0638 to reduce --

6732
05:27:48,749 --> 05:27:51,986
to significantly increase levels
of fetal hemoglobin by HPLC,

6733
05:27:51,986 --> 05:27:54,655
which is our clinical gold
standard and reduce cellular

6734
05:27:54,655 --> 05:27:57,157
sickling in a synergistic
and in additive way.

6735
05:27:59,560 --> 05:28:01,362
Another screen,

6736
05:28:01,362 --> 05:28:03,197
another target that came out
of our initial screens

6737
05:28:03,197 --> 05:28:05,332
is a molecule called ZNF410.

6738
05:28:05,332 --> 05:28:07,101
And this emerged
as a positive hit

6739
05:28:07,101 --> 05:28:09,303
in one of our CRISPR screens
as well.

6740
05:28:09,303 --> 05:28:13,107
This is work led by--
in Garrett Lobo's Lab as well,

6741
05:28:13,641 --> 05:28:15,809
involving if we deplete ZNF410,

6742
05:28:15,809 --> 05:28:18,979
we can significantly increase
levels of gamma globin.

6743
05:28:18,979 --> 05:28:22,683
And this works by
modulating levels of CHD4.

6744
05:28:22,683 --> 05:28:25,986
So ZNF410 represses fetal
hemoglobin and modulating CHD4.

6745
05:28:26,520 --> 05:28:29,557
Very intriguingly, CHD4 is the
only direct functional target

6746
05:28:29,557 --> 05:28:32,192
of ZNF410 and erythroid cells.
It's remarkably specific.

6747
05:28:32,192 --> 05:28:37,131
So this work came out of John
Jang Long in in Garrett's Lab.

6748
05:28:37,131 --> 05:28:39,433
And at the same time,
Dan Bauer's group published

6749
05:28:39,433 --> 05:28:43,871
nearly identical results,
with the target of CHD4 that,

6750
05:28:44,872 --> 05:28:47,942
the ZNF410 bound regulatory
elements completely account

6751
05:28:47,942 --> 05:28:51,312
for the effects of ZNF410
on fetal hemoglobin repression.

6752
05:28:51,312 --> 05:28:52,646
So it comes up with this model

6753
05:28:52,646 --> 05:28:54,114
where there's this genome
wide unique

6754
05:28:54,114 --> 05:28:58,485
and really conserved set of
motif clusters upstream of CHD4

6755
05:28:58,485 --> 05:28:59,853
that drive its transcription.

6756
05:28:59,853 --> 05:29:02,356
And by knocking this out,
we can decrease CHD4

6757
05:29:02,356 --> 05:29:04,725
and potentially increase levels
of fetal hemoglobin

6758
05:29:04,725 --> 05:29:06,860
in future treatment
of sickle cell disease.

6759
05:29:08,596 --> 05:29:10,831
Another interesting study that
came out of Mitch Weiss's group

6760
05:29:10,831 --> 05:29:14,201
at St. Jude
identified a HIF1-alpha and VHL

6761
05:29:14,201 --> 05:29:15,936
as a modulator
of fetal hemoglobin.

6762
05:29:16,637 --> 05:29:19,473
They show that VHL loss leads
to fetal hemoglobin induction

6763
05:29:19,473 --> 05:29:22,776
via stabilization, interestingly
of HIF1-alpha upregulation.

6764
05:29:23,410 --> 05:29:26,380
So we see here that targeting
directly a VHL leads

6765
05:29:26,380 --> 05:29:28,282
to increases in gamma globin,

6766
05:29:28,282 --> 05:29:31,018
and in doing it does so
by stabilizing HIF1-alpha

6767
05:29:31,018 --> 05:29:32,620
in a HIF1-alpha
dependent mechanism.

6768
05:29:32,620 --> 05:29:34,989
If we knock out HIF1-alpha,
we actually lose that induction

6769
05:29:34,989 --> 05:29:36,824
of fetal hemoglobin that's seen.

6770
05:29:36,824 --> 05:29:38,926
And interestingly, this actually
works by promoting

6771
05:29:38,926 --> 05:29:40,494
direct interactions

6772
05:29:40,494 --> 05:29:42,096
between what's called
the locus control region,

6773
05:29:42,096 --> 05:29:43,831
which is the super enhancer
that's present

6774
05:29:43,831 --> 05:29:46,567
in the beta globin locus
and the gamma globin promoter.

6775
05:29:47,368 --> 05:29:50,404
And as by a series of capture C
studies that are shown here

6776
05:29:50,404 --> 05:29:52,439
in which we have a model --
at high oxygenation,

6777
05:29:52,439 --> 05:29:55,342
you have HIF1-alpha degradation,
but with low oxygenation,

6778
05:29:55,342 --> 05:29:57,344
HIF1-alpha is actually
stabilized and promotes

6779
05:29:57,344 --> 05:29:59,546
these contacts between the LCR

6780
05:29:59,546 --> 05:30:01,348
and the gamma
globin gene region.

6781
05:30:01,348 --> 05:30:04,218
So Mitch's Lab asked,
can we actually induce this

6782
05:30:04,218 --> 05:30:06,520
by stabilizing HIF1-alpha
using a class of compounds

6783
05:30:06,520 --> 05:30:08,255
that's being studied
in anemia of CKD

6784
05:30:08,255 --> 05:30:10,524
called prolyl
hydroxylase inhibitors?

6785
05:30:10,524 --> 05:30:13,861
And indeed, if we treat cells
in vitro with prolyl hydroxylase

6786
05:30:13,861 --> 05:30:17,464
inhibitors you see stabilization
of HIF1-alpha.

6787
05:30:18,232 --> 05:30:20,200
That's, again, HIF1-alpha
dependent with a knockout

6788
05:30:20,200 --> 05:30:23,771
and is directly correlative with
induction of fetal hemoglobin

6789
05:30:23,771 --> 05:30:26,573
indicating this might be
an evolutionary conserved way

6790
05:30:26,573 --> 05:30:28,342
to regulate fetal hemoglobin,

6791
05:30:28,342 --> 05:30:31,578
but also might lead to ways
we can modulate this

6792
05:30:31,578 --> 05:30:33,013
using small molecules

6793
05:30:33,013 --> 05:30:34,915
to increase levels
of fetal hemoglobin

6794
05:30:34,915 --> 05:30:36,517
in sickle cell disease.

6795
05:30:37,351 --> 05:30:38,986
One of the most interesting
studies that came out

6796
05:30:38,986 --> 05:30:41,622
was presented at plenary ASH
this past year

6797
05:30:41,622 --> 05:30:44,692
and as a, just published
in science a few months ago,

6798
05:30:44,692 --> 05:30:47,561
is a study done by Novo Nordisk
that looked -- using --

6799
05:30:47,561 --> 05:30:50,831
essentially, using a screen
of cell bond degraders,

6800
05:30:50,831 --> 05:30:53,967
cell bond -based degraders
of transcription factors,

6801
05:30:53,967 --> 05:30:56,704
trying to identify how can we
directly target transcription

6802
05:30:56,704 --> 05:30:59,173
factors using small molecules.

6803
05:30:59,173 --> 05:31:01,742
And so they did a screen
looking at fetal hemoglobin

6804
05:31:01,742 --> 05:31:04,011
and then Y axis and cell counts,
the X axis.

6805
05:31:04,011 --> 05:31:06,480
You want to be able and
essentially to identify targets

6806
05:31:06,480 --> 05:31:08,148
that allow for induction
of fetal hemoglobin

6807
05:31:08,148 --> 05:31:09,416
without affecting viability.

6808
05:31:09,416 --> 05:31:11,418
And they identified
this compound C,

6809
05:31:11,418 --> 05:31:13,153
which remarkably
is very specific

6810
05:31:13,153 --> 05:31:14,621
for the degradation
of the transcription vector

6811
05:31:14,621 --> 05:31:18,025
called whiz which is targets
and depletes this

6812
05:31:18,025 --> 05:31:19,626
at a very low concentration.

6813
05:31:20,861 --> 05:31:23,430
They then went to modify
and optimize this compound

6814
05:31:23,430 --> 05:31:24,932
and actually tested this
in vitro

6815
05:31:24,932 --> 05:31:27,601
and in vivo xenotransplant
mouse models

6816
05:31:28,102 --> 05:31:29,403
as well as in
non-human primates,

6817
05:31:29,403 --> 05:31:32,306
and showed that they saw dose
dependent increases

6818
05:31:32,306 --> 05:31:33,507
in gamma globin transcript

6819
05:31:33,507 --> 05:31:36,110
as well as increases
in F cells and reticulocytes.

6820
05:31:36,944 --> 05:31:38,812
And mechanistically,
it's still a little bit unclear

6821
05:31:38,812 --> 05:31:41,582
how this works but what
they propose in the paper

6822
05:31:41,582 --> 05:31:43,383
is this actually might
support repressive

6823
05:31:43,383 --> 05:31:46,386
methylation of chromatin
and might actually be modulated

6824
05:31:46,386 --> 05:31:49,323
through the EHMT1/2
repressive complex.

6825
05:31:49,923 --> 05:31:51,825
So more common mechanism,
but really interesting

6826
05:31:51,825 --> 05:31:54,294
that we can do a screen
where we can actually identify,

6827
05:31:54,294 --> 05:31:56,063
directly identify molecules

6828
05:31:56,063 --> 05:31:58,532
that are involved
in fetal hemoglobin regulation.

6829
05:31:59,166 --> 05:32:02,069
In terms of EHMT1/2 methyl
transferase inhibition,

6830
05:32:02,069 --> 05:32:03,837
this actually would
published a few --

6831
05:32:03,837 --> 05:32:05,472
excuse me, a few years ago
at the same time

6832
05:32:05,472 --> 05:32:07,007
by Ben Ebert's Lab

6833
05:32:07,007 --> 05:32:11,645
as well as Jeff Miller's group
using a compound called NC0638,

6834
05:32:11,645 --> 05:32:13,847
in which they saw dose
dependent increases

6835
05:32:13,847 --> 05:32:15,449
in fetal hemoglobin levels

6836
05:32:16,183 --> 05:32:19,453
following either EHMT1/2
or G9a inhibitions same complex.

6837
05:32:20,053 --> 05:32:24,191
And this actually acts
by increasing or de-repressing

6838
05:32:24,191 --> 05:32:25,793
the gamma globin gene region

6839
05:32:25,793 --> 05:32:27,961
and increasing context
between gamma globin

6840
05:32:27,961 --> 05:32:29,897
and the locus control region.

6841
05:32:29,897 --> 05:32:32,132
And so you switch
from more of a adult-like state

6842
05:32:32,132 --> 05:32:33,434
to a fetal like state

6843
05:32:33,434 --> 05:32:35,702
and might serve also as
a modulator of fetal hemoglobin

6844
05:32:35,702 --> 05:32:36,970
in sickle cell disease.

6845
05:32:36,970 --> 05:32:40,107
And there are on ongoing large
animal studies for this as well.

6846
05:32:42,109 --> 05:32:45,045
One of the most further advanced
compounds that's being studied

6847
05:32:45,045 --> 05:32:46,447
currently
is a compounds being developed

6848
05:32:46,447 --> 05:32:48,882
by Fulcrum Therapeutics
in the inhibition

6849
05:32:48,882 --> 05:32:50,951
of the Polycomb Repressive
Complex 2,

6850
05:32:50,951 --> 05:32:54,454
or PRC2 called FTX-6058
or pociredir.

6851
05:32:55,589 --> 05:32:57,191
And by inhibiting PRC2,

6852
05:32:57,191 --> 05:32:59,193
they've shown you can increase
levels of fetal hemoglobin

6853
05:32:59,193 --> 05:33:00,794
and there's labs
that are currently studying

6854
05:33:00,794 --> 05:33:03,230
how this is specifically
working mechanistically.

6855
05:33:04,698 --> 05:33:06,133
There's some of the clinical
trial data

6856
05:33:06,133 --> 05:33:08,135
presented at EHA this past year,

6857
05:33:08,135 --> 05:33:10,370
an ongoing Phase 1b study
called the PIONEER Study,

6858
05:33:10,370 --> 05:33:13,740
where they dosed patients
up to 12 milligrams daily

6859
05:33:13,740 --> 05:33:14,975
for 12 weeks,

6860
05:33:14,975 --> 05:33:18,011
and they saw a dose dependent
increase in fetal hemoglobin

6861
05:33:18,011 --> 05:33:19,913
as well as
a significant increase in fetal

6862
05:33:19,913 --> 05:33:21,582
hemoglobin from baseline change.

6863
05:33:22,115 --> 05:33:24,685
So we're eagerly rating
the additional data

6864
05:33:24,685 --> 05:33:27,154
from this likely to be
presented at ASH this year

6865
05:33:27,154 --> 05:33:29,323
and how this affects patients
at higher doses

6866
05:33:29,323 --> 05:33:30,557
and whether there's
any off target

6867
05:33:30,557 --> 05:33:33,327
or other other side effects
with this compound as well.

6868
05:33:35,295 --> 05:33:38,899
One of the studies
that is interesting in

6869
05:33:38,899 --> 05:33:40,167
a different methodology

6870
05:33:40,167 --> 05:33:44,705
is actually to be able
to deplete repressive

6871
05:33:44,705 --> 05:33:46,974
co-repressors
of BCL11A including DNMT1.

6872
05:33:47,541 --> 05:33:50,344
So it's been known for a while
that molecules like decitabine

6873
05:33:50,344 --> 05:33:52,412
can actually decrease DNMT1.

6874
05:33:52,412 --> 05:33:54,815
And this study, this phase
1 study in sickle cell patients

6875
05:33:54,815 --> 05:33:56,817
actually combine this
with tetrahydrouridine,

6876
05:33:56,817 --> 05:33:59,186
which inhibits Cytidine
Deaminase and potentiates

6877
05:33:59,186 --> 05:34:02,689
the effects of decitabine
in repressing DNMT1.

6878
05:34:03,390 --> 05:34:06,994
And so this is a study
that looked at this decitabine

6879
05:34:06,994 --> 05:34:10,998
THU combination drug given twice
a week for eight weeks

6880
05:34:10,998 --> 05:34:12,866
and increasing doses.

6881
05:34:12,866 --> 05:34:14,868
And in this they saw
significant increases,

6882
05:34:14,868 --> 05:34:18,338
especially at the higher dose
in fetal hemoglobin levels

6883
05:34:18,338 --> 05:34:20,073
as well as F cell number.

6884
05:34:20,073 --> 05:34:23,143
And there's a current ongoing
trial called the ASCENT1 trial

6885
05:34:23,143 --> 05:34:25,579
using this looking at
1-to-1 ratio of either

6886
05:34:25,579 --> 05:34:27,381
once weekly,
twice weekly or placebo

6887
05:34:28,048 --> 05:34:30,584
in terms of F cell induction
using this compound.

6888
05:34:30,584 --> 05:34:32,452
So more to come on this
in the coming in --

6889
05:34:32,452 --> 05:34:34,054
the coming year or two.

6890
05:34:35,689 --> 05:34:37,190
Two more compounds
I wanted to talk about.

6891
05:34:37,190 --> 05:34:39,026
And then I want to talk about
something a little bit of work

6892
05:34:39,026 --> 05:34:42,562
from my lab as well.
There's a set of compounds

6893
05:34:42,562 --> 05:34:45,766
looking at inhibiting
of complex called LSD1.

6894
05:34:45,766 --> 05:34:48,435
This is work done
by Doug Engel's lab

6895
05:34:48,435 --> 05:34:51,572
in which they treated
sickle cell mice

6896
05:34:51,572 --> 05:34:53,040
with this RN-1 inhibitor

6897
05:34:53,040 --> 05:34:54,608
and saw increases
in fetal hemoglobin

6898
05:34:54,608 --> 05:34:55,943
and reversion
from sickling state

6899
05:34:55,943 --> 05:34:57,210
to a non-sick state.

6900
05:34:57,210 --> 05:35:00,013
And this is thought to be
proceeding via mechanism

6901
05:35:00,013 --> 05:35:02,883
of PGC1-alpha increase

6902
05:35:02,883 --> 05:35:04,851
which leads to increases
in fetal hemoglobin,

6903
05:35:04,851 --> 05:35:07,020
decreased sickling,
and decreased hemolysis.

6904
05:35:07,788 --> 05:35:09,690
And interestingly, in terms
of combinatorial therapy,

6905
05:35:09,690 --> 05:35:11,892
thinking about this, which I'll
get to a little bit in my --

6906
05:35:11,892 --> 05:35:14,695
in some of my work,
there's actually been work

6907
05:35:14,695 --> 05:35:18,265
coming that Don Lavelle worked
on that looking at increases

6908
05:35:18,265 --> 05:35:19,900
in reticulocytes
and gamma globin

6909
05:35:19,900 --> 05:35:21,335
when you combine decitabine,

6910
05:35:21,335 --> 05:35:24,171
as I showed you previously
with LSD1 inhibition

6911
05:35:24,171 --> 05:35:27,207
via RN-1 showing additive
or even synergistic effects

6912
05:35:27,207 --> 05:35:29,543
as far
as fetal hemoglobin induction.

6913
05:35:29,543 --> 05:35:31,378
And this is also shown
in non-human primates

6914
05:35:31,378 --> 05:35:32,913
in this study.
So it'd very interesting

6915
05:35:32,913 --> 05:35:35,115
to see how this replicates
in some of the --

6916
05:35:35,115 --> 05:35:37,951
in human and clinical studies
that are ongoing right now.

6917
05:35:38,685 --> 05:35:40,087
And the final thing
I wanted to mention

6918
05:35:40,087 --> 05:35:41,355
is a really interesting study

6919
05:35:41,355 --> 05:35:45,525
coming out of Bioverative
and Betty Pace's group

6920
05:35:45,525 --> 05:35:47,394
looking at the role
of Nrf2 activation

6921
05:35:47,394 --> 05:35:49,396
in fetal hemoglobin induction.
So they had shown

6922
05:35:49,396 --> 05:35:52,299
previously that
in treating with this compound,

6923
05:35:52,299 --> 05:35:55,102
dimethyl fumarate
can increase Nrf2 levels

6924
05:35:55,102 --> 05:35:57,537
and that can increase
gamma globin levels

6925
05:35:57,537 --> 05:36:00,941
and also increase heme
scavenging and detoxification

6926
05:36:00,941 --> 05:36:02,776
and decrease reactive
oxygen species.

6927
05:36:03,810 --> 05:36:05,912
And so, in relationship to this,

6928
05:36:05,912 --> 05:36:07,681
there's actually a study
just came out this year

6929
05:36:07,681 --> 05:36:09,383
looking at the role
of another compound

6930
05:36:09,383 --> 05:36:11,084
repurposing a drug
that's already out there,

6931
05:36:11,084 --> 05:36:14,621
simvastatin, which is used for
treatment of high cholesterol.

6932
05:36:14,621 --> 05:36:15,889
In which they showed,

6933
05:36:15,889 --> 05:36:18,425
at least in vitro
that simvastatin treatment

6934
05:36:18,425 --> 05:36:20,994
could achieve high levels
of fetal hemoglobin induction

6935
05:36:20,994 --> 05:36:22,663
and increase in stabilize Nrf2.

6936
05:36:22,663 --> 05:36:24,831
And so it'll be interesting
to see if this holds true in,

6937
05:36:24,831 --> 05:36:26,133
in vitro models

6938
05:36:26,133 --> 05:36:28,935
and whether this is something
that could be used potentially

6939
05:36:28,935 --> 05:36:30,937
in the treatment
of sickle cell disease.

6940
05:36:31,738 --> 05:36:34,307
So I wanted to mention
two stories

6941
05:36:34,307 --> 05:36:35,942
kind of that
we're working on in lab,

6942
05:36:35,942 --> 05:36:38,612
one of which is
a set of compounds called IMiDs.

6943
05:36:38,612 --> 05:36:41,815
So IMiDs are very interesting in
that they recapitulate machinery

6944
05:36:41,815 --> 05:36:45,619
that's already present in cells.
That's E3 ubiquitin ligase,

6945
05:36:45,619 --> 05:36:48,188
essentially a cereblon DDB1,
CUL4,

6946
05:36:48,188 --> 05:36:51,291
and ROC1 complex
that tags endogenous substrates

6947
05:36:51,291 --> 05:36:52,526
or degradation
in the proteasome.

6948
05:36:52,526 --> 05:36:55,328
IMiDs actually bind
to this cereblon pocket

6949
05:36:55,328 --> 05:36:58,598
and recruit neo substrates
for degradation that's present.

6950
05:36:58,598 --> 05:37:02,269
And so this class of drugs
was originally used in the 1950s

6951
05:37:02,269 --> 05:37:04,371
for morning sickness in women,

6952
05:37:04,371 --> 05:37:07,074
and was withdrawn because
of it teratogenic effects.

6953
05:37:07,074 --> 05:37:10,610
However, in the 1990s IMiDs
became used in the treatment

6954
05:37:10,610 --> 05:37:12,212
of multiple myeloma

6955
05:37:12,212 --> 05:37:14,414
a plasma cell disorder
of the bone marrow,

6956
05:37:14,414 --> 05:37:17,050
and was approved both
lenalidomide and pomalidomide

6957
05:37:17,050 --> 05:37:19,186
for treatment
in multiple myeloma patients.

6958
05:37:20,353 --> 05:37:21,888
One of the things that's
very interesting

6959
05:37:21,888 --> 05:37:25,058
that has not been recognized
in the field as robustly,

6960
05:37:25,058 --> 05:37:27,627
is that IMiDs are actually
very potent inducers

6961
05:37:27,627 --> 05:37:29,229
of fetal hemoglobin in vitro.

6962
05:37:30,163 --> 05:37:33,233
So originally work done
by Griff Rogers back in 2007,

6963
05:37:33,233 --> 05:37:36,069
had shown that thalidomide
at high doses

6964
05:37:36,069 --> 05:37:38,572
increases levels of gamma globin
and F cell levels

6965
05:37:39,639 --> 05:37:41,208
and work done by Kyle Chan.

6966
05:37:41,208 --> 05:37:43,176
And Celgene actually showed this
is also true

6967
05:37:43,176 --> 05:37:46,113
by in with lenalidomide
and pomalidomide

6968
05:37:46,113 --> 05:37:47,948
at a significantly lower doses,

6969
05:37:47,948 --> 05:37:50,016
so much more potent induction
of fetal hemoglobin

6970
05:37:50,016 --> 05:37:52,986
at much lower doses.
One of the seminal works

6971
05:37:52,986 --> 05:37:54,621
and most comprehensive works
that was done

6972
05:37:54,621 --> 05:37:56,990
was by Brian Del Mobitz
and Leo Blanc's group,

6973
05:37:57,491 --> 05:37:59,593
in which they showed
that pomalidomide treatment

6974
05:37:59,593 --> 05:38:01,495
decreases repressors
such as BCL11A

6975
05:38:02,229 --> 05:38:05,098
and decreases other repressors
such as SOX6 reverting cells

6976
05:38:05,098 --> 05:38:06,433
to a more fetal-like state

6977
05:38:06,433 --> 05:38:09,469
and acts early in
erythroid differentiation,

6978
05:38:09,469 --> 05:38:11,204
unlike some of the other
targets like HRI

6979
05:38:11,204 --> 05:38:12,806
that we've shown previously.

6980
05:38:13,874 --> 05:38:16,276
So the question is,
is this also true in patients?

6981
05:38:16,276 --> 05:38:17,477
And so in this study,

6982
05:38:17,477 --> 05:38:20,180
they actually looked
at multiple myeloma patients

6983
05:38:20,180 --> 05:38:22,082
that have been treated
with pomalidomide

6984
05:38:22,082 --> 05:38:23,850
and asked after
pomalidomide treatment,

6985
05:38:23,850 --> 05:38:25,552
do they see higher levels
of fetal hemoglobin?

6986
05:38:25,552 --> 05:38:28,355
And in fact, they do in these
three patients shown here.

6987
05:38:28,855 --> 05:38:30,690
This at the same time
was a study,

6988
05:38:30,690 --> 05:38:32,325
a phase 1 study led
by Abdullah Cutler

6989
05:38:32,325 --> 05:38:34,561
that looked at
pomalidomide treatment

6990
05:38:34,561 --> 05:38:37,430
in sickle cell disease patients
in escalating doses.

6991
05:38:37,430 --> 05:38:39,666
And remarkably, they actually
saw higher levels

6992
05:38:39,666 --> 05:38:41,168
of fetal hemoglobin
in this study

6993
05:38:41,168 --> 05:38:43,603
at the three milligram
per day or higher dose,

6994
05:38:43,603 --> 05:38:47,073
which is similar to what's used
in multiple myeloma patients.

6995
05:38:47,073 --> 05:38:48,842
So it's possible that, you know,

6996
05:38:48,842 --> 05:38:53,280
if we had a broader therapeutic
window via other modulators,

6997
05:38:53,280 --> 05:38:55,115
could we increase levels
of fetal hemoglobin

6998
05:38:55,115 --> 05:38:56,983
in a safe and effective way?

6999
05:38:56,983 --> 05:38:58,552
And some of the work
we previously published

7000
05:38:58,552 --> 05:39:01,254
showed this may be true.
So as I mentioned before,

7001
05:39:01,254 --> 05:39:03,256
HRI is this regulator
of fetal hemoglobin.

7002
05:39:03,256 --> 05:39:06,426
If we co-deplete HRI and treat
with pomalidomide,

7003
05:39:06,426 --> 05:39:09,462
we see significant levels
of fetal hemoglobin induction.

7004
05:39:09,462 --> 05:39:11,631
Now, if we decrease
the pomalidomide dose by tenfold

7005
05:39:11,631 --> 05:39:13,934
or a hundred-fold, we see
a dose dependent decrease.

7006
05:39:13,934 --> 05:39:16,536
But if we treat
and deplete this,

7007
05:39:16,536 --> 05:39:19,206
this dose by tenfold
and co-deplete with HRI,

7008
05:39:19,206 --> 05:39:22,676
we actually see persistence of
high levels of fetal hemoglobin

7009
05:39:22,676 --> 05:39:24,945
despite a tenfold decrease
in pomalidomide,

7010
05:39:25,478 --> 05:39:28,215
which is interesting to me
in that it's possible

7011
05:39:28,215 --> 05:39:30,250
we could maintain
on-target effects

7012
05:39:30,250 --> 05:39:33,253
by limiting other off-target
effects of drugs like IMiDs.

7013
05:39:33,253 --> 05:39:34,487
This is RNA-Seq data

7014
05:39:34,487 --> 05:39:36,723
that we generated
indicating at high dose

7015
05:39:36,723 --> 05:39:38,658
we see high levels
of gamma globin induction

7016
05:39:38,658 --> 05:39:40,160
and decrease
in B-cell of an A.

7017
05:39:40,160 --> 05:39:42,829
If we decrease the dose
of pomalidomide at tenfold,

7018
05:39:42,829 --> 05:39:45,532
we can see the same degree
of F cell induction,

7019
05:39:45,532 --> 05:39:47,434
but half the number
of genes changed.

7020
05:39:48,501 --> 05:39:50,971
So it's possible by doing,
using combinatorial therapy,

7021
05:39:50,971 --> 05:39:52,439
we might be able to limit

7022
05:39:52,439 --> 05:39:55,675
some of the undesirable
side effects of these inducers

7023
05:39:55,675 --> 05:39:58,745
while still maintaining high
levels of our on-target effect,

7024
05:39:58,745 --> 05:40:00,180
which is increasing
fetal hemoglobin

7025
05:40:00,180 --> 05:40:02,082
for the treatment
of sickle cell disease.

7026
05:40:02,082 --> 05:40:04,184
And I think really,
despite this really robust data

7027
05:40:04,184 --> 05:40:07,153
in vitro the clinical
aspect of this,

7028
05:40:07,153 --> 05:40:08,989
bringing this to patients
remains unrealized and I --

7029
05:40:08,989 --> 05:40:10,757
she just looked
and it's very interesting,

7030
05:40:10,757 --> 05:40:13,860
this pomalidomide is being
tested in a bleeding disorder

7031
05:40:13,860 --> 05:40:16,162
called hereditary
hemorrhagic telangiectasia

7032
05:40:16,162 --> 05:40:17,764
and was just published
eight hours ago

7033
05:40:17,764 --> 05:40:19,032
in the New England Journal,

7034
05:40:19,032 --> 05:40:21,167
that they're able
to use pomalidomide

7035
05:40:21,167 --> 05:40:24,471
to actually significantly reduce
bleeding risk in HHT patients.

7036
05:40:25,005 --> 05:40:26,840
The side effects people worry
about with these drugs

7037
05:40:26,840 --> 05:40:29,576
are thrombosis mostly
and neuropathy.

7038
05:40:29,576 --> 05:40:31,578
They did not see increased
thrombosis or neuropathy

7039
05:40:31,578 --> 05:40:32,946
in these patients
that were treated.

7040
05:40:32,946 --> 05:40:34,781
And so I think many
of the side effects

7041
05:40:34,781 --> 05:40:36,783
we've seen in the past
with IMiDs are more related

7042
05:40:36,783 --> 05:40:38,885
to the underlying
clonal disorders and myeloma

7043
05:40:38,885 --> 05:40:40,920
rather than anything per se,
to the drug itself.

7044
05:40:40,920 --> 05:40:43,390
So I think much more to comment,
we're working on this in lab,

7045
05:40:43,390 --> 05:40:44,791
trying to understand
the mechanism

7046
05:40:44,791 --> 05:40:46,026
and many of
the others as well.

7047
05:40:46,026 --> 05:40:47,994
And bringing this to patients
ultimately would be either

7048
05:40:47,994 --> 05:40:49,529
repurposing
these drugs for treatment

7049
05:40:49,529 --> 05:40:51,498
or understanding the mechanism
to develop better drugs

7050
05:40:51,498 --> 05:40:53,099
is a goal of the field too.

7051
05:40:54,601 --> 05:40:57,504
So I wanted to leave you
with one last little story

7052
05:40:57,504 --> 05:41:00,373
and just a short story that's
going on in our lab right now

7053
05:41:00,373 --> 05:41:02,809
involving a newly identified
regulator of fetal hemoglobin

7054
05:41:02,809 --> 05:41:05,011
called PP6C or PPP6C.

7055
05:41:06,146 --> 05:41:08,848
So initially we worked
a lot on HRI

7056
05:41:08,848 --> 05:41:10,483
and we actually
are collaborating to develop

7057
05:41:10,483 --> 05:41:12,018
direct kinase inhibitors
of HRI,

7058
05:41:12,018 --> 05:41:14,788
which is very exciting and have
some really interesting data

7059
05:41:14,788 --> 05:41:16,389
in some animal models currently.

7060
05:41:17,223 --> 05:41:19,292
But we elected to perform
a phosphatase knockout screen

7061
05:41:19,292 --> 05:41:21,261
to understand are there
compensatory phosphatases

7062
05:41:21,261 --> 05:41:23,196
that might be regulating
these pathways

7063
05:41:23,196 --> 05:41:25,565
and we understand
better mechanisms

7064
05:41:25,565 --> 05:41:28,702
of red cell development
and fetal hemoglobin control.

7065
05:41:28,702 --> 05:41:31,871
So we performed
a CRISPR-Cas9-based screen,

7066
05:41:32,639 --> 05:41:35,675
again using HIC2-Cas9 cells
and a phosphatase library.

7067
05:41:35,675 --> 05:41:38,545
And so ordered into fetal
hemoglobin high in low cells.

7068
05:41:38,545 --> 05:41:39,779
And we can plot the data
like this

7069
05:41:39,779 --> 05:41:41,614
in which we look
at read counts on the x axis

7070
05:41:41,614 --> 05:41:44,484
and fetal hemoglobin low
and a high on the Y axis.

7071
05:41:44,484 --> 05:41:46,753
Anything above the identity line
indicates a gene

7072
05:41:46,753 --> 05:41:48,021
that when depleted leads

7073
05:41:48,021 --> 05:41:49,456
to higher levels
of fetal hemoglobin,

7074
05:41:49,456 --> 05:41:51,458
which is what
we we'd like to achieve.

7075
05:41:51,458 --> 05:41:53,126
And in five of the six
guides tested,

7076
05:41:53,126 --> 05:41:55,528
we found a gene called
PP6C or PPP6C.

7077
05:41:56,363 --> 05:41:57,597
So what is this?

7078
05:41:57,597 --> 05:41:59,399
So this is actually
the catalytic subunit

7079
05:41:59,399 --> 05:42:00,800
and protein phosphate 6.

7080
05:42:00,800 --> 05:42:03,370
It's a holoenzyme complex
that enables --

7081
05:42:03,370 --> 05:42:05,105
it's expressed in a variety
of different tissues

7082
05:42:05,105 --> 05:42:06,673
and cell types.

7083
05:42:06,673 --> 05:42:09,776
But the specific regulation
of some of these factors,

7084
05:42:09,776 --> 05:42:11,911
including three different PP6Rs,

7085
05:42:11,911 --> 05:42:13,546
and three different anchor
and repeating domains

7086
05:42:13,546 --> 05:42:16,182
allows for
very specific functions

7087
05:42:16,182 --> 05:42:18,051
in different cell
types and tissues.

7088
05:42:18,051 --> 05:42:19,586
Previously,
this has been described

7089
05:42:19,586 --> 05:42:20,787
in cell cycle progression,

7090
05:42:20,787 --> 05:42:22,555
innate immunity and MEK/ERK
signaling pathways,

7091
05:42:22,555 --> 05:42:24,124
but has not previously
been described

7092
05:42:24,124 --> 05:42:26,993
as a fetal hemoglobin regulator.
And one of the intriguing parts

7093
05:42:26,993 --> 05:42:28,361
about this holoenzyme
enzyme complex

7094
05:42:28,361 --> 05:42:32,031
is that one of the subunits,
the PP6R1complex, is --

7095
05:42:32,031 --> 05:42:34,701
actually seems to be selectively
expressed in red cells

7096
05:42:34,701 --> 05:42:37,270
at the time point at which
we are making many of the fate

7097
05:42:37,270 --> 05:42:39,139
decisions involving fetal
hemoglobin regulation.

7098
05:42:39,139 --> 05:42:41,474
So this could serve as a red
cell selected target

7099
05:42:41,474 --> 05:42:43,109
for increasing fetal
hemoglobin levels.

7100
05:42:43,109 --> 05:42:45,545
And I don't have time
to show you all the data today,

7101
05:42:45,545 --> 05:42:46,946
able to show you a subset

7102
05:42:46,946 --> 05:42:48,715
in which we are able to validate
these initial results

7103
05:42:48,715 --> 05:42:50,650
in primary
human erythroid cells,

7104
05:42:50,650 --> 05:42:53,052
as well as in sickle CD34
erythroid cells,

7105
05:42:53,686 --> 05:42:54,988
which we deplete PP6C.

7106
05:42:54,988 --> 05:42:57,824
We see a doubling of F cells
either at or

7107
05:42:57,824 --> 05:43:01,728
even sometimes exceeding
BCL11A plus sgRNA depletion,

7108
05:43:01,728 --> 05:43:03,797
which is what's used
in the clinical trials

7109
05:43:03,797 --> 05:43:06,666
that we just heard about
in four different donors here,

7110
05:43:06,666 --> 05:43:08,668
and a significant increase
in Fs,

7111
05:43:08,668 --> 05:43:11,938
in hbF by HPLC
using both of these guides here.

7112
05:43:13,473 --> 05:43:16,342
We've also shown this to be true
in xeno transplant models

7113
05:43:16,342 --> 05:43:18,945
and NBSGW
and vivo mechanistically.

7114
05:43:18,945 --> 05:43:21,648
We think this proceeds, at least
in part via BCL11A depletion,

7115
05:43:21,648 --> 05:43:22,882
we see loss of BCL11A

7116
05:43:22,882 --> 05:43:26,019
in a dose dependent manner
following PPP6C loss.

7117
05:43:26,019 --> 05:43:27,554
And we've tested
a variety of different

7118
05:43:27,554 --> 05:43:29,255
other targets downstream,

7119
05:43:29,255 --> 05:43:30,723
including many
I've described here today

7120
05:43:30,723 --> 05:43:32,258
and we do not see any changes.

7121
05:43:32,258 --> 05:43:33,526
So we're still trying
to understand

7122
05:43:33,526 --> 05:43:35,795
the mechanism connecting PP6C
to BCL11A,

7123
05:43:35,795 --> 05:43:37,430
but we think this is
the primary mechanism

7124
05:43:37,430 --> 05:43:39,833
that drives its effect
on fetal hemoglobin.

7125
05:43:40,800 --> 05:43:44,737
And just to add you one last
piece of data and far as PP6CR1,

7126
05:43:44,737 --> 05:43:47,207
we ask,
can we deplete PP6R1directly

7127
05:43:47,207 --> 05:43:48,675
and recapitulate many of
the effects

7128
05:43:48,675 --> 05:43:51,444
that we see by
depleting the catalytic subunit?

7129
05:43:51,444 --> 05:43:54,747
So if we deplete either PP6C
or PP6CR1,

7130
05:43:54,747 --> 05:43:56,549
we see a loss of both
indicating they're both

7131
05:43:56,549 --> 05:43:59,686
required for stability
of this hollow enzyme complex,

7132
05:43:59,686 --> 05:44:02,055
decrease or depletion of PP6C

7133
05:44:02,055 --> 05:44:04,691
or PP6R1 leads
to increases in gamma globin

7134
05:44:04,691 --> 05:44:06,593
without changes in beta globin

7135
05:44:06,593 --> 05:44:08,561
and significant increases
in F cells

7136
05:44:09,395 --> 05:44:11,331
that recapitulate
the vast majority of the effects

7137
05:44:11,331 --> 05:44:12,932
we see with PP6C loss

7138
05:44:12,932 --> 05:44:16,236
indicating this could be
a red cell selective modality

7139
05:44:16,236 --> 05:44:17,837
to be able to increase
fetal hemoglobin

7140
05:44:17,837 --> 05:44:21,174
without off-target effects
on other tissues and cell types.

7141
05:44:21,174 --> 05:44:23,243
So much more to come on this.
We're actually in the process

7142
05:44:23,243 --> 05:44:25,044
of generating
phosphoproteomics data

7143
05:44:25,044 --> 05:44:28,014
to understand what are
the direct targets of PP6C

7144
05:44:28,014 --> 05:44:29,949
on either BCL11A
directly or other intermediates

7145
05:44:29,949 --> 05:44:32,051
in the regulation
of fetal hemoglobin.

7146
05:44:32,051 --> 05:44:34,654
But we think this could be
a potentially interesting target

7147
05:44:34,654 --> 05:44:36,089
for modulating fetal hemoglobin

7148
05:44:36,089 --> 05:44:37,991
in sickle cell patients
in the future.

7149
05:44:39,325 --> 05:44:41,361
Great.
So I think I made it on time.

7150
05:44:41,961 --> 05:44:44,931
So I'd like to thank the
organizers, Swee Lay, John,

7151
05:44:44,931 --> 05:44:46,199
Jennifer, and Monica.

7152
05:44:46,199 --> 05:44:48,201
It's really been a fantastic
conference so far and much more

7153
05:44:48,201 --> 05:44:50,803
to come in the NHLBI
for hosting the conference

7154
05:44:51,304 --> 05:44:52,972
as well as the NIDDK
for funding.

7155
05:44:53,673 --> 05:44:55,608
My collaborators at UPenn,
including the Blobel Lab,

7156
05:44:55,608 --> 05:44:57,911
the She Lab, Peslak Lab,
and the Chondro's Lab

7157
05:44:58,811 --> 05:45:00,246
as well as our collaborators
at Penn State

7158
05:45:00,246 --> 05:45:02,515
and my own lab that I just
started this December

7159
05:45:02,515 --> 05:45:04,284
and have I be able
to recruit a postdoc,

7160
05:45:04,284 --> 05:45:06,286
a couple of technicians
and a biomathematicia

7161
05:45:06,286 --> 05:45:07,720
and very exciting work.

7162
05:45:07,720 --> 05:45:09,289
Hopefully more to come
and many more meetings

7163
05:45:09,289 --> 05:45:12,258
where I can interact with really
fantastic folks in the field.

7164
05:45:12,258 --> 05:45:14,561
So thank you.
I'm happy to take any questions.

7165
05:45:17,330 --> 05:45:18,898
Haydar Frangoul: We have
a couple online.

7166
05:45:18,898 --> 05:45:20,500
Scott Peslakak: Great.

7167
05:45:22,068 --> 05:45:23,303
Haydar Frangoul: We'll get
the --

7168
05:45:23,303 --> 05:45:24,837
we'll get the questions here.

7169
05:45:24,837 --> 05:45:27,040
And there are a couple online.
I want to leave time for them.

7170
05:45:27,040 --> 05:45:30,443
Swee Thein: So one,
two of all of them.

7171
05:45:31,778 --> 05:45:35,081
One thing I may have missed,
but I'm just wondering,

7172
05:45:35,982 --> 05:45:41,521
did you ever consider
this PHI group of compounds?

7173
05:45:41,521 --> 05:45:45,792
There are now six of them that
under clinical development

7174
05:45:46,326 --> 05:45:49,729
for treating an anemia
in chronic sickle cell

7175
05:45:49,729 --> 05:45:50,964
chronic kidney disease.
Scott Peslakak: Yeah.

7176
05:45:50,964 --> 05:45:52,165
Swee Thein: And in fact,

7177
05:45:52,165 --> 05:45:53,766
two or three of them
were even been approved.

7178
05:45:53,766 --> 05:45:55,001
Scott Peslakak: Exactly, yeah.

7179
05:45:55,001 --> 05:45:56,903
Swee Thein: In Europe.
And of course you --

7180
05:45:56,903 --> 05:46:00,139
for me, following the literature
too, of [unintelligible]

7181
05:46:00,139 --> 05:46:02,141
actually increases
fetal hemoglobin.

7182
05:46:02,675 --> 05:46:05,478
So I may have missed it,

7183
05:46:05,478 --> 05:46:07,013
but I just wonder
what your thoughts

7184
05:46:07,013 --> 05:46:08,748
are on this group
of compounds

7185
05:46:08,748 --> 05:46:09,949
Scott Peslakak: In terms of the,

7186
05:46:09,949 --> 05:46:11,417
the prolyl
hydroxylase inhibitors?

7187
05:46:11,417 --> 05:46:12,652
Swee Thein: For repurposing
them.

7188
05:46:12,652 --> 05:46:13,920
Scott Peslakak: Yeah, yeah.

7189
05:46:13,920 --> 05:46:15,455
Swee Thein: For treating
sickle cell disease.

7190
05:46:15,455 --> 05:46:16,656
Scott Peslakak: Yeah.
I mean, I think that's --

7191
05:46:16,656 --> 05:46:18,324
I think repurposing drugs

7192
05:46:18,324 --> 05:46:19,759
that are already approved
for other reasons,

7193
05:46:19,759 --> 05:46:22,528
especially ones
that don't impair levels

7194
05:46:22,528 --> 05:46:24,097
of hemoglobin and in fight --

7195
05:46:24,097 --> 05:46:25,598
in fact might
increase hemoglobin

7196
05:46:25,598 --> 05:46:27,400
is beneficial, I think.

7197
05:46:27,400 --> 05:46:30,603
You know, I have talked with
a couple of folks about this

7198
05:46:30,603 --> 05:46:31,904
in terms of we worry

7199
05:46:31,904 --> 05:46:33,873
about sometimes
increasing levels of hemoglobin

7200
05:46:33,873 --> 05:46:36,776
and whether that's detrimental
as far as viscosity.

7201
05:46:36,776 --> 05:46:38,411
I'm not sure that's as relevant

7202
05:46:38,411 --> 05:46:40,713
or as true if you have
fetal hemoglobin,

7203
05:46:40,713 --> 05:46:42,148
how that actually
contributes to viscosity.

7204
05:46:42,148 --> 05:46:43,850
So I think it might be useful,

7205
05:46:43,850 --> 05:46:46,252
even if it increases
overall hemoglobin levels,

7206
05:46:46,252 --> 05:46:47,920
it could be beneficial.

7207
05:46:47,920 --> 05:46:49,322
I'm not as familiar
with those --

7208
05:46:49,322 --> 05:46:51,224
with that specific
set of papers,

7209
05:46:51,224 --> 05:46:54,027
but I think it's certainly
repurposing drugs

7210
05:46:54,027 --> 05:46:55,461
to be able to treat
sickle cell patients

7211
05:46:55,461 --> 05:46:57,196
in a way that we could test

7212
05:46:57,196 --> 05:46:59,499
in a more rapid cycle
of clinical trials

7213
05:46:59,499 --> 05:47:01,701
would be beneficial,
I think, for the field.

7214
05:47:03,936 --> 05:47:06,072
Male Speaker: So Scott, yeah,
that was really terrific.

7215
05:47:07,240 --> 05:47:09,542
I have a question.
Really just wondering

7216
05:47:09,542 --> 05:47:12,145
if you have any insight
or inside knowledge

7217
05:47:12,145 --> 05:47:15,982
about the wiz degrader.
So we were all like blown away

7218
05:47:15,982 --> 05:47:17,617
with the ASH presentation,
right?

7219
05:47:17,617 --> 05:47:19,986
Yeah, but they -- but they
showed only effort ticks.

7220
05:47:19,986 --> 05:47:21,287
Scott Peslakak: Yeah.

7221
05:47:21,287 --> 05:47:22,522
Male Speaker: In the
non-human primate,

7222
05:47:22,522 --> 05:47:24,857
two of three had
quite substantial rises

7223
05:47:24,857 --> 05:47:26,192
in effort ticks

7224
05:47:26,192 --> 05:47:28,161
[phonetic sp], but they didn't
show fetal hemoglobin.

7225
05:47:28,161 --> 05:47:30,663
And I'm always
very suspicious when

7226
05:47:30,663 --> 05:47:34,667
the last figure is effort ticks
and there's no protein data.

7227
05:47:34,667 --> 05:47:38,037
And in between the time
of the ASH presentation

7228
05:47:38,037 --> 05:47:40,373
and the publication,
there's still no protein data.

7229
05:47:40,373 --> 05:47:41,607
Scott Peslakak: Yeah.

7230
05:47:41,607 --> 05:47:43,676
Male Speaker: So do you know
whether they measured

7231
05:47:43,676 --> 05:47:44,877
and it was low?

7232
05:47:44,877 --> 05:47:48,681
I can't imagine that they didn't
measure fetal hemoglobin.

7233
05:47:48,681 --> 05:47:51,551
So my assumption
is that it's not high,

7234
05:47:51,551 --> 05:47:54,587
but it's a lot of cells with a
little bit of fetal hemoglobin.

7235
05:47:54,587 --> 05:47:55,788
Scott Peslakak: Yeah.
Male Speaker: Can you comment?

7236
05:47:55,788 --> 05:47:57,090
Scott Peslakak: It's a
good question.

7237
05:47:57,090 --> 05:47:59,359
I can tell you that
in the publication,

7238
05:47:59,359 --> 05:48:02,328
you know, they did see effects
in most of their nine,

7239
05:48:02,328 --> 05:48:04,230
even primates,
but not all of them.

7240
05:48:04,230 --> 05:48:05,665
And so that's
an intriguing result as well.

7241
05:48:05,665 --> 05:48:06,966
You know, is there --

7242
05:48:06,966 --> 05:48:09,602
and I think this is an important
question for the field,

7243
05:48:09,602 --> 05:48:13,272
are there signaling pathways
that in certain patients,

7244
05:48:13,272 --> 05:48:16,042
patients we might modulate
and we might not have effects?

7245
05:48:16,042 --> 05:48:17,343
And this is really important.

7246
05:48:17,343 --> 05:48:19,045
This is really why
it's important to understand

7247
05:48:19,045 --> 05:48:20,246
these basic mechanisms,

7248
05:48:20,246 --> 05:48:22,415
because if we just develop
lots and lots of drugs

7249
05:48:22,415 --> 05:48:24,417
and don't understand why,
we have absolutely no idea

7250
05:48:24,417 --> 05:48:25,985
which patients are going
to benefit,

7251
05:48:25,985 --> 05:48:28,354
for how long
and in what combinations.

7252
05:48:28,354 --> 05:48:31,691
I do think combinatorial therapy
is probably every other red --

7253
05:48:31,691 --> 05:48:32,959
every other blood disorder

7254
05:48:32,959 --> 05:48:34,293
thinks about
combinatorial therapy.

7255
05:48:34,293 --> 05:48:35,661
And to think we can just have
one drug

7256
05:48:35,661 --> 05:48:38,297
that's going to be
the perfect drug for everybody,

7257
05:48:38,297 --> 05:48:41,134
I think is wishful thinking.

7258
05:48:41,901 --> 05:48:44,070
To get to your exact question,
I don't know.

7259
05:48:44,070 --> 05:48:45,671
I do think that there --

7260
05:48:46,506 --> 05:48:49,242
I think the mechanisms
that are underlying wiz

7261
05:48:49,242 --> 05:48:51,677
are probably different
than those

7262
05:48:51,677 --> 05:48:53,646
with other cereblon-based
modulators,

7263
05:48:53,646 --> 05:48:55,114
including pomalidomide.

7264
05:48:55,114 --> 05:48:58,484
But specifically in terms
of the F protein level.

7265
05:48:58,484 --> 05:49:00,486
I'm not entirely sure.
Yeah.

7266
05:49:00,486 --> 05:49:01,687
Haydar Frangoul: Okay.

7267
05:49:01,687 --> 05:49:03,723
There's a --
there are a couple there.

7268
05:49:03,723 --> 05:49:04,924
Yeah, go for it.

7269
05:49:04,924 --> 05:49:06,359
Manu Platt: Okay, so just
a really quick question.

7270
05:49:06,359 --> 05:49:07,860
Sorry. Yeah.

7271
05:49:07,860 --> 05:49:09,662
This is also a great
coverage of the field,

7272
05:49:09,662 --> 05:49:10,863
so not a clinician.

7273
05:49:10,863 --> 05:49:13,132
So you've kind of answered my --
your last bit, but --

7274
05:49:13,132 --> 05:49:16,302
so what's the idea that these
other fetal hemoglobin modifiers

7275
05:49:16,302 --> 05:49:17,603
would be applied to patients

7276
05:49:17,603 --> 05:49:19,272
where either hydroxyurea
doesn't work,

7277
05:49:19,272 --> 05:49:22,041
or like how do you see it
rolling out to actual patients

7278
05:49:22,041 --> 05:49:23,476
and that insurance
coverage would work

7279
05:49:23,476 --> 05:49:24,911
or that it would hit
a new target

7280
05:49:24,911 --> 05:49:26,846
or that people's fear
of hydroxyurea

7281
05:49:26,846 --> 05:49:29,148
would not be scared
in these new modifiers?

7282
05:49:29,148 --> 05:49:31,350
How do you see
that affecting the patients?

7283
05:49:31,350 --> 05:49:32,952
Scott Peslakak: Yeah,
it's a really good question.

7284
05:49:32,952 --> 05:49:36,489
I will say there are scenarios
where I worry about,

7285
05:49:36,489 --> 05:49:38,558
you know, generally hydroxyurea
is very safe, very effective.

7286
05:49:38,558 --> 05:49:40,560
It is not shown
to be toxic in any way.

7287
05:49:40,560 --> 05:49:41,861
There are scenarios
where I worry

7288
05:49:41,861 --> 05:49:43,462
about using hydroxyurea
for example,

7289
05:49:43,462 --> 05:49:46,499
after a bone marrow transplant
or after gene therapy

7290
05:49:46,499 --> 05:49:49,302
where patients have gotten
busulfan conditioning.

7291
05:49:49,302 --> 05:49:51,003
I think there is actually
a higher risk

7292
05:49:51,003 --> 05:49:53,472
in giving hydroxyurea
after that scenario.

7293
05:49:54,073 --> 05:49:56,843
I think in terms of whether
that has been shown,

7294
05:49:56,843 --> 05:49:59,011
but that's what's been shown
in the PV field

7295
05:49:59,011 --> 05:50:00,713
and previously actually.

7296
05:50:00,713 --> 05:50:03,349
I think in terms
of being able to predict

7297
05:50:03,349 --> 05:50:06,052
and who might benefit
and who might not,

7298
05:50:06,052 --> 05:50:08,855
I agree, this is a really
incredibly important question.

7299
05:50:09,655 --> 05:50:11,524
Reduction remains a standard
of care

7300
05:50:11,524 --> 05:50:13,659
for all patients with SS
and SBE to zero disease

7301
05:50:13,659 --> 05:50:14,961
starting at very young ages.

7302
05:50:14,961 --> 05:50:16,596
And I think it's going to be
a very long time

7303
05:50:16,596 --> 05:50:19,599
before that gets replaced
by anything where we say,

7304
05:50:19,599 --> 05:50:20,867
no, we shouldn't
give hydroxyurea.

7305
05:50:20,867 --> 05:50:23,269
But in patients,
in adult patients,

7306
05:50:23,269 --> 05:50:25,071
we oftentimes have difficulty
getting to maximum

7307
05:50:25,071 --> 05:50:26,672
tolerated dose
because of neutropenia,

7308
05:50:26,672 --> 05:50:28,241
because of other side effects.

7309
05:50:28,241 --> 05:50:30,443
It's actually much more, I think
in the pediatric setting,

7310
05:50:30,443 --> 05:50:32,845
we probably can push most,
if not all patients

7311
05:50:32,845 --> 05:50:34,714
to get really good levels
of fetal hemoglobin in adults.

7312
05:50:34,714 --> 05:50:36,215
It's much more challenging.

7313
05:50:36,215 --> 05:50:38,851
And so having other ways
to modulate globin

7314
05:50:38,851 --> 05:50:41,721
switching other than Hydra
in the adult phase of life,

7315
05:50:41,721 --> 05:50:42,989
I think is really critical.

7316
05:50:42,989 --> 05:50:44,590
And that's where we're going
to see a lot of these be used,

7317
05:50:44,590 --> 05:50:45,925
I think.

7318
05:50:45,925 --> 05:50:48,127
Haydar Frangoul: Okay. There are
a couple of questions online.

7319
05:50:48,127 --> 05:50:52,298
One was they want you
to discuss the pros

7320
05:50:52,298 --> 05:50:54,233
and cons of the targets
you mentioned

7321
05:50:54,233 --> 05:50:56,636
and which one is you
are the most excited about.

7322
05:50:56,636 --> 05:50:58,638
Scott Peslakak: Yeah.
I'm a little biased, I guess.

7323
05:50:58,638 --> 05:51:00,373
I can tell you that we're really
excited about heme

7324
05:51:00,373 --> 05:51:02,408
regulated inhibitor
and HRI kinase ambition.

7325
05:51:02,408 --> 05:51:04,110
I think the benefits of HRI,

7326
05:51:04,110 --> 05:51:07,580
this is red cell specific
and HRI knockout mice

7327
05:51:07,580 --> 05:51:09,649
really don't show
significant phenotypes

7328
05:51:09,649 --> 05:51:11,250
other than in severe
iron deficiency

7329
05:51:11,250 --> 05:51:13,352
and maybe in thalassemia
has been shown by Jane,

7330
05:51:13,352 --> 05:51:14,654
Jane and Chen's group.

7331
05:51:14,654 --> 05:51:18,124
But overall, HRI in inhibition
is very well tolerated

7332
05:51:18,124 --> 05:51:19,625
and seems to be
one of the earliest

7333
05:51:19,625 --> 05:51:20,860
and best targets
that we know.

7334
05:51:20,860 --> 05:51:22,128
I think IMiDs are --
since are --

7335
05:51:22,128 --> 05:51:23,362
they're already approved,

7336
05:51:23,362 --> 05:51:25,598
understanding how these work
and potentially

7337
05:51:25,598 --> 05:51:28,200
there are thalassemia physicians
in Southeast Asia

7338
05:51:28,200 --> 05:51:29,936
that actually can't --
don't have access to blood

7339
05:51:29,936 --> 05:51:32,271
and need to increase
levels of hemoglobin

7340
05:51:32,271 --> 05:51:35,274
and are using thalidomide
off-label for patients

7341
05:51:35,274 --> 05:51:36,809
to be able to increase
levels of hemoglobin

7342
05:51:36,809 --> 05:51:38,244
and, and fetal hemoglobin
in particular.

7343
05:51:38,244 --> 05:51:39,512
So there's actually
real world data.

7344
05:51:39,512 --> 05:51:41,180
This might be beneficial to --

7345
05:51:41,180 --> 05:51:44,283
not to sickle cell patients,
but to thalassemia patients.

7346
05:51:44,283 --> 05:51:45,751
I think in terms
of the molecules

7347
05:51:45,751 --> 05:51:48,187
that are out there right now
I would be to --

7348
05:51:48,187 --> 05:51:49,422
Dr. Tisdale's question,

7349
05:51:49,422 --> 05:51:51,190
I'd be interested to see
the protein level for whiz,

7350
05:51:51,190 --> 05:51:53,092
that's probably one
of the more exciting ones

7351
05:51:53,092 --> 05:51:54,493
as far as effect size.

7352
05:51:54,493 --> 05:51:57,163
But I really think
all of these compounds

7353
05:51:57,930 --> 05:51:59,131
have pluses and minuses,

7354
05:51:59,131 --> 05:52:02,034
and I do think
it would be helpful

7355
05:52:02,034 --> 05:52:05,137
to be able to think about
how these signaling pathways

7356
05:52:05,137 --> 05:52:07,373
are modulated at baseline
to be able to choose better.

7357
05:52:07,373 --> 05:52:08,975
We're a ways away
from doing that,

7358
05:52:08,975 --> 05:52:11,010
but I think Dr. Bauer's earlier
talk about,

7359
05:52:11,010 --> 05:52:12,712
you know, actually thinking
about how to predict,

7360
05:52:12,712 --> 05:52:14,513
you know, off target effects
for his CRISPR guides.

7361
05:52:14,513 --> 05:52:16,415
We can do something similar.

7362
05:52:16,415 --> 05:52:18,484
I think with overall
signaling pathways

7363
05:52:18,484 --> 05:52:20,653
in sickle cell disease patients,
it's going to take a while,

7364
05:52:20,653 --> 05:52:23,856
but to do that, we need to
understand how this works first.

7365
05:52:23,856 --> 05:52:25,157
Haydar Frangoul: The last
question came in,

7366
05:52:25,157 --> 05:52:27,159
which I think is important,
that nobody --

7367
05:52:27,159 --> 05:52:30,630
I mean, this is close
to my heart, is SC patients.

7368
05:52:31,330 --> 05:52:33,733
You mean SC patients are a --

7369
05:52:33,733 --> 05:52:36,936
I mean, I can tell you that for
the gene therapy trials we did,

7370
05:52:36,936 --> 05:52:39,071
none of them included
SC patients.

7371
05:52:39,071 --> 05:52:41,273
And you know,
anecdotally lock has,

7372
05:52:41,273 --> 05:52:42,942
it is when --
because Javi got approved,

7373
05:52:42,942 --> 05:52:45,411
the first three referrals
to our site were SC

7374
05:52:45,411 --> 05:52:47,013
and we said no,
because there is no data.

7375
05:52:47,013 --> 05:52:48,247
And I'm not aware of any data

7376
05:52:48,247 --> 05:52:52,184
in the persistent fetal
hemoglobin world

7377
05:52:52,184 --> 05:52:56,422
to be convincingly showing that
high F will help SC patients.

7378
05:52:56,422 --> 05:52:58,791
Scott Peslakak: Yeah, I think
that's a great question.

7379
05:52:58,791 --> 05:53:00,693
I think part of the issue
is that --

7380
05:53:00,693 --> 05:53:02,628
I remember speaking
with Dr. Lydia Ecker

7381
05:53:02,628 --> 05:53:04,397
about this actually
at a conference a few,

7382
05:53:04,397 --> 05:53:05,731
maybe about a few months ago,
a year ago.

7383
05:53:05,731 --> 05:53:07,500
And really, SC is really
an orphan disease.

7384
05:53:07,500 --> 05:53:10,336
It's -- we cluster it in
with SS and SB to zero,

7385
05:53:10,336 --> 05:53:11,804
but I don't think
we really understand

7386
05:53:11,804 --> 05:53:14,373
at a very basic level
how SC works.

7387
05:53:14,373 --> 05:53:16,342
And why say hydroxyurea
doesn't really work

7388
05:53:16,342 --> 05:53:17,943
in the majority of SC patients.

7389
05:53:18,511 --> 05:53:20,546
And I think -- so we now are --

7390
05:53:21,147 --> 05:53:22,982
I believe in the field,
I haven't used this personally,

7391
05:53:22,982 --> 05:53:24,950
but we now are close to having
a mouse model for SC

7392
05:53:24,950 --> 05:53:26,886
to be able to understand
how this works mechanistically

7393
05:53:26,886 --> 05:53:28,454
and test
some of these compounds.

7394
05:53:28,454 --> 05:53:29,655
I think you're right.

7395
05:53:29,655 --> 05:53:31,057
In terms of,
we don't necessarily know

7396
05:53:31,057 --> 05:53:33,392
that F induce F induction
improves SC,

7397
05:53:33,392 --> 05:53:36,395
but we think based on real world
data that it probably does.

7398
05:53:37,229 --> 05:53:40,199
And I -- it's a vastly
understudied,

7399
05:53:40,199 --> 05:53:42,134
but incredibly
important field to study

7400
05:53:42,134 --> 05:53:44,570
because these patients
have a tremendous

7401
05:53:44,570 --> 05:53:46,405
phenotypic variability.
Some are as severe,

7402
05:53:46,405 --> 05:53:48,407
if not more so than SS disease
and some are not.

7403
05:53:48,407 --> 05:53:51,444
And understanding how this works
at a very basic level

7404
05:53:51,444 --> 05:53:53,145
is going to be critical
to know what works best.

7405
05:53:53,145 --> 05:53:54,847
But I do think
this could be beneficial many

7406
05:53:54,847 --> 05:53:56,949
of these compounds
in SC patients as well.

7407
05:53:57,483 --> 05:53:59,685
Swee Thein: You know,
I can agree with you more.

7408
05:53:59,685 --> 05:54:02,254
I think it's a very much
understudy disease.

7409
05:54:02,254 --> 05:54:05,891
Everybody thinks a bit
as another sickle cell syndrome.

7410
05:54:06,492 --> 05:54:07,726
It's complex.

7411
05:54:07,726 --> 05:54:11,130
I mean, even when the highest
fetal hemoglobin I've seen,

7412
05:54:11,730 --> 05:54:13,866
I see is like 6 percent.

7413
05:54:13,866 --> 05:54:17,303
Even when you have
the older hemoglobin at QTLs.

7414
05:54:17,303 --> 05:54:20,806
Whereas I've seen them
as high as like 29, 30 percent,

7415
05:54:21,340 --> 05:54:24,577
not the Mendelian form of HF.

7416
05:54:24,577 --> 05:54:26,679
And then of course,
there's this C component

7417
05:54:26,679 --> 05:54:30,082
that actually adds
to the you know,

7418
05:54:30,082 --> 05:54:33,152
the viscosity problem
and MCHC problem.

7419
05:54:33,152 --> 05:54:36,122
Yeah. So, and then of course,
don't forget,

7420
05:54:36,122 --> 05:54:38,257
it can also
co-inherit hyperglycemia.

7421
05:54:39,191 --> 05:54:44,897
That adds know even more
of a interacting factor

7422
05:54:45,564 --> 05:54:50,369
in the disease differently
to that hyperglycemia.

7423
05:54:51,403 --> 05:54:53,739
Haydar Frangoul: Well, thank you
so much for the talk.

7424
05:54:53,739 --> 05:54:56,642
We are doing great on time.
We are one minute early.

7425
05:54:56,642 --> 05:54:58,744
We have a break until 3:45.

7426
05:54:59,478 --> 05:55:03,959
Please reconvene at 3:45.
Thank you.

7427
05:55:03,959 --> 05:55:07,629
Well, it is my pleasure
to introduce our second speaker,

7428
05:55:07,629 --> 05:55:10,465
which is Dr. John Tisdale.

7429
05:55:11,199 --> 05:55:12,768
He is going to talk
about the increased

7430
05:55:12,768 --> 05:55:15,704
anti-sickling potential
genetic approaches.

7431
05:55:15,704 --> 05:55:18,106
Dr. Tisdale is
a senior investigator

7432
05:55:18,106 --> 05:55:19,741
and chief of the cellular
and molecular

7433
05:55:19,741 --> 05:55:23,545
therapeutic branch
of the national Heart line

7434
05:55:23,545 --> 05:55:26,782
on Blend Institute,
NHLBI, at the NIH.

7435
05:55:26,782 --> 05:55:30,085
It's my pleasure to let
Dr. Tisdale take custodian.

7436
05:55:36,158 --> 05:55:37,526
John Tisdale: Okay.

7437
05:55:37,526 --> 05:55:40,362
Thank you very much
for the opportunity to speak.

7438
05:55:40,362 --> 05:55:45,734
Thank you Jennifer and Monica
for welcoming us back to Jamaica

7439
05:55:45,734 --> 05:55:47,436
and back to the Pegasus.

7440
05:55:47,436 --> 05:55:49,304
It's really an honor
to be here again.

7441
05:55:51,406 --> 05:55:54,142
So I think much of
what I'm going to say

7442
05:55:54,142 --> 05:55:55,544
has already been said,

7443
05:55:55,544 --> 05:55:58,246
but I can use
some of the same slides

7444
05:55:58,246 --> 05:56:01,149
that you've already seen
to make some different points.

7445
05:56:03,285 --> 05:56:07,289
This is a slide that I'm really
happy to show here today.

7446
05:56:07,289 --> 05:56:10,926
This is a figure
that my colleagues

7447
05:56:10,926 --> 05:56:17,065
Swee Lay Thein and Bill Eaton
and I made just four years ago.

7448
05:56:17,666 --> 05:56:20,969
Okay. So we have these
anti-sickling approaches

7449
05:56:20,969 --> 05:56:22,170
to sickle cell disease,

7450
05:56:22,170 --> 05:56:24,406
including current treatments
like hydroxyurea,

7451
05:56:24,406 --> 05:56:25,807
reactivating fetal hemoglobin,

7452
05:56:25,807 --> 05:56:27,743
keeping cells from sickling
before they get back

7453
05:56:27,743 --> 05:56:31,013
to the lungs,
allogeneic transplantation

7454
05:56:31,013 --> 05:56:33,148
where we take somebody else's
bone marrow stem cells,

7455
05:56:33,148 --> 05:56:36,051
do a transplant
and fix the disease.

7456
05:56:36,051 --> 05:56:38,320
And then there was this
dotted line

7457
05:56:38,320 --> 05:56:43,291
which separates
those current treatments

7458
05:56:43,291 --> 05:56:45,027
from the future treatments.

7459
05:56:45,027 --> 05:56:47,029
So I get to move
that line over now

7460
05:56:47,596 --> 05:56:50,265
because both gene addition
and gene editing,

7461
05:56:50,265 --> 05:56:53,769
as you heard earlier
have been now

7462
05:56:53,769 --> 05:56:57,072
FDA approved
in December of last year.

7463
05:56:58,840 --> 05:57:00,575
So that's a big deal.

7464
05:57:00,575 --> 05:57:04,980
We finally have something
that we can offer to patients

7465
05:57:04,980 --> 05:57:07,416
that's transformative,
potentially curative,

7466
05:57:07,416 --> 05:57:10,118
that doesn't involve them
finding a donor in the family.

7467
05:57:10,118 --> 05:57:14,089
And then I'll just update
the results of the HGB-206 study

7468
05:57:14,089 --> 05:57:18,226
in the 210 extension,
just in the interest of showing

7469
05:57:18,226 --> 05:57:20,295
this other anti-sickling
approach.

7470
05:57:20,295 --> 05:57:22,964
And there'll be more information
about this tomorrow,

7471
05:57:22,964 --> 05:57:28,203
both in terms of screening
for genetic changes

7472
05:57:28,203 --> 05:57:29,871
that might influence results.

7473
05:57:29,871 --> 05:57:33,208
And also, you know,
looking at patient outcomes.

7474
05:57:34,176 --> 05:57:37,712
But this is a study where
instead of getting your cells

7475
05:57:37,712 --> 05:57:40,482
harvested and manufactured
with CRISPR

7476
05:57:40,482 --> 05:57:43,118
cutting the BCL11A
erythroid enhancer,

7477
05:57:43,118 --> 05:57:46,288
instead they go to a central
manufacturing facility

7478
05:57:46,288 --> 05:57:48,957
where a lentiviral vector
based on HIV

7479
05:57:51,326 --> 05:57:56,198
is used to transfer a copy
of the beta globin gene

7480
05:57:58,100 --> 05:57:59,868
to those hematopoietic
stem cells,

7481
05:57:59,868 --> 05:58:01,636
and hopefully in a high
enough efficiency

7482
05:58:01,636 --> 05:58:04,339
that it provides
for anti-sickling.

7483
05:58:04,339 --> 05:58:07,075
And in this case,
there's a beta T87Q change

7484
05:58:08,009 --> 05:58:12,347
which is in hopes of making
this more anti-sickling

7485
05:58:12,347 --> 05:58:14,216
than just standard beta globin.

7486
05:58:15,650 --> 05:58:17,352
So these have been
published now groups

7487
05:58:17,352 --> 05:58:19,788
A and B in the first manuscript

7488
05:58:19,788 --> 05:58:22,591
on the left and group C
on the right.

7489
05:58:22,591 --> 05:58:24,893
And I'll show you updated
results that Julie Kanter

7490
05:58:24,893 --> 05:58:27,662
presented at ASH last year.

7491
05:58:27,662 --> 05:58:30,599
First, that there was
a great hemoglobin response.

7492
05:58:30,599 --> 05:58:32,868
So we had this definition
of hemoglobin response.

7493
05:58:32,868 --> 05:58:36,771
It was like, you know,
an increase in greater

7494
05:58:36,771 --> 05:58:41,143
than three grams per deciliter
of the total hemoglobin

7495
05:58:41,143 --> 05:58:46,248
or greater than 10 total grams
per deciliter.

7496
05:58:46,248 --> 05:58:48,316
So there was a, so-called
hemoglobin response,

7497
05:58:48,316 --> 05:58:50,485
and we wanted
at least 30 percent

7498
05:58:50,485 --> 05:58:52,621
of that coming from vector.

7499
05:58:52,621 --> 05:58:54,689
So this is what we initially
planned to be the,

7500
05:58:54,689 --> 05:58:56,057
you know,
the outcome measure.

7501
05:58:56,057 --> 05:59:00,162
We wanted to see that the vector
worked, it made hemoglobin --

7502
05:59:00,162 --> 05:59:02,197
it improved
the total hemoglobin.

7503
05:59:02,197 --> 05:59:06,434
And -- but what we saw was
that pain was also going away,

7504
05:59:06,434 --> 05:59:09,271
and that was a much
more difficult measure.

7505
05:59:10,238 --> 05:59:13,909
Acute pain episodes
that require hospitalization.

7506
05:59:13,909 --> 05:59:16,211
So-called severe VOEs.

7507
05:59:16,211 --> 05:59:19,147
The FDA wanted us
to use as an -- as an outcome

7508
05:59:19,147 --> 05:59:22,384
because that's, you know,
what was used for hydroxyurea,

7509
05:59:22,384 --> 05:59:25,854
for example.
And for the globin response,

7510
05:59:25,854 --> 05:59:30,825
the majority of patients had
this globin response 87 percent,

7511
05:59:30,825 --> 05:59:33,762
and all of those that reached
it maintained it long-term.

7512
05:59:33,762 --> 05:59:36,331
And here you can just see
the improvement in hemoglobin

7513
05:59:36,331 --> 05:59:40,435
over time in the fraction
and blue coming from the vector,

7514
05:59:40,435 --> 05:59:42,204
very similar to what high dog

7515
05:59:42,204 --> 05:59:46,041
just showed
for the CRISPR approach.

7516
05:59:46,041 --> 05:59:49,544
So these slides
all look remarkably similar.

7517
05:59:49,544 --> 05:59:52,080
These are different patients,
different approaches.

7518
05:59:52,681 --> 05:59:55,717
Again, to that same point,
here's pain.

7519
05:59:55,717 --> 05:59:59,621
And this is severe
vaso-occlusive events again,

7520
05:59:59,621 --> 06:00:03,525
as defined very similarly
to the hydroxyurea study.

7521
06:00:03,525 --> 06:00:06,228
You see the red dots
on the left, many of them.

7522
06:00:06,228 --> 06:00:08,296
Just a few red dots
on the right,

7523
06:00:08,897 --> 06:00:12,000
most patients had resolution
of the severe pain.

7524
06:00:12,000 --> 06:00:14,836
But there are dots remaining
and that's, you know,

7525
06:00:14,836 --> 06:00:19,241
something maybe we can discuss.
It keeps percolating up.

7526
06:00:19,241 --> 06:00:22,844
There are some patients
with chronic pain

7527
06:00:22,844 --> 06:00:24,946
that require hospitalizations.

7528
06:00:24,946 --> 06:00:26,348
They were shorter
when they came in,

7529
06:00:26,348 --> 06:00:28,483
much shorter
than what they were afterwards.

7530
06:00:28,483 --> 06:00:30,952
But some patients are indeed
still having pain.

7531
06:00:33,088 --> 06:00:35,223
And as was showed
in the last talk,

7532
06:00:35,223 --> 06:00:39,427
there was near normalization
of hemolysis markers.

7533
06:00:39,427 --> 06:00:42,264
So, you know, for some patients
that normalize completely,

7534
06:00:42,264 --> 06:00:45,433
for some, they don't normalize
completely as a group,

7535
06:00:45,433 --> 06:00:46,701
it's almost normal.

7536
06:00:46,701 --> 06:00:49,537
So this looks great,
but there's still, you know,

7537
06:00:49,537 --> 06:00:50,872
maybe something
going on there

7538
06:00:50,872 --> 06:00:52,107
that we might be able
to do better

7539
06:00:52,107 --> 06:00:54,776
if we had higher efficiency
of gene transfer

7540
06:00:54,776 --> 06:00:57,712
or a higher efficiency
of beta globin expression,

7541
06:00:57,712 --> 06:01:01,016
or higher levels of fetal
hemoglobin induction,

7542
06:01:01,650 --> 06:01:05,820
with the CRISPR approach.
The, you know, the --

7543
06:01:06,588 --> 06:01:09,924
what we saw was typical
of an auto transplant.

7544
06:01:11,259 --> 06:01:12,861
We didn't have any
veno-occlusive disease

7545
06:01:12,861 --> 06:01:14,396
from the busulfan conditioning,

7546
06:01:14,396 --> 06:01:17,666
and there were no vector-related
integration events.

7547
06:01:18,500 --> 06:01:22,203
And we had one death in group C
from pre-existing --

7548
06:01:22,904 --> 06:01:26,441
what to be preexisting
cardiopulmonary disease.

7549
06:01:28,410 --> 06:01:30,945
So the first patient
has now been signed up.

7550
06:01:31,546 --> 06:01:34,082
The table here is responsible
for that patient.

7551
06:01:34,082 --> 06:01:35,550
Maybe they can give us
some updates.

7552
06:01:35,550 --> 06:01:39,387
I know that Gina Kolata wrote
another article just yesterday

7553
06:01:39,387 --> 06:01:41,056
or something
in the New York Times

7554
06:01:41,056 --> 06:01:42,891
because a patient got infused.

7555
06:01:42,891 --> 06:01:44,526
So there's another article
just like this one

7556
06:01:44,526 --> 06:01:46,127
in the New York Times by Gina

7557
06:01:47,495 --> 06:01:50,632
cataloging
the first patient here.

7558
06:01:51,566 --> 06:01:52,967
But we have new technology.

7559
06:01:52,967 --> 06:01:55,070
So this is a shout out
for Swee Lay.

7560
06:01:55,070 --> 06:01:56,338
The reason for this slide.

7561
06:01:56,338 --> 06:02:01,009
You've already heard that
this really important study

7562
06:02:01,009 --> 06:02:03,878
which demonstrated BCL11A
as a quantitative trait

7563
06:02:03,878 --> 06:02:06,047
locus affecting
F cell production,

7564
06:02:06,047 --> 06:02:08,416
really launched
a whole new field.

7565
06:02:08,416 --> 06:02:14,489
And we and others wondered,
you know, can we inhibit BCL11A,

7566
06:02:14,489 --> 06:02:15,790
cut the gene and cell for --

7567
06:02:15,790 --> 06:02:19,961
cut the erythroid enhancer once
that was discovered as a way to,

7568
06:02:19,961 --> 06:02:21,629
you know,
fix sickle cell disease?

7569
06:02:21,629 --> 06:02:24,432
And you've heard the whole story
now unfold just before.

7570
06:02:25,166 --> 06:02:27,669
And just another shout out
to Swee Lay,

7571
06:02:27,669 --> 06:02:30,372
she just awarded
the Shaw prize,

7572
06:02:30,372 --> 06:02:32,440
which is, you know,
like a Nobel Prize.

7573
06:02:32,440 --> 06:02:37,178
So [applause]

7574
06:02:37,178 --> 06:02:39,447
with Stu Orkin who did a lot
of the work you know,

7575
06:02:39,447 --> 06:02:41,216
characterizing
the erythroid enhancer

7576
06:02:41,216 --> 06:02:43,451
and all with Dan Bauer,
as you heard earlier.

7577
06:02:44,119 --> 06:02:46,287
So it turns out
we can do that.

7578
06:02:47,689 --> 06:02:51,025
Dan showed the bottom
left panel earlier showing

7579
06:02:51,025 --> 06:02:53,595
that if you cut
the erythroid enhancer,

7580
06:02:53,595 --> 06:02:55,463
you get just as much
fetal hemoglobin

7581
06:02:55,463 --> 06:02:59,868
in the right red
encircled bar

7582
06:02:59,868 --> 06:03:01,836
as you do
by cutting the gene itself.

7583
06:03:01,836 --> 06:03:04,139
So this way you can
make it erythroid-specific

7584
06:03:04,639 --> 06:03:06,908
and not affect anything else
that BCL11A

7585
06:03:06,908 --> 06:03:09,677
might be doing
in amato cord stem cells.

7586
06:03:09,677 --> 06:03:12,313
And in fact, we did some work
with Dan,

7587
06:03:12,313 --> 06:03:15,150
where we tested this
in the non-human primate.

7588
06:03:15,150 --> 06:03:18,653
And at first we did
a competitive repopulation assay

7589
06:03:18,653 --> 06:03:22,190
where we competed BCL11A
erythroid enhancer edited cells

7590
06:03:22,190 --> 06:03:25,860
with AAVS1 edited cells.
So this should be inert.

7591
06:03:25,860 --> 06:03:29,230
So that served as our control,
and we had equivalent in graft,

7592
06:03:29,230 --> 06:03:31,900
and we had no perturbations
in hematopoiesis.

7593
06:03:31,900 --> 06:03:33,268
We had robust fetal hemoglobin.

7594
06:03:33,268 --> 06:03:37,005
And this looked like, you know,
it could be a go in the clinic.

7595
06:03:37,005 --> 06:03:40,475
And in fact high note
didn't show these data.

7596
06:03:40,475 --> 06:03:43,044
This is first New England
Journal publication

7597
06:03:43,645 --> 06:03:44,913
with this trial.

7598
06:03:44,913 --> 06:03:47,382
And note here, this is a patient
with thalassemia

7599
06:03:47,382 --> 06:03:50,685
where all of the hemoglobin
is coming from fetal

7600
06:03:50,685 --> 06:03:51,886
and it goes to normal.

7601
06:03:51,886 --> 06:03:53,588
So there are
no more transfusions

7602
06:03:53,588 --> 06:03:56,124
and a complete normalization
of hemoglobin.

7603
06:03:56,124 --> 06:03:58,827
So it's working for thalassemia
really quite well.

7604
06:04:00,161 --> 06:04:01,529
And he showed you this,
you know,

7605
06:04:01,529 --> 06:04:03,298
just like this slide
that I showed.

7606
06:04:04,098 --> 06:04:07,135
There are only a few dots
after this approach.

7607
06:04:08,903 --> 06:04:10,505
And again, FDA approved.

7608
06:04:11,139 --> 06:04:13,208
So one thing that I did want
to highlight is we've looked

7609
06:04:13,208 --> 06:04:15,677
at our allogeneic
transplant experience.

7610
06:04:15,677 --> 06:04:19,447
Now, in 163 patients,
it asks the same question,

7611
06:04:19,447 --> 06:04:21,049
what happens to pain?

7612
06:04:22,383 --> 06:04:24,419
Deepika
had looked at one year,

7613
06:04:24,419 --> 06:04:26,988
and we saw in those patients
at one year

7614
06:04:27,522 --> 06:04:29,958
that there was still
quite a bit of pain

7615
06:04:29,958 --> 06:04:32,193
that patients were reporting
and some pain

7616
06:04:32,193 --> 06:04:33,795
that required hospitalization.

7617
06:04:35,363 --> 06:04:38,466
But after two years
in these 163 patients,

7618
06:04:38,466 --> 06:04:39,767
we saw almost no pain.

7619
06:04:39,767 --> 06:04:44,706
So in yellow is the first year,
and in red is the second year.

7620
06:04:44,706 --> 06:04:47,175
And these patients are patients
that rejected

7621
06:04:47,175 --> 06:04:49,244
where you would
expect pain to return.

7622
06:04:49,244 --> 06:04:51,045
But there's still, you know,

7623
06:04:51,045 --> 06:04:53,348
a few patients
who are having pain

7624
06:04:53,348 --> 06:04:57,785
even after successful transplant
beyond the first year.

7625
06:05:00,522 --> 06:05:03,491
Well, HIV-based
antiviral vectors have now,

7626
06:05:03,491 --> 06:05:06,127
you know, proven effective
for a number of disorders.

7627
06:05:06,127 --> 06:05:07,328
You see here, you know,

7628
06:05:07,328 --> 06:05:12,233
there's ones for thalassemia
sickle cell disease,

7629
06:05:12,233 --> 06:05:15,503
as I mentioned,
adrenoleukodystrophy,

7630
06:05:15,503 --> 06:05:17,205
severe combined
immunodeficiency.

7631
06:05:17,205 --> 06:05:20,675
So these vectors are being used
in other settings

7632
06:05:20,675 --> 06:05:22,443
also successfully.

7633
06:05:24,045 --> 06:05:26,481
So we've made a lot of strides
in the way that we do this.

7634
06:05:26,481 --> 06:05:28,483
You know, we can --
we can --

7635
06:05:28,483 --> 06:05:30,685
in graph cells that
we've genetically modified

7636
06:05:30,685 --> 06:05:33,187
and prove that those
genetic modifications

7637
06:05:33,187 --> 06:05:35,156
can reverse the disease.

7638
06:05:35,156 --> 06:05:36,958
But as has been mentioned
several times today,

7639
06:05:36,958 --> 06:05:39,727
we have to use busulfan
to get these cells

7640
06:05:39,727 --> 06:05:41,796
and it's really no fun.

7641
06:05:41,796 --> 06:05:43,898
We have to ablate the marrow,
support the patient,

7642
06:05:43,898 --> 06:05:47,135
give transfusions of blood
and platelets, give antibiotics

7643
06:05:48,102 --> 06:05:49,704
and then hopefully
get the patient through.

7644
06:05:49,704 --> 06:05:52,140
So we've been looking
to try to replace

7645
06:05:52,140 --> 06:05:54,842
that toxic chemotherapy
with an antibody

7646
06:05:54,842 --> 06:05:57,145
that can be linked
to a drug to see

7647
06:05:57,145 --> 06:06:00,748
if we can get engraftment
at the same level.

7648
06:06:01,416 --> 06:06:04,652
And we've tried it with a couple
of different antibodies.

7649
06:06:04,652 --> 06:06:06,988
This first one is to CD45,

7650
06:06:06,988 --> 06:06:09,457
which is expressed on
all hematopoietic stem cells,

7651
06:06:09,457 --> 06:06:11,025
so we can target those cells.

7652
06:06:12,327 --> 06:06:13,962
We can use a site specific
payload

7653
06:06:13,962 --> 06:06:17,065
to just rid the body of those
cells and those cells only.

7654
06:06:17,765 --> 06:06:21,369
And in the case of CD45,
we deplete the immune cells too.

7655
06:06:21,369 --> 06:06:23,571
So we could also use it in a --

7656
06:06:23,571 --> 06:06:26,407
in a bone marrow transplant
for a brother or sister.

7657
06:06:26,407 --> 06:06:29,110
And for this, Dan already
showed some of this.

7658
06:06:29,110 --> 06:06:31,212
We were looking at a double
editing strategy

7659
06:06:31,212 --> 06:06:34,015
because if you edit
at the plus 55

7660
06:06:34,015 --> 06:06:36,017
and plus 58 that he showed,

7661
06:06:36,551 --> 06:06:39,988
you can get higher levels
of fetal hemoglobin

7662
06:06:39,988 --> 06:06:41,222
both in vitro here

7663
06:06:41,222 --> 06:06:45,226
and an engrafted immunodeficient
mice when you edit it,

7664
06:06:45,226 --> 06:06:51,165
both plus 55 and plus
58 higher than either alone.

7665
06:06:51,165 --> 06:06:53,301
So we're looking at improving
the efficiency

7666
06:06:53,301 --> 06:06:56,437
of fetal hemoglobin induction
while looking

7667
06:06:56,437 --> 06:07:00,675
at whether we could get
grafts in without busulfan.

7668
06:07:02,210 --> 06:07:06,381
And these are the monkey studies
that we did with Bob Donahue,

7669
06:07:06,381 --> 06:07:10,385
who's here in the audience
looking at double editing

7670
06:07:11,586 --> 06:07:16,557
for the plus 55
and the plus 58 and conditioning

7671
06:07:16,557 --> 06:07:20,928
with either busulfan
or antibody.

7672
06:07:20,928 --> 06:07:22,697
And you can see
the in vitro results

7673
06:07:22,697 --> 06:07:25,166
we had very nice fetal
hemoglobin induction

7674
06:07:25,166 --> 06:07:28,770
higher with the double
editing here up to 80 percent.

7675
06:07:29,337 --> 06:07:32,240
And when we grafted animals
with busulfan shown in gray,

7676
06:07:32,240 --> 06:07:35,276
we got really nice levels
of indels persisting over time.

7677
06:07:35,877 --> 06:07:40,615
These are weeks post-transplant.
So these are many years out now.

7678
06:07:40,615 --> 06:07:42,984
So 80, 90 percent indels
in the busulfan

7679
06:07:42,984 --> 06:07:46,454
treated group in the three
animals that received antibody,

7680
06:07:46,454 --> 06:07:49,090
similar levels of indels

7681
06:07:49,090 --> 06:07:52,026
and similar levels
of fetal hemoglobin induction.

7682
06:07:52,026 --> 06:07:54,162
What Dan didn't show
is that later

7683
06:07:54,162 --> 06:07:56,464
we challenged these animals
with phlebotomy

7684
06:07:57,065 --> 06:08:00,735
to sort of stress
their erythropoiesis.

7685
06:08:00,735 --> 06:08:02,970
And you can see
that they went right back up

7686
06:08:02,970 --> 06:08:07,608
to the levels that we saw
right at the time of transplant

7687
06:08:07,608 --> 06:08:09,110
when they were indeed stressed.

7688
06:08:09,110 --> 06:08:11,746
And I think this is probably
more like we would see

7689
06:08:11,746 --> 06:08:14,082
in the setting of thalassemia
or sickle cell disease,

7690
06:08:14,082 --> 06:08:17,618
where, you know, they're having
to work overtime to repopulate.

7691
06:08:19,854 --> 06:08:23,124
We also just marked the cells
with the lentiviral vector

7692
06:08:23,124 --> 06:08:24,459
that had a barcode inside.

7693
06:08:24,459 --> 06:08:26,961
So we could see how many got in,
how many got marked,

7694
06:08:26,961 --> 06:08:28,963
and how they contributed
over time.

7695
06:08:28,963 --> 06:08:31,065
And whether it was similar
to busulfan

7696
06:08:31,065 --> 06:08:32,967
because we wanted to answer
the question

7697
06:08:32,967 --> 06:08:36,571
that was posed by Mark earlier,
like you know,

7698
06:08:36,571 --> 06:08:39,006
do we get enough cells in
with a transplant,

7699
06:08:39,006 --> 06:08:43,511
with this conditioning too
have polyclonal hematopoiesis?

7700
06:08:43,511 --> 06:08:45,813
And indeed we did.
We had a Shannon index,

7701
06:08:45,813 --> 06:08:48,816
which is a measure of the
complexity of hematopoiesis

7702
06:08:48,816 --> 06:08:51,886
that was similar in the antibody
treated animals

7703
06:08:51,886 --> 06:08:55,957
when compared to busulfan
TBI or TBI.

7704
06:08:56,557 --> 06:08:59,193
And here you can see
the contribution of those clones

7705
06:08:59,794 --> 06:09:03,397
over the first year
in this animal in six months

7706
06:09:03,397 --> 06:09:04,999
and the second animal.

7707
06:09:05,933 --> 06:09:08,836
We then went on
to look at antibody to see kit

7708
06:09:09,370 --> 06:09:11,906
which is more exclusively
expressed on hematopoietic

7709
06:09:11,906 --> 06:09:13,207
stem and progenitor cells.

7710
06:09:13,207 --> 06:09:17,278
So CD117 in this antibody
drug conjugate

7711
06:09:17,278 --> 06:09:20,214
we used in the context
of a lentiviral vector

7712
06:09:20,214 --> 06:09:24,685
expressing a smear to BCL11A
much like the children's --

7713
06:09:25,520 --> 06:09:28,356
the Boston Children's Study
by David Williams.

7714
06:09:29,123 --> 06:09:32,493
And you can see we got
equivalent vector copy number

7715
06:09:33,327 --> 06:09:35,029
in the antibody
conditioned animals

7716
06:09:35,029 --> 06:09:38,199
when compared to the two
busulfan conditioned animals.

7717
06:09:38,199 --> 06:09:41,135
We had similar levels
of hemoglobin F induction.

7718
06:09:41,836 --> 06:09:44,238
But the one thing
that was really remarkable

7719
06:09:44,238 --> 06:09:45,940
with the use of the antibody

7720
06:09:45,940 --> 06:09:48,209
is that the menstrual cycle
did not change.

7721
06:09:48,209 --> 06:09:52,013
So it was one menstrual cycle
per month in the females,

7722
06:09:52,013 --> 06:09:54,549
whereas they, you know,
they were markedly reduced

7723
06:09:54,549 --> 06:09:56,584
in the busulfan and TBI animals.

7724
06:09:56,584 --> 06:09:59,253
So Bob had the brilliant idea of
just sending these animals

7725
06:09:59,253 --> 06:10:04,826
back to group housing to see
if they would reproduce.

7726
06:10:04,826 --> 06:10:08,462
And in fact, four of the six
in the first mating season

7727
06:10:08,462 --> 06:10:09,964
had successful pregnancies.

7728
06:10:09,964 --> 06:10:13,501
So this is, you know, as good as
it gets for mating in a --

7729
06:10:13,501 --> 06:10:16,437
in a --
in captivity four of six.

7730
06:10:16,437 --> 06:10:20,374
So this preserved fertility,
which is a --

7731
06:10:20,374 --> 06:10:21,776
which is a big concern.

7732
06:10:21,776 --> 06:10:24,478
In fact, two of these animals
were in the ICU together

7733
06:10:25,046 --> 06:10:28,282
before they went out,
you know, to the island [laughs]

7734
06:10:28,282 --> 06:10:31,552
and re-found
each other and reproduced.

7735
06:10:31,552 --> 06:10:36,324
So we also tried gene conversion

7736
06:10:37,859 --> 06:10:40,795
and for that
we made the sickle mutation

7737
06:10:40,795 --> 06:10:42,697
and we were using
HDR with CRISPR

7738
06:10:42,697 --> 06:10:45,733
because we wanted to see do
these cells and graft well,

7739
06:10:45,733 --> 06:10:47,568
because this is another
anti-sickling approach

7740
06:10:47,568 --> 06:10:48,803
that's really elegant.

7741
06:10:48,803 --> 06:10:51,839
You know, just make the beta
S mutation back to beta.

7742
06:10:51,839 --> 06:10:53,641
That should work brilliantly,
right?

7743
06:10:54,242 --> 06:10:57,845
But it turns out hemato partic
stem cells are resistant to HDR,

7744
06:10:57,845 --> 06:11:04,552
and though we could get like
60 percent correction,

7745
06:11:04,552 --> 06:11:09,056
which was making the beta
S mutation in those cells,

7746
06:11:09,056 --> 06:11:10,258
they didn't even graft well.

7747
06:11:10,258 --> 06:11:12,827
So up top you can see
they dropped

7748
06:11:12,827 --> 06:11:16,530
to like 1 percent
in these two animals, HDR

7749
06:11:16,530 --> 06:11:20,034
but the indels persisted,
you know, 40 and 20 percent.

7750
06:11:20,034 --> 06:11:21,535
So we already knew
we could make indels

7751
06:11:21,535 --> 06:11:23,738
and they engraft
and they'll persist.

7752
06:11:23,738 --> 06:11:26,107
But if the cell has to go all
the way through homology

7753
06:11:26,107 --> 06:11:29,010
directed repair,
those cells either don't engraft

7754
06:11:29,010 --> 06:11:31,345
or, you know,
we're not really getting into

7755
06:11:31,345 --> 06:11:33,180
the amato cord
stem cell with HDR.

7756
06:11:33,180 --> 06:11:35,016
So that looked like a strategy

7757
06:11:35,016 --> 06:11:37,184
that maybe
we should leave aside.

7758
06:11:37,184 --> 06:11:40,421
And I think Graphite Bio learned
this lesson the hard way

7759
06:11:40,421 --> 06:11:43,557
in their first patient
where they saw similar levels.

7760
06:11:45,426 --> 06:11:49,163
So now Hena, but in the lab,
is looking at strategies

7761
06:11:49,163 --> 06:11:52,099
for comparing anti-sickling
approaches for sickle cell.

7762
06:11:52,099 --> 06:11:55,736
So she's looking at gene
edition, you know,

7763
06:11:55,736 --> 06:11:59,206
with the BB305 vector
BCL11A disruption

7764
06:11:59,206 --> 06:12:02,643
with CRISPR-Cas9,
and base editing,

7765
06:12:02,643 --> 06:12:05,646
which we've chosen
to make them a Cas mutation.

7766
06:12:05,646 --> 06:12:08,049
This is a --
this is a hemoglobin variant

7767
06:12:08,049 --> 06:12:10,551
that should be --
should be benign.

7768
06:12:11,118 --> 06:12:13,788
And then we can look to see
how well we do

7769
06:12:14,655 --> 06:12:17,391
whether we inhibit
sickling equivalently

7770
06:12:17,391 --> 06:12:19,627
and then put those through
the animal models.

7771
06:12:21,362 --> 06:12:24,966
So, so far she's shown that
she can get really good editing.

7772
06:12:24,966 --> 06:12:27,335
So, you know, with the BCL11A
editing,

7773
06:12:27,335 --> 06:12:28,769
we've gotten
really good at that.

7774
06:12:28,769 --> 06:12:31,205
We get 95 percent
pretty much every time.

7775
06:12:31,739 --> 06:12:34,642
Makassar editing, not bad,
about 80 percent.

7776
06:12:34,642 --> 06:12:36,577
Not as good as BCL11A,
but pretty good.

7777
06:12:36,577 --> 06:12:40,915
Vector copy number for
the T87Q vector of round one.

7778
06:12:40,915 --> 06:12:42,216
So all of these are what,
you know,

7779
06:12:42,216 --> 06:12:44,352
what you would get
typically in the clinic.

7780
06:12:45,686 --> 06:12:48,222
And fetal hemoglobin induction
with the BCL11A

7781
06:12:48,222 --> 06:12:50,057
editing of 60 percent,

7782
06:12:50,057 --> 06:12:53,494
40 percent endogenous
with the T87Q vector.

7783
06:12:53,494 --> 06:12:56,530
And then when we look at anti
sickling in Wan Lee

7784
06:12:56,530 --> 06:13:00,468
and Bill Eaton's assay which has
been very predictive for us

7785
06:13:00,468 --> 06:13:02,003
even in the clinical setting,

7786
06:13:02,003 --> 06:13:05,873
we can see a really
nice inhibition of sickling

7787
06:13:05,873 --> 06:13:08,843
and really almost no sickling
frequency in these cells

7788
06:13:09,777 --> 06:13:13,581
after differentiation
into red cells ex vivo.

7789
06:13:15,116 --> 06:13:17,018
So it looks like when we do well

7790
06:13:17,018 --> 06:13:20,187
and we have
an efficient strategy,

7791
06:13:20,187 --> 06:13:23,190
that the anti-sickling
properties are pretty similar.

7792
06:13:23,190 --> 06:13:27,561
And she's now comparing them
in the mouse and in fact,

7793
06:13:27,561 --> 06:13:29,797
harvesting them now
for secondary transplants.

7794
06:13:29,797 --> 06:13:32,166
And for a look
at the hemoglobins,

7795
06:13:32,166 --> 06:13:34,268
because you can only really
get red cells out of the marrow.

7796
06:13:34,268 --> 06:13:37,938
So we do this
at their four-month time point.

7797
06:13:37,938 --> 06:13:41,242
But then, you know, there's all
this use of this mouse model,

7798
06:13:41,242 --> 06:13:43,544
this immunodeficient mouse model
to teach us

7799
06:13:43,544 --> 06:13:45,513
whether strategies are working.

7800
06:13:45,513 --> 06:13:49,316
And I've always been sort
of reluctant to accept those

7801
06:13:49,316 --> 06:13:50,785
because when I first started
in the field,

7802
06:13:50,785 --> 06:13:52,453
we used mouse data to justify

7803
06:13:52,453 --> 06:13:55,356
our human transplant
marking studies.

7804
06:13:55,356 --> 06:13:57,892
And, you know, we could get
50 percent in the mice

7805
06:13:57,892 --> 06:14:00,294
and we got like one
in a million in the human.

7806
06:14:00,294 --> 06:14:02,263
So there was a big disconnect.

7807
06:14:02,263 --> 06:14:06,667
But these transplants
where you take human cells

7808
06:14:06,667 --> 06:14:08,836
and you put them
into immunodeficient mice

7809
06:14:08,836 --> 06:14:12,706
may be better than just
transplanting mouse into mouse.

7810
06:14:13,874 --> 06:14:15,209
So we've been trying for years

7811
06:14:15,209 --> 06:14:18,579
to make this rhesusized
mouse model.

7812
06:14:18,579 --> 06:14:22,249
That is, we take rhesus
CD34 cells, not human,

7813
06:14:22,249 --> 06:14:23,884
and put them into the mouse

7814
06:14:23,884 --> 06:14:26,620
because that way
we could do parallel studies

7815
06:14:26,620 --> 06:14:28,222
when we do a transplant
in the monkey

7816
06:14:28,222 --> 06:14:30,391
and we get 10 percent
of whatever,

7817
06:14:30,391 --> 06:14:33,727
if we took a fraction of those
cells and put in those mice,

7818
06:14:33,727 --> 06:14:37,264
and we also got 10 percent.
We would be much more likely

7819
06:14:37,264 --> 06:14:40,734
to believe that that mouse
is a relevant model.

7820
06:14:40,734 --> 06:14:42,336
And we've just never been
able to do it,

7821
06:14:42,336 --> 06:14:45,106
because every time
we've tried it doesn't work.

7822
06:14:45,106 --> 06:14:49,310
So Hasan Demirci in the lab
decided to try again.

7823
06:14:49,310 --> 06:14:51,278
And this time it worked.

7824
06:14:51,278 --> 06:14:54,115
We got really good engraftment
in these mice

7825
06:14:54,815 --> 06:14:58,752
actually higher
with rhesus cells in blue here.

7826
06:14:58,752 --> 06:15:01,188
The reason it falls off later
is because it did so well

7827
06:15:01,188 --> 06:15:04,325
that the mice got graft versus
host disease at the six months.

7828
06:15:04,325 --> 06:15:07,428
So we started losing animals
except for the ones

7829
06:15:07,428 --> 06:15:10,064
that were only
engrafted at low levels.

7830
06:15:10,064 --> 06:15:12,900
But suffice it to say,
we now have robust engraftment.

7831
06:15:12,900 --> 06:15:19,073
We can look to see whether
we can predict with this model.

7832
06:15:19,073 --> 06:15:21,108
And one of the things that
we did is we took animals

7833
06:15:21,108 --> 06:15:22,743
that we've had for years,

7834
06:15:22,743 --> 06:15:25,613
like these two animals
that we've had, you know,

7835
06:15:25,613 --> 06:15:28,516
for years
with marking in their blood

7836
06:15:28,516 --> 06:15:31,785
with green fluorescence protein
or yellow fluorescence protein

7837
06:15:31,785 --> 06:15:34,155
when we were doing
competitive repopulation,

7838
06:15:34,155 --> 06:15:35,389
looking at different assay,

7839
06:15:35,389 --> 06:15:37,591
I mean, looking
at different vector designs.

7840
06:15:38,192 --> 06:15:41,395
And in this animal we had
almost equivalent GFP/YFP.

7841
06:15:41,395 --> 06:15:43,397
So 2 percent, 5 percent.

7842
06:15:43,397 --> 06:15:47,067
And you can see the readout
in this mouse is,

7843
06:15:47,067 --> 06:15:49,036
you know, around 5 percent.

7844
06:15:49,537 --> 06:15:52,473
So very similar to what
the animal has been showing us

7845
06:15:52,473 --> 06:15:53,774
for now many years.

7846
06:15:53,774 --> 06:15:55,709
And in this animal where there's
a much bigger difference

7847
06:15:55,709 --> 06:15:58,979
between GFP and YFP 15

7848
06:15:58,979 --> 06:16:02,616
and four, we see,
you know, around 25 and five.

7849
06:16:02,616 --> 06:16:07,421
So it seems to be recapitulating
at least what we have in vivo.

7850
06:16:07,421 --> 06:16:12,092
So we're hopeful that this will
help us to to move forward

7851
06:16:12,092 --> 06:16:14,028
in assessing these approaches.

7852
06:16:15,729 --> 06:16:18,299
But one thing that also keeps
bubbling up here

7853
06:16:18,299 --> 06:16:20,067
is that this is hard to do,

7854
06:16:20,067 --> 06:16:26,207
you know, even in -- you know,
in well-resourced countries.

7855
06:16:26,207 --> 06:16:27,675
I'm not really sure
what to call it.

7856
06:16:27,675 --> 06:16:32,179
Now, knowing that this line

7857
06:16:32,179 --> 06:16:35,115
is so low
in terms of income for country.

7858
06:16:36,016 --> 06:16:38,352
But you -- we really need to be
able to do this

7859
06:16:38,352 --> 06:16:39,887
in a different way
than a transplant.

7860
06:16:39,887 --> 06:16:43,157
So Francis, who's already been
alluded to by Wilbur earlier

7861
06:16:44,058 --> 06:16:47,328
was giving a talk at ASGCT
a few years ago,

7862
06:16:49,096 --> 06:16:50,731
and he really said it right.

7863
06:16:50,731 --> 06:16:53,534
You know, we have to come up
with a strategy

7864
06:16:53,534 --> 06:16:56,470
because even before
acknowledging that, you know,

7865
06:16:56,470 --> 06:16:59,907
patients are spread across
Africa and India, we just --

7866
06:17:00,507 --> 06:17:04,078
we don't have the ability
to do this.

7867
06:17:04,078 --> 06:17:06,146
It's just out of the question.

7868
06:17:06,146 --> 06:17:07,748
We don't have the ability
to do it.

7869
06:17:07,748 --> 06:17:13,420
So we need to make some in
vivo gene editing strategies.

7870
06:17:13,420 --> 06:17:16,357
So we're working on that now
so we can get rid of the need

7871
06:17:16,357 --> 06:17:17,858
for all this,
you know,

7872
06:17:17,858 --> 06:17:20,294
harvesting,
processing, gene addition,

7873
06:17:20,294 --> 06:17:22,863
gene editing, freezing,
transporting,

7874
06:17:23,731 --> 06:17:26,800
you know conditioning
to where we could make it --

7875
06:17:26,800 --> 06:17:28,035
you know,
we could take these tools

7876
06:17:28,035 --> 06:17:31,839
and stick them in a viral vector
or nanoparticle and just inject

7877
06:17:31,839 --> 06:17:34,708
and hopefully have
that go in and fix the patient.

7878
06:17:34,708 --> 06:17:36,176
That way we could just,

7879
06:17:36,176 --> 06:17:38,245
you know,
make it work all in one visit.

7880
06:17:38,946 --> 06:17:41,248
And so we've been looking
at antibody drug conjugates,

7881
06:17:41,248 --> 06:17:44,785
as I showed you, for depleting
of amato cord stem cells.

7882
06:17:44,785 --> 06:17:47,721
But that proved to us that
we can reach these stem cells.

7883
06:17:47,721 --> 06:17:50,524
So this CD117 targeted ADC,

7884
06:17:50,524 --> 06:17:52,726
goes in and knocks out
the hematopoietic

7885
06:17:52,726 --> 06:17:55,462
stem cells
equivalently to busulfan.

7886
06:17:55,462 --> 06:17:56,930
So if we could take
this antibody

7887
06:17:56,930 --> 06:17:58,832
and hook it to a vector
or hook it

7888
06:17:58,832 --> 06:18:01,802
to a lipid nanoparticle,
maybe we could get in.

7889
06:18:01,802 --> 06:18:04,305
So even looking to make
lentiviral vectors

7890
06:18:05,039 --> 06:18:08,008
and, you know, to put on
their surface these antibodies.

7891
06:18:09,009 --> 06:18:11,512
We've done that
with a C kit antibody

7892
06:18:11,512 --> 06:18:14,748
and in a cell line
that variably expresses C kit,

7893
06:18:14,748 --> 06:18:18,519
you can see after screening
by phase display,

7894
06:18:18,519 --> 06:18:21,422
a bunch of different scFVs,
we found a number of them

7895
06:18:21,422 --> 06:18:25,192
that are very selective
for CD117,

7896
06:18:25,192 --> 06:18:28,562
positive cells over
CD117 negative cells.

7897
06:18:28,562 --> 06:18:31,065
And we're incorporating
those into vectors now

7898
06:18:31,065 --> 06:18:34,134
to try to get a transfer.

7899
06:18:34,134 --> 06:18:37,237
And we can also do
the same thing with peptides.

7900
06:18:37,237 --> 06:18:40,007
So we're using peptides

7901
06:18:40,007 --> 06:18:42,910
to basically decorate
lipid nanoparticles

7902
06:18:42,910 --> 06:18:46,080
because it's a lot easier
chemically to get a peptide

7903
06:18:46,080 --> 06:18:47,681
hooked to a lipid nanoparticle.

7904
06:18:48,816 --> 06:18:51,719
And we've, you know, screened
again with phase display,

7905
06:18:52,252 --> 06:18:54,054
this time both
with negative selection.

7906
06:18:54,054 --> 06:18:56,490
So we start them first
on the negative cell line

7907
06:18:56,490 --> 06:18:57,958
and then on
a positive cell line,

7908
06:18:57,958 --> 06:19:01,362
and then sometimes rescreen
and then select the media

7909
06:19:01,362 --> 06:19:03,997
and the cell lysate.
So we know cells that are --

7910
06:19:03,997 --> 06:19:05,766
you know,
peptides that are binding,

7911
06:19:05,766 --> 06:19:08,469
and then peptides that are
binding and internalizing.

7912
06:19:08,469 --> 06:19:10,003
And these are some
of the results we get.

7913
06:19:10,003 --> 06:19:12,406
We've done it with a bunch
of different levels of plasma

7914
06:19:12,406 --> 06:19:14,475
just because we thought
that might interfere

7915
06:19:14,475 --> 06:19:17,811
and we find overlap
between external and internal.

7916
06:19:17,811 --> 06:19:21,382
And then we start looking to see
if those can be used.

7917
06:19:21,382 --> 06:19:23,417
And these are just some of them
that, again, we've screened

7918
06:19:23,417 --> 06:19:28,589
for transfer of GFP in this
positive negative cell line.

7919
06:19:28,589 --> 06:19:32,559
And again, some that are very
selective for the CD117

7920
06:19:33,260 --> 06:19:34,862
positive cell line.

7921
06:19:35,896 --> 06:19:38,098
So I'll summarize by saying
that, you know,

7922
06:19:38,098 --> 06:19:39,400
gene therapy works.

7923
06:19:39,400 --> 06:19:41,034
Finally, the last time
I was here,

7924
06:19:41,034 --> 06:19:43,070
we were, you know,
hoping to be here.

7925
06:19:44,171 --> 06:19:47,508
I think with improvements
in the anti-sickling properties,

7926
06:19:47,508 --> 06:19:48,776
we should be able
to make it better.

7927
06:19:48,776 --> 06:19:51,078
Of course, we need
long-term follow-up.

7928
06:19:51,078 --> 06:19:54,515
Toxicities are still a problem.
Hopefully we can get antibodies

7929
06:19:54,515 --> 06:20:00,120
working so we can get away
from this toxic chemotherapy.

7930
06:20:00,120 --> 06:20:02,556
And of course, you know,
if we could figure out a way

7931
06:20:02,556 --> 06:20:05,426
to deliver
these genetic tools in vivo,

7932
06:20:05,426 --> 06:20:08,395
we should be able to reach
where the patients mostly are.

7933
06:20:08,996 --> 06:20:11,165
And I think, you know,
delivery through antibody

7934
06:20:11,165 --> 06:20:14,301
or peptide methods
could help us do that.

7935
06:20:14,301 --> 06:20:17,037
And, you know,
global distribution of vaccines

7936
06:20:17,037 --> 06:20:18,772
that were based
on lipid nanoparticles,

7937
06:20:18,772 --> 06:20:20,707
the same lipid nanoparticles

7938
06:20:20,707 --> 06:20:22,576
that we're actually
using in these --

7939
06:20:23,343 --> 06:20:26,647
in these studies were used
for the COVID vaccine

7940
06:20:26,647 --> 06:20:27,915
that was distributed widely.

7941
06:20:27,915 --> 06:20:31,618
So we think we have at least
infrastructure available too,

7942
06:20:31,618 --> 06:20:36,390
to roll that out if, you know,
we can make it work efficiently.

7943
06:20:36,390 --> 06:20:39,626
So I'll stop there and
acknowledge all of the people

7944
06:20:39,626 --> 06:20:41,995
that have helped
and take any questions.

7945
06:20:47,067 --> 06:20:48,836
Haydar Frangoul: I'm going to
start with my first question.

7946
06:20:48,836 --> 06:20:53,373
So you have a lot of experience
at the NIH using,

7947
06:20:54,274 --> 06:20:55,776
you know,
haploidentical transplant

7948
06:20:55,776 --> 06:20:58,111
with patients
that having mixed chimerism.

7949
06:20:58,111 --> 06:20:59,513
You know, in gene therapy,

7950
06:20:59,513 --> 06:21:01,415
those products we are
infusing into patients

7951
06:21:01,415 --> 06:21:03,016
are not a hundred
percent edited.

7952
06:21:03,016 --> 06:21:05,452
So some products are 60,
70 percent edited.

7953
06:21:06,086 --> 06:21:10,224
In your patients who are mixed
chimerism, long-term post haplo,

7954
06:21:10,224 --> 06:21:12,693
do their hemolysis markers
totally normalized?

7955
06:21:14,661 --> 06:21:15,963
John Tisdale: No.

7956
06:21:15,963 --> 06:21:19,199
So I actually have a fellow
who's working on that now.

7957
06:21:20,267 --> 06:21:24,404
Actually she's faculty
now at, at Children's.

7958
06:21:24,404 --> 06:21:28,075
And she's also observed
that patients

7959
06:21:28,075 --> 06:21:30,010
with mixed chimerism
also have --

7960
06:21:30,978 --> 06:21:33,714
as at -- you know, as we've seen
in all these patients,

7961
06:21:34,314 --> 06:21:38,252
mild elevation in reticulocytes
as compared to those

7962
06:21:38,252 --> 06:21:41,955
who have full donor chimerism
in all compartments

7963
06:21:41,955 --> 06:21:44,791
where the reticulocyte count
seems to be normalized.

7964
06:21:44,791 --> 06:21:47,761
And if we look by flow
at those reticulocytes,

7965
06:21:47,761 --> 06:21:49,363
we enrich for hemoglobin S.

7966
06:21:49,997 --> 06:21:51,999
Haydar Frangoul: Interesting.
Okay.

7967
06:21:51,999 --> 06:21:53,200
John Tisdale: Mark.

7968
06:21:53,200 --> 06:21:54,501
Mark Walters: Hey. Hey John.
That was a great talk.

7969
06:21:54,501 --> 06:21:55,702
John Tisdale: Thanks Mark.

7970
06:21:55,702 --> 06:21:56,937
Mark Walters: I wanted
to pick your brain

7971
06:21:56,937 --> 06:21:59,640
a little bit about HDR
in the hematopoietic,

7972
06:21:59,640 --> 06:22:01,275
the true hematopoietic
stem cell

7973
06:22:02,075 --> 06:22:05,712
because I we've reviewed
both Cindy Dunbar's paper

7974
06:22:06,780 --> 06:22:09,182
about that topic
in the non-human primates

7975
06:22:09,182 --> 06:22:11,518
and then the data
you presented today.

7976
06:22:11,518 --> 06:22:18,325
Have you tried ways
of optimizing the health

7977
06:22:18,325 --> 06:22:20,894
of the hematopoietic
stem cell through cycling

7978
06:22:20,894 --> 06:22:25,098
and media manipulations
or inhibitors of non-hemology

7979
06:22:25,098 --> 06:22:28,635
and joining as a way
to improve that outcome?

7980
06:22:29,136 --> 06:22:31,305
And or do you have
other ideas about

7981
06:22:31,305 --> 06:22:33,941
how we might accomplish
that in the future?

7982
06:22:34,908 --> 06:22:38,512
John Tisdale: So, yeah.
So these two animals,

7983
06:22:38,512 --> 06:22:40,747
we had optimized
all the way up to using,

7984
06:22:42,382 --> 06:22:44,651
you know,
multiple adjuvants in the --

7985
06:22:45,652 --> 06:22:50,591
in the cytokine cocktail
that the cells were cultured

7986
06:22:50,591 --> 06:22:55,095
in along with I53,
I53 to inhibit 53PP1.

7987
06:22:55,963 --> 06:22:59,666
So that's inclusive of those,
what what I've shown.

7988
06:23:00,534 --> 06:23:02,603
We've tried to further optimize

7989
06:23:03,270 --> 06:23:05,038
and we haven't been able
to make it

7990
06:23:05,038 --> 06:23:07,307
any better
than what we've seen so far.

7991
06:23:07,307 --> 06:23:09,977
We've been sort of banging
our heads against the wall.

7992
06:23:09,977 --> 06:23:14,615
And so, you know, we've tried
base editing, prime editing,

7993
06:23:14,615 --> 06:23:17,484
and those seem to be working now

7994
06:23:17,484 --> 06:23:19,353
with the same efficiency
that we can get.

7995
06:23:19,353 --> 06:23:22,923
We can get 60 percent HDR
with CRISPR,

7996
06:23:23,557 --> 06:23:29,429
but we can also get 60,
80 percent with prime editing.

7997
06:23:29,429 --> 06:23:30,864
And we can get hemoglobin CESAR

7998
06:23:30,864 --> 06:23:33,934
as I showed at about 80 percent
with base editing.

7999
06:23:33,934 --> 06:23:36,303
So we think
there may be advantages

8000
06:23:37,004 --> 06:23:38,572
to just nicking the DNA

8001
06:23:38,572 --> 06:23:40,407
as opposed to
double strand breaks

8002
06:23:40,407 --> 06:23:43,276
that you get with these
newer editing methods

8003
06:23:43,276 --> 06:23:46,847
that we're now pursuing.
So --

8004
06:23:46,847 --> 06:23:48,515
Mark Walters: Yeah. Great.
Great talk John, as always.

8005
06:23:48,515 --> 06:23:50,317
Do you -- to follow-up
on Dr. Walter's question,

8006
06:23:50,317 --> 06:23:53,520
do you think that if we're able
to get that level of HDR

8007
06:23:53,520 --> 06:23:54,955
or prime editing
or anything else,

8008
06:23:54,955 --> 06:23:58,158
do you think it'll matter what
the age of the stem cell is?

8009
06:23:58,825 --> 06:24:00,293
And do you think if --

8010
06:24:00,293 --> 06:24:02,462
say older patients
where we try to do this,

8011
06:24:02,462 --> 06:24:04,865
it might be more challenging
to get efficient editing

8012
06:24:04,865 --> 06:24:06,967
or about the same?

8013
06:24:06,967 --> 06:24:08,268
John Tisdale: Yeah,
I do think age

8014
06:24:08,268 --> 06:24:11,338
is going to play a role both
in the efficiency of editing

8015
06:24:11,338 --> 06:24:14,174
and, you know,
in the engraftment long-term

8016
06:24:14,174 --> 06:24:17,644
and the dangers that might
befall the patient having,

8017
06:24:18,245 --> 06:24:20,280
you know,
started at an older age

8018
06:24:20,280 --> 06:24:22,182
and then have their
hematopoietic compartment

8019
06:24:22,182 --> 06:24:26,153
whittled down to a much
smaller number to reconstitute.

8020
06:24:26,153 --> 06:24:29,723
So I mean, I think it's true
for most of the things

8021
06:24:29,723 --> 06:24:31,258
that we've tried to do
in gene therapy

8022
06:24:31,258 --> 06:24:34,127
is that younger is seems
to always be better.

8023
06:24:34,127 --> 06:24:35,729
Mark Walters: Yeah.
Okay. Thanks.

8024
06:24:36,797 --> 06:24:39,466
Haydar Frangoul: Okay.
Well, thank you, John.

8025
06:24:40,000 --> 06:24:44,705
It is my distinct honor
to present the next speaker.

8026
06:24:44,705 --> 06:24:46,640
A lot of the work
that I talked about,

8027
06:24:47,307 --> 06:24:49,376
a lot of it has to do
with the work you did.

8028
06:24:49,376 --> 06:24:53,346
So again, congratulations
on the big award.

8029
06:24:53,346 --> 06:24:56,383
Dr. Swee Lay
Thein is going to present

8030
06:24:56,383 --> 06:24:57,684
increasing anti-sickling

8031
06:24:57,684 --> 06:25:00,754
potential
pharmacologic approaches.

8032
06:25:00,754 --> 06:25:04,124
She is a senior investigator
and chief of Sickle Cell branch

8033
06:25:04,124 --> 06:25:06,093
within the National Heart,
Lung and Blood

8034
06:25:06,093 --> 06:25:08,395
Institute of the National
Institute of Health.

8035
06:25:09,196 --> 06:25:10,430
Thank you.

8036
06:25:10,430 --> 06:25:14,735
[applause]

8037
06:25:14,735 --> 06:25:17,404
Swee Thein: Thank you, Haydar.
It's a pleasure to be here.

8038
06:25:18,338 --> 06:25:21,041
So let's see. Do I just -- okay.

8039
06:25:22,209 --> 06:25:27,347
So I'm going to talk
about anti-sickling approaches

8040
06:25:27,347 --> 06:25:31,618
using pharmacological means.

8041
06:25:31,618 --> 06:25:36,156
Oops, what did I do now?
I've broken this. Okay.

8042
06:25:41,394 --> 06:25:42,996
I've nothing to disclose,

8043
06:25:42,996 --> 06:25:45,932
but I will discuss
some off-label drugs.

8044
06:25:46,800 --> 06:25:50,103
So this is the outline
of my talk.

8045
06:25:50,103 --> 06:25:51,538
First, I'm going to give you
an overview

8046
06:25:51,538 --> 06:25:54,541
of sickle cell pathophysiology,
just a very quick one

8047
06:25:54,541 --> 06:25:57,978
because I know all of you're
very familiar with it already.

8048
06:25:58,945 --> 06:26:01,348
And the developments
in therapeutic targets.

8049
06:26:01,348 --> 06:26:02,616
I'm going to talk about

8050
06:26:02,616 --> 06:26:05,685
the current pharmacological
antidisciplinary approaches

8051
06:26:06,319 --> 06:26:11,091
and the scientific rationale
and the possible concerns

8052
06:26:11,091 --> 06:26:14,494
that have been raised on
compromising oxygen delivery,

8053
06:26:15,095 --> 06:26:18,165
utilizing approaches based
on increasing

8054
06:26:18,165 --> 06:26:20,000
hemoglobin oxygen affinity.

8055
06:26:21,067 --> 06:26:23,904
And then when time permits
also talk about

8056
06:26:23,904 --> 06:26:27,941
other potential pharmacological
anti-sickling approaches.

8057
06:26:29,609 --> 06:26:33,146
So just to remind us about
the Global Burden

8058
06:26:33,146 --> 06:26:34,548
of sickle cell disease,

8059
06:26:34,548 --> 06:26:36,216
and we've heard a lot
about it today,

8060
06:26:36,216 --> 06:26:40,887
already, currently is estimated
that there are 7 to 8 million

8061
06:26:40,887 --> 06:26:45,091
sickle cell patients worldwide
and migrations actually changing

8062
06:26:45,091 --> 06:26:46,793
the sickle cell
disease landscape.

8063
06:26:48,662 --> 06:26:51,665
This is a very simple
representation

8064
06:26:51,665 --> 06:26:54,601
of the pathophysiology
of sickle cell disease,

8065
06:26:54,601 --> 06:26:57,871
which we know is caused by
the presence of hemoglobin S

8066
06:26:58,605 --> 06:27:00,540
due to a single base mutation.

8067
06:27:01,041 --> 06:27:04,978
And this abnormal hemoglobin
S polymerizes when oxygenated,

8068
06:27:05,512 --> 06:27:09,950
and it is the root cause
that leads to the change

8069
06:27:09,950 --> 06:27:13,186
in the red cell
structure and function,

8070
06:27:13,186 --> 06:27:14,754
what we refer to as sickling.

8071
06:27:15,722 --> 06:27:19,326
So here the current
therapeutic options.

8072
06:27:19,860 --> 06:27:23,230
We've all heard about transplant
genetic therapy.

8073
06:27:23,763 --> 06:27:31,471
The four drug approved options
covering the hydroxyurea,

8074
06:27:31,471 --> 06:27:35,041
voxelotor,
L-glutamine and crizanlizumab.

8075
06:27:35,041 --> 06:27:38,044
Each of these have
their own limitations.

8076
06:27:38,612 --> 06:27:42,616
And at this point, I'd also like
to mention that crizanlizumab

8077
06:27:43,149 --> 06:27:48,455
has been withdrawn at EMA
in Europe and the MHRA in UK

8078
06:27:48,455 --> 06:27:52,993
has revoked approval in 2023
for its lack of efficacy.

8079
06:27:53,660 --> 06:27:57,597
And what is recalled treatment
in Europe in January, 2024.

8080
06:27:59,099 --> 06:28:02,002
So I want to talk
about hydroxyurea.

8081
06:28:04,004 --> 06:28:06,506
Clearly then,
there is an unmet need

8082
06:28:06,506 --> 06:28:09,309
for an effective
disease-modifying drug

8083
06:28:09,309 --> 06:28:10,911
that can be taken orally.

8084
06:28:12,279 --> 06:28:14,614
We're all working towards
getting more treatment,

8085
06:28:14,614 --> 06:28:16,917
some in qualified
curative therapies,

8086
06:28:16,917 --> 06:28:19,586
but a large majority do not.

8087
06:28:19,586 --> 06:28:22,322
Especially the patients
that I look after

8088
06:28:22,322 --> 06:28:23,957
who are adult patients

8089
06:28:23,957 --> 06:28:26,326
who becoming more sensitive
to hydroxyurea

8090
06:28:26,893 --> 06:28:32,399
and they need something actually
to improve the quality of lives.

8091
06:28:34,501 --> 06:28:37,871
So hemoglobin S polymerization,
as you all know,

8092
06:28:37,871 --> 06:28:40,206
is the root cause
of sickle cell disease

8093
06:28:40,206 --> 06:28:43,043
and it polymerizes
only when it's oxygenated.

8094
06:28:44,911 --> 06:28:46,680
Increasing oxygen affinity

8095
06:28:46,680 --> 06:28:50,050
to inhibit
hemoglobin S polymerization

8096
06:28:50,050 --> 06:28:52,786
has been discussed for years
even by Ernest Butler.

8097
06:28:53,620 --> 06:28:57,857
And the tremor itself is --

8098
06:28:57,857 --> 06:29:03,897
you know, it moves from
the low oxygen affinity state,

8099
06:29:03,897 --> 06:29:09,169
which is a T form to R.
You know, very rapidly.

8100
06:29:10,704 --> 06:29:13,807
And the idea then is
if you can keep the --

8101
06:29:13,807 --> 06:29:16,109
it in the oxygen-bound form,

8102
06:29:16,109 --> 06:29:20,714
then this will actually inhibit
hemoglobin as polymerization.

8103
06:29:21,614 --> 06:29:24,951
So voxelotor or oxybryta
or GBT440

8104
06:29:26,052 --> 06:29:29,789
was FDA approved
conditionally in November,

8105
06:29:29,789 --> 06:29:33,827
2019 for treating anemia
and sickle cell disease

8106
06:29:33,827 --> 06:29:35,662
in people
were 12 years and older.

8107
06:29:36,329 --> 06:29:40,967
And actually, initially,
it was started for treating.

8108
06:29:40,967 --> 06:29:43,403
You know, the endpoint was VOCs,

8109
06:29:44,070 --> 06:29:46,606
but they noticed that electro
hemoglobin increase,

8110
06:29:46,606 --> 06:29:48,475
so then it would change then

8111
06:29:48,475 --> 06:29:50,377
to an endpoint
of hemoglobin increase.

8112
06:29:51,277 --> 06:29:56,416
So it is a small molecule
that stabilizes the hemoglobin

8113
06:29:56,416 --> 06:29:58,184
in an oxygenated state

8114
06:29:58,752 --> 06:30:02,255
to reversible
binding to the amino-terminus

8115
06:30:02,255 --> 06:30:04,324
of the alpha chain
of hemoglobin.

8116
06:30:05,125 --> 06:30:09,662
And this potentially inhibits
hemoglobin S polymerization.

8117
06:30:10,430 --> 06:30:12,465
So there have been many studies
now,

8118
06:30:12,465 --> 06:30:15,702
Phase I/II, Phase IIa,
Phase III.

8119
06:30:15,702 --> 06:30:19,105
All you know, randomized double
blind placebo control

8120
06:30:19,606 --> 06:30:23,877
and then we show to
generally say, well tolerated.

8121
06:30:24,577 --> 06:30:31,017
And it -- patients show an
increase in hemoglobin with a --

8122
06:30:31,985 --> 06:30:34,621
accompanied by reduction
in hemolysis

8123
06:30:34,621 --> 06:30:36,623
and also sickling parameters,

8124
06:30:36,623 --> 06:30:40,960
which is consistent with this
effect in reducing sickling.

8125
06:30:41,728 --> 06:30:44,898
And mostly, recently,
there's a prospect study,

8126
06:30:44,898 --> 06:30:48,701
which is a post-marketing
open label observation study

8127
06:30:49,469 --> 06:30:52,605
where they followed
150 patients

8128
06:30:52,605 --> 06:30:54,707
and they've been followed
for five years

8129
06:30:54,707 --> 06:30:57,243
and they confirm
the improved hemoglobin

8130
06:30:57,243 --> 06:30:59,245
and reduced
hemolytic markers.

8131
06:31:02,282 --> 06:31:05,819
So the principle
of increasing oxygen affinity

8132
06:31:05,819 --> 06:31:08,721
to inhibit hemoglobin
S polymerization

8133
06:31:08,721 --> 06:31:10,356
is quite straightforward.

8134
06:31:10,356 --> 06:31:14,861
Because when hemoglobin
contains oxygen and offloading,

8135
06:31:14,861 --> 06:31:18,965
it reverses to the T state,
when it's de-oxygenated.

8136
06:31:18,965 --> 06:31:21,501
And that's when it polymerizes.

8137
06:31:23,103 --> 06:31:28,041
The problem though is as you
can see, that when you --

8138
06:31:29,109 --> 06:31:31,945
a drug binds to --
in the oxygenized state,

8139
06:31:33,046 --> 06:31:36,950
the binding has been released
quickly when oxygen is needed.

8140
06:31:36,950 --> 06:31:41,654
But actually in voxelotor case
it is bound very tightly.

8141
06:31:42,288 --> 06:31:44,491
And what I'd like
to show you this is.

8142
06:31:44,491 --> 06:31:51,965
Oh, sorry. How do I go back?
So here is actually --

8143
06:31:54,601 --> 06:31:57,637
well, you can see the panel
on the right

8144
06:31:57,637 --> 06:32:02,809
is a real patient that
we treated and the blue line

8145
06:32:02,809 --> 06:32:05,145
is before the patient
received treatment.

8146
06:32:05,879 --> 06:32:09,182
And the gray line is what
we actually saw

8147
06:32:09,182 --> 06:32:13,086
in the oxygen association curve.
The dotted line is expected.

8148
06:32:13,786 --> 06:32:15,388
And here we calculated

8149
06:32:15,388 --> 06:32:18,892
that there was
21 percent modification.

8150
06:32:18,892 --> 06:32:20,793
And you can see
there's a little bump

8151
06:32:20,793 --> 06:32:23,129
because that's a bit
that has moved to the left

8152
06:32:23,630 --> 06:32:25,532
when it is oxygen-bound.

8153
06:32:25,532 --> 06:32:28,134
And when it is treated
with 200 micromolar,

8154
06:32:28,134 --> 06:32:31,704
is fully saturated, it's
completely shifted to the right.

8155
06:32:33,706 --> 06:32:38,945
So as I said, there were
concerns that, you know, okay,

8156
06:32:38,945 --> 06:32:44,217
overall it is safe -- it's --
there was no reduction in VOC

8157
06:32:44,217 --> 06:32:46,386
but there was no increase
in VOC either.

8158
06:32:47,187 --> 06:32:50,456
But there was significant
increase in hemoglobin

8159
06:32:50,456 --> 06:32:52,892
with reduction
in hemolytic markers

8160
06:32:52,892 --> 06:32:55,094
and improvement
in the surrogate markers.

8161
06:32:55,762 --> 06:33:00,667
The question then is, will there
be compromised oxygen delivery

8162
06:33:00,667 --> 06:33:02,502
in the long-term?

8163
06:33:02,502 --> 06:33:06,072
And this was a concern
that was raised by Bob Hebbel

8164
06:33:06,839 --> 06:33:11,144
and Hadland
very early on in 2018.

8165
06:33:12,178 --> 06:33:16,082
And he's wrote this thing
about rising hemoglobin.

8166
06:33:16,082 --> 06:33:18,851
It is a pyrrhic victory.

8167
06:33:18,851 --> 06:33:21,287
I had look up this word because
I didn't know what it means.

8168
06:33:21,287 --> 06:33:22,555
And it's actually --

8169
06:33:22,555 --> 06:33:25,725
it means that it is one
that is not worth winning

8170
06:33:25,725 --> 06:33:27,727
because so much is a loss
to achieve it.

8171
06:33:28,361 --> 06:33:29,963
Because you know,

8172
06:33:30,496 --> 06:33:34,133
you have 30 percent
modifications of the tetramer

8173
06:33:35,268 --> 06:33:38,137
and this raised
the hemoglobin of course

8174
06:33:38,137 --> 06:33:39,906
because it used
to reduce sickling.

8175
06:33:40,540 --> 06:33:42,008
But if it's 30 percent,

8176
06:33:42,008 --> 06:33:46,279
then you have to improve
the hemoglobin 8 to 11.4

8177
06:33:46,279 --> 06:33:51,384
simply to acquire the 30 percent
of oxygen delivery capacity

8178
06:33:51,384 --> 06:33:54,988
that is now lost by binding
the drug in the first phase.

8179
06:33:55,488 --> 06:33:59,926
So that was a concern.
And then, you know, Bill --

8180
06:33:59,926 --> 06:34:02,929
I worked with Bill Eaton
and we were also worried.

8181
06:34:03,563 --> 06:34:07,900
So he carried out
in vivo modeling

8182
06:34:07,900 --> 06:34:10,303
or actually vivo
modeling red cells,

8183
06:34:10,303 --> 06:34:15,475
oxygen disassociation, sickling,
and also just didn't look

8184
06:34:15,475 --> 06:34:19,145
at how they,
you know, deliver the oxygen.

8185
06:34:19,145 --> 06:34:24,317
So what -- if showed that,
in fact, voxelotor really --

8186
06:34:24,317 --> 06:34:28,187
it monthly reduces sickling
when you do the sickling curves,

8187
06:34:28,187 --> 06:34:32,325
but it only actually
let go of his oxygen

8188
06:34:32,325 --> 06:34:36,396
at very low oxygen pressure,
like 2 percent.

8189
06:34:36,396 --> 06:34:39,265
And this is a situation
where we see in the kidneys.

8190
06:34:40,566 --> 06:34:44,470
And it was accompanied by
a very nicely written commentary

8191
06:34:44,470 --> 06:34:46,472
by Charles Quinn
and Russell Ware.

8192
06:34:47,540 --> 06:34:52,478
And they in fact wrote
this commentary

8193
06:34:52,478 --> 06:34:55,448
saying there's a very fine
delicate balance

8194
06:34:55,448 --> 06:34:58,818
between oxygen affinity of
hemoglobin and oxygen delivery.

8195
06:34:59,686 --> 06:35:04,724
So increasing oxygen affinity
should delay the polymerization,

8196
06:35:04,724 --> 06:35:08,961
but at a potential cost
of decreasing oxygen delivery.

8197
06:35:11,798 --> 06:35:14,867
And essentially,
in sickle cell disease,

8198
06:35:14,867 --> 06:35:18,805
to have and to hold may not
always be the best approach

8199
06:35:18,805 --> 06:35:20,406
[laughs].

8200
06:35:20,406 --> 06:35:22,642
And -- but we need
perspective study,

8201
06:35:22,642 --> 06:35:27,880
longitudinal studies to see
how it affects tissue perfusion

8202
06:35:27,880 --> 06:35:32,018
like NIRs and the brain MRIs.
And I believe that there are

8203
06:35:32,018 --> 06:35:34,954
current studies
undergoing for that.

8204
06:35:34,954 --> 06:35:37,390
That means more studies
reported,

8205
06:35:37,390 --> 06:35:39,525
but it's very difficult
because they're short term

8206
06:35:39,525 --> 06:35:41,994
and there's only a very
small number of patients.

8207
06:35:45,098 --> 06:35:49,535
So the next trial,
which shows a lot of promise

8208
06:35:49,535 --> 06:35:54,407
but it's not FDA-approved yet,
is activating pyruvate kinase.

8209
06:35:54,407 --> 06:35:56,242
And this is anti-sickling.

8210
06:35:56,242 --> 06:35:59,846
And the clues to this actually
have been laid long ago even.

8211
06:36:00,813 --> 06:36:04,650
First, I was just saying
to [unintelligible]

8212
06:36:04,650 --> 06:36:05,918
last night --

8213
06:36:05,918 --> 06:36:08,855
you know, we referred a patient
to sickle cell trait,

8214
06:36:08,855 --> 06:36:10,456
but she had severe
sickle cell disease.

8215
06:36:10,456 --> 06:36:11,924
The only thing
I could find in --

8216
06:36:11,924 --> 06:36:15,495
find in her was
that she was PK deficient

8217
06:36:15,495 --> 06:36:18,631
and she's inherited
one mutation in PKLR.

8218
06:36:19,232 --> 06:36:21,467
And in fact,
when I looked up the literature,

8219
06:36:22,034 --> 06:36:23,736
somebody else in France,

8220
06:36:24,437 --> 06:36:28,541
Michel Cohen-Solal reported
another case in 1998.

8221
06:36:29,675 --> 06:36:32,578
And in his patient
he could measure the DPG levels.

8222
06:36:32,578 --> 06:36:34,680
They were very high
and he showed

8223
06:36:34,680 --> 06:36:40,486
that it affected
the oxygen affinity with very --

8224
06:36:40,486 --> 06:36:42,422
and then very high 2,3-DPG.

8225
06:36:42,422 --> 06:36:46,492
2,3-DPG is a substrate
in the glycolytic pathway

8226
06:36:47,427 --> 06:36:50,530
and it is a key player
in oxygen dissociation.

8227
06:36:52,064 --> 06:36:55,101
The other thing was noted
is that Sam Charache

8228
06:36:55,101 --> 06:36:57,837
already observed
like 50 years ago,

8229
06:36:57,837 --> 06:37:01,774
more than 50 years ago,
that 2,3-DPG is very high

8230
06:37:01,774 --> 06:37:04,110
in rich cells
bringing sickle cell disease.

8231
06:37:04,677 --> 06:37:05,978
And this was confirmed

8232
06:37:05,978 --> 06:37:10,116
by a more recent publication
in Nature Medicine.

8233
06:37:11,117 --> 06:37:13,586
And finally this clever --

8234
06:37:13,586 --> 06:37:16,756
this idea
that we could perhaps reduce

8235
06:37:16,756 --> 06:37:21,260
due to DPG in sickle
erythrocytes as a modality

8236
06:37:21,260 --> 06:37:25,465
for ameliorating all the
complication sickle cell disease

8237
06:37:25,465 --> 06:37:26,666
is really not new.

8238
06:37:26,666 --> 06:37:30,670
It was actually proposed
by Poillon in Blood 1995.

8239
06:37:31,871 --> 06:37:36,476
So, it took us such a long time,

8240
06:37:36,476 --> 06:37:39,445
but because we needed
a PK activator to come along,

8241
06:37:41,080 --> 06:37:44,150
just to remind you of your --
okay, the two key factors

8242
06:37:44,150 --> 06:37:46,285
that promote
sickling sickle cell disease.

8243
06:37:46,986 --> 06:37:50,990
2,3-DPG is very high in patients
with sickle cell disease

8244
06:37:51,557 --> 06:37:56,195
and increasing 2,3-DPG
decreases oxygen affinity.

8245
06:37:57,196 --> 06:37:59,599
And as you know,
hemoglobin S polymerizes

8246
06:37:59,599 --> 06:38:01,434
only when deoxygenated

8247
06:38:01,434 --> 06:38:05,238
and it stabilizes the S
in the polymerizing form.

8248
06:38:06,672 --> 06:38:10,376
We also know the ATPs decrease
in sickle cell disease

8249
06:38:10,376 --> 06:38:14,280
and ATP is very important
in maintaining the hydration

8250
06:38:15,147 --> 06:38:20,953
and maintaining the iron and
water hemostasis in red cells.

8251
06:38:21,621 --> 06:38:24,156
And we have -- decrease ATP,

8252
06:38:24,156 --> 06:38:26,092
the increased
red cell rehydration,

8253
06:38:26,092 --> 06:38:28,961
increased hemoglobin
S polymerization,

8254
06:38:29,662 --> 06:38:32,031
and all the problems
that come with sickling.

8255
06:38:34,600 --> 06:38:36,836
This is just a summary

8256
06:38:36,836 --> 06:38:41,007
of what are the ongoing
clinical studies suffices to say

8257
06:38:41,007 --> 06:38:45,878
that we completed the first
Phase I dose escalation study

8258
06:38:45,878 --> 06:38:47,580
showing that was
generally safe.

8259
06:38:47,580 --> 06:38:49,649
And now we have
an extended study

8260
06:38:49,649 --> 06:38:52,418
and there's an open label study

8261
06:38:52,418 --> 06:38:55,788
in the Netherlands
it's undergoing.

8262
06:38:55,788 --> 06:38:59,592
So Agios has now
moved on and take --

8263
06:38:59,592 --> 06:39:02,428
started the Phase II/II

8264
06:39:02,428 --> 06:39:04,730
randomized placebo
control study.

8265
06:39:04,730 --> 06:39:08,568
Phase II completed
the enrollment and now in fact

8266
06:39:08,568 --> 06:39:11,604
Phase III,
which is multicenter,

8267
06:39:11,604 --> 06:39:15,575
I think 101 hundred centers
globally is already closed

8268
06:39:15,575 --> 06:39:17,510
because it's multicenter

8269
06:39:17,510 --> 06:39:23,215
and likely to have the main
complete enrollment in October.

8270
06:39:24,016 --> 06:39:29,989
Now there's another generation
also of PK activator,

8271
06:39:29,989 --> 06:39:33,626
which is manufactured by Agios
and it's called AG-946.

8272
06:39:33,626 --> 06:39:37,363
And this has also been shown
to be generally saved

8273
06:39:37,363 --> 06:39:41,968
and increased
ATP decreased DPG

8274
06:39:41,968 --> 06:39:48,074
in keeping with
the mechanism of the drug.

8275
06:39:49,108 --> 06:39:54,280
And another company which is --
which was former therapeutics

8276
06:39:54,280 --> 06:40:01,887
now brought over by Novo Nordisk
is etavopivat or FT-4202 then.

8277
06:40:02,455 --> 06:40:06,926
And they also published
recently Phase II/III study

8278
06:40:06,926 --> 06:40:11,263
showing that it was also safe
and led to hemoglobin increase,

8279
06:40:13,032 --> 06:40:19,538
decreased DPG, increased ATP,
all promising favorable results.

8280
06:40:20,439 --> 06:40:25,111
So this is not to say
that you know,

8281
06:40:25,111 --> 06:40:27,747
there are no concerns
about PK activators.

8282
06:40:28,814 --> 06:40:32,118
What do we know so far
on the mechanistic implications

8283
06:40:32,118 --> 06:40:33,919
for clinical benefits?

8284
06:40:33,919 --> 06:40:39,358
Metaevent and etavopivat
activates the endogenous world

8285
06:40:39,358 --> 06:40:40,893
type PK

8286
06:40:40,893 --> 06:40:44,230
and generally living
shouldn't be safe and tolerable.

8287
06:40:44,830 --> 06:40:47,867
It increases ATP,
decrease DPG levels

8288
06:40:48,467 --> 06:40:52,304
in a dose-dependent manner
in keeping with its mechanism.

8289
06:40:53,105 --> 06:40:58,144
It improved hemoglobin,
reduced the hemolytic markers,

8290
06:40:58,144 --> 06:41:00,946
increased oxygen affinity
and reduced sickling.

8291
06:41:01,847 --> 06:41:06,318
There were no increase in VOC.
In some small studies suggestion

8292
06:41:06,318 --> 06:41:08,988
that there was a decreased
VOC frequency,

8293
06:41:08,988 --> 06:41:11,957
but I think this is still
relatively short-term studies

8294
06:41:11,957 --> 06:41:13,559
and a small number of patients.

8295
06:41:14,393 --> 06:41:17,596
The same concerns that were
raised was raised for --

8296
06:41:17,596 --> 06:41:21,767
voxelotor was also raised
for these PK activators.

8297
06:41:22,601 --> 06:41:25,271
Will decrease due to DBG levels,

8298
06:41:26,405 --> 06:41:29,108
compromise oxygen delivery
in the long-term.

8299
06:41:29,942 --> 06:41:34,013
And in that same commentary
by Bob Hebbel,

8300
06:41:34,947 --> 06:41:36,315
he said while decreasing

8301
06:41:36,315 --> 06:41:40,720
DBG actually instigate
oxygen offloading but --

8302
06:41:41,253 --> 06:41:45,624
and it doesn't involve
any changes in the --

8303
06:41:45,624 --> 06:41:51,397
oxygen hemoglobin conversion

8304
06:41:52,031 --> 06:41:54,400
is not without
physiological impact.

8305
06:41:55,901 --> 06:41:58,938
And the more recent editorial
by Frank Bunn,

8306
06:41:59,538 --> 06:42:01,774
also cautions us to the --

8307
06:42:02,475 --> 06:42:05,444
you know, that we have to
evaluate properly new drugs

8308
06:42:05,444 --> 06:42:07,813
which are designed
to treat specific anemia

8309
06:42:08,447 --> 06:42:11,050
that should include
a thorough understanding

8310
06:42:11,050 --> 06:42:13,052
of the underlying
pathophysiology

8311
06:42:13,586 --> 06:42:17,056
with a focus
on enhancing oxygen transport.

8312
06:42:19,125 --> 06:42:21,627
So what is the difference

8313
06:42:21,627 --> 06:42:24,864
between these antidisciplinary
mechanisms of voxelotor

8314
06:42:24,864 --> 06:42:26,132
and PK activators?

8315
06:42:26,132 --> 06:42:28,968
I think it's very relevant
to understand that.

8316
06:42:30,236 --> 06:42:35,241
Well, enhancing PK activity --
okay, decreases 2,3-DPG

8317
06:42:35,241 --> 06:42:37,843
but it also increases ATP.

8318
06:42:38,878 --> 06:42:44,617
So decrease 2,3-DPG,
destabilize hemoglobin S fibers.

8319
06:42:44,617 --> 06:42:50,556
And this oxygen dissociation
and binding of 2,3-DPG

8320
06:42:50,556 --> 06:42:55,694
to hemoglobin S is rapid unlike
that of voxelotor

8321
06:42:55,694 --> 06:42:57,596
which actually binds
very tightly

8322
06:42:58,764 --> 06:43:02,668
until very low oxygen pressure,
like, 2 percent.

8323
06:43:03,636 --> 06:43:07,673
Another thing is that
when you decrease 2,3-DPG,

8324
06:43:07,673 --> 06:43:10,276
it is also accompanied
by increased pH

8325
06:43:10,276 --> 06:43:13,913
and a decreased MCHC
which are also anti-sickling.

8326
06:43:14,680 --> 06:43:17,783
But I think as I come
to kind of work with mitapivat,

8327
06:43:18,350 --> 06:43:20,085
it's the increase in ATP

8328
06:43:20,085 --> 06:43:24,156
which is actually
the main factor that --

8329
06:43:24,156 --> 06:43:25,758
for the clinical benefit.

8330
06:43:26,659 --> 06:43:29,028
Because ATP is essential
for RBC hydration

8331
06:43:29,028 --> 06:43:30,896
and the membrane integrity.

8332
06:43:30,896 --> 06:43:33,232
Another thing is that we in --

8333
06:43:33,232 --> 06:43:36,802
under trying to work out
the mechanism of the mitapivat,

8334
06:43:36,802 --> 06:43:38,904
we found that
it actually reduces

8335
06:43:38,904 --> 06:43:41,340
the tyrosine phosphorylation
of band 3,

8336
06:43:42,141 --> 06:43:45,945
which is a key player
in maintaining the red cell

8337
06:43:45,945 --> 06:43:48,981
membrane skeleton integrity.

8338
06:43:50,516 --> 06:43:53,285
There were other concerns
that were also raised

8339
06:43:53,285 --> 06:43:56,188
about activating PK
in sickle cell disease,

8340
06:43:56,188 --> 06:44:00,292
which was raised by none other
than Jane Little, you know,

8341
06:44:00,292 --> 06:44:03,963
[laughs] who says, you know,
PK activators could actually --

8342
06:44:03,963 --> 06:44:08,834
because by improving
the lower glycolytic flux,

8343
06:44:08,834 --> 06:44:10,836
which is the one, you know,

8344
06:44:10,836 --> 06:44:13,472
below the hexose monophosphate
shunt,

8345
06:44:14,340 --> 06:44:17,042
we could actually affect
the HMP shunt,

8346
06:44:17,042 --> 06:44:21,747
which is the primary source
for recycling NADP.

8347
06:44:21,747 --> 06:44:24,817
And this could compromise
the ability of the red cells

8348
06:44:24,817 --> 06:44:26,886
to combat oxidative stress.

8349
06:44:28,120 --> 06:44:30,522
But in fact
when you activate PK,

8350
06:44:30,522 --> 06:44:33,792
it actually increases
the whole glycolytic flux

8351
06:44:33,792 --> 06:44:35,828
and there's increased
glucose uptake.

8352
06:44:35,828 --> 06:44:39,365
So I don't think it's too much
of a concern to worry about.

8353
06:44:39,865 --> 06:44:42,334
And I mean knowing
beta-thalassemia mouse,

8354
06:44:42,902 --> 06:44:48,173
mitapivat actually increase
the GSH and GSSG ratio,

8355
06:44:48,807 --> 06:44:50,743
suggesting that this HMP shunt

8356
06:44:50,743 --> 06:44:52,478
is actually increased
by mitapivet.

8357
06:44:53,746 --> 06:44:56,448
More recently, we then also
carried out

8358
06:44:56,448 --> 06:45:00,619
a multi-omics analysis
of red cells in patients

8359
06:45:00,619 --> 06:45:03,188
with sickle cell disease
on our extended treatment.

8360
06:45:04,056 --> 06:45:06,091
And on the left here,
you show --

8361
06:45:06,091 --> 06:45:10,796
I show you the heat map
of the mitochondrial proteins.

8362
06:45:10,796 --> 06:45:12,264
And what was so remarkable

8363
06:45:12,264 --> 06:45:15,434
was that within two weeks
of taking mitapivat,

8364
06:45:16,235 --> 06:45:18,704
the mitochondrial proteins,
in fact,

8365
06:45:19,605 --> 06:45:24,443
dropped tremendously to --
in -- consistent with the --

8366
06:45:24,443 --> 06:45:26,345
with the increase in hemoglobin.

8367
06:45:27,046 --> 06:45:31,050
And this is accompanied
by a very nice commentary

8368
06:45:31,050 --> 06:45:32,851
from Andrea Glenthoj

8369
06:45:33,585 --> 06:45:37,923
and would show
that actually increasing --

8370
06:45:37,923 --> 06:45:43,295
activating PK, actually
goes beyond the ATP increase.

8371
06:45:43,295 --> 06:45:47,866
And it has a lot of multiple
beneficial tropic effects.

8372
06:45:51,637 --> 06:45:53,973
So another concern
that was raised

8373
06:45:53,973 --> 06:45:56,842
is when you withdraw hemolysis

8374
06:45:56,842 --> 06:45:59,111
and mitapivat
abruptly discontinues.

8375
06:46:00,112 --> 06:46:05,551
I think this has been reported
in the patient's PK deficiency

8376
06:46:06,118 --> 06:46:08,287
and it appears
to be patient dependent.

8377
06:46:08,287 --> 06:46:12,624
In our experience, I've had two
patients who abruptly stopped.

8378
06:46:12,624 --> 06:46:15,627
One left his medicine bag

8379
06:46:15,627 --> 06:46:18,931
which contains hydroxyurea
and mitapivat in the car

8380
06:46:18,931 --> 06:46:21,133
when he was rushing
to catch a plane.

8381
06:46:21,133 --> 06:46:22,801
He was without it for 10 days

8382
06:46:23,435 --> 06:46:25,237
and actually
we were worried sick.

8383
06:46:25,237 --> 06:46:26,839
We tried to -- in the --

8384
06:46:27,973 --> 06:46:29,942
sending by FedEx
to where he was saying,

8385
06:46:29,942 --> 06:46:31,810
but he didn't appear
to receive it.

8386
06:46:31,810 --> 06:46:33,612
When he came back
his hemoglobin dropped,

8387
06:46:33,612 --> 06:46:37,049
he was very tired and exhausted
but he didn't get a VOC.

8388
06:46:37,816 --> 06:46:40,519
So of course I think this is
patient-dependent

8389
06:46:41,186 --> 06:46:43,956
but nonetheless all patients
should be fully informed

8390
06:46:44,523 --> 06:46:48,627
of the risk and medication
adherence reinforced.

8391
06:46:50,963 --> 06:46:55,401
So I want to come back to the
band 3 tyrosine phosphorylation.

8392
06:46:55,401 --> 06:46:58,804
Because this is a clue
that has now led me

8393
06:46:58,804 --> 06:47:02,674
into the next potential
anti-sickling treatment.

8394
06:47:04,043 --> 06:47:07,980
One thing which we notice in our
dose escalations study was that,

8395
06:47:07,980 --> 06:47:10,315
why did
the hemoglobin increase,

8396
06:47:10,315 --> 06:47:14,186
which we notice persists
even after we stopped mitapivat.

8397
06:47:14,720 --> 06:47:17,122
You know, that we stopped it
for four weeks

8398
06:47:17,122 --> 06:47:19,191
and it remained
at the same level.

8399
06:47:19,191 --> 06:47:20,626
The only thing I could think of

8400
06:47:20,626 --> 06:47:23,128
is there's increased
red cell survival

8401
06:47:24,596 --> 06:47:27,699
and the key culprit
is such a band 3,

8402
06:47:28,400 --> 06:47:31,070
which is an intermembrane
protein.

8403
06:47:31,070 --> 06:47:33,238
It has two main functions.

8404
06:47:33,238 --> 06:47:38,243
It's anion exchange
protein responsible

8405
06:47:38,243 --> 06:47:42,981
for the oxygen
and carbon dioxide exchange.

8406
06:47:43,916 --> 06:47:46,885
And it's also crucial
for maintaining its integrity.

8407
06:47:47,453 --> 06:47:49,621
So what you see down here
is cartooned.

8408
06:47:51,723 --> 06:47:57,096
The band 3 is the N-terminal,
you'll get two tyrosines there.

8409
06:47:57,096 --> 06:48:02,401
They are responsible
for actually interacting

8410
06:48:02,401 --> 06:48:06,338
with the anchoring
spectrum skeletal complex

8411
06:48:06,338 --> 06:48:08,740
that maintains the integrity
of the red cells.

8412
06:48:09,775 --> 06:48:14,713
And when it is fossil-related,
it actually dissociates

8413
06:48:14,713 --> 06:48:17,516
or interferes
with the association.

8414
06:48:18,217 --> 06:48:22,154
And these two sites, actually
docking sites for S kinase.

8415
06:48:22,855 --> 06:48:26,492
What we found
was that mitapivat

8416
06:48:26,492 --> 06:48:31,497
actually reduces this band
3 tyrosine phosphorylation.

8417
06:48:31,497 --> 06:48:34,633
So what I'd like to show you
is you look at the bottom panel,

8418
06:48:34,633 --> 06:48:36,268
which is in blue

8419
06:48:36,268 --> 06:48:39,805
and that is a band
3 thyrosine phosphorylation.

8420
06:48:39,805 --> 06:48:42,841
And it shows the dose-dependent
decrease.

8421
06:48:44,209 --> 06:48:50,182
On the top you see that this
increased binding with PTP1B,

8422
06:48:50,182 --> 06:48:55,454
which is actually the protein
tyrosine phosphatase 1B,

8423
06:48:55,454 --> 06:48:58,090
which is the --
constitutes phosphatase.

8424
06:48:58,090 --> 06:49:00,659
And there's also increased
binding with anchoring.

8425
06:49:01,960 --> 06:49:05,797
And we know that it is not
true inhibiting sick

8426
06:49:06,632 --> 06:49:09,535
because of the increased PTP1B.

8427
06:49:10,402 --> 06:49:14,406
Because the phosphorylation
of band 3

8428
06:49:14,406 --> 06:49:18,076
is actually a balance
between the kinase activity

8429
06:49:18,076 --> 06:49:20,412
and it constitutes
phosphatase activity.

8430
06:49:21,246 --> 06:49:24,349
So mitapivat,
which we think through ATG,

8431
06:49:25,517 --> 06:49:27,786
increases the calcium pump
to move out.

8432
06:49:27,786 --> 06:49:29,888
So there's more PTPB
coming in.

8433
06:49:31,957 --> 06:49:35,460
Affects it by reducing the band
3 tyrosine phosphorylation

8434
06:49:35,460 --> 06:49:36,862
that way.

8435
06:49:36,862 --> 06:49:41,500
So then the idea either is
tyrosine phosphorylation

8436
06:49:41,500 --> 06:49:44,102
band 3 impacts integrity
risk of membrane.

8437
06:49:44,970 --> 06:49:49,274
So if you can reduce the
tyrosine phosphorylation band 3,

8438
06:49:49,274 --> 06:49:51,910
this has a potential
as a sickle cell disease

8439
06:49:51,910 --> 06:49:53,779
modifying therapeutic agent.

8440
06:49:56,315 --> 06:49:59,585
And I love this diagram of Annu,
plus in his review.

8441
06:50:00,219 --> 06:50:03,455
Because now I really think
sickle cell disease,

8442
06:50:03,455 --> 06:50:06,458
we should think of it
as a biomechanical disease.

8443
06:50:06,458 --> 06:50:10,128
The hemoglobin S polymers
may be the root cause,

8444
06:50:10,128 --> 06:50:12,698
but it is those
damaged red cells

8445
06:50:12,698 --> 06:50:15,100
which are the rascal
that carry all the damage.

8446
06:50:16,101 --> 06:50:19,671
So this -- on the left side here

8447
06:50:20,339 --> 06:50:22,241
is the vicious cycle
of sickling.

8448
06:50:22,941 --> 06:50:24,309
So if you can come up --

8449
06:50:24,309 --> 06:50:26,745
somehow interfere
with the shape change,

8450
06:50:27,613 --> 06:50:33,919
and I think if we can inhibit
SYK or spleen tyrosine kinase,

8451
06:50:34,453 --> 06:50:37,256
this will reduce the tyrosine
phosphorylation

8452
06:50:37,256 --> 06:50:38,890
restoring its function,

8453
06:50:38,890 --> 06:50:41,360
restores the red cell
membrane integrity,

8454
06:50:41,360 --> 06:50:42,828
will reduce fragmentation.

8455
06:50:42,828 --> 06:50:47,032
The red cell membrane, blebbing,
reduce the micro-vesicles

8456
06:50:47,032 --> 06:50:49,701
and all the other
erythrocystic DAMPs

8457
06:50:49,701 --> 06:50:51,303
which trigger the inflammation.

8458
06:50:52,771 --> 06:50:55,907
So S inhibitors
can break this vicious cycle.

8459
06:50:56,875 --> 06:51:01,513
And so with that in mind
we look at those SYK inhibitors

8460
06:51:01,513 --> 06:51:03,815
that have already been
FDA approved

8461
06:51:04,316 --> 06:51:06,318
for treating other diseases.

8462
06:51:06,985 --> 06:51:08,587
Of course there's matinib,

8463
06:51:09,655 --> 06:51:12,024
but fostamatinib
was kind of at hand.

8464
06:51:12,691 --> 06:51:14,393
So we tested fostamatinib

8465
06:51:15,093 --> 06:51:19,031
and his active biology compound
is R406.

8466
06:51:19,031 --> 06:51:24,202
So what you could see
is that Fosta actually showed

8467
06:51:24,202 --> 06:51:26,104
a dose-dependent --

8468
06:51:27,839 --> 06:51:30,676
the band 3 tyrosine
phosphorylation reduce

8469
06:51:31,209 --> 06:51:36,815
but this dose-dependent
decrease with the dose

8470
06:51:36,815 --> 06:51:40,319
and also with the same dose
increase in time.

8471
06:51:41,520 --> 06:51:42,854
And on the right here --

8472
06:51:42,854 --> 06:51:46,625
side here is the loci
to show it's deformability.

8473
06:51:47,559 --> 06:51:52,698
So on the top is --
you see the hemoglobin AA cells.

8474
06:51:52,698 --> 06:51:54,666
It didn't affect
AA cells at all

8475
06:51:54,666 --> 06:51:59,571
because AA cells hardly have any
band 3 tyrosine phosphorylation.

8476
06:51:59,571 --> 06:52:03,108
The band 3 is not so heavily
in tyrosine phosphorylation.

8477
06:52:03,775 --> 06:52:05,744
The round circles are the SS.

8478
06:52:06,244 --> 06:52:10,482
And here you could see
the blank line is a control

8479
06:52:10,982 --> 06:52:15,220
and there's a dose-dependent
increase or decrease --

8480
06:52:15,220 --> 06:52:17,356
increase in the formability,

8481
06:52:17,356 --> 06:52:20,092
which is measured
by an elongation index,

8482
06:52:20,092 --> 06:52:22,694
meaning that the cells
can be stretched better.

8483
06:52:23,762 --> 06:52:29,368
And the bottom is using R406,
the active biological compound.

8484
06:52:31,169 --> 06:52:33,538
I'm almost done. Time's up.
Okay.

8485
06:52:33,538 --> 06:52:36,408
You can hang me off
if you want [laughs].

8486
06:52:36,408 --> 06:52:39,378
So this is the sickling curves
which I did with --

8487
06:52:40,245 --> 06:52:41,847
worked with Bill Eaton.

8488
06:52:42,447 --> 06:52:44,916
And essentially
for those of you --

8489
06:52:45,550 --> 06:52:47,552
of you who not familiar
with this assay,

8490
06:52:48,120 --> 06:52:51,656
they're subjected to slow
the oxygenation and we --

8491
06:52:51,656 --> 06:52:56,461
the parameter we use is that
what is a fraction of the risk,

8492
06:52:56,461 --> 06:53:01,466
the cells that are sickle
at the -- no --

8493
06:53:01,466 --> 06:53:03,869
how long does it take
for 50 percent of the cells

8494
06:53:03,869 --> 06:53:05,170
to be sickle?

8495
06:53:05,170 --> 06:53:07,372
So the longer the time
the better.

8496
06:53:07,372 --> 06:53:12,110
And here we saw R406
and fostamatinib

8497
06:53:12,110 --> 06:53:14,813
and these curves
are very similar to mitapivat

8498
06:53:14,813 --> 06:53:17,816
when I first started the essay.

8499
06:53:18,717 --> 06:53:23,722
So just to sum up now, we --
I spoke about mitapivat,

8500
06:53:23,722 --> 06:53:27,959
voxelotor, but this --
don't forget

8501
06:53:27,959 --> 06:53:30,862
reducing intracellular
hemoglobin concentration

8502
06:53:30,862 --> 06:53:34,900
is also one key mechanism
and under development

8503
06:53:34,900 --> 06:53:37,736
is restricting iron
and erythropoiesis.

8504
06:53:39,304 --> 06:53:41,807
It's not practical, you know,

8505
06:53:41,807 --> 06:53:44,075
for patients
who reduce iron intake

8506
06:53:44,075 --> 06:53:46,578
but is a clinical trial
investigating

8507
06:53:46,578 --> 06:53:50,248
the utility
of ferroportin inhibitor,

8508
06:53:50,248 --> 06:53:51,850
which is when vamifeport.

8509
06:53:52,551 --> 06:53:56,855
But I would like to add
a sixth one to Bill's list.

8510
06:53:56,855 --> 06:54:01,493
Bill's list that maintaining
integrity of red cell membrane

8511
06:54:01,493 --> 06:54:04,463
and the skeleton integrity
is very important.

8512
06:54:05,764 --> 06:54:07,699
So I just --
I just want to acknowledge

8513
06:54:07,699 --> 06:54:11,670
and thanks on key collaborators,
and thank you very much.

8514
06:54:11,670 --> 06:54:15,640
[applause]

8515
06:54:15,640 --> 06:54:17,676
Haydar Frangoul: Okay.
We'll take some questions

8516
06:54:18,310 --> 06:54:20,745
and I have one online question
if there is none.

8517
06:54:22,881 --> 06:54:24,483
I can ask
the online question

8518
06:54:24,483 --> 06:54:26,518
while they are finding
a microphone.

8519
06:54:26,518 --> 06:54:29,688
Based on your understanding of
the mechanism of PK activation,

8520
06:54:29,688 --> 06:54:32,858
to what extent
do you think mitapivat

8521
06:54:32,858 --> 06:54:35,193
that will reduce rate
of pain crisis

8522
06:54:35,193 --> 06:54:36,795
in ongoing Phase III trial?

8523
06:54:39,197 --> 06:54:41,600
Swee Thein: Well,
in the Phase II

8524
06:54:41,600 --> 06:54:43,368
which is standard review,

8525
06:54:44,135 --> 06:54:45,937
there are already
some suggestions

8526
06:54:45,937 --> 06:54:48,707
that it reduces
pain frequency.

8527
06:54:49,307 --> 06:54:51,243
But this observation
is only for 12 weeks.

8528
06:54:51,243 --> 06:54:52,477
Haydar Frangoul: Okay.

8529
06:54:52,477 --> 06:54:54,246
Swee Thein: And for those of us

8530
06:54:54,246 --> 06:54:56,214
who looked
after sickle cell operations,

8531
06:54:56,214 --> 06:54:58,350
they do have up
and down periods.

8532
06:54:58,350 --> 06:55:00,318
We need to assess it
for a longer time.

8533
06:55:01,820 --> 06:55:03,188
I think Jane has a --

8534
06:55:03,188 --> 06:55:04,623
Female Speaker: Yeah,
I had a quick question.

8535
06:55:04,623 --> 06:55:05,924
And I have to clarify.

8536
06:55:05,924 --> 06:55:07,292
Actually, Victor
GoDuket [phonetic sp]

8537
06:55:07,292 --> 06:55:10,195
is the one who pointed out
the possible risk to me

8538
06:55:10,195 --> 06:55:11,930
in a conversation
with another person.

8539
06:55:11,930 --> 06:55:13,498
And I don't want to take --

8540
06:55:13,498 --> 06:55:14,833
I mean I thought it was
really smart of him

8541
06:55:14,833 --> 06:55:17,669
to ask that question
about the --

8542
06:55:17,669 --> 06:55:19,905
you know, whether the oxidant
stress would be more --

8543
06:55:19,905 --> 06:55:21,106
Swee Thein: Please.

8544
06:55:21,106 --> 06:55:23,642
Female Speaker: Sorry.
But I guess my question

8545
06:55:23,642 --> 06:55:25,343
is an add-on
to the one you just had,

8546
06:55:25,343 --> 06:55:29,314
which is for all of these agents
that improve hemoglobin,

8547
06:55:29,314 --> 06:55:31,249
I mean that is
the central problem,

8548
06:55:31,249 --> 06:55:35,987
but the pain from the BMT stuff
sounds like it takes months

8549
06:55:35,987 --> 06:55:39,691
to maybe a year to go away
once the red cells are fixed.

8550
06:55:40,559 --> 06:55:43,295
How, where do you think
these -- you know,

8551
06:55:43,295 --> 06:55:47,365
PK activators
and oxygen affinity

8552
06:55:47,365 --> 06:55:50,735
changer will land
in resolving pain?

8553
06:55:50,735 --> 06:55:52,337
How long do you think
that'll take

8554
06:55:52,337 --> 06:55:53,838
if you use the bone
marrow transplant

8555
06:55:53,838 --> 06:55:57,175
as kind of a model of that?
Or do you think that's relevant?

8556
06:55:57,175 --> 06:55:58,577
Swee Thein: Well, I think
there's open --

8557
06:55:58,577 --> 06:56:04,115
but you know, I'm thinking about
the patients that I look after

8558
06:56:05,350 --> 06:56:08,119
who don't meet that --
your eligibility criteria,

8559
06:56:08,119 --> 06:56:10,188
for care eligibility
or transplant

8560
06:56:11,156 --> 06:56:14,025
and will become very sensitive
in hydroxyurea.

8561
06:56:14,826 --> 06:56:19,030
And at least hydroxyurea is --
increased the hemoglobin, right?

8562
06:56:19,030 --> 06:56:21,066
Meaning they increase
the hemoglobin.

8563
06:56:22,033 --> 06:56:23,735
But they still get sickly pain.

8564
06:56:23,735 --> 06:56:26,571
But whatever it is
in hemoglobin, they can make --

8565
06:56:27,172 --> 06:56:32,577
will try to maintain the
integrity and the cell survival.

8566
06:56:32,577 --> 06:56:35,213
So at least they can have
a good quality of life.

8567
06:56:36,114 --> 06:56:40,018
And I do have patients here
who have done extremely well.

8568
06:56:41,019 --> 06:56:43,388
Female Speaker: I guess,
I'm just asking if you have a --

8569
06:56:43,388 --> 06:56:45,824
if you break a red cell
and it gets inflamed,

8570
06:56:45,824 --> 06:56:47,425
you know, you get
the white cells inflamed

8571
06:56:47,425 --> 06:56:49,294
and the endothelium inflamed

8572
06:56:49,294 --> 06:56:51,329
and then you stop
breaking the red cells.

8573
06:56:52,397 --> 06:56:55,133
How many weeks or months
do you think it'll --

8574
06:56:55,834 --> 06:56:59,037
or do you -- it'll take
before that process breaks?

8575
06:57:00,505 --> 06:57:03,074
Swee Thein: Well, I think
if you can break it early --

8576
06:57:03,074 --> 06:57:05,577
in fact I was showing
the vicious cycle

8577
06:57:05,577 --> 06:57:10,315
there that you know, the pain
that comes in an acute attack,

8578
06:57:11,049 --> 06:57:16,087
it is actually from the --
to me I think it is --

8579
06:57:16,087 --> 06:57:18,490
a lot of is actually
in the red cell.

8580
06:57:18,490 --> 06:57:20,725
When it breaks,
it releases the, hemo,

8581
06:57:20,725 --> 06:57:23,294
it releases the self
mitochondrial DNA

8582
06:57:23,294 --> 06:57:26,464
and these are
the inflammatory triggers.

8583
06:57:27,866 --> 06:57:29,901
And if you can
actually contain it

8584
06:57:30,635 --> 06:57:32,237
then we can stop it blowing up.

8585
06:57:34,039 --> 06:57:35,573
Female Speaker: Thank you.

8586
06:57:35,573 --> 06:57:37,142
Haydar Frangoul: Scott, do you
still have a question?

8587
06:57:37,142 --> 06:57:38,743
Scott Peslak: Yeah.

8588
06:57:38,743 --> 06:57:40,145
Haydar Frangoul: Time for
one more quick question.

8589
06:57:40,145 --> 06:57:41,746
I will do a last speaker.

8590
06:57:45,483 --> 06:57:47,152
Scott Peslak: Great, great talk,
Swee Thein.

8591
06:57:47,152 --> 06:57:50,088
I -- you know, to come back
to the SC conversation,

8592
06:57:50,088 --> 06:57:51,790
I was just curious about
what your thoughts are.

8593
06:57:51,790 --> 06:57:54,225
You know, the mechanism
you're saying

8594
06:57:54,225 --> 06:57:57,696
is it can improve hydration
of the cell, right?

8595
06:57:57,696 --> 06:57:59,397
And that's one of the things
that we see in SC.

8596
06:57:59,397 --> 06:58:01,299
And so I'm curious
the population that I have.

8597
06:58:01,299 --> 06:58:02,734
The biggest challenge
with our patients

8598
06:58:02,734 --> 06:58:04,669
with high hemoglobin
and SC disease

8599
06:58:04,669 --> 06:58:07,672
where we worry about
driving hemoglobin

8600
06:58:07,672 --> 06:58:09,207
too high
with drugs like mitapivat.

8601
06:58:09,207 --> 06:58:10,642
And I'm curious
what your thoughts are

8602
06:58:10,642 --> 06:58:13,645
and what the risk is for that in
those higher hemoglobin patients

8603
06:58:13,645 --> 06:58:16,147
as to whether it's offset
or if there's any risk there

8604
06:58:16,147 --> 06:58:17,749
for driving
hemoglobin too high.

8605
06:58:19,951 --> 06:58:23,154
Swee Thein: I haven't treated
any SC patients yet in my --

8606
06:58:23,154 --> 06:58:24,856
it's still under trial,
of course.

8607
06:58:25,356 --> 06:58:30,528
And if it is more ATP
that is increased,

8608
06:58:30,528 --> 06:58:32,797
that is the, I think,

8609
06:58:32,797 --> 06:58:38,436
the main benefit underlying
the mechanism of it improvement,

8610
06:58:39,204 --> 06:58:42,173
I think it would actually
should help see patients.

8611
06:58:42,173 --> 06:58:44,342
And I believe it is
the same mechanism

8612
06:58:44,342 --> 06:58:48,980
that, you know, underlies
the benefit in PKD patients

8613
06:58:48,980 --> 06:58:50,815
and in thalassemia patients.

8614
06:58:53,218 --> 06:58:54,819
Haydar Frangoul: Well,
thank you so much.

8615
06:58:58,957 --> 06:59:01,292
Our last speaker
is Dr. Edward Benz.

8616
06:59:02,026 --> 06:59:04,529
He is presenting the emergence
of genetic therapies

8617
06:59:04,529 --> 06:59:05,797
for sickle cell disease,

8618
06:59:05,797 --> 06:59:08,800
a curative treatment or
treatment with curative intent.

8619
06:59:09,801 --> 06:59:12,470
Dr. Benz is president
and CEO emeritus

8620
06:59:12,470 --> 06:59:15,874
of the Dana-Farber Cancer
Institute and Director Emeritus

8621
06:59:15,874 --> 06:59:17,142
and principal investigator

8622
06:59:17,142 --> 06:59:19,511
of the Dana-Farber
Harvard Cancer Center.

8623
06:59:37,629 --> 06:59:39,130
Can you hear us?
I think you're good to go.

8624
06:59:39,130 --> 06:59:40,331
Edward Benz: I can hear you now.

8625
06:59:40,331 --> 06:59:41,599
Haydar Frangoul: Okay, perfect.

8626
06:59:41,599 --> 06:59:42,834
Edward Benz: I just got
permission.

8627
06:59:42,834 --> 06:59:44,235
Yeah, I just got
permission to unmute

8628
06:59:44,235 --> 06:59:46,204
and I'm going to share
my screen now

8629
06:59:47,705 --> 07:00:11,830
[laughs].

8630
07:00:12,363 --> 07:00:14,432
My screen visible, everyone?

8631
07:00:21,806 --> 07:00:23,408
Are you able to hear me?

8632
07:00:25,910 --> 07:00:27,145
Haydar Frangoul: Yes,
we can hear you,

8633
07:00:27,145 --> 07:00:29,113
and we can see your slides.
You are good to go.

8634
07:00:29,113 --> 07:00:30,315
Edward Benz: Okay. Okay, good.

8635
07:00:30,315 --> 07:00:33,518
I was hearing a little bit
of feedback, like echo.

8636
07:00:34,586 --> 07:00:36,321
But I think we can go ahead.

8637
07:00:36,321 --> 07:00:38,122
So thank you very much
for the opportunity

8638
07:00:38,122 --> 07:00:39,858
to spend some time
with you today.

8639
07:00:39,858 --> 07:00:43,161
I'm very sorry I can't be
with you in person.

8640
07:00:44,062 --> 07:00:47,632
But I thought I'd like
to just speak with you

8641
07:00:47,632 --> 07:00:51,369
for a few minutes about
the Cure Sickle Cell Initiative

8642
07:00:51,369 --> 07:00:55,406
and how we're thinking
about the new developments

8643
07:00:55,406 --> 07:00:57,675
in genetic therapies
for sickle cell disease,

8644
07:00:57,675 --> 07:01:02,280
the fact that we now
have two gene-based therapies

8645
07:01:02,280 --> 07:01:05,116
that are in clinical
practice, FDA approved.

8646
07:01:06,050 --> 07:01:10,021
We're watching how those end up
being utilized

8647
07:01:10,021 --> 07:01:12,957
in clinical practice
and where we --

8648
07:01:12,957 --> 07:01:16,194
how we think about some of
the opportunities and challenges

8649
07:01:16,194 --> 07:01:17,829
these developments present.

8650
07:01:17,829 --> 07:01:21,532
And so I'm going to
very quickly summarize

8651
07:01:21,532 --> 07:01:24,035
an overview
of where things stand now,

8652
07:01:24,035 --> 07:01:27,372
recognizing that you've probably
heard some of this today

8653
07:01:27,372 --> 07:01:30,975
and you'll hear more about
these therapies tomorrow,

8654
07:01:31,943 --> 07:01:36,014
how we're assessing the positive
and negative aspects

8655
07:01:36,014 --> 07:01:37,649
of these new developments,

8656
07:01:37,649 --> 07:01:39,851
and then there --
how this NIH initiative,

8657
07:01:39,851 --> 07:01:41,953
called the
Cure Sickle Cell Initiative,

8658
07:01:41,953 --> 07:01:45,456
is trying to address
some of these things the future,

8659
07:01:45,456 --> 07:01:49,093
with the ultimate goal
being not just having effective

8660
07:01:49,093 --> 07:01:50,762
and safe therapies
available --

8661
07:01:50,762 --> 07:01:53,498
that's really
the critical first step --

8662
07:01:53,498 --> 07:01:57,936
but also making sure that
these therapies are accessible,

8663
07:01:57,936 --> 07:02:01,773
affordable by
the entire community

8664
07:02:01,773 --> 07:02:04,042
that could benefit from them.

8665
07:02:04,642 --> 07:02:08,379
So as you've heard already
and you'll, as I say,

8666
07:02:08,379 --> 07:02:11,683
hear again tomorrow
in more detail,

8667
07:02:12,216 --> 07:02:14,686
there are two therapies
available.

8668
07:02:14,686 --> 07:02:18,289
One uses gene editing technology
in a very elegant way

8669
07:02:18,823 --> 07:02:21,826
to alter a control element

8670
07:02:21,826 --> 07:02:24,696
that in the normal course
of events shut down --

8671
07:02:24,696 --> 07:02:28,566
shuts down fetal hemoglobin
production after birth.

8672
07:02:29,133 --> 07:02:31,536
And by altering
this control element

8673
07:02:31,536 --> 07:02:34,439
so that it can no longer
function, fetal hemoglobin

8674
07:02:34,439 --> 07:02:38,876
is allowed to proceed
in adult stem cells.

8675
07:02:38,876 --> 07:02:44,415
This therapy, developed
by Crispr and Vertex,

8676
07:02:44,415 --> 07:02:47,352
and based on the technology
and science

8677
07:02:47,352 --> 07:02:49,854
developed by Stu Orkin
and [unintelligible]

8678
07:02:49,854 --> 07:02:55,727
and other colleagues, as proven
in early trial results,

8679
07:02:56,327 --> 07:03:01,099
to be effective, so far,
to have safe outcomes,

8680
07:03:01,099 --> 07:03:03,868
and based on a few years
of experience,

8681
07:03:03,868 --> 07:03:06,404
to be durable so far.

8682
07:03:08,072 --> 07:03:12,076
The second therapy, developed by
a company called Bluebird Bio,

8683
07:03:12,076 --> 07:03:16,714
takes advantage of the ability
to synthesize the hemoglobin

8684
07:03:16,714 --> 07:03:21,085
that has a biochemical
blocking effect

8685
07:03:21,085 --> 07:03:22,887
on the sickling
of hemoglobin,

8686
07:03:22,887 --> 07:03:25,156
and thereby
the sickling of cells.

8687
07:03:25,156 --> 07:03:28,626
And similarly to
the other therapy,

8688
07:03:29,293 --> 07:03:33,197
it has proven
to be effective so far

8689
07:03:34,132 --> 07:03:41,339
and to be durable so far and to
have a good, safe profile.

8690
07:03:41,906 --> 07:03:46,544
So we have these therapies now,
and that's a good development,

8691
07:03:46,544 --> 07:03:48,146
but as you've also heard,

8692
07:03:48,646 --> 07:03:53,684
the delivery of these genetic
therapeutic agents,

8693
07:03:54,852 --> 07:03:56,788
it still requires
the equivalent

8694
07:03:56,788 --> 07:04:00,091
of a autologous
bone marrow transplant,

8695
07:04:00,091 --> 07:04:02,827
which carries with it
many of the same risk

8696
07:04:02,827 --> 07:04:06,297
and disadvantages,
the cumbersomeness,

8697
07:04:06,798 --> 07:04:12,804
and the expense of allogeneic
bone marrow transplantation,

8698
07:04:12,804 --> 07:04:16,307
which can be curative
in sickle cell disease,

8699
07:04:16,307 --> 07:04:19,610
as you well know,
with one exception is,

8700
07:04:19,610 --> 07:04:21,846
of course, since this is
an autologous transplant,

8701
07:04:21,846 --> 07:04:26,317
you don't have the issue
of graft-versus-host disease.

8702
07:04:27,285 --> 07:04:30,755
So when you look at where
we stand with this,

8703
07:04:30,755 --> 07:04:34,125
we have [unintelligible]
that are -- look very promising.

8704
07:04:34,125 --> 07:04:35,660
Are they curative
therapies?

8705
07:04:35,660 --> 07:04:38,663
Well, in our minds
in the Cure Sickle Cell

8706
07:04:38,663 --> 07:04:41,766
Initiative -- and I think
in the minds of many people,

8707
07:04:41,766 --> 07:04:44,135
certainly in the minds
of patients

8708
07:04:44,135 --> 07:04:48,940
and their support systems,
their loved ones, caregivers --

8709
07:04:49,974 --> 07:04:52,610
curative therapy
is truly only curative

8710
07:04:52,610 --> 07:04:56,047
if it can be accessed
by everyone who requires

8711
07:04:56,814 --> 07:05:01,352
or would benefit greatly
from a cure.

8712
07:05:01,352 --> 07:05:03,654
And in that sense,
we have a ways to go,

8713
07:05:04,388 --> 07:05:06,657
because this is
an ex vivo method.

8714
07:05:07,325 --> 07:05:11,329
Right now, although you've heard
some promising early research,

8715
07:05:12,463 --> 07:05:14,599
the only way that
we have clinically

8716
07:05:15,299 --> 07:05:18,369
to target hematopoietic
stem cells

8717
07:05:18,369 --> 07:05:21,372
that have to be modified
for these therapies to work

8718
07:05:22,039 --> 07:05:26,110
is by removing them
from the patient's bone marrow,

8719
07:05:26,110 --> 07:05:28,012
mobilizing them
into the peripheral blood

8720
07:05:28,012 --> 07:05:29,614
and extracting them,

8721
07:05:30,148 --> 07:05:35,620
and then modifying them outside
the body and reinfusing them

8722
07:05:35,620 --> 07:05:39,357
after we ablate
the patient's own bone marrow

8723
07:05:39,357 --> 07:05:43,594
with what is currently
genotoxic therapy with busulfan.

8724
07:05:44,128 --> 07:05:46,898
And the research
you've already heard about,

8725
07:05:46,898 --> 07:05:49,934
and I think will hear more
about tomorrow, I think,

8726
07:05:49,934 --> 07:05:55,139
is a critically important step
in improving the accessibility

8727
07:05:55,907 --> 07:06:00,745
of a clinical and safety
perspective of these therapies.

8728
07:06:00,745 --> 07:06:02,780
But there's still
a lot of work to be done

8729
07:06:02,780 --> 07:06:07,118
to get these things
into clinical practice.

8730
07:06:07,685 --> 07:06:10,454
There's also the complexity
of the therapy itself.

8731
07:06:10,454 --> 07:06:12,123
There's only a few centers.

8732
07:06:12,924 --> 07:06:16,861
I think Vertex has authorized
a number of centers

8733
07:06:16,861 --> 07:06:18,496
around the country
and overseas,

8734
07:06:18,496 --> 07:06:21,866
and Bluebird, just a few
that are actually able

8735
07:06:21,866 --> 07:06:25,503
to support
the complexity of this therapy.

8736
07:06:25,503 --> 07:06:26,938
And it -- basically, centers

8737
07:06:26,938 --> 07:06:32,143
that have a high-functioning
bone marrow transplant facility

8738
07:06:32,143 --> 07:06:35,179
and also a high-functioning
cell manipulation facility,

8739
07:06:35,179 --> 07:06:38,115
since these cells have to be
handled very much

8740
07:06:38,115 --> 07:06:40,651
like you would handle
a therapeutic drug,

8741
07:06:40,651 --> 07:06:42,420
with all of the safeguards

8742
07:06:43,788 --> 07:06:48,192
and the additional issue
of protection from infection.

8743
07:06:48,192 --> 07:06:50,728
Requires
a long-term hospitalization.

8744
07:06:50,728 --> 07:06:54,232
The cost is two to three million
dollars, and the way --

8745
07:06:54,232 --> 07:06:57,868
that is basically just
for the therapy itself

8746
07:06:58,402 --> 07:07:00,137
and does not always include --

8747
07:07:00,805 --> 07:07:03,507
in the way these
pricing negotiations go,

8748
07:07:03,507 --> 07:07:06,544
does not always include
the additional ancillary

8749
07:07:06,544 --> 07:07:09,647
costs of hospital support
and pre-hospital

8750
07:07:09,647 --> 07:07:14,418
and post-hospital support
for the patients going through

8751
07:07:14,418 --> 07:07:17,722
the actual
transplantation process.

8752
07:07:17,722 --> 07:07:21,592
Insurance coverage
across the country for --

8753
07:07:21,592 --> 07:07:25,196
at the present time has been
what I would call spotty.

8754
07:07:25,930 --> 07:07:31,335
Some private insurers
have agreed to cover close

8755
07:07:31,335 --> 07:07:33,037
to all of the costs of this.

8756
07:07:33,037 --> 07:07:37,241
Others cost -- cover the cost
of the actual therapeutic agent

8757
07:07:37,975 --> 07:07:41,545
but rely on whatever
other systems for coverage

8758
07:07:41,545 --> 07:07:45,883
they have in place for the other
parts of the treatment.

8759
07:07:45,883 --> 07:07:48,786
Governmental coverage,
since most of our patients

8760
07:07:48,786 --> 07:07:54,358
are not old enough for Medicare
or necessarily qualify

8761
07:07:54,358 --> 07:07:58,796
under Disability Act policies,
is through Medicaid.

8762
07:07:58,796 --> 07:08:00,698
And Medicaid
goes state by state,

8763
07:08:00,698 --> 07:08:04,335
and the states have been
very variable so far

8764
07:08:04,335 --> 07:08:06,804
in how they're approaching
coverage for this.

8765
07:08:06,804 --> 07:08:11,676
So expense is a major obstacle
to generalized accessibility.

8766
07:08:11,676 --> 07:08:13,778
That's one of the things
that we're going to take --

8767
07:08:13,778 --> 07:08:16,113
try to take advantage of
with the Cure Sickle Cell

8768
07:08:16,113 --> 07:08:17,815
Initiative to meet.

8769
07:08:18,783 --> 07:08:20,217
We've talked about durability.

8770
07:08:20,217 --> 07:08:25,456
We've had a few years of
observation of these therapies,

8771
07:08:25,456 --> 07:08:28,693
and the longest-treated
patients, up to half a decade.

8772
07:08:30,394 --> 07:08:33,698
But we don't know, for therapy
that's intended and designed --

8773
07:08:33,698 --> 07:08:37,068
and actually, the price
is being justified

8774
07:08:37,068 --> 07:08:41,005
by the fact that these are
one-time lifetime therapies --

8775
07:08:41,005 --> 07:08:46,143
we do not yet know if
these therapies will indeed last

8776
07:08:46,143 --> 07:08:48,546
for a lifetime,
if those modified cells

8777
07:08:49,246 --> 07:08:53,684
will function in the way
we have modified them to do

8778
07:08:54,385 --> 07:08:56,420
for the rest
of the patients' lives.

8779
07:08:57,021 --> 07:08:58,622
And then critically,

8780
07:08:59,190 --> 07:09:01,992
these therapies can stop
the disease process.

8781
07:09:01,992 --> 07:09:04,862
In other words, the advantage
of these therapies

8782
07:09:04,862 --> 07:09:09,133
is that they address the root
cause of sickle cell disease,

8783
07:09:09,133 --> 07:09:13,738
which is the accumulation
of this altered hemoglobin S.

8784
07:09:13,738 --> 07:09:17,208
But will they arrest or correct
preexisting end organ damage

8785
07:09:17,208 --> 07:09:20,511
or the psychosocial damage
or the pain

8786
07:09:20,511 --> 07:09:24,815
diathesis that has developed
over time in these patients?

8787
07:09:25,616 --> 07:09:28,719
These are going to require
long-term follow-up observation

8788
07:09:28,719 --> 07:09:33,657
and care, and our view
is that just as cancer survivors

8789
07:09:33,657 --> 07:09:37,128
now have access cancer
survivorship network

8790
07:09:37,128 --> 07:09:41,298
of resources at these
highly sophisticated centers,

8791
07:09:41,298 --> 07:09:43,134
that sickle cell patients
should be able

8792
07:09:43,134 --> 07:09:48,072
to access those
very same resources where for --

8793
07:09:48,072 --> 07:09:51,542
the focus is on what are
the clinical needs

8794
07:09:51,542 --> 07:09:55,846
of a survivor
of a critical illness.

8795
07:09:55,846 --> 07:10:00,217
So if these therapies
do meet the curative intent

8796
07:10:00,217 --> 07:10:01,819
and become curative therapies,

8797
07:10:02,453 --> 07:10:05,623
what about the long-term
leftover consequences,

8798
07:10:05,623 --> 07:10:08,392
and what system
will we have in place

8799
07:10:09,160 --> 07:10:10,795
to provide that kind of care?

8800
07:10:11,362 --> 07:10:14,632
Then I think there are open
questions, who should get it?

8801
07:10:14,632 --> 07:10:17,802
In other words,
when is sickle cell disease

8802
07:10:18,369 --> 07:10:23,240
sufficiently severe
to justify the risks

8803
07:10:23,240 --> 07:10:28,112
and the burdens we just
discussed, and at what age?

8804
07:10:29,213 --> 07:10:33,317
There's arguments now
that the younger at which

8805
07:10:33,317 --> 07:10:35,152
we can treat
these patients safely,

8806
07:10:35,820 --> 07:10:38,522
the better, before all these
end organ damage

8807
07:10:38,522 --> 07:10:41,826
or psychosocial changes
or mental health changes

8808
07:10:41,826 --> 07:10:44,995
and neuropsychiatric
changes develop.

8809
07:10:45,963 --> 07:10:49,800
All that said, and all these
things that represent

8810
07:10:49,800 --> 07:10:54,505
the less than completely
perfect therapies

8811
07:10:54,505 --> 07:10:57,441
that these are,
these are a major step forward.

8812
07:10:57,441 --> 07:10:59,510
They're good news
for our patients,

8813
07:10:59,510 --> 07:11:03,047
and what we need are better ways
to deliver therapeutic payloads

8814
07:11:03,047 --> 07:11:06,784
simply, durably,
and efficiently.

8815
07:11:06,784 --> 07:11:09,453
And that's where the NIH

8816
07:11:09,453 --> 07:11:12,122
decided to develop
the Cure Sickle Cell Initiative,

8817
07:11:12,122 --> 07:11:14,091
and I serve
as executive director

8818
07:11:14,091 --> 07:11:15,693
and I'm presenting today

8819
07:11:15,693 --> 07:11:18,395
to represent the work
of many colleagues

8820
07:11:18,395 --> 07:11:21,465
and many patients
and community participants

8821
07:11:21,465 --> 07:11:24,635
in what we're
trying to achieve.

8822
07:11:24,635 --> 07:11:28,539
So our vision is to accelerate
the development

8823
07:11:28,539 --> 07:11:31,342
of genetic therapies
at curing sickle cell disease

8824
07:11:31,342 --> 07:11:34,778
and using a patient-focused
research environment

8825
07:11:34,778 --> 07:11:37,348
where we engage
patient community

8826
07:11:37,348 --> 07:11:41,151
and the caregiving community
in our deliberations,

8827
07:11:41,151 --> 07:11:44,121
in our interactions
with different stakeholders

8828
07:11:44,121 --> 07:11:46,957
who are all trying
to advance these therapies,

8829
07:11:46,957 --> 07:11:49,426
and really, now,
with a much stronger purpose,

8830
07:11:49,426 --> 07:11:52,463
not so much on
the development of therapies,

8831
07:11:52,463 --> 07:11:54,765
although we still
will keep an eye on that

8832
07:11:54,765 --> 07:11:56,834
and support things
where we can,

8833
07:11:56,834 --> 07:12:00,271
but really on increasing
this issue of accessibility,

8834
07:12:00,271 --> 07:12:04,008
safety, removing financial,
administrative barriers,

8835
07:12:04,008 --> 07:12:05,409
and so forth.

8836
07:12:05,409 --> 07:12:07,611
And to do that,
we're going to take advantage

8837
07:12:07,611 --> 07:12:12,650
of some of the structural
elements of this initiative

8838
07:12:13,350 --> 07:12:21,025
to engage partners
who are usually not so easy

8839
07:12:21,592 --> 07:12:26,196
to involve
using the NIH's usual rubrics

8840
07:12:26,196 --> 07:12:30,367
and rules for where
you can deploy funds,

8841
07:12:30,367 --> 07:12:35,606
where you can seek applications
for grant support, and so forth.

8842
07:12:35,606 --> 07:12:39,577
The whole idea is just focus
on developing

8843
07:12:39,577 --> 07:12:41,278
these strategies
for better care.

8844
07:12:42,246 --> 07:12:45,716
So we've focused up until now
on gene

8845
07:12:45,716 --> 07:12:48,485
editing and gene
transfer methodologies.

8846
07:12:48,485 --> 07:12:55,759
We are opening our window
to look at small molecules

8847
07:12:55,759 --> 07:12:59,697
as the beginning efforts
that at least some drugs

8848
07:12:59,697 --> 07:13:02,366
that have been reported on

8849
07:13:02,366 --> 07:13:04,568
in the recent American Society
of Hematology meetings,

8850
07:13:04,568 --> 07:13:08,472
for example,
that might be small molecules

8851
07:13:08,472 --> 07:13:11,175
that address things like
fetal hemoglobin switching

8852
07:13:11,976 --> 07:13:13,777
and could achieve
something very similar

8853
07:13:13,777 --> 07:13:15,512
to what the gene
therapies could.

8854
07:13:15,512 --> 07:13:19,450
So we will look at small
molecule strategies as well.

8855
07:13:20,651 --> 07:13:23,687
The idea of the initiative
is to bring together

8856
07:13:23,687 --> 07:13:26,423
all these different
stakeholders, as I mentioned,

8857
07:13:26,423 --> 07:13:29,693
with a particular emphasis
on involving patient families,

8858
07:13:30,227 --> 07:13:31,762
people who take care
of sickle cell

8859
07:13:31,762 --> 07:13:36,567
rather as caregivers or as
medical professional providers.

8860
07:13:37,434 --> 07:13:39,770
And the thing
this makes it different

8861
07:13:39,770 --> 07:13:41,639
from most of what NIH does

8862
07:13:41,639 --> 07:13:47,478
is this thing we call the
other transactional authority.

8863
07:13:48,078 --> 07:13:51,048
And what -- there are
a few federal agencies --

8864
07:13:51,048 --> 07:13:52,650
and the NIH is one of them --

8865
07:13:53,350 --> 07:13:56,487
out of the many, many hundreds
of federal agencies

8866
07:13:56,487 --> 07:14:02,426
that have the ability
to use this OTA methodology.

8867
07:14:02,426 --> 07:14:05,596
And without getting into
the complexities of it,

8868
07:14:05,596 --> 07:14:11,101
it's a way that the government
permits an agency to fund things

8869
07:14:11,101 --> 07:14:16,840
not necessarily strictly falling
within their charter,

8870
07:14:17,975 --> 07:14:21,045
their sort of legislated
window of things.

8871
07:14:21,045 --> 07:14:24,314
For the NIH, that's usually
hypothesis-driven grants,

8872
07:14:25,215 --> 07:14:29,586
certain scientific development
contracts, clinical trials,

8873
07:14:31,722 --> 07:14:34,925
forming databases,
and some other things like that,

8874
07:14:34,925 --> 07:14:40,297
but not to do things
that involve funding

8875
07:14:40,297 --> 07:14:42,833
that's shared
with a private company,

8876
07:14:42,833 --> 07:14:45,736
for example,
with other government agencies.

8877
07:14:45,736 --> 07:14:48,572
There's some things
that are possible within NIH,

8878
07:14:48,572 --> 07:14:50,207
but they're quite restricted.

8879
07:14:51,008 --> 07:14:53,444
They're -- and they're
a bit cumbersome to do.

8880
07:14:53,444 --> 07:14:56,647
So the other
transactional authority

8881
07:14:56,647 --> 07:14:58,482
gives us much more flexibility

8882
07:14:58,482 --> 07:15:01,985
to fund things that are
scientifically much higher risk

8883
07:15:02,853 --> 07:15:07,291
and may require partnerships
that are not possible

8884
07:15:07,291 --> 07:15:10,728
within our usual grants
and contracts mechanisms

8885
07:15:10,728 --> 07:15:13,731
to share information
more flexibly.

8886
07:15:14,531 --> 07:15:16,767
Those of you who have worked
within the government know

8887
07:15:16,767 --> 07:15:19,670
that it's sometimes
remarkably hard to share

8888
07:15:19,670 --> 07:15:21,438
information, communicate,

8889
07:15:21,438 --> 07:15:25,242
and interact in real-time
basis flexibly with other --

8890
07:15:25,242 --> 07:15:28,145
even with other
government agencies

8891
07:15:28,679 --> 07:15:32,349
or professional societies
and foundations and so forth.

8892
07:15:32,883 --> 07:15:35,486
And it allows us to look
at multiple shots on both.

8893
07:15:35,486 --> 07:15:39,790
Originality is not necessarily
a limiting factor here.

8894
07:15:39,790 --> 07:15:43,761
If somebody has developed
a better way to do something,

8895
07:15:44,394 --> 07:15:48,532
even if it's utilizing
already established --

8896
07:15:48,532 --> 07:15:51,168
or scientific understanding.

8897
07:15:51,168 --> 07:15:54,438
And it allows us
also to change direction

8898
07:15:54,438 --> 07:15:57,174
instead of waiting
until a grant expires,

8899
07:15:57,174 --> 07:16:00,878
that we can do things
differently right away.

8900
07:16:01,578 --> 07:16:06,316
So to do that, we've tried to
build a comprehensive approach

8901
07:16:06,316 --> 07:16:08,619
that would take advantage
of these advantages

8902
07:16:08,619 --> 07:16:11,655
of the other transaction
authority to fill gaps

8903
07:16:11,655 --> 07:16:14,858
that are not covered by other
traditional funding strategies

8904
07:16:14,858 --> 07:16:19,129
and to fund research both within
academia and the private sector

8905
07:16:19,129 --> 07:16:21,465
to identify the most
promising therapies.

8906
07:16:21,465 --> 07:16:26,203
And I should point out that this
is not in any way a replacement

8907
07:16:27,271 --> 07:16:33,777
or a cannibalization of the
current NIH-funded activities.

8908
07:16:33,777 --> 07:16:35,512
This is mostly done
through the Heart, Lung,

8909
07:16:35,512 --> 07:16:38,148
and Blood Institute,
the initiative,

8910
07:16:38,148 --> 07:16:40,517
that all of the things
that are in place

8911
07:16:40,517 --> 07:16:43,287
and all of the opportunities
to receive support

8912
07:16:43,287 --> 07:16:47,357
through traditional NIH
mechanisms are still there.

8913
07:16:47,357 --> 07:16:49,626
We are not touching that.

8914
07:16:49,626 --> 07:16:51,595
We're not taking any funds
away from that.

8915
07:16:51,595 --> 07:16:56,834
These are supplemental funds to
be creating more flexible ways

8916
07:16:56,834 --> 07:17:00,504
to advance toward the goal
of curative therapy,

8917
07:17:01,004 --> 07:17:03,574
and as I mentioned,
would allow us to partner

8918
07:17:03,574 --> 07:17:05,943
in different ways
to engage the community

8919
07:17:05,943 --> 07:17:09,479
in different real-time ways
that are done --

8920
07:17:09,479 --> 07:17:14,084
at least not done easily
within the NIH constraints.

8921
07:17:14,084 --> 07:17:17,521
So here's a few of our
initiative activities.

8922
07:17:18,021 --> 07:17:22,526
We're -- we have created
a patient engagement process

8923
07:17:22,526 --> 07:17:25,262
that is working well through
our community in [phonetic sp]

8924
07:17:25,262 --> 07:17:30,767
panel, and membership
in all of our working committees

8925
07:17:30,767 --> 07:17:32,469
and in our executive
committee itself,

8926
07:17:32,469 --> 07:17:35,405
the patient and provider
representatives.

8927
07:17:36,273 --> 07:17:38,709
We are working
on consolidating

8928
07:17:38,709 --> 07:17:41,845
and making more
user-friendly databases

8929
07:17:41,845 --> 07:17:45,415
and data management,
natural history studies,

8930
07:17:46,216 --> 07:17:50,554
and comparative controls
and any other things you need

8931
07:17:50,554 --> 07:17:53,323
to move things through
the clinical trials process,

8932
07:17:54,191 --> 07:17:56,560
biomanufacturing
and standardization

8933
07:17:57,527 --> 07:17:59,796
to make the development
and manipulation

8934
07:17:59,796 --> 07:18:02,165
these cells more efficient.

8935
07:18:02,165 --> 07:18:04,368
We're supporting
clinical trials,

8936
07:18:04,368 --> 07:18:06,536
supporting outcomes research.

8937
07:18:06,536 --> 07:18:08,772
We're supporting a cost
effectiveness [unintelligible]

8938
07:18:08,772 --> 07:18:10,374
through the University
of Washington,

8939
07:18:10,374 --> 07:18:14,411
so just to give you a flavor
of some of the activities

8940
07:18:14,411 --> 07:18:15,879
that we're going through.

8941
07:18:15,879 --> 07:18:18,448
And this is just gives you
a quick peek

8942
07:18:18,448 --> 07:18:23,987
at some of the partners
that we've developed over time.

8943
07:18:23,987 --> 07:18:26,556
You see, these are things
not possible

8944
07:18:26,556 --> 07:18:31,028
within the usual NIH rubrics
and rules --

8945
07:18:31,929 --> 07:18:33,630
working with
professional societies,

8946
07:18:33,630 --> 07:18:36,500
working with the Stem Cell
Institute in California,

8947
07:18:36,500 --> 07:18:41,204
working with CMS on coverage
and payment issues, et cetera.

8948
07:18:43,340 --> 07:18:46,777
So I want to finish by just
telling you what we're hearing,

8949
07:18:46,777 --> 07:18:49,579
and I don't claim
that we are hearing everything

8950
07:18:50,981 --> 07:18:53,850
or that I can cover everything
that we're hearing in this talk.

8951
07:18:53,850 --> 07:18:57,220
But from engaging with
the patient community

8952
07:18:57,220 --> 07:18:59,056
and through focus groups,

8953
07:18:59,056 --> 07:19:02,025
through the work in real time
on our subcommittee, these --

8954
07:19:02,793 --> 07:19:04,594
through the development
of materials

8955
07:19:04,594 --> 07:19:07,998
and our online interactions
with the community,

8956
07:19:09,633 --> 07:19:13,804
and also with traveling around
[inaudible]

8957
07:19:13,804 --> 07:19:17,607
of the country --
this map is out of date.

8958
07:19:17,607 --> 07:19:19,476
We've gone to
the west coast now,

8959
07:19:19,476 --> 07:19:21,511
not quite as confined
to the east coast.

8960
07:19:21,511 --> 07:19:25,882
This started during the pandemic
when overnight travel

8961
07:19:25,882 --> 07:19:28,118
was a bit more
of a challenge,

8962
07:19:28,118 --> 07:19:30,921
but we've been pretty much
around the country now,

8963
07:19:30,921 --> 07:19:34,458
engaging groups and hearing
what patients want to say.

8964
07:19:34,458 --> 07:19:36,827
And this is what we're hearing.

8965
07:19:37,527 --> 07:19:39,863
Most families and patients
are quite excited

8966
07:19:39,863 --> 07:19:41,665
to have these treatments
available,

8967
07:19:41,665 --> 07:19:43,266
want to get them if they can,

8968
07:19:44,167 --> 07:19:47,537
want to know if they can be able
to afford it or access it.

8969
07:19:47,537 --> 07:19:49,940
We've talked about
some of the challenges there.

8970
07:19:50,874 --> 07:19:55,112
Very strong emphasis on if I go
through all this, will it last?

8971
07:19:55,645 --> 07:20:00,217
Will I be trading the dangers
of sickle cell disease

8972
07:20:00,217 --> 07:20:02,552
with the --
for the dangers of leukemia?

8973
07:20:02,552 --> 07:20:04,454
Now we know that the chances

8974
07:20:04,454 --> 07:20:08,692
of developing myelodysplastic
syndrome or leukemia

8975
07:20:08,692 --> 07:20:14,097
are quite small in the trials
that we've seen so far,

8976
07:20:14,097 --> 07:20:17,501
but they are known to --
by the patient community,

8977
07:20:17,501 --> 07:20:20,537
and of course, because of
the nature of the disease

8978
07:20:20,537 --> 07:20:24,641
that -- being discussed,
that is a concern for patients.

8979
07:20:24,641 --> 07:20:28,745
So -- and we've heard
really great communication

8980
07:20:28,745 --> 07:20:31,681
with patients
about the pros and cons,

8981
07:20:32,382 --> 07:20:34,918
the risks and benefits
of going forward

8982
07:20:34,918 --> 07:20:37,788
with these therapies
is important.

8983
07:20:37,788 --> 07:20:40,057
And I'll finish up by telling
you some other efforts

8984
07:20:40,057 --> 07:20:41,358
we're trying to make to see

8985
07:20:41,358 --> 07:20:45,162
if we could make the prediction
of those risks more accurate.

8986
07:20:45,162 --> 07:20:47,597
Will a cure affect my identity?

8987
07:20:47,597 --> 07:20:51,101
I'm always reminded
when I've seen a patient

8988
07:20:51,101 --> 07:20:53,336
with any disease
who has suddenly --

8989
07:20:53,336 --> 07:20:55,138
been living with that disease
for a long time

8990
07:20:55,138 --> 07:20:57,274
and suddenly is no longer
dealing with it

8991
07:20:57,274 --> 07:20:59,376
that there is a bit
of an identity crisis.

8992
07:20:59,376 --> 07:21:03,513
This is well known
in the community of deaf persons

8993
07:21:04,047 --> 07:21:06,016
who have their hearing restored,

8994
07:21:06,016 --> 07:21:08,085
because they have lived
in a community.

8995
07:21:08,085 --> 07:21:10,187
They've lived within
a support system

8996
07:21:10,187 --> 07:21:15,325
that find the boundary
conditions of their life

8997
07:21:15,325 --> 07:21:17,694
are around
their chronic illness,

8998
07:21:17,694 --> 07:21:19,596
and if that is suddenly altered,

8999
07:21:19,596 --> 07:21:25,001
it requires a really significant
reset of one's sense of self

9000
07:21:25,635 --> 07:21:27,771
and one's aspirations
and ambitions

9001
07:21:27,771 --> 07:21:31,108
and capabilities to achieve
those might be.

9002
07:21:31,108 --> 07:21:34,177
So, what's life without
the disease going to be like?

9003
07:21:34,177 --> 07:21:39,049
We've heard a lot of that
in talking to our patients.

9004
07:21:39,049 --> 07:21:40,517
And then of course,
the blood picture,

9005
07:21:40,517 --> 07:21:41,985
they can expect to be better,

9006
07:21:41,985 --> 07:21:44,554
but what about all the other
chronic problems,

9007
07:21:44,554 --> 07:21:46,723
the end organ damage, the pain,

9008
07:21:47,757 --> 07:21:51,962
any of the preexisting
neuropsychiatric damage

9009
07:21:51,962 --> 07:21:53,830
that this disease
has done to them?

9010
07:21:53,830 --> 07:21:56,233
And those are still
open questions.

9011
07:21:56,233 --> 07:21:58,034
And then will I get
the follow up I need?

9012
07:21:58,034 --> 07:21:59,803
Will I lose my care team?

9013
07:21:59,803 --> 07:22:02,372
Those patients fortunate enough
to be getting their care

9014
07:22:02,372 --> 07:22:06,309
at good sickle cell center
or sickle cell clinic

9015
07:22:06,309 --> 07:22:09,346
worry that they won't
be able to get that.

9016
07:22:09,346 --> 07:22:12,716
Now that turns out
not to be true,

9017
07:22:12,716 --> 07:22:15,318
that people are not going
to abandon these patients,

9018
07:22:15,318 --> 07:22:19,589
but it is a legitimate question
for people to raise.

9019
07:22:19,589 --> 07:22:24,427
And that's where I come back the
notion of a survivorship program

9020
07:22:24,427 --> 07:22:26,796
that we're trying
to help develop

9021
07:22:27,497 --> 07:22:30,500
for our patients
who undergo these therapies.

9022
07:22:30,500 --> 07:22:33,103
So here's what we're --
finally, what we're funding.

9023
07:22:33,603 --> 07:22:39,276
We're open to input from people
who are trying to develop

9024
07:22:40,143 --> 07:22:44,214
simpler, safer,
cheaper delivery.

9025
07:22:44,214 --> 07:22:46,950
We've heard some presentations
in that today,

9026
07:22:48,185 --> 07:22:52,155
maybe some more tomorrow.
Small molecule drugs,

9027
07:22:52,155 --> 07:22:55,125
which clearly would be
simpler to deliver.

9028
07:22:55,125 --> 07:22:59,329
So we are having a workshop
coming up in October.

9029
07:22:59,329 --> 07:23:01,932
We're going to be hearing from
people working in this field

9030
07:23:01,932 --> 07:23:05,268
and seeing if there's ways that
we can use our funding mechanism

9031
07:23:05,902 --> 07:23:11,508
to accelerate the advances
in this early-stage research.

9032
07:23:11,508 --> 07:23:15,745
Also, similarly, for non-
genotoxic conditioning regimens,

9033
07:23:15,745 --> 07:23:17,647
because in the meantime,

9034
07:23:18,315 --> 07:23:21,384
while all these other therapies
may be developing,

9035
07:23:21,384 --> 07:23:24,454
patients will be getting bone
marrow transplants.

9036
07:23:24,454 --> 07:23:26,856
They will be getting
ex vivo gene therapy.

9037
07:23:27,724 --> 07:23:29,693
And we -- as soon as possible,

9038
07:23:29,693 --> 07:23:32,128
we'd like to see if we can
accelerate the development

9039
07:23:32,128 --> 07:23:34,898
of some of the genotoxic
conditioning regimens

9040
07:23:34,898 --> 07:23:38,235
that you just heard about
a couple of presentations ago.

9041
07:23:38,735 --> 07:23:40,904
We are developing
this long-term follow up.

9042
07:23:40,904 --> 07:23:44,874
This includes survivorship
studies, mostly to collect data,

9043
07:23:45,675 --> 07:23:48,545
but also to develop programs

9044
07:23:49,179 --> 07:23:53,483
that we might incent people
to develop at these care sites

9045
07:23:53,984 --> 07:23:57,654
to manage long-term
survivorship issues.

9046
07:23:57,654 --> 07:24:00,257
We have developed
national cell bank resource,

9047
07:24:00,257 --> 07:24:04,628
so you can get bio samples
for doing some of these studies

9048
07:24:04,628 --> 07:24:09,165
on targeting hematopoietic
stem cells, for example.

9049
07:24:09,165 --> 07:24:10,500
And we're funding a study

9050
07:24:10,500 --> 07:24:13,003
on so-called
clonal hematopoiesis

9051
07:24:13,003 --> 07:24:15,238
of indeterminate potential.

9052
07:24:15,238 --> 07:24:19,309
This is a factor that we all
have in our bone marrows,

9053
07:24:19,309 --> 07:24:22,579
and as we age,
we develop mutations

9054
07:24:22,579 --> 07:24:24,114
in our bone marrow stem cells

9055
07:24:24,114 --> 07:24:29,252
that increase the risk
of a number of illnesses,

9056
07:24:29,252 --> 07:24:30,887
including the likelihood
of hemalogic

9057
07:24:30,887 --> 07:24:32,088
[phonetic sp]

9058
07:24:32,088 --> 07:24:36,226
malignancy, to see if there
are ways to identify

9059
07:24:36,226 --> 07:24:41,331
those individuals
whose so-called CHIP situation

9060
07:24:41,331 --> 07:24:45,068
may be more protective
or more high risk

9061
07:24:45,769 --> 07:24:47,871
in undergoing
these therapies.

9062
07:24:47,871 --> 07:24:51,374
And then we are using
cost effectiveness analysis,

9063
07:24:51,374 --> 07:24:55,478
our ongoing study of that,
to make the case with CMS

9064
07:24:56,680 --> 07:24:59,716
and with private insurers
that they should be covering

9065
07:24:59,716 --> 07:25:03,286
this care more comprehensively
and more completely

9066
07:25:04,154 --> 07:25:06,156
and with a better
reimbursement system

9067
07:25:06,156 --> 07:25:08,258
that doesn't put
the provider institutions

9068
07:25:08,258 --> 07:25:11,995
at risk of having to collect
the reimbursement

9069
07:25:11,995 --> 07:25:18,234
after paying $3 million per
patient to start the therapy.

9070
07:25:18,835 --> 07:25:23,573
So that's where we stand,
and we're here today

9071
07:25:23,573 --> 07:25:26,343
mostly to make you aware
of what we're trying to do

9072
07:25:27,377 --> 07:25:28,945
and welcoming your input.

9073
07:25:29,612 --> 07:25:32,382
Just use our website,
the Cure Sickle Cell

9074
07:25:33,450 --> 07:25:35,819
Initiative --
or the curesickle.org,

9075
07:25:35,819 --> 07:25:39,556
and we will keep you apprised
of where what you're working on

9076
07:25:39,556 --> 07:25:41,925
and what we're working
on my align

9077
07:25:41,925 --> 07:25:46,830
and how we may engage together
in making this situation

9078
07:25:46,830 --> 07:25:51,101
even more promising for
our patients and their families.

9079
07:25:51,634 --> 07:25:52,936
So thank you very much.

9080
07:25:52,936 --> 07:25:54,971
I'll be happy
to take any questions.

9081
07:25:55,505 --> 07:25:58,575
[applause]

9082
07:25:58,575 --> 07:26:00,310
Haydar Frangoul: Thank you,
Dr. Benz.

9083
07:26:00,310 --> 07:26:02,579
I will entertain few questions
from the audience,

9084
07:26:02,579 --> 07:26:05,014
but I want to --
can I add something to your list

9085
07:26:05,014 --> 07:26:09,152
that you put in there myself
on your cure sickle cell?

9086
07:26:10,320 --> 07:26:14,758
Can I add a big plug in
for fertility preservation

9087
07:26:14,758 --> 07:26:16,359
for individuals
with sickle cell disease

9088
07:26:16,359 --> 07:26:17,727
going through gene
therapies and --

9089
07:26:17,727 --> 07:26:18,995
Edward Benz: Yes.

9090
07:26:18,995 --> 07:26:20,196
Haydar Frangoul: --
curative therapies?

9091
07:26:20,196 --> 07:26:22,399
Edward Benz: I'm so happy --
thank you. Thank you.

9092
07:26:22,399 --> 07:26:27,237
I'm so happy you said that.
I meant to tell you

9093
07:26:27,237 --> 07:26:30,507
that we are working very hard
on that from two perspectives.

9094
07:26:30,507 --> 07:26:33,676
You know, one is clearly
better technology

9095
07:26:33,676 --> 07:26:37,180
that would make fertility loss
less of a risk,

9096
07:26:37,180 --> 07:26:41,351
but the most real-time thing
is we're working with CMS

9097
07:26:41,351 --> 07:26:43,686
to make sure patients are
covered for those treatments.

9098
07:26:43,686 --> 07:26:47,524
And that's another reason
to try to take advantage

9099
07:26:47,524 --> 07:26:49,192
of the survivorship system

9100
07:26:49,192 --> 07:26:50,794
that's in place
for cancer patients.

9101
07:26:50,794 --> 07:26:54,697
Cancer patients in many states,
not all,

9102
07:26:54,697 --> 07:26:56,533
but a fairly large
number of states

9103
07:26:56,533 --> 07:26:59,102
can get coverage
for fertility preservation

9104
07:26:59,102 --> 07:27:00,603
for their chemotherapy,

9105
07:27:00,603 --> 07:27:02,472
but we're not able to get it
for our patients

9106
07:27:02,472 --> 07:27:04,474
undergoing bone
marrow transplant

9107
07:27:04,474 --> 07:27:06,676
or therapies for sickle cell.

9108
07:27:06,676 --> 07:27:09,012
In some states you can,
but very few.

9109
07:27:09,012 --> 07:27:12,649
So we are working with CMS
and private insurers on that.

9110
07:27:12,649 --> 07:27:13,917
Haydar Frangoul: Yeah.

9111
07:27:13,917 --> 07:27:16,419
I personally don't think
a patient should be choosing

9112
07:27:16,419 --> 07:27:18,254
between a cure
and having a family.

9113
07:27:18,254 --> 07:27:20,657
They should have both.
But that's my point.

9114
07:27:20,657 --> 07:27:21,991
Edward Benz: I completely agree.

9115
07:27:21,991 --> 07:27:25,295
Haydar Frangoul: Any questions
from -- okay.

9116
07:27:25,295 --> 07:27:26,763
Jane Little: This is
Jane Little from UNC.

9117
07:27:26,763 --> 07:27:29,432
Thanks, Dr. Benz.
I had a question.

9118
07:27:29,432 --> 07:27:31,401
In hemophilia
and cystic fibrosis,

9119
07:27:31,401 --> 07:27:33,503
the long-term follow up
is embedded

9120
07:27:34,037 --> 07:27:36,940
within their own
longitudinal registries.

9121
07:27:36,940 --> 07:27:39,843
And I -- and that seems like
a good model for sickle cell.

9122
07:27:39,843 --> 07:27:41,978
I wonder what your thoughts
are about that.

9123
07:27:42,879 --> 07:27:45,615
Edward Benz: Yes.
I agree, and that's one aspect

9124
07:27:45,615 --> 07:27:47,417
of long-term follow up
that I think,

9125
07:27:48,218 --> 07:27:53,923
although we're working
with the usual NIH HLBI efforts,

9126
07:27:53,923 --> 07:27:55,758
is that they are doing that.

9127
07:27:55,758 --> 07:27:57,927
They put together
under the rubric

9128
07:27:57,927 --> 07:28:02,532
of a natural history study
that they're --

9129
07:28:04,033 --> 07:28:06,069
what they're trying to do
is coordinate the databases

9130
07:28:06,069 --> 07:28:09,806
so that the long-term
follow up data can be there.

9131
07:28:09,806 --> 07:28:11,908
We're trying to work now
on a program

9132
07:28:11,908 --> 07:28:16,412
to make sure that people who are
not necessarily participating

9133
07:28:16,412 --> 07:28:18,581
or contributing
to those databases,

9134
07:28:18,581 --> 07:28:20,617
if these patients
undergo these therapies,

9135
07:28:20,617 --> 07:28:25,788
that they will be supported
to put the necessary data,

9136
07:28:25,788 --> 07:28:27,657
you know,
to use the right templates,

9137
07:28:27,657 --> 07:28:31,094
to enter the right data fields
in and standardize

9138
07:28:31,094 --> 07:28:32,795
those as best we can.

9139
07:28:33,863 --> 07:28:36,466
The survivorship model
I talked about focused

9140
07:28:36,466 --> 07:28:40,236
more on the actual delivery
of the care

9141
07:28:40,870 --> 07:28:42,605
as well as gathering
the data.

9142
07:28:44,040 --> 07:28:46,409
Jane Little: Think the
consistent templates is --

9143
07:28:46,409 --> 07:28:48,845
that's a really
important feature. Thanks.

9144
07:28:49,579 --> 07:28:50,914
Edward Benz: Yes, I agree.

9145
07:28:50,914 --> 07:28:52,749
Haydar Frangoul: Well, I would
like to thank all the speakers.

9146
07:28:52,749 --> 07:28:54,717
If there are no questions,

9147
07:28:54,717 --> 07:28:57,587
I think there are some closing
remarks going to be given.

9148
07:28:58,721 --> 07:29:01,224
Monika will be giving
the closing. Thank you.

9149
07:29:03,960 --> 07:29:06,963
Monika Asnani: Closing remarks
are really short [laughs].

9150
07:29:06,963 --> 07:29:09,198
We have had a long,
wonderful days.

9151
07:29:09,198 --> 07:29:11,668
Long, so we are tired,
but I must say,

9152
07:29:11,668 --> 07:29:14,771
I'm sure you all agree,
we've had a fabulous day.

9153
07:29:15,305 --> 07:29:17,507
And it's going to be even better
tomorrow, if at all possible.

9154
07:29:17,507 --> 07:29:18,675
[applause]

9155
07:29:18,675 --> 07:29:22,679
So thank you to all the speakers
for working so hard, Dr. Benz,

9156
07:29:23,713 --> 07:29:27,317
and all the chairs.
Thank you to the admin team.

9157
07:29:27,317 --> 07:29:29,052
[unintelligible]
because really --

9158
07:29:29,052 --> 07:29:30,320
[applause]

9159
07:29:30,320 --> 07:29:32,589
-- working across two
different regions.

9160
07:29:33,122 --> 07:29:36,693
We'll do a bigger thanks
tomorrow, but thanks, all.

9161
07:29:36,693 --> 07:29:39,896
Go and have a good evening.
Enjoy. Rest.

9162
07:29:39,896 --> 07:29:41,631
Go to the pool,
those of you who want to.

9163
07:29:41,631 --> 07:29:43,533
Go get some food,
and get some rest.

9164
07:29:43,533 --> 07:29:45,435
See you all tomorrow
bright and early.

9165
07:29:48,004 --> 07:29:49,539
Sorry? Oh.

9166
07:29:49,539 --> 07:29:54,077
The speakers are to meet --
where, Nancy? At the lobby?

9167
07:29:54,077 --> 07:29:55,278
Female Speaker: Yeah.

9168
07:29:55,278 --> 07:29:56,980
Moninka Asnani: By 6:30 p.m.

9169
07:29:56,980 --> 07:29:59,215
Those of you
who have a speakers' dinner --

9170
07:29:59,983 --> 07:30:04,120
6:15 p.m., sorry.
You meet downstairs at 6:15 p.m.

9171
07:30:04,120 --> 07:30:07,156
so you can reach
your venue on time.

9172
07:30:07,857 --> 07:30:11,761
And see you all tomorrow.
We begin sharp at 8:30 a.m.