Good morning.
Welcome from the National Library of Medicine,
the National Institutes of Health.
My name is Jeff Reznick.
I'm chief of the History of Medicine Division.
On behalf of the Office of the Interim Director, I have the great privilege
of offering these welcome words and moderating today's proceedings.
I also have the great privilege of thanking our co-sponsor,
the Friends of the National Library of Medicine, the lab.
The friends are indeed wonderful friends of our institution,
and we are very grateful to each
and every one of them, and especially to their board of directors.
I also wish to thank the outstanding media
and communications team here at the NLM and at the NIH
for their time and their talent dedicated to this very special program.
And of course, my colleagues and I thank you for joining us today,
all of you from near and far for the annual NLM Lindbergh Lecture,
which is part of our scientific symposium, Science Society
and the legacy of Donald A.B. Lindbergh, M.D..
One housekeeping note.
You will see a live feedback button under your video stream.
If you have a question during the course of our proceedings
or comment, please use this button and send it to us.
Now let's begin.
I'm going to turn things over to my colleague
Gerry Sheehan, who will get us started
with welcome remarks on this very exciting day.
Gerry, over to you.
Thank you very much, Jeff, and hello and welcome to everyone.
It's great to see so many people joining us for today's event.
My name is Jerry Sheehan.
I'm the deputy director
of the National Library of Medicine for Policy and External Affairs.
And I am honored and privileged to welcome you to the fourth
annual Lindbergh King Lecture and Scientific Symposium.
This lecture series was established in 2015
as a forum to bring together insights on the current state
and the future of bioinformatics and pathobiology,
and convey them to a broad, scientific and public audience.
Today's Lindbergh King lecture honors the legacy
and contributions of the namesakes of the lecture series.
Former NLM director Donald A.B.
Lindbergh and former NLM Deputy Director for Research and Education, Dr.
Donald West King.
I am sure that they, like many of us, would have wished
that we could gather for today's event in person.
But knowing Dr.
Lindbergh as the leader who first brought computers into the library
and arguably brought libraries into the world of computing,
it seems altogether fitting and proper to to honor the legacy of doctors
Lindbergh and King.
Even in this virtual forum today.
And thank you for doing so.
I am pleased that we have a diverse lineup of speakers
and as well so many of you in the audience who are here with us today
to help us honor the legacies of the great doctors, Lindbergh and King.
And I thank you all for joining what is sure to be
an enjoyable, exciting and interesting day.
It's now my pleasure to introduce the first
among today's distinguished list of speakers, Dr.
Heidi Rehm.
Dr. Reem is the chief genomics officer at the Center for Genomic Medicine
and the Department of Medicine at Massachusetts General Hospital.
She also has the distinction of serving as the chair of the NLM Board of Regents.
Welcome, Dr. Tim.
I'll turn over to you.
Thank you, Jerry.
It's it's my distinct pleasure to welcome everybody to today's scientific
symposium on Science, Society and the legacy of Donald Lindbergh.
We just have an outstanding lineup of sessions and speakers,
and I'm sure you are all going to enjoy the day, the whole day.
But before we kick things off, a few of us will make some introductory remarks.
And I just wanted to share some personal perspectives
as we think about the legacy of Donald Lindbergh.
He directed the NLM for over 30 years and made a major
and lasting impact on biomedical science in that period.
He extensively engaged his Board of Regents,
and I'm very delighted to be on that board and chairing it this year.
And he also engaged many outside constituent groups to ensure
that NLM would provide important and useful services to the community.
Today, we take
for granted that we have a pub bed and other basic tools at our disposal.
But it was actually Dr.
Lindbergh who established many of these tools and made sure
importantly that they were
freely available to the community and also near and dear to my heart.
Is his work in establishing and CBI,
the National Center for Biotechnology Information, which has provided data
storage access, annotation resources to the genomics community for many years.
And I did want to share one example of the important role of Dr.
Lindbergh's work and his establishment of NCB
, and that is the launch of the Clean Bar database.
And any of you who know me
know just how near and dear that database is to my heart.
So a little history.
About ten years ago, a group of clinical laboratory geneticists,
including myself, were working to develop a database
to share classified variants that we were generating in our labs.
And we really recognized we needed to all come together.
Unfortunately, our first endeavor to create such a database
and get buy in to contribute to it was actually unsuccessful.
But then we discovered that
NCBA was thinking about creating a variant database of this sort.
And so we abandoned our first approach and partnered with MPI to provide
input to the development of clean air with the NCI team.
So it would fit our needs and we worked to support it
as the location for all of the clinical labs to share their data.
This time the effort took off and now, as many of you
know, clean air has become the go to place for not only U.S.
labs, but actually the world to share classified variants.
And I actually credit the reputation of NCI
as a trusted resource for long term sustainability of key genomic resources,
as well as the ability to remain free from commercial bias
as the key to the success of clean air
when we were not able to do that through another endeavor before that.
And in fact, the voluntary willingness of commercial labs and other submitters
to willingly share their data in clean air for no strings attached access
by the broader community really is a testament
to the reputation of TBI and what has been built.
And in clear indeed clean air has become a core resource
for both clinical and research applications of human genetics
and has contributed to the accurate diagnosis of millions
of patients receiving genetic testing every year.
It's just a wonderful success story.
I'm sure that my colleagues and other speakers today
will include their own stories of the many lasting impacts that Dr.
Lindbergh has had on our field.
But with that, I will turn it over to our next speaker.
Thank you very much for joining us today.
Thank you for those remarks, Dr.
Reem, and for getting us started today.
Jeff Resnick, I'm going to turn back to you for the rest of the program.
Thank you, Jerry.
And thanks indeed, Dr. Reed.
Now, it's my pleasure to introduce Glen Campbell,
who for more than a decade has served masterfully
as chair of the Friends of the National Library of Medicine.
And most recently, Glen was managing director
for the British Medical Journal, the BMJ in the Americas.
And prior to his time with the BMJ, he was executive vice president
for global medical research at Elsevier, where he had publishing responsibility
for more than 420 journals in the health sciences,
more than half of which were published in partnership with society.
Welcome to you, Glen, and thanks for joining us today.
Thanks, Jeff.
And thank you, Dr.
Ream and Gerry, for the kind words of introduction.
And on behalf of Dr.
Redman, Barbara Redmond, our President and the Board of Directors of the Friends
of the National Library of Medicine and all friends
of the National Library of Medicine.
It's my pleasure and an honor to welcome you as well
to the 2000 2022 Lindbergh
King Lecture and the scientific symposium, the legacy of Dr.
Donald AB Lindbergh.
The friends are pleased to co-sponsor the annual Lindbergh King Lecture
once again
with our friends and distinguished colleagues
of the American Medical Informatics Association.
And we're particularly enthusiastic to hear from Dr.
Cohan, whose passion for using data and new tools
to accelerate the clinical application of biomedical research was shared by Dr.
Lindbergh and Dr. King.
We are pleased as well with to join with our colleagues
at the National Library of Medicine to sponsor today's scientific
symposium on Dr.
King's legacy. Dr. King.
I'm sorry, Dr. Lindbergh's legacy. Dr.
Lindbergh was a great communicator,
a candid and caring person in his exchanges with every individual
and active listener and a lifelong learner with a wry sense of humor.
His impact on the public health is for one who was a
highly valued
one, who highly valued measurable outcomes
immeasurable.
And incorporating this year's King Lindbergh lecture
into the scientific symposium on the legacy of Dr.
Lindbergh provides the opportunity to hear from those whose leadership
today in biomedical informatics, leadership, training and library
research builds on his roundtable groundbreaking work.
Over the 30 plus years that Dr.
Lindbergh was director of the NLM, he transformed the library from the
passive to active player in delivering improved health care outcomes.
Today, his successor, the cheerfully dynamic Dr.
Brennan and her leadership team, recognize Dr.
Lindbergh's legacy as the library evolves,
as a center of biomedical discovery and data powered health.
The friends are very grateful and appreciative of Jeff Resnick
and everyone at the library and AMIA, as well
as today's speakers and preventers, for their tremendous efforts to ensure
that today's event will be an engaging and thrilling one.
Thank you.
Thank you, Glenn.
And thanks again to you
and everyone on the board of the Friends of the National Library of Medicine.
Now it's my distinct pleasure to introduce Dr.
Gretchen Purcell, Jackson, President and chair of the Board of Directors
for the American Medical Informatics Association, AMIA,
also vice president and scientific medical officer at Intuitive Surgical
and Associate Professor of Surgery, Pediatrics and biomedical informatics
at the Vanderbilt University Medical Center.
Dr. Jackson is an internationally recognized biomedical musician,
an accomplished clinical surgeon with over 30 years of contributions
to informatics, research and surgical science.
In her current position at Intuitive Surgical. Dr.
Jackson is a health care technology executive focused on scientific strategy,
and she practices pediatric surgery at Vanderbilt Vanderbilt Children's Hospital.
Welcome to you.
Dr. Jackson, thanks for joining us today.
Over to you.
Thank you so much.
I am so grateful for this opportunity to speak at this National Library
of Medicine Symposium on honoring the legacy of Dr.
Donald A.B. Lindbergh.
I am not only the board chair for the American Medical
Informatics Association, but also a great cold former recipient
of a National Library of Medicine pre doctoral fellowship
which supported my Biomedical Informatics Training and Ph.D.
research at Stanford University.
I'm excuse me.
I am honored today
to speak on behalf of the American Medical Informatics Association, or AMIA,
which I am sure, as most of you know, is the leading scientific health
informatics professional organization in the United States.
And it's really an important part of Dr.
Lindbergh's legacy.
AMIA now represents over 5000 biomedical and health informatics professionals
who work across academics, industry, health systems, nonprofits and government.
And AMIA now hosts three well-attended scientific meetings each year,
including the Informatics Summit, focused on bio and clinical research
informatics, the clinical informatics meeting,
and, of course, the annual symposium in November.
Some of the most important of Dr.
Lindbergh's contributions to informatics were his organization in the development
of scientific activities and professional societies,
which supported the growth and evolution of our field.
And I will speak briefly about these contributions to conferences
in professional organizations to review this piece of history.
So as many of you know, in 1977, Dr.
Lindbergh presented at the first symposium
on computer applications in Medical Care, or Shamsi,
which then was a local meeting in the Washington, D.C.
area of engineers, scientists and clinicians who met to discuss scientific
but clinically relevant papers at the intersection of computers and medicine.
The first Proceedings of Shamsi was published by Triple E, and it featured
67 papers, and the meeting hosted 250
attendees with no concurrent sessions.
Dr. Lindbergh attended this meeting regularly as interest increased,
and he was recruited to the first board of directors as the first member
from outside of Washington when Shamsi was legally incorporated
and began to attract a national and international audience.
This meeting rapidly evolved with the introduction of posters,
parallel tracks, panels, tutorial system demonstrations
in the student paper competition within five years.
In 1987, the chairman, Daniel Harris,
noted that just reading the scientific work was not enough.
You had to be there for the informal conversations in the hallways
that often led to significant collaborations and innovations.
And this was certainly my experience when I attended my first Shamsi meeting
as a student in 1991, and at that time, Dr.
Lindbergh was the president of AMIA.
AMIA, as we know it today,
came from the convergence of professional societies and conferences, and Dr.
Lindbergh played a key role in each component.
At the 1982 CMC meeting, Maurice Cohen
hosted a small meeting of informatics leaders, including Dr.
Lindbergh, to propose the creation
of the American College of Medical Informatics, or Acmi.
Acmi elected its first class of fellows
in 1985 and subsequently incorporated.
Academy Fellowship remains one of the highest honors one can receive
for substantive and sustained contributions to the field of informatics.
Now, in the early 1980s, the American Association
for Medical Systems and Informatics, MCI, emerged
as the leading professional organization for computer systems in medical care
as a result of the merger of the Society for Computer Medicine
and the Society for Advanced Medical Systems.
M.S. held its own scientific meeting in the spring,
usually on the West Coast, so as not to conflict with Shamsi.
And Dr.
Lindbergh served on the board of AMC in the mid 1980s.
By the late 1980s, the overlap of the interest
and the leaderships across AMC, Shamsi and Acmi was substantial,
and their three boards agreed that a merger to create
a single organization would be in the best interest of all.
Dr. Lindbergh was selected as the founding president of this
new organization, the American Medical Informatics Association,
which was legally incorporated in 1993.
Acme became a self-governing entity as part of Aimia, and AMC was dissolved.
The annual meeting of AMIA was called Shamsi for the first five years
after this merger and in 1987 became
the AMIA annual symposium . Now, Dr.
Lindbergh's contributions to AMIA during his tenure as president
included the creation of the Acme Retreats,
Amy as committees,
the professional specialty groups, which are now known as working groups,
and the executive executive director role as well as direction to the Publications
Committee to create a new journal which eventually became the Journal
of the American Medical Informatics Association.
Our flagship journal, This Wonderful History of AMIA and Dr.
Lindbergh Center roles are described in this publication, shown on this slide
authored by Jan Van Den, Marian, Bob and Ted Short live.
Dr. Lindbergh led the
evolution of medical informatics societies and meetings
not only in the United States, but also globally.
The International Medical Informatics Association image
was created in 1967, and Dr.
Lindbergh served as the U.S.
representative to MDA for the American Federation of Information
Processing Societies Ethics in the 1980s.
Dr. Lindbergh also served as the chair of the Organizing Committee for India's
1986 international meeting med info, which took place in Washington, D.C.
when metadata when med info returned to
the United States in 2004 in San Francisco.
Dr. Lindbergh personally arranged for the Nelms Fogarty International Center
to provide support for attendees from Third World countries.
As the current board chair for AMIA, which has been my professional home
for three decades, and the scientific program chair
for the 2022 AMIA Annual Symposium in Washington, DC .
I am so grateful for the contributions of Dr.
Lindbergh to informatics societies and scientific forums,
which are only a teeny tiny piece of Dr.
Lindbergh's legacy.
I thank you all again for the opportunity to provide
opening remarks for this symposium, and I hope you will enjoy the day
as much as I will.
Thank you, Dr.
Jackson.
A fantastic history lesson and much to learn there and to explore.
Thank you very, very much.
It's now my pleasure to introduce Shannon Jones, who is director
of libraries for the Medical University of South Carolina Libraries in Charleston.
She is also director for Region Two of the network
of the National Library of Medicine, a longtime volunteer
for the Medical Library Association, or MLA.
Shannon currently serves as president of the association in 2018.
Shannon co-founded the MLA reads Virtual Book Discussion Club
to provide a forum where participants can learn, discuss
and process the implications of a variety of topics on their work
as information professionals and in their personal lives.
She is also coeditor of Diversity and Inclusion
in Libraries A Call to Action and Strategies for Success,
as well as the forthcoming volume entitled Cultural Humility in Libraries.
Shannon Jones, welcome and thank you for joining us today
to represent the Medical Library Association.
Thank you and good morning, everyone.
I'm bringing you greetings from Charleston, South Carolina.
I am both humbled and honored to welcome each of you to the Limburg Lecture
and Scientific Symposium on behalf of the nearly 3000 health
information professionals that comprise the Medical Library Association,
or, as we affectionately call it, my life as an association.
The Marley community believes
that quality information is essential for improved health.
We aspire to be the association of the most visible,
valued and trusted health information experts.
And most importantly, we strive to enhance the quality
of health care, education and research in our environments.
Since 2003 to honor Dr.
Lindbergh's legacy, Emily awards the Limburg Research Fellowship
annually aimed at expanding the research knowledge base,
linking the information services provided by librarians to improve
health care and advances in biomedical research.
For 30 years, Dr.
Lemberg supported the Mission and Goals of Medical Association
and was a strong champion and advocate for health science librarians
throughout the nation and the world.
I'm one of those librarians that remembers leadership, service and advocacy.
So 20 years ago today,
I arrived in Bethesda and I am for my first day
as a member of the 2002 cohort of alum, Associate Fellows and alum.
I launched my career as a health sciences librarian.
I met some wonderful professionals.
I had the opportunity to post, to participate in meaningful projects,
and I was exposed to tools and good information
that have made the journey to standard for you to date.
And amazing, right?
In that Lindbergh's 24 or his three posts on Emily website
and you all go and check it out that the Lindbergh mentions
that he learned two things at Amherst College.
One was a love for biology, and the other was the thrill of discovery.
I share in this love.
I too love discovering new things, new information
and new concepts, which is what I'm most excited about today.
I hope today's program and the speakers who will come before you.
Excuse me, evoke the same sentiment for you.
I also hope that you discover
new information that would enhance your professional journey.
A sincere thanks to the program
organizers for the invitation to join today.
And to each of you, I say welcome to the program.
Thank you very much.
And it's a privilege
to have you here and appreciate your your welcome remarks tremendously.
It is a day of discovery, and you could not have framed that more beautifully.
Thank you.
It's now my pleasure to introduce Kent Smith,
who will introduce our keynote speaker for today.
Ken Smith was deputy director of the National Library
Medicine from 1980 to 24, and previous to
that was also director of administration at the NLM for eight years.
As deputy, he was responsible for program development
and evaluation policy for formulation
and coordination of library activities.
Notably, he served as president of the National Federation
of Advanced Information Services and also
of the International Committee on Scientific and Technical Information.
Ken Smith, welcome and thank you for joining us today.
Over to you.
Oh, thanks.
Thank you for the introduction, Jeff.
You know, it's a real pleasure to be part of this year's
lecture and symposium that has been established,
as you know, in the honor of Don Limbaugh and Don King.
You know, Dr.
King was also a key member of the Anaheim family.
He was a noted scholar, a great pathologist.
A lover of medical history
and really a wonderful, kind and most generous colleague.
And of course, it is particular
pleasure to be here to celebrate
the legacy of Donald AB Lombard.
A man I had the honor and privilege of working beside
during his first 20 years as the director.
He was a brilliant man, a born leader.
And one who brought with him a clear vision as to how to provide better
and wider access to biomedical information,
not only for the benefit of the nation's health professionals,
but also the general public.
His leadership and motivating
skills created a team that brought success
and realized his vision that he stated
early on when he arrived.
And so it seems totally appropriate,
as we remember, Don, that our keynote speaker today
is also a very successful visionary in medical science.
Dr. Isaac on is the main Marian B Nelson,
professor of biomedical informatics at the Harvard Medical School.
Chair of its Department of Biomedical Informatics
and is the Associate Professor of medicine at the Brigham and Women's Hospital.
Now, some of you may also be interested knowing that he previously
had been the director of the Conway Medical Library at Harvard's.
Now I'm going to tell you right up front
that I will not try to cover all of his honors and accomplishments
contained in his 66 three page
CV, but just highlight a few of them.
He began his formal
education at the International School of Geneva, Switzerland.
He received, with honors his Bachelor of Science
in Biology from Brown University and his M.D.
m.p.h., Ph.D.
from Boston University, including some doctoral work,
I might add, with the clinical decision making group at the M.I.T.
lab for computer science.
Now he has published well over 500 papers in the medical literature
and is the author of the widely used book entitled
Microarrays for an Integrated OMICS.
He's a distinguished member
of the Institute for Medicine.
The American Society for Clinical Investigation
and of course, the American College of Medicine for Max.
And that explains effort have been driven by his vision
of what biomedical researchers could do
to find new cures and deliver the best patient care.
As Dr.
William Tierney put it, and I quote from him, Dr.
Cohan has revolutionized many areas of biomedical informatics
and has changed the way we practice patient care delivery.
That statement actually was made when Dr.
Cohan was awarded the prestigious Maurice Colin Award of Excellence
from the American College of Medicine Medical.
With this recognition, one could say
perhaps that he completed the AMIA trifecta, having also received
the Williams Stead Award for Thought Leadership in Informatics
and the Donna Lab Limburg Award for Innovation
in Informatics.
Highlight among many of his accomplishments
is his initiative in translating genomic research
into the clinical environment.
Its name sort of brings back sort of that essence of the George
Lucas Star Wars, as is call it to be true
or informatic for integrating biology and the bedside
I to be to provides sort of a technical solution to informatics to exchange
across institutions and is now a standard component
of hundreds of analytic projects throughout the world.
In Dr.
Paddy Brennan's musings from the mezzanine, I learned the Dr.
Guy has a little motto called
Make our data work for US.
Data.
Our speaker said, and I quote from him,
It means that let's not just use it for the real reason.
Most of it is accumulated at present, which is in order
to satisfy administrate or reimbursement process.
But instead, let's use it to improve health care.
So, folks, I'm pleased to present to you from way up there
in God's country our distinguished keynote speaker, Dr.
Isaac Culhane.
Thank you, Dr.
Smith.
What a remarkable introduction.
It's in the can.
I will now use that recording for all future introductions.
Thank you. That was. That was wonderful.
I am so honored to be the keynote speaker
today and truly
gratified because Dr.
Lindbergh, Don, was an oversize figure in my entire career.
And I'm going to say it now just because I'm what I'm going to otherwise forget.
I do want to thank everybody who has participated in this program
from Jeff Resnick, all the public participants, the Friends
of National Library of Medicine, the National Library of Medicine,
or colleagues for making this moment possible.
It is indeed
frustrating and sad that we have not been able to come together for two years.
And this is, I think, a first step towards
remediating some of that disturbing
trend. So.
I would like to say, first of all, that Dr.
Lindbergh really embodied what those of us who trained in pediatrics
like to say is the most important part of teaching, which is modeling.
He modeled for us what leaders looked like
in bio embodied medicine, period.
As Dr.
Smith said, he was a born leader.
I don't know if he was a born leader, but by the time I met him,
he was without a doubt a leader and a statesman.
And he showed how to be a leader,
not just in the modern sense
of visionary and brashness, but also in dealing
with a complex ecosystem which at times can be frustrating as I'll touch upon.
He really
drove innovations that have transformed
so many parts of medicine, but it was not all smooth sailing
and less of a statesman , less of a leader may have gone frustrated
and said things that might have actually impeded further progress. But
at least in his public face, he was always calm,
steadfast and optimistic.
He would say wry jokes
about some of the obstacles,
but he would not actually let
civility falter at any point.
And in that respect, I think.
We are all reminded what leadership
looks like and.
Although I feel often I
use this moment to remind myself of what that looks like. So
without further
ado, let's start the keynote.
So in thinking about what I wanted
to say about Van Limburg.
There was a recurrent theme
in all my discussions with him.
And frankly, and much of the programs that he funded,
including some of my own grants,
and that was in making information
and knowledge get distributed out
not only to doctors.
But to patients.
And although I will not make up this point later on.
Now Dr.
Reem pointed out about clinic bar.
Important resource for both
clinical labs and.
Doctors throughout the world. But.
Dr. Lindbergh also sponsored the genetic home reference,
which was a genetic reference
specifically targeted towards.
Consumers understanding two things.
Okay.
Unfortunately, most doctors don't know enough genetics to be able to explain it
well to patients and sick of all that patients deserve
and can profit personally
in their health by understanding genetics better.
And so I decided that the theme I would
address,
although there could have been many other themes and many other dimensions of Dr.
Lindbergh's accomplishments, the theme I would ask for was.
Who will be the primary purveyor
of authoritative medical knowledge to the US patient.
And I will outline.
Dr. Bloomberg's contributions,
which are very impressive.
I don't think I am taking anything away to say that Dr.
Lindbergh's work.
Has been very successful, but it's not completed.
And you'd want us to continue.
Pushing forward in the direction he started us.
And I will articulate some of the gap and then I will close
by putting down my bets,
my chips, as to where
the future lies.
And I would I have the conceit.
Which I think is based somewhat on facts that Dr.
Lindbergh would agree with the way I have laid down my chips.
If only because he had inspired
many of my prejudices in that regard.
So let me just tell you what the themes.
I'm going to address R first of all.
What are the necessary ingredients
to having these
this information and data go towards patients?
First of all, there has to be
mechanisms of sharing,
mechanisms of data and knowledge sharing
and a culture of data sharing.
A culture that begets trust and more data sharing.
There has to be transparency and accountability.
And we tend to forget about the accountability
part of it. But.
Having people.
Not only share data, but follow up
has had a theories been proven.
Have the hypotheses been tested and going to that
full cycle
in the scientific discovery cycle?
The other theme is optimism and innovation,
that there is a continued opportunity for all of us to advance.
Medicine and biomedical science
because of the ingenuity
of the human spirit, especially as
embodied in America
by the National Library of Medicine at the NIH.
That the other is scientific skepticism.
Skepticism, which is not to accept all theories
from the beginning as being God's word.
And in fact.
Assuming very much in the spirit of science
that most theories will, in the backs of worlds,
be proven to be approximate and will have to be refined.
Very importantly.
That data.
Actual data.
The raw data are so crucial
to actually distinguishing truth from fiction.
Hypotheses from.
Well found the science.
Finally again, I do not think I am taking over from Dr.
Lindbergh. In fact,
I know he was proud about the fact that his success.
Lay and
finding superb colleagues to.
Take his vision
and translate it into what ultimately became success.
And that includes.
Colleagues such as Dr.
Smith.
Colleagues such as Dr.
K colleagues as such as Dr.
Humphries, colleagues such as Dr.
Macrae, who I mentioned in their names
now and I have missed others and apologies for all of you.
But these were colleagues and our colleagues of Dr.
King who made several of the projects, I should say, and David Lipman,
several of his projects that I will appropriately
credit to his leadership actually come to fruition.
And so part of his inspiration and genius were finding
the right colleagues to actually.
Do the trusted job of actually
moving forward. So.
I put this slide here to remind me to make the following statement.
I think there is a risk.
That we forget how crucial.
Academic and scientific leaders
in biomedicine. And.
I am reminded
by the fact that the current
director of the National Library Medicine
is a.
Doctor and a nursing professional
that perhaps I should have used the word health professional rather than doctors.
But nonetheless, in this slide, it's doctors that doctors can
and should lead in and this vision of innovation
and scientific discovery and that we should not.
Only defer to.
Individuals who have perhaps training in business and commerce
but do not understand some of the underlying
goals and science of the biomedical enterprise.
And so you see here, Dr.
Limberg and although we're not gonna talk about it today, Dr.
Limberg was also a pioneer, for example, in artificial intelligence.
He created the A.I.
Room, the expert system that did expert diagnosis
of drugs, logical disorders, and.
That's.
Tells me that
there is plenty of precedent for doctors leading efforts
in the knowledge, discovery and artificial intelligence.
And we should encourage more doctors to be in that role.
Shown also there, too,
on the left on the screen is Dr.
Octo Barnette, a colleague of
Dan's at Maastricht, Massachusetts General Hospital,
who, along with four MIT undergrads, undergraduates,
built the mumps system that now underlies
most of the electronic health record systems
in the world, including
EPIC, for example. And.
Those that huge innovation back in the 1960s, mind
you, was led by doctors,
leading undergraduates from MIT.
And I do think this this model.
Can and should be emulated because these individuals
have many of the concerns
that the health care system and patients need to have.
And just parenthetically,
we see Randy Miller back there in the background, who is also
has been a leader in many aspects
of biomedical informatics, but also a pioneer in artificial intelligence.
I think that for the
younger folks on this call, it's important
that we remind ourselves,
the world that we lived in when Dr.
Lindbergh took the helm of the National Library of Medicine.
Unfortunately, I am old enough
so that I can remember what that world looked like.
So in 1984,
I was a. A
third year medical student and.
When?
I wanted to.
Search.
Medical literature, I had two options.
One is to look at these books that had indexes of all the published literature.
Index medicus.
Or I could see something very priestly
and remote looking librarians typing into a terminal
that linked to Medline that would, in some arcane
query language, return the.
Articles that were up to date
on the queries that we are rounding on patients needed to have.
That's where it was that
you had to be
part of a medical school or have access to this paid Medline.
This paid service that accessed Medline.
Trials were shrouded in mystery.
A trial would be started by an academic center
or a company. And.
Sometimes the primary endpoint
would be met, would not be met.
These and either the secondary endpoint
would be substituted as the headline of the publication.
You really can track it.
And so all bets are off.
When something was published, was that that original hypothesis
that was tested, or was this just a hypothesis that
survived multiple hypothesis
testing after the primary hypothesis failed?
That's where we were in clinical trials.
And the patients have access
to their medical records? No.
In theory, in some abstract, legalistic sense.
Maybe they did.
But. Probably the most
glaring example of an amusing example
of the fact that they had no access to the record is a Seinfeld skit
where Elaine essentially gets blacklisted by her doctors
for daring to ask her doctor what exactly was written in the record.
There was no such access.
And that meant, among other things, that incorrect assessments of the patient
just mistakes would go on for decades.
Uncorrected.
Data was not shared.
You'd have a scientific discovery, a genomic sequence
discovered in one place, not shared with any other center
unless you had a special relationship
or a friendship or a material transfer agreement.
Incredible delays, therefore,
in the progress of science.
But paradoxically.
And we'll get back to this.
Trust in expertize was in a max at a maximum.
I would actually like to hypothesize.
The reason this trust was so high
was because everything was so opaque.
People did not know what was going on underneath the hood and therefore.
Pronouncements could go
essentially unchallenged because the underlying data,
the underlying knowledge was not broadly available.
But nonetheless, this is a.
The fact that
the trust expertize is now at historic lows, as I will describe,
is a challenge that we must face and.
I think if you had predicted this back in 1984.
People would be confused by this paradoxical,
apparently paradoxical effect.
So let's enter.
The multiple.
Dimensions of Dr.
Lindbergh's success.
So instead of.
A few individuals fortunate to have accounts
with commercial services accessing Medline.
Medline became a free service open to the public,
and then the web got wrapped
around it in PubMed.
And what you see here is the exponential rise of.
The data available
through PubMed and the CBI.
And if you look on the Y axis to the right,
you see
the millions of users per day.
So it's phenomenal.
Millions of users per day. Per day.
But I think among the most cheering
aspects of these millions of users a day is different.
Surveys have shown that between 25 to 50% of those users
are not institutional researchers,
they're educators, they're the public.
And so there's been this huge efflorescence of data
sharing, of information sharing that previously did not exist.
Back in 1984.
And this is because of Dr.
Ginsburg's direct investments in these programs. And.
Picking the leaders to bring forward these efforts.
This also pertains to the growth
of sharing of genomic data.
So that again,
GenBank.
Then within CBI.
Demonstrated that there was
enormous synergies, not multiplicative, but exponential synergies
by having sharing so that you could now discover
through simple search all the variance.
Discovered so far and find out
that your patients have that variant has.
What is the consequence on protein function
of a change in a DNA sequence?
And this spread to all the other kinds of high throughput measurements
that the genomic and post genomic revolution have led to.
And these did not happen by accident.
These were specific programs that had to be fought for
in budgetary allocations through Congress that Dr.
Lindbergh and his colleagues
advocated for and succeeded to do.
But it was by no means assured of success.
Next.
There was really no communities
of information sharing even within academic campuses.
That would be the medical library, the medical school, the hospitals.
And because this program is no longer present, but I you probably don't know
the acronym I AIM's Integrated Advanced Information Management Systems.
These were generous grants
that were led out of the National Library of Medicine that allowed the integration
of data across these academic health centers
and sometimes community health centers in a way that created a culture of sharing,
a culture of democratization, of data
that had not existed.
So again, we take this for granted now,
but it took specific programs to generate.
In 1984,
there was a babble of a variety of terminologies
that described
pathologic pathological samples, that described
billing codes, that described
terms for two index
journals.
And each of those had their own or their own vocabularies.
And yet they were describing different parts of the elephant,
different parts of the biomedical research knowledge base.
But they were not.
Immediately comparable
if someone had described their thing in snow bed, the pathology language,
you could not say if it was anything like
the thing that had been described in mesh.
The terminology for journals and some of the book covers
were not only not linked to these other vocabularies, but they were
proprietary.
You'd have to pay money to access them.
And so in a in a far reaching.
Effort, Dr.
Limberg.
Got both funding and the political alignment
to allow these different vocabularies to be put together.
Into the unified medical language system led by many,
including leaders such as
Duck. Dr.
Humphreys on this zoom to provide
a tool that is now used all the time to actually compare
and align data generated from all these
different systems.
I mentioned before
the obscure state of trials in 1984.
It was a significant act of political leadership
to convince Congress that despite their constituencies
from pharmaceutical companies and other research organizations
in various states, it was in the public interest
for trials to be registered ahead of time
so that the primary endpoints
that the trial was intended to test
were made explicit before the trial was run,
and then to have journals adopt those standards
so that our leading journals, medical journals, would require
registration in clinical trials dot gov
before a trial was published.
All that we take for granted
and with the leadership of Dr.
Lindbergh and Dr.
McCrae, this act of political and technical leadership actually happened.
I should also point out that patients
use clinical trials that or all
the time to find out when they have,
unfortunately, an advanced cancer or a rare disease.
Is there a study out there anywhere
that actually studies this disease that they can
and what its enrollment status can they enroll in it?
It's been used extremely broadly in ways that were never
previously thought of.
I put this last,
but it could end up being
the most impactful work of Dr.
Limburg.
He was absolutely convinced, not least of all,
because of his early work in artificial intelligence,
that that clinical data had to be available
in electronic format and had to be widely sharable
and ultimately had to be in the control of patients.
And with his patients, statesman like patients,
which I described at the beginning, he funded a multiple set of initiatives
from a early 1999 to use electronic health record initiative.
That actually ended up being the first grant I ever got
from the NIH
all the way through to
efforts I'll describe later.
Much.
Not only was
it personally important to me because I was involved in some of
these efforts and but was funded by the National Library Medicine, but
it really led, as I hope I will convince you to,
a transformation of the way
electronic health record
data is shared and disseminated.
So let's talk about that first grant that I got.
The first grant that I got was a new one through the National Library of Medicine.
And it was part of this vision that Dr.
Lindbergh had of data sharing through electronic health records.
So tracking health records already existed by that time.
Again, I mentioned that they already were around in the 1960s
due to visionaries like Dr. Barnett.
But the RFA asked for
ways to share across institutions,
and I proposed back in 1995, I believe, a mechanism
to share data using something that at the time was completely novel.
The World Wide Web and what we proposed was to share
data across health care institutions and working with Dr.
Barnett and Charlie Safran and others with funding from the National Library
of Medicine, which, by the way, was key to my career development.
Harvard sometimes runs a very Darwinian system, which is you don't get funded.
You are.
As they say, history.
So through this
grant we actually have running in 1996 as published in this
scam article stamps
either being that conference that Gretchen reference
we had running in 1996 a program that in real time access data
at the Beth Israel at Children's Hospital and MDH so that in real time you can see.
If the patient had been seen at any one of those institutions
and if they had been seen at multiple institutions, data would be collated
on the fly to create a history of that
patient. Many
subsequent developments turn that into
programs that others used.
Beth Israel integrated multiple health care systems
around that around that technology, but also the
the various regional
data aggregation efforts
that were implemented under President Obama's
high tech act used that on the fly
integration approach.
At the same time,
something rather bizarre.
And at the time impudent
was also funded by the National Library of Medicine,
something called the personal Internet work Notary and Garden.
This is the work that I did with my thesis.
Also for my thesis about former thesis advisor Professor Peter Sullivan of MIT.
He had previously described
in a project called the Garden Angel Project that was funded by ARPA.
A mechanism for having conflicts
or agents safeguarding patients health, I said.
The first step is to actually have a patient control
of those data.
And in fact, what we did was we actually showed
how we could actually use web simple web pages to encrypt.
This example, formatted
data of the patient that had been extracted out of trunk
health record systems, and that this data would then be under patient control
and could be shared with others for research and for clinical care.
And this ended up being the.
This effort, funded by the National Library of Medicine,
ended up being the progenitor of multiple projects.
Some of them, the somewhat ill fated health vault and Google
health efforts of the 1990s ultimately led to
the intellectual descendant, which I'll get to,
which is the person controlled Apple health record
that now accesses over 800
academic health centers and provides patients control
over their own data.
The early work
that I just described led to many other large projects
actually not funded by the National Library of Medicine,
but were direct users of technology
that have been funded by the National Library Medicine.
So for example, a more across the United States pathology
data sharing network called the Shared Pathology Informatics
Network, funded by the National Cancer Institute, was a direct
use repurposing of the code base that we've actually developed
for the W3 EMR system that I described at the beginning
under the CSA.
We actually actually demonstrated, actually used and published
several studies that cost whole academic health centers
that use this distributed sharing mechanism that we had first
demonstrated through that first grant
that I got through the National Academies.
But that was definitely
following the script written.
RFA That National Library of Medicine had written an important point
of all these efforts is that in these distributed queries,
and I think this is something that we're a revisit in spades
in the coming years, is given the fact that it is
unlikely for reasons of privacy,
property and culture that we're not going to be able
to generate one huge planetary database of all patients,
that we're going to have distributed queries that allows us to have
a statistically well-grounded pursuit of health.
The understanding that distributed queries.
Allow us to create the paradigmatic.
The whole is greater than the sum of the parts results.
And this again, thanks to the National Library,
Medicine's funding was amply demonstrated.
The kind words of
Dr. Smith that
reference the eye to be to and yes that that's I'm sure
when we came up with the name R2-D2 wasn't too far from our thinking,
but informatics for integrating biology at bedside.
This is a collection of open source modules that allowed us
to liberate the data in a multiplicity of different vendors
electronic health record systems, so that first, for the first time,
academic quality improvement researchers
and geneticists could actually access data from the health care system
and analyze it.
This this system because it was free
and open source and funded, by the way people think of it
because it's funded under the CDC Office of director program of as Dr.
Zerhouni, think of it as just
a direct program.
In fact, the National Library of Medicine stepped in specifically
to support the HIV two project
and added their own budget to it in order.
To fulfill what
they saw as a realization of their own vision.
And what we showed was the following.
And we showed it multiple studies that if you merely used.
The samples that were drawn every day out of patients
shown here on the on the x axis is time in weeks.
So this is weeks.
And on the x axis is occurring, on the y axis is number of patients.
And we show that just in one health care system.
You could accumulate.
Thousands of samples per year.
For common diseases like depression or mudslide arthritis.
And links them to their clinical characterizations.
An electronic health record.
Allowing us to do genomic studies at literally 1% of the cost
and hundred times the speed of.
The old school method
of taking decades to complete a cohort.
And I think this inspired many other efforts
to use health care systems as living laboratories
for genomic discovery research, where we use both the biomaterials
of our patients with their consent and the electronic health record phenotype
or clinical characterization to drive and accelerate research.
I have to note parenthetically that many of us as patients
assumed that the health care system was doing this
along with learning with every new patient.
Of course that's not true.
But this really helped drive for many health care systems.
Health care systems drive that realization forward.
I show this diagram that my colleague
and collaborator Ken Mandell actually generated
to show a
interesting outcome
of that early investment in the personal Internet work.
Notary and Garden Ping Project.
I told you about a patient's control of electronic health record.
And because we developed those technologies,
we were very prepared in 2009
when President Obama had announced the high tech
act to actually propose in the human genome medicine,
the somewhat impertinent suggestion, well, why can't health I.T.
be more like the iPhone if I don't like my camera app
or I don't like my.
Mapping app.
I can download a new one and substitute it
not so for a order entry system where I have to replace the whole system.
So we ask why could there not be such modularity?
And the government actually
supported
that question by investing in us.
As part of the own sees the Office of National Coordinators
funding under President Obama's direction of
these strategic initiatives.
And that led to something called the Smart on Fire Project.
This is a project that's created an application programing interface
that was independent of the underlying electronics health record vendor.
It was adopted by multiple electronic health record vendors,
including the leading ones, so that you could have a common access point to data.
And in a great example of doctors
leading the charge, in the sense of Dr.
Limberg and Dr.
Barnett, we had two doctors,
Dr. Josh Mandel now at Microsoft, and Dr.
Ricky Bloomfield now at Apple Computer,
who actually led the
migration of that
initial API into a common standard
that it was now part of the 21st Century Cures Act that Congress passed.
And that Apple
made part of its Apple health
technology stack so that now today patients
can access through their iPhones
their data from over 800 hospitals and growing of thousands.
And there is for the Android platform a similar effort going forward
so that we already have tens of millions of Americans who can access their data,
their labs,
their medications, their procedures in ways that were previously not possible.
And so and this is under their control, and they can actually choose
to share that data with others.
So that's a pretty long reach for
efforts that Dr.
Lindbergh started back in the 1990s.
And it's just the beginning.
I mentioned that
trust was at an all time high back when Dr.
Lindbergh started his leadership of national medicine.
Unfortunately, there's been a collapse of lead of trust and
trust in
expertize and leadership across multiple domains.
And I want to point out that even before COVID way before COVID,
this study done in 2013,
in the JAMA in JAMA internal medicine,
I found it very surprising at the time, but
it ended up being.
Predictive.
And this was a study looking at how consumers
perceived favorable or unfavorable,
different uses of their data.
And I don't think we would be surprised to hear
that because of their history
with the health care system.
African-Americans, for example, were less trusting of various
users of their data
than those of European origin.
What was surprising was that across all ethnicities,
there was a high degree of trust for the doctors using the data.
And not surprisingly, there was a large amount of distrust
of commercial use by drug companies or insurance companies of data.
But what surprised me was that.
Public health was also
seen as a less trusted user of their data,
patient data, than the doctors.
And I think that's a problem that we have to deal with.
And this problem only got accentuated
by the pandemic.
And the leadership of the CDC has acknowledged
that we have a problem here and they have undertaken
a massive rethinking of how we communicate and how we present data
so that we can actually restore confidence.
And I do believe that.
We will see historically.
We will see historically that we went from high confidence
in the 1980s to low confidence currently.
But as we develop along the path that Dr.
Lindbergh laid out for us, better access to the primary data,
allowing a rich ecosystem, a reinterpretation,
a reanalysis that there's going to be a regrowth.
Of the faith
and the expertize in expertize and in data
driven analysis.
So what is the way forward?
How do we go from here?
So one path is clearly
just starting, which is the CDC is really revisiting
how it looks at the aggregate of data for public health
as gathered from various health care systems.
And by the way, as a point of pride,
I want to point out that those of you who have used
QR codes in various states from Massachusetts to
the to California documenting your vaccination, are actually using smart
inspired technology that, again, Apple, Microsoft and others helped
push into the public domain.
There is another alternative
which may happen and looks like it's happening,
which is large data companies are going to step in.
And this is
a new
story about Amazon acquiring one medical
a large health care distributed concierge like health care system.
So now Amazon, in addition to having access to
the widgets and movies that you buy, will also,
for a certain group of patients, know a lot about their health care status.
Amazon also has
pharmacies in several of its Wholefoods stores
and also has a
pharmaceutical delivery service.
And they also have a polypill service
that a recent New England Journal of Medicine,
talking about different people show has been very effective, actually reducing
disease. So.
Caution to the academic health centers or commercial
or community health care centers.
The notion of the power
of data enabling better decision making.
It's not restricted to.
Just the conventional health care system.
But large data players have already figured out how to.
Commoditize and add value to individuals.
Data are jumping into the fray.
Apple Computer similarly to the fray.
I have to say, they have an impressive model of privacy
where any data that I described in the Apple
health record is actually not accessible to them or searchable by them.
It remains only under patient control.
Google has many important efforts in this space
and multiple relationships with large health care systems to help them
apply knowledge, discovery and
and clinical management
to these large databases that they have developed.
There is an alternative model,
one I happen to like a lot, which is Consumer Reports.
Consumer Reports is a nonprofit agency and.
They are.
Have really only one
customer, the consumer, and they rate
various.
Household.
Or automotive products.
And give you some sense
of the best dollar performance tradeoff.
Would be, would we be so lucky
to have a comparison of all the checkpoint inhibitors
in such a fashion or of all the heart medications?
Wouldn't it be great to see which one give you the best efficacy?
Now, unfortunately, Consumer Reports does not have that
role, does not see himself taking on that
role.
The FDA,
unfortunately, also doesn't see itself taking on the role
if it validates drugs as meeting its endpoints.
But it's not.
Running a Consumer Reports like function
and where it's, you know, looking at
how do we compare the top ten
cancer drugs that's not in the FDA's remit,
although they do a fine job of evaluating individual
agents and devices under the terms of the trials
that clinicaltrials.gov specify.
The National Library of Medicine.
Actually does a pretty good job
of providing through access from clinicaltrials.gov
to the literature of trials, to lecture a basic science to the actual
underlying data, provides access to all of those data and permits
a multiplicity of private, nonprofit and commercial efforts
to try to make sense of that for the consumer.
But it does not actually do that job of synthesizing.
All that data for the individual.
It has chosen not to for a variety of reasons,
and as one would wonder, whether it's
even possible for it to do it for the multiplicity of purposes.
I think it's done a fantastic job for the task
it has set itself for, which is to make the data maximally available
to the largest group of individuals and notably the larger public.
So I would actually like to argue that Dr.
Lindbergh and this is going to be in closing, that Dr.
Lindbergh actually showed us the real way forward and.
I'm going to cite.
I guess myself and Jeremy Berg
in an article that we published in Science In Memoriam
for Donald Abe Limber, and I was writing with this with Jeremy.
I had the opportunity to read through many transcripts.
Of interviews with Dr.
Limberg and many of which were great music because the man actually
did have a wry sense of wry and dry sense of humor.
But this one is a really good one.
Early on, Don recognized that medicine needed to be more data driven.
During his residency training, his data driven approach
to medicine landed him in hot water with a surgery department.
When he showed the silicone that the silicone used for cardiac bypass
was causing extensive embolization, that means bits of blood and gunk
going through your arteries, causing stroke and death.
Only upon showing the surgeon's imaging data was he able to change their practice.
So. There's many things that are interesting about this story.
A he had a finding
that implicated a patient health. B.
He didn't just say, Hey, you idiots.
You're hurting your patients. No.
He met with them.
He showed them the primary data and convinced them through their own
conscience and the visibility of data, what the right thing is to do.
But the part that's less obvious
is this went through the mind of Dr.
Limberg.
The doctor, the care for the patient.
And I do think.
That what we will see in the future.
The future Don Lindbergh's of the world,
whether they have the title M.D.
or nurse practitioner or physician associate or either.
Or maybe some other new term that we have yet to determine.
There will be this expert who understands the biology, the medicine,
the clinical concerns of the patient
and brings it together.
In full understanding.
And I have to say,
since it was 2022, assisted
by machine learning.
Agents that look at across
the entire corpus of.
Human knowledge, medical knowledge, particularly
including the National Library of Medicine, to bring to that expert.
In a caring, patient, specific way.
What's the right thing to do?
I do think that
there's huge value in the health professional.
I'll use the term doctor as a useful handle as a doctor
who knows you, who knows what your preferences are,
truly understands literature, who makes available to themselves
the knowledge of science,
and who brings to you that expert judgment?
I think that is the place that we are going and in doing
and going in that direction. I.
Do hope and I trust
that we're heading in the direction that Dr.
Limberg so ably started us so many years ago.
Thank you for your attention.
I hope I did not
bore and
I'm glad to take any questions if there's any time
remaining.
Thank you, Dr.
Galani, for that outstanding presentation.
Very thought provoking, of course.
So those of you who are watching
look for the live feedback button under your video stream.
And that's the button you can use to send questions or comments to Dr.
Carney via me.
We do have one comment that's come in.
In communicating with patients
either individually or on mass, communicating
or caring about them is essential to their reception of your message.
I was privileged to know Don Wennberg throughout my entire association with NLM,
beginning in 1979
when he was on the board of Scientific Counselors of the Lister Hill Center.
Don communicated caring in every interaction I had with him
and he ever saw and ever saw him have with others.
He may not have agreed with everyone, but he was never disagreeable.
I believe that that was essential to why we are honoring him today
and why, of course, Dr.
Varney, in the way that you did, honoring Dr.
Lindbergh's scientific and leadership legacy.
So sharing that comment.
So that's a terribly eloquent common and then a far better job
than I did of summarizing the fact that a.
Did not advance.
He did not advance his views by confrontation or by
piling on instead by persuasion and data.
And absolutely, yes, there's nothing
that substitutes for knowing that someone cares about you.
And it's that clinical relationship that I think that relationship between
the care provider and the recipient of that care, that relationship
which has to be data driven because it's it's not enough to be caring.
You have to be caring and truly expert and up to date.
And in fact, back in the 1980s,
I remember being taught by medical in my medical school
that unfortunately, many well known doctors were famous and respected,
even though they were not stated that informed because they were charming
and persuasive, but they did not have the underlying science.
We need both.
We need a data driven expert who is genuinely caring,
and that's going to be the essence of the biomedical profession.
For its future and otherwise.
I will predict and I'm not predicting this because I don't think we'll go there.
There will not be a medical profession if we don't actually
grab that challenge of being trusted
or being dedicated to the patient's
well-being, making that clear where our
priorities are, and demonstrating that we are truly data driven.
So that's a very insightful comment.
Thank you.
Thank you. Yes, indeed.
Another comment has come in.
Dr. Lundberg was also never condescending in manner
when he shared his knowledge and expertize as Dr.
Kahane's last anecdote illustrated.
So further further to your point.
How dare you make that not? Yes.
Condescending is just.
And in fact, condescension, I would
say, is probably one of the dominant notes of Twitter
and probably among its most destructive, I think condescension,
which is often unearned and always wrong,
is something that you never, never,
ever saw in a leader
such as Don, Dr. Lindbergh.
And I think any hint of it is incredibly destructive
to the tissue of trust that we have to reestablish.
Yes, indeed.
And much of social media is confrontational and divisive
and only only reinforces that condescension in the worst way.
Unfortunately.
Can you tell us?
Questions come in about the medical humanities, the way in which
the medical humanities can serve
as a vehicle to educate practitioners of medicine
to to augment their empathy to patients.
The comment is really a comment that's come in that can you speak
to the current state, perhaps of the medical humanities
and in the advancement of the culture of medicine that you described?
That's a very insightful question.
I will first answer it tangentially and then
the center.
I think that's medical humanities and is art and incredibly point.
First of all in the history of medicine.
We like to think how modern we are, but
much of what we experience has happened before.
So, for example, understanding what
a revolution antibiotics was in the 1940s,
but then how there was arrests of multiple antibiotics
with similar properties and how claims were made for certain antibiotics
being different than other antibiotics, which were not actually data driven .
Understanding that history, I think would give will give the doctors
who understand it certain amount of humility and looking at current
trials, let's say about state of the art.
Cancer or viral therapies.
And so I think understanding the way medical progress has
humanity is such as the history of medicine
will really give us appropriate
humility.
And that in this broad march forward of science,
we've got to the individual patient relationship.
I think understanding how much.
Value patients get.
And when I say value, I mean not just reassurance
but actual positive health outcomes
are obtained out of a vital.
And trusting and informed relationship
above and beyond any scientific breakthrough,
above and beyond any
specific therapies.
Understanding that from the medical community, humanities
and the value of that human interaction.
And I'm not even talking about the important placebo effects.
I'm talking about how we actually influence patients
in ways that are helpful.
And that change the utilities
their outcomes in important ways.
There are few other ways to understand that without
really engaging with the medical humanities.
So I could not agree more with the implication of that question.
Thank you.
We have time for one more question on the very heels of your response.
Let me ask it to you, because it is it is a great follow on.
What are the unintended consequences of patients
receiving test results before their clinicians?
My experience, this person writes, is that without the support of content
of the clinician context, it can be anxiety producing.
I fully agree and I don't want to get too personal,
but I remember all too well getting a very, very disturbing
report through a portal of result
on a family member and.
Unfortunately understanding its meaning
and it was very, very depressing.
And if I had not been a medical professional,
I'm not sure what I would have done with it.
And there is there are many opportunities for misreading of those results.
There is no doubt about that.
But I think we have to always you know, there's in medicine, we always worry about
false positives and false negatives and it comes down to a trade off.
And if I would look it.
There's been so much that's been done unintentionally
by not in a bad way, by not communicating
in a timely way with patients.
That.
That, for example,
is a slightly amusing example.
My doctor took my
lipid levels in anticipation of deciding
whether or not to do a STEM intervention
and basically never looked up the results because he got busy.
But I looked at my own results and I was able to close the loop with him.
That happens all the time.
And I think on balance.
We're better off
having more and faster access to our data than not.
Now, that's not a stretch to say we have to accept the way things are.
I do think.
That in a smarter.
Adrian, the health care system,
if there was a meaningful result
with possibly dire consequences,
there would be a many technological means
to mutely loop in the expert clinician
to have a conversation with the patient.
It just so happens that our
billing oriented.
Health automation is not oriented that way,
so it doesn't have to be this way.
But given the current sum of cards that we've been dealt,
I would rather err on the side of more faster sharing than less sharing.
But at the same time, through personal experience, I totally agree.
We could do far better in providing expert oversight,
especially in cases of dire information shared with the patient.
Thank you very much.
Thank you, Dr. Krone, very much.
And again, for your outstanding thought provoking presentation.
We're going to leave it there.
And on behalf of the National Library Medicine, thank you again very, very much.
To all of our viewers.
We're going to take a short break.
We will reconvene at 10:45 a.m.
Eastern Time.
So join us back here in about 15 minutes.
And we look forward to seeing you.
Thank you again for joining us this morning and again
throughout our proceedings.
If you have a question or comment, please send it to
to us by the live feedback button underneath the video stream.
So we're going to take our break and we'll see you back here in 15 minutes.
Thank you. Thank you again very much.
Welcome back to the 2022 Lindbergh
King Lecture and Scientific Symposium here at the National Library of Medicine.
National Institutes of Health.
I'm Jeff Resnick.
I'm chief of the History Medicine Division at the National Library of Medicine
and have the distinct pleasure of moderating today's proceedings.
For those of you who are just joining us, please use the live feedback
button under your video stream to send us questions or comments.
We're going to proceed now with the first panel of our outstanding program of today
entitled Lindbergh and the Advancement of Science through Research Training.
It's my pleasure.
Now to introduce the chair of this panel, Dr.
Lucila Honor Machado, who is associate dean for informatics
and technology at the University of California, San Diego, where she is
also founding chair of the UCSD Health Department of Biomedical Informatics.
Previously, Dr.
Ana machado was on the faculty of Brigham and Women's Hospital, Harvard
Medical School, and affiliated with the MIT Division of Health.
Sciences and technology.
Her own research focuses on privacy, preserving distributed
analytics for health care and the biomedical sciences.
In this regard, she directs the patient centered,
scalable National Network for Effectiveness Research
and the NIH funded National Center for Biomedical Computing, known as DASH.
We're honored to welcome her today as chair of our first panel, Dr.
Ana machado.
Thank you very much for your valuable time and your engagement with us.
And I'm going to turn things over to you.
Thank you.
Thank you so much for the invitation to moderate this panel.
As we have just heard from Professor Cohen, his presentation by Dr.
Lindbergh's legacy is unparalleled.
And it touched the lives of so many people, so many faculty,
trainees and professionals in academia, industry and government.
This panel will address his legacy on the advancement of science
through research training, and it includes prominent informatics experts
who are leading impactful initiatives in their institutions in the country
and in the world.
Dr. Josh Denny is director of the All of US Research Program NIH
Flagship Precision Medicine Initiative, and will discuss
the role of electronic health records in computing medicine in the development
of an unprecedented resource for scientists everywhere
who will have free access to genomes, electronic health records and participant
reported data from the most diverse cohort in the world.
Dr. Graziella Gonzalez.
Aaron Enders, professor
of computational biomedicine at Cedars-Sinai Medical Center.
We'll speak about Dr.
Lindbergh's vision and investment in training without many,
without which many of the speakers might have taken career
directions much different than they have today.
Biomedical informatics might not have succeeded as an independent discipline
if those investments
were not made at a critical time when computers were just starting
to become an essential component of health sciences and health care.
And Dr. Nicholas detonated.
Associate professor of biomedical informatics at Columbia University
will speak about how observational data can and has been used for
biomedical discovery, including the role in generating new hypotheses
in addition to the known role of testing those hypotheses.
This distinguished panel consists of a small sample of outstanding researchers
who benefited from research training at the leading institutions that held
the prestigious T 15 training grants from the National Library of Medicine.
Not only those who were recipients of scholarships
and fellowships from this grants benefited from an alumni investment.
All their students included benefited from the curriculum,
the social structure, and from being around
the exceptional trainees funded by the Teach 15 program such as Dr.
Gretchen Purcell , Jackson and many other current leaders in the field.
Our three speakers cover a small portion of what biomedical informatics has become.
For example, trends for research funding from NLM over the years
indicate that II artificial intelligence was funded since the eighties,
and the impacts of electronic health
records would have on
health care was anticipated early on.
This trends are described in a recently highly recommended book about Dr.
Lindbergh's legacy, edited by Doctors Humphreys, Logan, Miller and SIEGEL
entitled Transforming Biomedical Informatics and Health Information Access.
As this book documents, Dr.
Lindbergh's impact in the field was profound, his legacy lives
on, and this panel was emblematic of his achievements.
It is an honor to close this panel,
and I will introduce our first speaker, who was Dr.
Josh Denny, chief executive officer of the NIH.
All of us research program.
He has been involved in all of us from its inception
and served as the principal investigator for the all of us data
and Research Center.
He's an elected member of the National Academy of Medicine,
the American Society for Clinical Investigation
and the American College of Medical Informatics.
As a physician scientist, Dr.
Dean is deeply committed to improving patient care
through the advancement of precision medicine.
Before joining NIH, he was both a practicing internist
and a researcher was professor of biomedical informatics
and medicine at Vanderbilt University Medical Center.
His research interests include use of electronic health records
and genomics to better understand disease and drug response.
He also led efforts implementing precision medicine to improve patient outcomes.
Joshua was a leader in the development of genome wide association
studies for use in phenotype risk scores.
Please welcome Dr.
Denny, who will speak about a legacy of computing medicine.
Accelerating precision medicine using.
Thank you so much, Lucille.
It's a real pleasure to come to you today and share some stories from my life
and how I see the transformational leadership of Dr.
Lynn really impacting and setting a course for a future of precision
medicine that can really impact people, people at really the point of care
and advancing knowledge and learning for really every patient encounter.
And, you know, if we think back at the time of where we were,
we really weren't there this time before his leadership.
And so, as we still have mentioned also, I just want to recognize
I was one of those 15 trainees as well
and the support of the innovation and idea
that doctors could engage following the model of Dr.
Lundberg himself and so many others, trained through these training programs
and become leaders in intersections of computer science, information
management and delivery of care really impacted my life and my trajectory.
So thanks so much, the organizers, to have a chance to present
to you and talk to you about this.
Process.
And so I want to just reflect back a little bit on how far medicine
has advanced really in this case, we'll say in the last 60 years
through research that was done on carefully organized,
often small cohorts of individuals carefully followed,
using paper in means, research projects
and intersections through phone calls.
Not so much the electronic health record.
And these efforts have really had transformational impacts
on medicine, the Framingham Heart Study being one of them.
There are so many others, and they gave us intervening
risk factors by which we had been able to change care.
And I would argue that
the goal of precision or maybe personalized medicine has really been
since the inception of medicine of how we tailor care to an individual.
But what we've learned through beginning these cohorts is how we could
use data to get smarter about intervening on things
that may be less visible and doing it using data in evidence basis.
And so, you know, one of our goals is how and our hope is how can we
similarly transform health with precision interventions over the next six years?
I think the goal of precision medicine and how we think about how we want
a personalized care is much bigger than, of course,
a a term like personalized medicine.
It is really about getting to the patient and really how we can improve their
trajectory of health beyond just disease, but also prevention, resilience
and the way in which they live their life
successfully in how they would define it.
And a lot of this, I think you can even look back
at the 1987 long range plan that Dr.
Lindbergh authored with input from others.
And in this, I just include a quote here about how
the most encouraging aspect of this report is the recommendation that the library
move as quickly as possible to translate existing raw technology of computers,
information and engineering sciences into products and services.
That, through its insight and understanding
of the special biomedical practices and needs, can improve health care in America.
And as I look through this in this book that was still just recommended
and thought about the impact and legacy of Dr.
Ellenberg on Precision Medicine, I really saw three points that emerged
next to me, and one of these was moving from the creation of not just literature
and making,
of course, that much more accessible than it ever had been to a wider audience,
but also storage and cataloging, emerging and digital data.
It's kind of obvious today that we needed to do this, but, you know, at the time,
moving the library into a library, not just to the published articles,
but of things like the genome and the Human Genome Project.
And and, you know, all those things were essential to accomplishing those goals.
And laying the foundation to build upon
the intellect has really been key and critical and called out from this long
range plan to develop electronic health records, repositories
and support things like clinical decision support.
And clinical decision support, I would argue, has never its need
has never become more obvious than what we see through
implementation of genetic data into health care.
And I think this will only continue whether or not, you know,
start to variant, start three variant
and how they're fundamentally different than a start 17 variant.
If you look at interpretation of a given genetic variant on drug metabolism
and so that evolving medicine really needs decision support that can
seamlessly partner with a physician to help guide them to the right solution.
And then a real premise and foundation and computational tools to link, search,
compare and analyze these kinds of resources such that
not just people reading the ledger, but, you know, computers and algorithms
can be consumer of the consumers of this kind of information as well.
And that, you know, march forward through so many tools has really helped.
And, you know, we have available, you know, big data resources across
all sorts of domains that are mineable accessible and clinically relevant
due to the last really now you can mark to the success
of the implementation of this long range strategic plan.
And so these are some of the many tools.
And Heidi, in their opening that Zach also highlighted some of these
and there are so many that aren't on here, I'm going to lean towards referencing
some of these that really have more of a clinical impact
as I talk about intersection of really a story of precision medicine
that I think is leading us to where the all of us research program is now.
And, you know, of these things, we have things that target
patients and people directly.
They're non-medical, as well as medical and research scientists
and really bringing them together so that we can build on knowledge.
I also want to reflect on how
my clinic space and our docket, our clinical charts.
What?
When I was just starting medicine, we were fortunate to be pretty early
adopters, actually, of information technology
and electronic medical records .
But the outpatient clinic,
as I was starting, had it, was just getting digitized.
And so imagine trying to look through these
to figure out who was on a given drug gets pulled from the market.
Imagine trying to do cross patient research.
You know, it was just so hard and so time consuming.
And so, you know, as we move to
electronic health records and this is a screenshot of our electronic
health records in the 2000, how can we use this for research?
And it turns out moving from clinical care
to research, use cases and doing
trends across patient kinds of research
was not something that was how these were originally architected.
In my initial queries, for instance, to try to look across patients
would require
lots of coding and algorithms to scan across serially different charts.
And so that was an evolution of time
and supported by a lot of research from the NLM.
And I want to give an example of what was the first cross
patient cross our
genome genome wide association study that had a new finding,
really relying purely on data in the R and in this case,
that algorithm on the left just shows you all the different information pieces
we had to pull.
I mean, to do things like manually coding for spelling errors, for instance,
and guessing how people would misspell things
and looking at all the different ICD nine codes and ZIP codes.
And that was doctors looking through charts and thinking through, Hey,
how might this get built? And coming up with this.
And this took us really about two years to execute
across these five medical record systems that each individually executed
within their site. It could take some time to do this.
And but they found that the algorithms work well.
Overall, we had more than a 90% positive values for our cases.
The controls, we could deploy this across different systems.
We could use genetic data.
It was derived for other purposes and know we could find something
that was new, a new association of a thyroid transcription factor
that was associated with people who had autoimmune thyroid disease.
And so it showed a promise of using this kind of technology.
Of course, this has been commonplace, really.
All major research cohort studies at this point are using electronic health records
as part of their research foundation.
And we also, because of resources like
Klingon and sorry at this point, Pub Med and then CBI and
and cataloging of genome wide association studies,
we were easily able to find things like this study which looked at people
who had a scheme stroke that we didn't realize
that they had any sort of atrial fibrillation or cardiac arrhythmias.
But through genetics, they identified a locus
that was associated strongly with atrial fibrillation.
And so, you know, you could basically do a study in one disease and define it
and carefully curated.
And the genetics actually told you
that there's an underlying cause you were probably missing.
And this is shown in other kind of clinical studies.
But even when this deep dove had really helped sort of elucidate
how in its early study how genetics
can start to tell you things that we don't clinically see.
And it's certainly been our model also as we think about drug discovery.
We still mentioned that
genome wide association studies, and that's been a case by which,
you know, we can use the richness of the electronic health record, really
categorizing all diseases, all drug exposures, all these lab results.
And instead of looking at just one disease, just like hypothyroidism,
you know, where those were derived from other studies
and we looked at a new disease,
we could take that and expand that into the scale of the genome
and figure out ways to map against different diseases
comprehensively.
And here I'm using the example of atrial fibrillation again.
And this really large study was study of 400,000 people.
You know, when they do that, when the gwas for atrial fibrillation
developed and shows across
the genome, all sorts of different associations.
And you can do this really fast.
Once you have these data, pull together and see all these associations.
But you can also ask the question, well, the genomics point all this.
What happens if I adjust for people who have atrial fibrillation?
Do we still have all these association with the genetics or are the genetics
actually more specific?
And there are clinical associations and you can see when you take away
those people have a fib, all the other stations and associations go away.
So it helps, you know, clinically, again, we're able to use tools and power
and scope of things like the electronic health record
to to understand derived genetics and then understand
the impact of those genetics much more quickly than we would.
And in a more maybe I would say reliable, confident way of of what we're finding.
So I want to give an example of how
all these kind of technologies, especially like the use of M.S.,
which really has been foundational for my work early with natural language
processing, are moving to things like
in how we just use as an inter lingua
among different vocabularies ICD nine and ICD ten.
Great work that Ellen did there in making this more consumable,
not to mention making things like snowmen available for everyone in the US.
So helpful to not have to work through and make those those linkages manually.
And so what we did is we took the Emerge Network, which had ten clinical centers,
ICD nine, ICD ten in and of themselves
may be hard to work between a clinical repository and the UK
Biobank, which has 500,000 people collected in the United Kingdom
, 200,000 of which, when we did the study, had whole exome sequencing
and clinical data derived from the UK.
And by use, by pulling it together, you know, we have standards around
sequencing data.
We have lots of journey data, things like the your mosque
and all the work that has been done around these codes.
We could map all those things relatively quickly together to around 3000
different phenotypes.
We can use Klingon and determine among these cancer
causing genes that we wanted to look at and see who had pathogenic variants
and essentially moving and adding a whole nother
country's data and interpreting all their genomes or something.
That is a process of weeks
after process approvals and all these things are compatible.
And we were able to analyze this huge dataset with rare variance in these
26 cancer genes and look at things like these associations across the difference.
So here we have a combined sets of 23 genes on the x axis
and a genome with each of those genes and using these data
sets across all these different sites.
We were able to, if one study, replicate all of the strong
gene cancer associations for these genes
in cleansed an omen and concludes non cancer
being a lot of non-cancer phenotypes
and there we were able to replicate in the study 70% of those
and then we identified 50 new associations,
most of which were not cancer.
But some are related to cancers as well and we actually can
look at their temporality as well in that
and show it in at least two cohorts, all enabled by the underpinnings
of all of these information technologies that we can use in a very rapid fashion
and not even have to think about the languages we're using.
That's really some of the power of all those tools that enables this
and similarly, countless other studies like it.
And so I've talked about how we began with things
like Framingham and manually derive survey instruments and exams
to incorporation of genomic data in those early atrial fibrillation studies
that also were using things like exams to derive that
and then the power of using health records.
But, you know, precision medicine and how we dissect individualize health
is much, much bigger than that.
And I just want to recognize there's so many plays to this
and the interrelations between them and getting them really powerfully
incorporated within one population of individuals
to share as much of this and coming technologies, imaging data,
mobile devices and other sorts of sensor technologies,
search and geospatial
and other determinations of social determinants of health
that we know are so important to understand
the diversity of our populations and their influences on health.
You know, these things come together and we really designed
the All of us research program that to help us think about how we can,
you know , think about the many inputs to help over time.
And we want to accelerate health research and medical breakthroughs
to enable individualized prevention and treatment and care for all of us.
We really want to focus on a diverse population
and understanding the variability that we all experience.
And we want to have a large size of at least a million participants
that do reflect the diversity of United States.
Over 95% of all genomic studies right now are of people of European ancestry.
We wanted to change that story, and you'll see that in a minute.
We really want to
make that large, rich biomedical dataset
following in a lens model and Dan's call
to as available to researchers as we can.
And it's really important that this be an ecosystem
where people can share data and follow their data practices to
ensure and promote reproducibility and interactivity,
share ability, find ability, index ability, all that kind of stuff.
And we really wanted to commit to a set of core values as well in this process.
And, you know, we've been successful,
I think, in enrolling a diverse audience and a large audience.
COVID has been challenging,
but we still enrolled over 520,000 participants that have consented.
It's very much ongoing.
We launched in 2018 and over
365,000 have contributed all the basic steps because participants
share longitudinal data as part of this.
Same with digital health technology.
They can link in their Fitbit data that they may have had for ten years
there, in some cases go back 40 years.
So we have longitudinal data that people are to share.
Even though this study started really in 2018,
we had this record of data that people are sharing with us.
It's really powerful that help us think about things.
And we recently
released our first set of genetic data, which included 100,000 genomes,
165,000 people with a race in those whole genomes.
We've observed 600 million variants so far.
400 million of those variants are not in common resources now.
Now, why is that?
So why are we seeing so many new variants?
And I think it's largely because we have a population
that generally hasn't been sequenced before, with over 50% diversity
by race and ethnicity, over 80% by
larger metrics, including disability,
social, sexual, gender, minorities, rural location, things such as that.
One of the challenges been mapping across different electronic health records
using common data models like OMAP and terminology work
such as you have was again, we've been able to do that and and now
you can see that we're getting greener our quality metrics
across our 17 or so different vendors represented
in many different versions because of the terminology systems.
Again, you can go from cancer to a term like malignant neoplastic disease
and lots of different terminologies that are mapped in without the user
having to do the work that all we had to do with hypothyroidism.
And what does this mean when you actually come to our participants
are a researcher doing a study and this is open now for researchers.
This is an example of my last Ph.D.
student at Vanderbilt before I moved to the NIH.
He defended in March 2021, he did a study
where he pulled together lots of data, including the Vanderbilt clinical data,
and found medications that might affect lipid response.
And known medications were the most powerful, as is is not unexpected.
But then a question from the audience, which was not me
after his three years of work. You know, you did this at Vanderbilt.
Can you replicate?
And so he was able to apply to all of us
for the first time.
Come in, do the training, come in and take his code from Vanderbilt,
basically cut and paste it and replicate this in about a week and send me
to a near final figure with all of us data combined
with Vanderbilt data and show very similar results.
And so I think that really shows a power of these kinds of things available across
60 plus medical centers.
He was able to combine this data really seamlessly because of the hard work
of all the decades before pulling these things together.
So using modern cloud technologies, you can work through things like this
where you can come in, describe with our tools
visually and point and click in the resource.
And this is not just all of us.
Now these models are being adopted elsewhere where you can build a cohort,
build a dataset, come in and bring technology at the end.
You write in our system and many others, you still do have to write some code,
but it can be a team enabled science where you had different
people from clinicians who don't know how to code, to people
who are data scientists and and biostatistician that work in the data.
And you can actually go and run as you like this
now using a cloud environment in 30 minutes
and find known associations or new associations.
And after building your cohort instead of a year's worth of work
and thousands of emails that studies like the hypothyroidism study originally took.
So with that, I want to thank everyone again.
Thanks so much to the organizers for inviting me to attend and
just appreciate the legacy Don left and created through the lab
that is now continuing and had such a big impact in my life.
Thank you so much,
Josh. It's impressive.
Where we will be.
All as a community have been achieving an impressive.
What you have in particular by leading the all of us program
we will have a set of questions at the end
and people will be able to use the Q&A button
or the chat depending on which group you are in.
And we will go ahead with the other two speakers
and then again to have the questions at the end. Dr.
Graziella Gonzales Hernandez is Vice Chair for Research and Education
in the Department of Computer Biomedicine at Cedars-Sinai Medical Center.
Prior to joining Cedars-Sinai, she was an associate professor
of informatics at University of Pennsylvania.
Her health language processing lab
moved to Cedars-Sinai and focuses
on natural language processing and machine
learning for knowledge, discovery, extracting and structured information
from clinical records, journal articles and social media postings
to elucidate data patterns, trends and relationships
that can aid the discovery process in areas such
as far more pharmacoepidemiology clinical research
or public health monitoring and surveillance.
Dr. Gonzalez Hernandez and her team have made available
to the Health Research Community novel approaches to complete pipelines
for information extraction from different sources using an LP.
Her experience includes mentoring of more than 50
new faculty, investigators, fellows, graduate students at the Masters and Ph.D.
levels, and she currently serves as a member of the NLM Scientific Board
of Advisors, as well as a member of the NIH BMA Grants Review Panel.
Please welcome Dr.
Gonzales and Hernandez talking about Dr.
Lindbergh's legacy to the advancement of biomedical
informatics, his vision of a new field or a new way.
Thank you so much.
It's a pleasure to be here.
When I was first asked to speak about Dr.
Lindbergh's legacy and this new feel
for a new age, it has always fascinated me. How?
How broad
and how wide his influence has been.
So just to share a little bit about about Dr.
Lindbergh being a lamb and my relationship and how I benefited
from from his wonderful contributions.
I remember being the first the first interaction
I had with him as a member of the of the review panel for the NLM.
We will sit at the NLM library
and the and then wait eagerly
for the morning update that he will bring to the review to the panelists.
Then he was, I think it was
one of the of the things that most impacted me
when I first arrive at the NLM and was there and was able to hear
his update on science and his views, and we will just sit there
and absorb all his of his
insights into this.
So I do not pretend to do
an overview of his legacy in this.
In this sense, there is a book actually on him
and I gather the cover of the book right there
that, if you want to check it out, is fascinating and said certainly
this morning again gave an excellent overview of all his legacy.
The thing that I want to emphasize is how
just like me, there's many researchers across the United States and even
around the world that have been their careers
undoubtedly reflect
a lot of his find a lot of his findings a lot of his
emphasis on information
as a means to improve health.
He will always emphasize the latest findings, the latest publications,
the latest ways that we could improve health and we will improve
the way that people are care
for the public health, individuals health.
So in my particular
career path,
I got to the NLM early on, the NLM got to me
finally on the, the, the data, but they share the funding.
So a lot of my funding comes
even to this day from the NLM.
Through the years, I like this little screenshot of how the NLM peppered
all my all my funding from the beginning and I'm eternally grateful,
but also for the opportunity to review proposals
I've served to this day in around 50 or so
NIH panels.
And through that, those of you that have reviewed proposals needs that
I've seen about 2000 or so proposals
from researchers around the nation.
And what is striking is how many of them used
the resources that have been developed by the NLM and NCBI.
Jam band PubMed is just.
The influence that the DNA.
LIM And Dr.
Limbaugh has got in in all of our research
is is is tremendous.
So this is the current year.
Again, the Olympics takes the lion's share
of of of what I am able to do
thanks to them and the continuous support.
One very important thing.
So when I was thinking how to focus this, this dog
and on the important contribution
the most important way that that I can
that the decided to go with was how
the NLM was an early supported supporter of real world data.
I think I have the the very first
or the oldest of grant
funded for the study of real world data.
And I remember that when I proposed that it was
there was hardly anything published on how to use social media data.
And I think the most interesting thing that I discovered
is that my proposal wasn't about any specific solutions.
What I propose was to study how it will be used,
how real world data from social media could be used for pharmacovigilance.
And so I never promised that I was going to find early signals
of adverse effects or actually the problem is what I was going to find at all.
All I wanted to do was to find
that those develop that those decibels of pool enable it.
So just like like social media, electronic health
records, of course, are foremost one of the
most important sources of real world data.
So coded, unstructured notes, large repository of clinical and genomic data
containing the they could then be built on an entry text
that that that that could address many knowledge gaps.
And one would think
we have been hearing about then the technical records being used
for all research and or studies.
One would think that they will be widely used,
that all these data from all these people out there will.
Certainly.
And just this presentation highlights that the importance of that
and it is one of the efforts, I think, that is more striking
on on its reach.
Social media can still contribute their stories in social media
that people share openly,
that people share without the structure of of of a questionnaire,
they sometimes go back in their history .
So this search that I like showing is I'm diagnosed with.
And if you if you focus on the middle story, they a medical student
diagnosed with obsessive compulsive disorder
as it gives a lot of the the bills
and what kinds of medications this person has use.
Then there's a lot of what we call a follow up story.
So many people retweet them, put their own little $0.02 on it, or
they share a similar story.
There's also obviously the things that are not the right thing,
like that other one.
So these tweets come from the feed directly,
and that's exactly how we see them.
So this one is it is is a contrast with the same search.
You can get really valuable information and you can get a lot of the noise.
The challenge is distinguishing the two and being able to develop the systems
that can distinguish the two.
The the, the, the the next striking factor
that I discovered through this through this.
Analysis of real world data is that is grossly underutilized.
I was invited to to write a paper
on biases in data.
And through this I started thinking like, okay, so how much of it.
How much of the data is in the structure portion
of all of the each other is a versus the coded portion.
So there are some studies on it.
That is a very interesting, though, beyond what I can talk about right now.
But it's about 70 to 80% of usable, actionable data
is in the unstructured portions of the data.
However, only about 40.5%.
And I'm being a little generous there of the studies based on each other's
use this free text.
99.5% of
them focus on just go to data.
And this is not so much the fault of the researchers running this study.
It's just data is not easily accessible.
Unstructured portions of the data are very hard to get.
You will have
every institution with few exceptions.
You will have a very hard time getting free access to it.
And even if you can access it and use it, there are not many standards on it.
So revisit that one.
Social media data.
Another foreign data is not officially used at this point
by any regulatory agency.
And I say officially, because unofficially it is.
And actually, if you if you count the FDA's declaration
that they use social media to to get early early signals about
COVID
treatments or fake COVID treatments, they mention that that's
how they get them, but they don't mention how
they use social media on their website.
So I guess a declaration on an official website could be seen as an official use
of social media.
However, there's like little information as to how it is done.
Social media data is used
mainly to inform other studies, like systematic reviews.
So like there's also references to finding mentions in social media to go back
and look at what is published about them and then add them to studies.
So, so
all of this data that we're surrounded
by needs a little bit more of a systematic approach.
So this is the paper I was referring to.
Best practices from big data analytics to address specific biases
in our understanding of the.
So in writing it, I saw, for example,
that studies that use our data
and that specifically have a finding that refers
to biological sex as a factor a difference
in in their in their studies
vary widely in the use of male and female records.
So we come
from 75% male, 25% female
all the way through the other way around 65%, 70%.
Many studies in between with a great imbalance
in the data that they use,
even if the finding is
specifically related to a biological sex.
So the data imbalance is one of the of the things
and the rate of use of this unstructured data.
Going back to that point that was making
these studies
as you saw the complete in that graph showed that you saw
all the studies we found that actually use unstructured portions.
So the way we write this is we found four,
six related terms and disparities for difference terms and try to get
the ones that had a finding that had to do with biological sex.
And found 67,424
articles in Medline, but only 469
made it across to include machine
learning A and B related terms. So
we use that as
a proxy for the use of unstructured data,
because that's the only possible way that you can really process this.
So when we saw six specific
differences, Dems only would get the 67,006.
And when we add the text mining or in a beat terms, we go down to less than 1%.
And it might seem that it's like, well, it's okay.
It might remind you what 1% means.
It sends you rushing to finding your your charger.
So that's how we how I think we shall feel about this is like
what are only 1% or less than 1%.
There's this urgency to correct that and not sit
and think that is already done is not done by any means.
And there's a lot that we can be done.
There's a lot that we can learn.
Though, we could be missing key information, key actionable information
by not using these unstructured portions of the electronic health record.
So the anecdote that Assad
included about the finding that Dr.
Linder had and the images of the use of silicone for cardiovascular surgery,
something like this might be already happening in one after another study here.
So if we just use coded data in this particular paper,
they were looking at hypoglycemic occurrence and severity extracted
from each other data when they use only codes, ICD nine codes for it,
they found about an even number of of a serious of
I mean they use any any of this
sorry with severity extracted only from gold.
Hypoglycemic occurrence
seemed to be about 46,000 from the from the dataset that they were using.
When they threw in an OBE, they found 83,000 about twice
as many occurrences were in a were identified.
And the actual balance of them also varied a little bit.
So we found they found a lot more of them mild and moderate.
Recorded their
cereals were still a. A
good number deals with an upbeat.
When you combine them though, the power comes through.
So when you combine A.P.
and ICD nine data, they file in the same dataset
about three times as many events.
Even if you discount the mild and moderate, they're still looking at
about twice as many using an API and ICD nine combined.
So the power structure, the structure portions of the record
is still untapped given the few that are there.
So moving from real world data
to real world evidence requires this advance
and AP machine learning and artificial intelligence approaches
that can really get everything that's there and put it into
the right conclusions and the right studies.
So just to give a sampling of of this challenges,
the challenges, obviously, real world leaders start from extracting the data .
So the methods are not widely available.
Many are just adult to the specific institution.
This example of of being able to deploy something that was done in one institution
and then applied to like the all of us data.
Those are the kinds of things that we're looking for.
We're looking for ways that we can deploy methods generically
or with minimal adaptation in different datasets.
This steps, unfortunately or this method unfortunately,
are inaccessible to the average healthcare researcher in general.
And then it's very hard to make sure that the data
that you're getting is high quality or was done in the proper way.
So that's also throws a little bit of a over
the dampening effect
on the use of the ATO, the extraction of the data.
The guidelines are lacking.
So using the data becomes challenging because the researchers don't have
a specific pathway to incorporate the data into traditional studies.
There is specific things that need to get to be done
before this can even happen, like normalizing terms.
So we're talking about adverse effects.
You need to normalize them so that all of the references to specific
adverse effects will be accounted for.
And then even probing the value of the data, it becomes difficult.
Many times it is dismissed as violence or very noisy.
It is difficult to think for funding.
Not impossible, but difficult because then you have to go through
many hoops that people are not familiar with and on.
Try to demonstrate that you're doing things the right way in order to
extract this data.
Use this data on a on a blight on the board.
Publication process is also difficult.
There is no standards, as there has been for a long time,
a standard of sharing data like genomic data.
But sharing data extracted from unstructured portions
of of records has a double
barrier there in privacy
and in just the practicality of sharing for reproducibility.
So there's still many challenges.
I will briefly, in the time that I have with me that I have, still
will share a couple of the projects that we've done
with funding from the NLM
and that we have share for general use.
We have datasets, we have annotated datasets
and we also have this pipeline for for processing this.
The Baby Minor is of the first end
to end pipeline for adverse event detection from social media.
It is now usable.
Actionable.
You can take data from the streaming API
and filter mentioned.
This is collected using drug names and variants
of drug names and then filters and classifies.
The user post for drug mentions identifies
a span of a name entity for ideas.
And then normalizes to the Arabs.
And he has been validated
and it can really be used
for taking advantage of this as a constant flash of data
that is still being directly from from users.
So we have numerous publications that they will do like 30 or so in
different findings from different analysis for different studies.
One of the, the the other was that
we have running on this
here is where the social media data
can be seen as complementary to a lot of the
of the studies that we have traditionally done in pregnancy.
We collected a cohorts of over 500,000 pregnant
women over now five years at three years at the beginning.
And then we would find it
have run studies on birth defects.
We have run studies on.
Now the latest ones
are on Kobe vaccine and other medications.
But basically,
just so you understand how this longitudinal data can contribute
to the body of knowledge that we have,
we get a.
Identify of women that announced a pregnancy and social media.
And then after filtering and classifying,
we can get the whole pregnancy timeline and tweets done during the pregnancy,
particularly in early pregnancy, and then after the baby's born.
So we can identify birth defects, we can identify
either illness or medications that we're taking at the beginning
of pregnancy, even before the woman herself
knows that that she's pregnant.
So we have
a very valuable data set that can be mined for four,
four different health studies.
Then we have also my social media
for the admission of changes in medication treatment.
So people share openly why
they change their medications or when they change their medications.
On mining, the resources becomes very important for us
studies in adherence and tolerability because many mild
adverse effects that are not even reported sometimes to payers.
The data database are the cause,
the underlying cost for switching medications.
So we have findings on
on this particular aspect of it.
Just to give you an idea.
So the adverse drug reaction was mentioned as a reason for medication switching,
about 99.2% of the of the
tweets that we found that mentioned changes in medication.
So so adverse effect was number one, the number one reason.
And so studying them in relationship to specific medications
will be something that can be done with social media.
Unique findings from social media can also be done by reducing the volumes.
To avoid that, it can be used in a mixed method study.
So this one in JAMA Network Open
was a box that is posted on Twitter and it was a qualitative study.
It was done by hand, but the only way that it can be done
by hand is by having all the automatic methods that can reduce it to the point
that humans can look at it.
And we found an interesting and interesting thing
that was not published in any other study about the use of statins
is that people were using them
as a as a way,
as a license to leave a eat and unhealthy diet
and not exercise because they are on studies.
Therefore, they no longer have to do any of that.
So so this
risk compensation behavior
became evident in not just one week, but in a number of the tweets.
And it required I mean, it is the way we took it is location lives.
Now, try to see if we can do another study, traditional study.
So in equal feed,
a traditional study says, well.
So all findings continue or data sets continue.
And I can say without a doubt that my career continues
because of all of this wonderful, wonderful
contributions that Dr.
Limber brought to our field.
And I can say that that basically is the birth of the field of medical informatics
is because of his vision
and his contribution to our.
Health studies.
Thank you.
Thank you so much, Graziella.
I think that was a great overview of your body of work
and also how an alum has been so influential
in that work.
I would like to introduce our final speaker, Dr.
Nicholas Seto Nati, who is Associate Professor of Biomedical Informatics
in the Departments of Biomedical Informatics Systems, Biology and Medicine
and is Director of Clinical Informatics at the Institute for Genomic Medicine
in the Comprehensive Cancer Center at Columbia.
He received his Ph.D.
from Stanford, where he focused on the development of novel, statistical
and conventional methods for observational data mining.
He applied his methods to drug safety surveillance and for the discovery
of dangerous adverse drug effects and in fact,
has identified and validated
previously unknown in serious drug drug interactions.
His lab at Columbia is focused on using this massive scale,
real clinical and molecular data for making robust and validated
scientific discoveries with a particular focus on detecting,
explaining and validating drug effects and drug interactions.
Dr. Antonetti is passionate about the integration of real world data,
such as those stored in electronic health records
into high dimensional data captured with next generation
sequencing, high throughput screening and other omics technologies.
And he does that to reimagine and rescale the scientific scientific method.
So please welcome Dr. S.A.
speaking on observational data for biomedical discovery.
Thank you for that amazing introduction.
And just to start, I just want to say super honored to be here
and speaking one with my amazing co panelists.
And then also for today and talking about Dr.
Lindbergh.
It's interesting.
I never got a chance to meet Dr.
Lindbergh in person,
which is unfortunate for me, especially because
it sounds like the more I read about him and hear about him from stories,
that his sense of humor is something that I would have really appreciated.
And but through all this reading, which has been just fantastic,
I've got to read some of his work and some of his writings,
but also a lot about perspectives on his impact on the field.
And it's been fantastic to see and kind of eye opening to see
all the ways that he's influenced me and even to the point
of some of the things I say
and some of the things I think, which I think are totally my ideas
were so clearly derived from his ideas
and planting the seeds far before I ever had a chance to learn them.
So I think it's really been a wonderful journey of self
and of exploration to rediscover Don in this way through his writing.
I just want to highlight one thing I read about him, which I thought was so cool,
which is in the sixties he was,
you know, like a lot of us in our early days, hacking
around, figuring out how to turn computers into things that do work for us.
But in the sixties that a lot of different technology than what we have now. So
so they were using punch cards and he actually built
the first laboratory information system using punch card programing.
And just 20 years later, he built the first A.I.
system to diagnose Rheumatologic disease.
So to go from developing on punch cards, which is something very advanced
laboratory information system on punch cards to developing a first say I for you
it's a logical diagnosis is one amazing and then think about that
just 2030 years later he was there to see the emergence of these tools,
these tools that we think of now
and all of the groundwork that he laid to make that happen.
So it's just been super great.
So I'm going to tell.
So I was also one of these trainees of the TI
15 program during my, my pre doctoral period.
And so I thought it would be fun to kind of dust off some slides.
So you'll see these slides are actually square shaped, they're very old
and tell the story of my Ph.D. work and then kind of couple
that with a newer version of that story that we've done then at Columbia.
And that I think is actually
really I didn't realize this
at the time, but really follows the philosophy that Dr.
Lumbergh had.
So I'm just going to dove into it a little bit here.
I love observational data
because observations start everything.
Charles Darwin sailed around the world to collect observations
of the biological world so that he could form new hypotheses,
hypotheses that we now know developed into the theory of evolution
in pharmacovigilance and drug safety, or some famous seminal scientist.
MacBride and once clinician scientists who discovered the association
between thalidomide use and birth defects, really kicking off
modern drug safety surveillance as we know it today.
And they all did it because they were making observations.
Darwin of the biological world, McBride and Lenz
of the clinical world, the patients that they were taking care of.
Now we're making observations at a scale
that dwarfs what these early scientists were able to do.
They were collecting data with their human senses.
It's an amount of data that you could describe on a
on a very small disk drive with bytes or terabytes of data.
Lindbergh could have coded this on his 20
kilobytes of RAM and his first laboratory information machine.
Right. Very small amount.
And now with new technologies like sequencing data and sequencing
hundreds of thousands, even millions of patients,
we have huge, massive datasets to trawl through.
To look for new hypotheses, to make new discoveries from.
So it's gone from being where we had just to observe our patients.
Maybe when they walk into the clinic and just clinician scientists
really having the opportunity to now having these electronic health records,
which you've seen, mentioned
multiple different ways and across y different strains of projects
that give us the ability to form hypotheses.
All of us gives all of us the ability to form hypotheses
using this data as a secondary data set, using it for discovering.
Now very widely used around the world.
I like to think of every drug order as an experiment.
As Josh said,
we can learn from every clinical observation.
And how do we do observational analysis?
How do we form hypotheses?
Well, when we're trying to do something that on an order of magnitude
much greater than traditional scientists has been able to,
we have to employ computers to help us do that.
I think part of Bloomberg's vision was really about
how do we use computers to help with every phase of the scientific method.
And one of those being generation of hypotheses.
And I like to think of data mining as really this phase.
It's using computational tools, informatics tools,
data science tools, whatever you want to call them today.
But it's using these advanced tools
to get computers to generate that hypotheses for us.
There's a problem with using these types of tools
and using observational data, and that has to do with confounding bias.
So I love to illustrate this with a picture of a couple of birds.
And here we have a blue bird and a red bird.
And so imagine that you live I live across the street from Central Park.
And so imagine we're walking around Central Park one day and we want to know
the relative populations of these birds that live in Central Park.
And so you walk around and you make tick marks on a notebook.
Every time you see a blue bird, you make a tick mark on the left.
And every time you see a red bird, you make a tick mark on the right.
And we get back to the apartment and we notice that we observed
five times as many blue birds as red birds in our walk through Central Park.
Now, what does this tell you about the simple question you wanted to ask,
which is what is the relative populations of these birds in Central Park?
Well,
in fact, it tells you absolutely nothing,
because I'm going to tell you something else about these birds.
These birds like bluebirds, you might be able figure out by looking at this image.
They're very friendly.
When they hear people come into the park, they fly to them and they treated them
and you notice them. The red birds, they hide.
They don't like people at all and they flutter and fly away.
And so the behaviors of these birds have actually confounded the data
that you were able to collect, making it impossible
to answer the simple question you have.
And this is not just true in our hypothetical example,
but this is true every day in the hospital system.
Patients, providers, health care practitioners are all making decisions
and their behaviors change.
What we can observe and these are observational data sets,
and their behaviors may invalidate them for very simple questions
that we think we could answer using these data.
I'm going to show
how we can focus on example of drug drug interactions
and through multiple data modality integration, we can actually address
some of those limitations and make real discoveries.
So drug interactions are a common cause of adverse events.
And understanding them will lead to better outcomes is very common for patients
to take multiple drugs at the same time, and that increases with age.
Right now, the main way in which we monitor the safety of drugs
when used in combination is through observational studies.
Clinical trials don't have the sample size or the power really to investigate
drug drug interactions holistically.
So we turn
to these large observational databases like the electronic health records
and like other databases that governments or inter-governmental organizations
maintain, like the FDA spontaneous adverse event reporting system.
And these are collections of adverse event reports
which are submitted by physicians and patients and providers
that we as pharmacy pharmacovigilance scientists can use to look
and see if there are any early signals of drug safety concern.
We decided to use this to study drug interactions.
The problem is most of the reports that are submitted submit spurious annotations.
Most of these drugs don't cause these adverse events,
and it becomes very difficult to decipher any one report.
As you can see here,
so what we did is we
identified some common sources of bias, one that came from concomitant drug use.
Basically, if two drugs are used together, it's very common for them
to be associated with the other drugs side effect.
And another bias that came from indication, namely that if a drug
is really commonly used for a specific indication, it's often reported with
that indication signs and symptoms and not actual those actual drug effects.
We use these to design a new algorithm, which we call the statistical correction
of uncharacterized bias that implicitly corrects for confounding.
We were able to apply this to discover
drug effects much with much more accuracy.
In one example, we were able to show that we can reduce
false positive rates very significantly while maintaining positive signals.
Now, what I'm showing you here is a set of antiarrhythmic acts
antiarrhythmic were commonly associated or reported with arrhythmia.
Many of those associations are actually spurious. They're
because of the indication being treated and not because of the drug itself.
But dope, it's allied
is one example of an antiarrhythmic that has a very narrow therapeutic window.
And in fact, it is known to increase arrhythmia in many patients.
And so what you can see here is in these circles,
our corrected measurement after we apply our method to correct for these signals.
And in the diamond's the original estimate,
we see that we've reduced the signal in most of these cases, but maintained it
for some important pro review signals.
Overall, we're able to show that we can implicitly correct
for age differences in these large observational cohorts.
We were showing you here are the 20 most biassed drugs
in terms of the average age of a patient taking these medications.
So then the top here, zanamivir is a drug whose average age of a patient
taking this is about 30 years younger than the average of the entire data set.
If you did a naive analysis without accounting for age,
then that would be a significant confounder.
But what we're able to show is that many of these top 20
we can implicitly correct for this without modeling age itself using our models.
So we're able to show that we can correct these biases.
Now, can we actually infer missing data stuff
that might not be directly reported or even observed?
Now, drug drug interactions are really common,
are commonly affected by this
in that there are not a lot of reports for drug interactions
and they may not be observed even when they do occur.
So we'd like to be able to implicitly identify them.
We built a model, supervised machine learning model
that was inspired by the way that physicians diagnose disease.
So when you walk into the hospital, you may have diabetes,
but you don't have diabetes written across your forehead.
Instead, it lies under some level of detection.
And so but so the doctor will instead use certain signs and symptoms.
So you might have pain in your extremities,
might have sweetened urine, or you might have high blood glucose.
These collectively can be used to form
a diagnosis of diabetes, even though it can't be directly seen.
So we're going to do something very similar.
But for adverse events, we hypothesize that there's a very severe adverse event,
drug interaction that is being unmeasured or unobserved,
but that through a collection of different signs and symptoms or other side effects
that are commonly associated with that more severe event, we can build a model
that can identify and then infer the presence of the drug interaction.
So we did that for several different types of models.
One was for a type two diabetes model.
We're able to predict if or try to identify
if drug combinations were increasing blood glucose.
Our top prediction from this was between paroxetine and Pravastatin.
Now, paroxetine was an anti is an antidepressant
that was commonly used at the time.
And Pravastatin was a cholesterol lowering drug,
one of a class of statins, which of course are very popular drugs over.
We estimate about a million patients are on this combination.
Back in about 2010.
So we did, though, as we went to a new database,
the totally different source of data and the electronic health records,
which was pretty novel at the time, and analyzed blood
glucose values for patients taking those combinations of drugs.
And what we found was that in patients taking the combination of drugs,
there was a significant increase in the blood
glucose values exposed for those patients exposed to that combination and no
change for the controls.
And when we include diabetics, we actually see an exaggerated increase
of 60 milligrams per deciliter increase in the blood glucose values,
something that could complicate diabetes therapy and treatment.
Now, this is where another parallel that I found between Dr.
and Bird existed,
because when I would normally give this talk, I would get to this point.
It was very early in my career.
I was very excited about this and I would give talks to maybe
different faculty or different seminars on campus and ended up
giving a talk to an epidemiology seminar.
And at this point they were very excited and thought that was very cool.
But they're also very concerned about confounders that I hadn't considered.
What times of day are these glucose values take in?
What are the patient populations?
Patients who are taking multiple drugs, probably sicker than patients
who take a single drug coming up with all different ways.
Kind of like Dr.
Linder faced a lot of pushback when he was first showing
the adverse events that he was discovering during surgery.
So ultimately,
what I ended up trying to do is go one step further.
And despite the weird build problem here, I did a mouse experiment
where we took mice and we gave we fed them this combination of drugs
and we measured their blood glucose to see if we could see the change there.
Can we establish this as a real causal relationship
rather than simply an association derived from observational sources?
So we had these mice
that we fed this high fat diet, put them on a pre-diabetic state,
and then we fed them combinations of these drugs.
And what we found was a 60 milligrams per deciliter increase in their blood
glucose values for
for the mice that were exposed to the combination versus the controls,
which is almost exactly what we found in humans and like Lindbergh
making headway with his fellow surgeons after he showed them the imaging data.
This really change the conversation for me.
And instead of being questions about confounding and why,
what other explanations there could be, the questions turned into biological
questions, questions about what the mechanism was.
Was it pharmacokinetic or was it pharmacodynamic?
How could we follow up?
What additional experiments could we do?
And it really changed what my entire career from that point on,
realizing the power of
using observational data coupled
with experiments and other validation techniques to establish causality
has been kind of
a hallmark of my career ever since.
And so that's the story I wanted to tell you today and another part of it.
But I was more fun
to kind of talk about my experience with kind of learning about Dr.
Ellenbogen and the many parallels.
And so I'm going to leave it at that, and I look forward to taking questions
and discussing with our my fellow members.
Thank you.
Thank you, Nick.
I think that's fascinating to to see how things evolved over time.
And this flashback of square slides was interesting, too.
Thank you so much.
So we have 10 minutes for questions.
And and I would like to start with one to to which one of you
if you were to pick one thing
in, we saw there are so many that Dr.
Lindbergh has done.
But what would you pick as like?
You know, I want to be like him.
I want to do X as well.
So why don't I started in the same order with Josh and Christi Island and Nick.
That's a that's a big question.
You know, I think a profound impact in leadership of an airline would be through
all the resources that were created and CBI, you know, sort of driven,
you know, has gone John Pub Mad Puppets, etc..
But, you know, when you when you phrase it as you did around
a personal characteristic, it would be that, you know, a doctor
wearing a computational hat, exploring the world
in a humble,
dry sort of way, at times
influencing a culture to investigate,
explore, learn and improve care.
You know, and that's a much more personal aspect of taking it.
And I think that character of his was so influential
on so many people.
Actually, I think we saw you may have been muted briefly.
Oh, thank you. Thank you, Josh Graziano.
Well, I think from
from my personal interactions with him, one of the things that struck me
and that I would like to emulate, I guess, is his capacity to listen.
So he will listen with attention.
And you sometimes
you get the feeling that the people like seem to be listening.
But the first thing they say, after
you finish something, they say something about themselves or something
about like totally different things that you were talking about.
But he will like question and he will bring examples.
So I remember on a more personal level, we were like
registering for one of the NLM events and he was by me
and he noticed that I had my nine year old with me.
So I took her on that occasion
and he started telling me about taking his own kids to conferences
and as, as he traveled and, and how much she'd made it made a difference to them.
And so so he's just a simple example,
I guess, nothing of the grandiose things in data that he did.
But I think it just reflects a way to go through life and listening
and noticing and then making making sure that the person that you're with.
Can understand or can see things the way you see them.
And by doing that, you learn.
What is it that it will take to show
this person, be it a group of physicians or whatever
it is that you're communicating with the best set of data
that that that exemplifies or that makes a point that grows better.
Thank you so much, Graciela and Nick.
Yeah, I think you know, I think it's the
I love those comments and the ability to listen.
I think that's so important.
And I think that's coming through.
What I hear and read about is leadership style.
And just I know I've been affected by the ability, if I could emulate
anything would be kind of the ability to lead by example and not by dictation.
And I think that that is a critical skill that is sometimes forgotten.
But when people have it and they do it right, it has such a broad impact.
And I think you're seeing that
with all the people that have been so strongly influenced by by Dr.
Lindbergh.
Thank you so much, Nick.
And abusing a little bit my moderator role.
Let me include my own account of what
I think is a tremendous and most influential
aspect of all his work.
I would say even though we cannot
measure directly, PubMed saved more lives than anything
any other computer intervention that I've ever seen.
And I like Zach.
I remember the times when we didn't have free access to that information.
It was so hard to get into a library,
go through books, or even the CDs
that were sold at the time in PubMed made such a difference in PubMed central
with Betsy and his work as well
is just extending that to yet another level.
So with that, I would like to conclude
and say that the legacy is
so large that we can with three panelists
in an abusive
moderator.
Praise everything that Dr.
Lindbergh has done.
But it has been such an honor to host this panel
and to be able to comment on this so many great achievements of Dr.
Lindbergh.
So thank you all and we'll see you next session.
Jeff, back to you.
Yes. Thank you, Dr.
Machado. Doctors Danny Gonzales.
Gonzales, Hernandez and and Nettie, thank you
very, very much, all three of you, for your outstanding presentations.
And Dr.
Machado, thank you for your chairing this very thought
provoking panel, and we appreciate it tremendously.
A lot to think about, a lot to reflect on for today and certainly for tomorrow.
With respect to Dr.
Lindbergh's legacy in science and and leadership
and also certainly on on your outstanding research
programs as you continue them and especially respectfully, Dr.
Denny, with respect to your work here at NIH, with regard to the key all of us
program that you continue to lead so wonderfully and excellent.
We're going to take a break now for 90 minutes
and we're going to return at 130 Eastern Time.
We welcome you back then
and we wish you a good break as we will all take one here as well.
So thank you again for joining us today
for the 2022 and Working Lecture and Scientific Symposium.
We'll see you back here in 90 minutes. Thank you.
Welcome back,
everyone, to the 2022 Lindbergh Kean Lecture and Scientific Symposium
here at the National Library of Medicine, National Institutes of Health.
My name is Jeff Resnick.
I'm chief of the National Library Medicine History Medicine Division.
And it's a distinct privilege for me today to be moderating our proceedings.
For those of you who are just joining, please look for the live feedback
button under your video stream to send us questions or comments.
Continuing our symposium, I'm going to turn things
right over to my National Library Medicine colleague, Jerry.
Jerry, over to you.
Thank you, Jeff.
Hello again to everyone and welcome back.
I hope you're enjoying today's event as much as I am.
I am Jerry Sheehan.
I'm the deputy director
of the National Library of Medicine for Policy and External Affairs.
And I had the great pleasure
of serving with both doctors, Lindbergh and King, during their time here at ILM.
And I'm pleased to be part of the leadership team
that's building on their legacy and helping carry them into the future.
We're joined in that effort, of course, by many, many capable
colleagues here at NIH and beyond,
all of us working under the inspired leadership of our two next speakers.
It's my
great pleasure to introduce them to you, Dr.
Laurence Tayback and Dr.
Patricia Flatley. Brannon
They will I will introduce them both and then they will continue
with with their remarks.
So let me do the two introductions.
Dr. Tayback has been performing the duties of the director
of the National Institutes of Health since December 20th of 2021.
He previously served as the principal deputy director
and the deputy ethics counselor of NIH, and before that, as the director
of the National Institute of Dental and Craniofacial Research.
Before coming to NIH, Dr.
Tayback was a professor
and dean at the University of Rochester in the great state of New York,
being trained as a doctor of dental surgery and has a Ph.D.
in optics.
His major research focus has been on the biochemistry and
function of glycoproteins.
Dr. Tayback continues work in this area, in fact,
maintaining an active research laboratory within the NIH intramural program.
In addition to his administrative duties,
he is an elected member of the National Academy of Medicine,
Fellow of the American Association for the Advancement of Science.
It has been a great friend to the NLM
during his time here at NIH.
After Toback's remarks will be followed by those of Patricia Brennan,
the director of the National Library of Medicine
and alum, as you have heard today.
If you didn't know before, is there a leader
in biomedical informatics and data science?
Research also oversees and manages vast literature resources
that span ten centuries, including print and a lot of electronic resources
that are used billions of times each year by millions of people in the U.S.
and abroad.
As NLM director Dr.
Brennan has positioned as a hub of data science nationally and internationally
and a lims extensive data information resources
are used to accelerate discovery, to engage better with new users
and help advance a workforce for a data driven future.
Dr. Brennan has a master of science degree in nursing from the University
of Pennsylvania and a Ph.D.
in industrial engineering from the University of Wisconsin, Madison.
She, too, is a member of the National Academy of Medicine
and holds fellowships in the American Academy of Nursing,
the American College of Medical Informatics
and the American Institute for Medical and Biological Engineering.
When to welcome both Dr.
Tabak and Dr. Brennan.
Thank them for joining today's symposium.
And I want to turn things over to you now to start us off.
Back to back.
Thank you again.
Well, thank you very much.
It's certainly a great pleasure to be joining you
all today for the Lindbergh King Lecture and Scientific Symposium.
And it's a particular honor
to be here to discuss the science,
society and the legacy of the Dr.
Donald Lindbergh.
I want to thank the hosts, the National Library of Medicine
and the Friends of the Lab, and,
of course, the many excellent speakers.
Now. Dr.
Lindbergh was a true visionary and pioneer.
As many of you know.
He was the director of the NLM for more than 30 years,
from 1984 to 2015,
and indeed was one of our longest serving leaders
at the National Institutes of Health.
Dr. Lindbergh received his M.D.
from the College of Physicians and Surgeons at Columbia University.
And I received my doctorate dental surgery degree
from the School of Dental Surgery, same institution a few years later.
But we did share stories
about faculty that we knew in common, and in particular what the surrounding
community was like during each of our tenures at the institution.
Dr. Lindbergh was always forward looking.
He was one of the very first to predict that computers would become
increasingly useful in biomedical research and in patient care.
And he he foresaw that medical informatics
would emerge as a formal research field and academic discipline.
Again, as some of you know, his training initially was as a pathologist,
but remarkably, he was able to reinvent himself
to become a leader in the use of computers, in medicine.
Dr. Lindbergh helped establish the American Medical Informatics
Association and became its founding president.
And he made notable contributions
to advanced information science
for use in medical diagnosis,
artificial intelligence and educational programs.
He created programs that transformed our approach
to information.
While Director of NLM, he developed long range plans
that really help deliver on these predictions that he made.
Under his
leadership, NLM embraced the Internet,
enabling the public health care providers and scientists
to have far more access to the medical literature,
clinical trials and consumer
health information than ever imagined.
He was committed to delivering high quality health
information to all from health professionals to the public,
no matter where they worked, lived, and at no cost to them.
Many of the resources he pioneered
remain in wide use today.
PubMed and PubMed central
repositories for medical literature.
ClinicalTrials.gov which provides
access to clinical trials and their results.
And Medline plus, which provides
consumer health information.
Dr. Lindbergh was integral to the establishment
of the National Center for Biotechnology Information, or NCI,
which is a division of the National Library of Medicine
that provides access to biomedical
and genomic information .
The NCB became a focal point for big data
before that term even became fashionable
and remains so even today.
NCB I supported databases
includes things like GenBank or Debugger.
Edition. Dr.
Lindbergh led important inter-agency programs.
He was the founding director of the National Coordination Office
for High Performance Computing and Communication
in the White House Office of Science and Technology Policy.
And he was the U.S.
national coordinator for the G-7 Global
Health Care Applications Project,
a framework for international cooperation
in medical informatics.
I'm so very pleased to see that Dr.
Lindbergh's scientific legacy is well-represented here today
by a diverse group of inspiring advocates
for bioinformatics, precision medicine,
computational sciences and library management.
We've certainly come a long way over the years,
yet much remains to be done.
My hope is that today's distinguished speakers,
along with all of you who are listening to their words,
will work together in concert to continue to advance
back to Lindbergh's exciting vision for the future of biomedical research.
Dad, I thank you,
and I'm very pleased to turn it over to my colleague, Dr.
Patricia Brennan.
Thank you very much, Larry.
Let me begin by thanking you for taking the time to be with us here today.
You are a colleague and a mentor to me, and I'm grateful for that.
I want to thank all of the people who worked to make this session come to
to for lots of planning, Jerry and and Jeff and in particular,
our friends at the friends of the National Library of Medicine.
This has been an important day.
My thanks also to all the speakers.
As I prepared my remarks, I reflected on the question,
What do you get when you stand on the shoulders of a giant?
What can you see?
I've had the good fortune of becoming the director
of the National Library of Medicine and l'm immediately
following the 30 plus year tenure of Donald A.B. Lindbergh.
I'm sure that each of you today treasure your own recollections of Don,
maybe from a conversation you've had or a laugh you've shared
with this great leader, this teacher, this visionary and colleague
who is also a husband to Mary, a father, a grandfather and friend.
I am both proud and humbled to stand on the shoulders
of this giant as I leave this incredible organization.
I know more viscerally than most of you.
Don's legacy as the director of the National Library of Medicine.
I sit in the office he occupied.
I walked down the halls. He walked.
I work with many of the people he hired, and I see and experience every day
the fruits of his judgment, his investments and his vision.
I also now sit where Don once set representing
the National Library of Medicine at the leadership table of the NIH,
along with the other institute and center directors.
Because Don paved the way, I have a platform to extend
the National Library of Medicine's
thought, leadership and technical assistance to guide the NIH,
its continued efforts to advance data driven discovery.
The goodwill and collaborative spirit engendered by Don across the NIH
opened doors for me and helped me deliver on his legacy to advance the promise
of science accelerated by broad access to the literature and data.
Don and I shared a particular commitment
to ensuring that the public benefits from indolence, efforts to assemble,
organize, preserve and disseminate biomedical knowledge for society.
It was his early vision that made Medline plus a trusted resource
for consumer health information and ensured that the Medline
excuse me, the PubMed Citation database and the PubMed central literature
repository were made open and accessible to everyone everywhere
with an internet connection at any time and place.
Please watch this video to take us back almost 25 years
to see the beginning of this effort.
Today on Capitol Hill, the National Library
of Medicine's Medline Internet database is made free to the public.
The superhighway on medical information
will now become a freeway.
This development by itself
may do more to reform and improve the quality of health care
in the United States than anything else we've done in a long time.
We actually it nlm alone answer a million inquiries a day, a day, a day.
It's a staggering amount.
It's going for 400 million a year.
We have tens of thousands of genomes, not just one.
And all of that has to be assembled
in a place where people can compute on it and learn from it.
And that's where in L.A.
is just a central hub of information that we all depend on.
Researchers are downloading data equivalent in size to the contents
of the entire Library of Congress every week.
That's amazing.
The real heart of Pupkin is
the links from each chemical
to other sources of information about its its biological properties.
When we were formulating the Framingham Share Program,
which in which we wanted to genotype the 10,000 participants
in the Framingham Heart Study, we wanted to put the genotypes
in the phenotypes together in a common database.
And before we knew it, there was DB gap database,
genotype and phenotype.
Oftentimes the National Library of Medicine
that I turn to, and not just as a reporter but also as a doctor,
there are 23 million citations on PubMed.
ClinicalTrials.gov is a place that I often send my patients.
I push Medline, plus I eat.
Breathe.
Medline Plus is just amazing, you know,
the amount of information that they have on the website.
You know, today there is virtually no lag between,
you know, is coming out of any kind of research activity.
And it's it's a clinical application.
The basic reason for that is what the National Library has done,
taking advantage of the new technology for the transmission of information.
Commitment to the public was also evident in his efforts
to educate the next generation of biomedical informatics scholars.
Frankly, I believe that of all the aspects of his job,
Don's engagement with the trainees was his favorite.
When you stand on the shoulders of a giant, you have a great advantage.
The foundation Don built and the relationships he established
provided me with a playbook right out of the gate.
However, I know that it is not enough to solely
rely on his vision to guide our future.
In one of our last conversations, he said to me, This is your game.
Make sure you play it well.
Well, in order to do that, I cannot simply stand on the shoulders of a giant.
I must keep my head up and my eyes forward to the future, to envision new pathways
and find new opportunities to bring forward the richness
of the National Library of Medicine for the benefit of science and society.
I close by inviting you to stand with me on the shoulders of this giant
to meld your sites with his , for it is not by holding tight
to that which he could see, but by using his vision
as a stepping point for our own that we will best serve his legacy.
Thank you and welcome.
Thank you, Dr.
Brennan. Thank you, Dr. Tayback, for your remarks.
And yes, I think highlighting the contributions and the legacy of Dr.
Lindbergh in the NLM and all of our services and users to the NIH community
and beyond internationally across the federal government.
Appreciate your comments on all of those dimensions of Dr.
Lindbergh's legacy.
And with that, want to help us move on with our program.
So, Dr.
Reznick, let me turn things back over to you for the remainder of the afternoon.
Thank you very much, Jerry.
I certainly echo your thanks to Dr. Tayback and Dr.
Brennan for their remarks,
which certainly underscore the scientific and leadership legacy of Dr.
Lindbergh in the current and certainly the future work of our institution.
Before we begin the next part of our program,
I'd just like to remind everyone watching
that today's proceedings in their entirety are being recorded
and will be made available soon in the NIH Video Cast Archive.
This archived recording is significant because it is permanent.
So many more can appreciate today's programs
and the wonderful presentations that we've heard.
And I'll also add that this permanence is apropos the legacy of Dr.
Lindbergh itself, its own permanence, in fact,
indeed its influence on the lives of so many
in library circles, many of
whom we've heard today, and many more who are watching, of course .
So now it's my distinct pleasure to introduce my colleague, Dr.
Clement McDonald, who will offer a personal remembrance of Dr.
Lindbergh.
Dr. McDonald is the chief data
chief health data standards officer here at the National Library of Medicine.
And in this role, he coordinates standards, efforts across the NLM
and the NIH, including the fast health care interoperability resources or fire
interoperability standard and vocabularies specific to clinical care.
Dr. McDonald previously served a dozen years as director of the National Library
of Medicine's Lister Hill National Center for Biomedical Communications
and as scientific director of its intramural research program.
Dr. MacDonald's research
focuses on electronic medical health records.
EMR says their use in clinical care and research
and data standards needed to feed yamaha's
and epidemiological studies of clinical databases.
Welcome, Dr. McDonald. I'm going to turn things over to you.
Thank you for joining us.
Excuse me, Clem, you're on mute.
We're not hearing you and Dr.
Hell slides the rapture.
Okay. Yeah.
So I appreciate this chance to talk about my personal experience
with Don and reflections and the stories I hear about him.
So some people think of them as distinct,
as distant, and perhaps a bit stiff.
But actually, he was a fun guy.
You like the laugh. You liked it a lot.
He was a renaissance man with broad and eclectic interests.
He was an excellent photographer.
And he had his own darkroom, black and white and color.
He was a cowboy.
He and his children all had horses and rode them together.
He loved music, especially opera, and had a big collection of opera CDs.
He loved art.
I remember his interest in Turner's watercolors because the Indianapolis
Art Museum had one of the biggest US collections of Turner.
And he loved music, especially mezzanine.
So I would like to include also the heard.
This already is inclusion of medical record technology
as an important part of an album research.
It was part of his tool 2006 Strategic Plan,
and he believed breathing life into medical informatics
from the beginning of his tenure at the library.
So An Alarm was a major funder of medical research
until recent years, when urban institutes discovered it.
He fostered the creation of AMIA and was its first president.
And I was privileged to be as it is. Exactly.
And had a cabinet for two years.
I love to listen to him talk
extemporaneously.
His phrasing was polished, lively and clever just as it flowed out of his mouth.
As though I had written and had edited is also willing to say what he thought.
Tell it like it was a rare treat in Washington.
So after I joined it all and he and I would often meet
at the end of the day and toward the end of the meeting, he would say,
Hey, how about coming home to dinner with Mary and me?
That's a lot of what you can't really bring a guest home on such short notice.
What would Mary say?
And she always said, yes, I had many late
invitation dinners with him many, many times with Mary's cooking.
They were gustatory delights.
Some people saw Don and started tough and it could be.
There was also great fun. He loved to laugh.
So those meetings with me and Mary for a special treat,
he and Mary, I
really can involve the combined almost in everybody's mind
because they always work together and how they connected.
There's a readymade script for a romantic comedy.
I got this.
I had a long talk with Mary recently.
She's a she.
When she met him, she was working on a little baby
in the Vanderbilt pediatric treatment room at Columbia Hospital.
She and her team were unsuccessful in drawing blood
after two sticks, and as a matter of principle,
she would not stick a child more than twice.
So she sent a note to the lab saying, I will.
Unable to draw a blood sample down was a resume in clinical pathology at that time,
and he showed up shortly thereafter ,
asking very arrogantly, No, those are her words.
Who wrote this note?
I did, she replied.
And he continued arrogantly.
What have you trained?
And she said, Simmons College, affiliated with Harvard.
And she asked, Where did you train?
He said, Amherst.
And then very shortly they brought it out.
Amherst has a football game with Williams in October.
Would you be my date?
She said, Well, I'm engaged to be married in December.
And he said explicitly, maybe another time.
However, he found out the next day and asked her again and she said okay.
After that he asked her on another day.
Can't go that day.
I have a prior appointment.
The appointment was to sit for her wedding to another guy.
Somehow they worked out another date.
She lived in Manhattan and the date was in New Jersey.
Coming back, he became very lost and ignored all of her admonitions
about how to get back to Washington Bridge on the way to Manhattan.
They circle for hours and finally found, despite his stubborn resistance
to her advice on the way that day, he asked her to marry him.
No mass gathered under Dan's Street.
She said yes.
I asked Mary, How could you decide to marry him after two days?
She said, We spent many hours together in New Jersey.
I also had another great privilege.
Mary called me over to Suburban Hospital to join
the immediate family for his last two days.
It was no longer fully conscious, but occasionally responding
with a moment or a grimace that suggested he understood something.
We held his hand at times.
Those two days with him and his immediate family,
their most precious moments and his last hours.
I got to kiss his forehead, squeeze his hand
and say good bye, old friend.
Thank you very much for being a chance to
present these stories to you.
Dr. MacDonald, thank you very, very much.
For pulling together those stories and reflections of Dr.
Lundberg and certainly Mary as well.
Thank you for sharing.
It's now my pleasure to introduce our next speaker, Dr.
Sally Howe, who's going to be joining us today by prerecorded video
to speak about Dr.
Lindbergh's high performance computing and communications leadership. As
Dr. Howe began her government
career in 1980 at the National Institute of Standards and Technology Nest,
where she worked in statistical computing and computational geometry.
And there she was, chief of the Scientific Computing Environments Division.
In 1992, she joined the newly established National
Coordinating Office for High Performance Computing and Communication, or PCC.
She worked there and at its center, the National Coordinating Office
for Networking and Information Technology R&D until 2007,
including as Associate Director from 2001 until 2007 .
From 2007.
Until her until her retirement in 2017, Dr.
Howe was at the National Library of Medicine
for the National Coordinating Office for HPC, have been located
since the mid 1990s and Elm. Dr.
Howe worked in the areas of health effects of climate change
and she built the print archive and finding aid
for the National Coordinating Office for PCC.
We certainly appreciate her pre-recording her presentation
as part of today's proceedings.
So I'm going to turn it over to Dr. Howe.
Hi. My name is Sally. How?
Thanks for inviting me.
My talk is about Don Lindbergh's high performance computing and communications
or HPC C Leadership and legacy.
Don Lindbergh led the HPC C program from 1992
when it was created until 1995.
I joined the new National Coordination
Office for HPC C in 1992
and stayed for 15 years.
I'll talk about events from the 1980s to the present.
Next slide.
This quote is from Walter
Isaacson's 2014 book, The Innovators.
It captures the impact of Don Lindbergh's HPC leadership.
It was a two step process
over the course of more than three decades, the federal government,
working with private industry and research universities,
designed and built a computing networking and information technology, research
and development or R&D program to help
federal science and engineering agencies.
Those efforts were formalized in the presidential HPC program.
Don Lindbergh was its first leader.
He laid the foundation and the framework for the program,
which continues to this day.
Walter Isaacson went on.
Then the government, through that infrastructure, open
to ordinary citizens and commercial enterprises.
This was the national information infrastructure
or and AI or Al Gore's information superhighway.
In 1994, the HPC program was asked to add R&D
for the I, Lindbergh and HPC.
He didn't miss a beat.
The HPC Plus and AI community
funded and conducted the R&D to make America's
digital revolution of Isaacson's title
The Extraordinary Success That It Is.
Next slide.
This story begins inside
eight federal science and engineering agencies.
Researchers say researchers and managers
in those agencies were making two discoveries.
Computational science, modeling and simulation was proving itself
to be the third leg of scientific inquiry,
alongside experimentation and theory.
In fact, computational science could do things that experimentation
could not do, such as modeling and simulation of phenomena
that were very big or very small,
very fast or very slow or very far away.
It could do modeling and simulation of phenomena
that were dangerous to health or safety
or were prohibitively expensive.
So computational science could help the agencies achieve their mission goals.
They were also
discovering that a supercomputer architecture could do both numeric
calculations and symbolic or text processing.
The agency needed both.
Those eight agencies were the Big Four,
the Defense Advanced Research Projects Agency, the Department of Energy,
the National Aeronautics and Space Administration,
and the National Science Foundation.
Plus the National Institute of Standards and Technology.
The National Oceanic and Atmospheric Administration,
the Environmental Protection Agency and the National Library of Medicine.
Next slide.
Given those discoveries,
the agencies found they had common needs to do computational science.
They needed general purpose supercomputers
for unclassified science and engineering R&D.
The agencies were funding R&D by manufacturers who were building
supercomputers that agencies and the private sector were buying.
They needed high speed networks to connect
supercomputers to the researchers who used them.
They were funding R&D by companies that were building those networks,
and the agencies and others were buying services.
The agencies also
required that their networks be interoperable.
All together, the agencies were funding and developing
the technologies underlying the Internet.
Those supercomputers and networks
would need to be ever faster and more capable.
That meant long term R&D, largely in universities and technology companies.
It would be expensive.
The agencies wanted to divide up the work
and have access to the results.
In those early days, few were thinking about ordinary
what ordinary citizens might need or want.
Next slide.
Under the umbrella of the Office of Science and Technology
Policy or OSTP in the Executive Office of the President.
The agencies laid out their case in a series of reports.
They recommended a balanced federal
R&D program in computer hardware,
software networks and education and training.
Next slide.
Their grand challenges, reports said.
Why grand challenges are fundamental problems in science
and engineering that have broad economic and scientific impact
and require high performance computing.
They spend climate and weather
machines like airplanes and cars.
The life sciences and general purpose tools
like visualization, imaging and virtual reality.
The visionary Don Lindbergh had written the book
The Computer and Medical Care in 1968.
He long knew that medicine and health care
needed powerful computers.
With the Global Change Research Act
becoming law in 1990,
Lindbergh observed that climate change was considered important
because it affected people.
He said he joined the next motor agency program
that also affected people.
That was IPCC.
Next slide.
What did Congress do?
It held hearings and funded R&D and procurements.
Senator Gore
and his colleagues in the House of Representatives
introduced high performance computing bills.
University and industry witnesses testified at hearings,
conveying support and offering good advice.
The HPC Act became law in December of 1991.
The EP said that the United States needed high performance
computing for national prosperity, national and economic security,
industrial production, engineering and scientific advancement.
That's still true today.
The act created a presidential program,
not the program led by an agency,
and was assigned responsibility to OSTP.
While informal planning and coordination had been fine,
a presidential program with growing requirements
and budgets and visibility warranted formal coordination.
That's where Don Lindbergh comes in.
The authorized appropriations
from sums otherwise authorized to be appropriated.
Funding was and still is
part of the regular budget process.
It wasn't a competition.
The law didn't give the program a name.
For many years it was the High Performance
Computing and Communications Program.
Next slide.
In the summer of 1992,
OSTP asked Don Lindbergh to lead a IPCC
that had two parts chairing the subcommittee,
which already existed and heading a new national coordination office.
Everyone was delighted.
He was the only HPC person who had both a national
and international reputation.
His selection signaled how important the government
thought both the program and the grand challenges were.
The agencies knew him and ILM,
and he could rely on the LIMS infrastructure
to get the CEO started quickly.
Next slide.
He set up a six person National Coordination Office.
Three of those people are in this picture, Dr.
Lindbergh's executive assistant, Pat Carson, and Charles Carlino,
who was the executive secretary of the chipset subcommittee.
The other three were a person and detail from there.
So an administrative assistant and myself.
Then on detail from this
next slide.
As we all know, Don Lindbergh was a curious
and voracious reader and a thinker across not just medicine and health care,
but also science and technology and the humanities.
He thought about how science and technology
could help people
before the HPC became law.
HPC people naturally associated themselves
primarily with their own agency or university or company.
They thought of themselves individually as hardware people
or software people or networking or applications.
Don Lindbergh helped them forge a new additional identity,
inviting them to his actions and his words
to be part of a broad HPC R&D community.
He did that by speaking at conferences and workshops on HPC
topics and visiting supercomputer centers.
He and the chipset met with supercomputer center directors,
leaders of software companies and leaders from the telecommunications industry.
He met with everyone who wanted to visit
and he talked to all of them about HPC. See?
In 1994, HPC
added R&D for the National Information Infrastructure
and AI R&D focus so focused on for applications areas
education, health care , manufacturing and digital libraries.
The HPC R&D community easily
expanded to include an AI R&D.
Donlin Berg remained
an Elm director while guiding PCC.
He spent mornings at his office on the mezzanine of an LMS
main building doing an elm work.
Then he spent afternoons at PCC National Coordination
Office doing PCC work.
The NCO was in D1,
the E4 basement of an Elms Leinster Hill
National Center for Biomedical Communications
and Elm was an early adopter of HPC technologies.
It moved key services to the Internet in early 1996 and offered
free public access to PubMed for
sports and retrieval of biomedical literature.
In 1997.
Its next fight.
In April 1993,
seven months after he became head of HP CC,
Don Lindbergh wrote his lessons learned.
He acknowledged his excellent, reliable
and self-motivated agency colleagues.
He introduced and welcomed every newcomer at their first tips.
That meeting kept up with their progress and asked
good questions to probe their views.
Next slide.
His HPC colleagues
had a surprising tolerance for the efforts required to adjust common goals
to satisfy the numerous agency mission requirements.
He made that easier.
The NCO started adding technical coordinators, subject matter professionals
who helped the agencies identify their shared
goals and document progress.
Next slide.
HPC needed
conscious application of ordinary management systems
and principles to the operation of the complex
HPC Project Project,
and it needed careful documentation
and formal dissemination of the results to agencies and the public.
To that end, the
NCO had full time technical writers
who drafted the annual supplements to the President's budget request
required by the law and drafted technical reports.
Next slide.
He wrote
that multi-agency budget cross cuts are worthwhile for projects
of clear national importance and cross-agency agency relevance.
Today there are only three.
Climate change, IPCC and nanotechnology.
Next slide.
This photo from the NCO for HP CC
Archive housed in NLM History of Medicine Division.
Looks like it was taken at the 1995 reception honoring Dr.
Lindbergh after he had stepped down as the chair and CEO director.
It reflects HPC sees several parts from left to right.
Our icon of inventing the internet
same and on the NLM Board of Regents
Tom Pike of NOA and Applications R&D Agency.
Norman Glick of the National Security Agency,
a computing systems R&D agency.
And Dr. Lindbergh.
Next slide.
Today.
PCC Is the networking and information
technology R&D or needed program.
It has 12 components.
The first six listed here trace their roots to the 1990s.
They include high capability computing,
infrastructure and applications and large scale networking.
The other six are newer.
They are R&D in large scale data artificial intelligence,
cybersecurity and privacy computing systems that help people
physical systems that have computers in them
and networks connected to them and robotics.
21 agencies participate.
The total budget is almost $8 billion,
and this is the largest at just over 2 billion.
NIH is number two at just under 2 billion.
24 NIH institutes and centers
plus NLM participate.
Sadly, NLM isn't
mentioned in the 2022 supplement.
Next slide.
But then supplement
notes that 30 years of PCC slash needed investments
underpinned our science and technology response to the pandemic.
They facilitated, facilitated
or enabled.
Rapid vaccine development.
Search for therapeutics and Cures.
Connectivity.
One thinks of the Internet, web browsers, search engines, smartphones
and video conferencing for many of us.
And access to supercomputers for COVID research
in early 2020.
Many, many HPC technologies needed
only to scale.
Without Donlin Works leadership,
HPC might have remained a technology R&D program
for the Federal Science and Engineering Engineering world.
With his leadership, a new broad
HPC C slash native community built and continues
to build the technologies underlying what
Walter Isaacson called a new economy.
Next slide.
HPC, CE technologies
and the knowledge and understanding they enable
now pervade every aspect of our lives.
In August 2022, just last month,
the Chips in Science Act became law.
It calls for OSTP to coordinate national scale technology,
R&D and transfer from federal agencies to the private sector.
The ACT identifies ten key technology focused areas
and five of which mention native topics.
Lindbergh's HPC See Now Named, could serve
as an excellent model for building their new community.
The End.
Thanks for watching.
Thanks very much to Dr.
Howe for her presentation.
And although she ends on a the end note, we all know
and as she mentioned 2 minutes earlier in her presentation, the story continues.
The leadership legacy of Dr.
Lindbergh remains squarely in place, along with now the leadership of Dr.
Brennan and future directors of the National Library of Medicine.
Thank you again, Dr. Howard.
Now we're going to proceed with the second panel of our program
entitled Lindbergh and the Evolution of the Library as Research Partner.
To this very end, it is my distinct pleasure to introduce
the chair of this second panel.
Teresa not serves as Associate Dean for the Virginia Commonwealth University
Libraries and Director of its Health Science Library.
Prior to joining Virginia Commonwealth University, she served
as the deputy director at the University of Maryland, Baltimore Health Sciences
and Human Services Library, and she held several positions
at the Texas Tech University Health Sciences Center
Library of the Health Sciences in Lubbock and in El Paso.
She was a 2526 National Library of Medicine Association
of Academic Health, Science Libraries and HHS Leadership Fellow.
And in 20 1718, she served as a mentor in the Leadership Development Program.
In 20 1617, she served
as President of the Medical Library Association, the MLA.
Theresa, not warm. Welcome to you.
Thank you for your time this afternoon.
I'm going to turn things over to you. Thank you.
Thank you for your kind introduction, Jeff.
Good afternoon.
I am pleased to welcome
you and all our distinguished panelists to the session on Lindbergh
and the evolution of the library as research partner.
As you've learned, Donald Abe Lindbergh was the visionary
leader of the National Library of Medicine for over 30 years.
He considered libraries of librarians key research partners.
Excuse me.
I was a fledgling health sciences librarian when Dr.
Lindbergh was appointed as the director of the National Library
of Medicine in 1984.
Dr. Charles Sargeant was my director at the time, and he had worked
closely with Lundberg, and they were both at the University of Missouri.
And Charlie was happy to share stories of his experience working with Lundberg.
And so.
Later, I had the privilege of attending the NLM
sponsored Woods Hole Biomedical Informatics Course,
an initiative that brought librarians, physicians,
health care providers informative sections together.
It was a transformative experience for many of us, and really
the first time I had the opportunity to interact directly with Dr.
Lindbergh.
He was visionary and inspiring and quite personable.
From my perspective, Dr.
Lindbergh initiated many programs that reshaped the work of health sciences,
librarians and researchers in the health sciences
while democratizing access to high quality health information and enhancing
clinical care through the application of biomedical informatics.
As we move forward, I would remind you that you can use the live feedback button
under your video window to send us questions,
and we'll
try to get to as many of your questions as possible after our panelists speak.
Today, our
panelists will share the current projects they are working on and how Dr.
Lindbergh's legacy echoes in their work.
Our first panel, Stephanie, is Christy Holmes.
Christy is the director of the Galtier Health Sciences Library
and Learning Center and Professor of Preventive Medicine in the Division
of Health and Biomedical Informatics at Northwestern University.
Feinberg School of Medicine in Chicago.
Christie served on the leadership team of the Northwestern University
Clinical and Translational Sciences Research Institute
and U.
States, where she directs evaluation and continuous improvement
for the Institute and several other programs and centers.
She also serves as the chief knowledge and excuse me,
the Chief of Knowledge Management and Northwestern's Institute
for Augmented Intelligence in Medicine
and directs the NL l am
the End and Health and National Evaluation Center.
Her work focuses on the discovery and equitable access
to knowledge through collaborative, computational and social action.
Today, Christie will speak on the Modern Library, found an article that Dr.
Lindbergh published in the Bulletin, the Medical Library Association, in 1996.
Christie, welcome.
Okay.
Great.
Thank you so much for that introduction.
Teresa, can you hear me? Okay?
Okay. Wonderful. Thank you.
I thank you all for the opportunity to join you today.
It is an absolute honor
to be part of this wonderful event that celebrates the life and legacy of Dr.
Lindbergh.
Before I begin my remarks, I'd like to take a moment to thank
the organizers, the National Library of Medicine, and the friends of the NLM.
Dr. Lindbergh's family and friends.
So many of my own collaborators and colleagues who have made profound
impact, impacts and influences on my own work are strong partners at Northwestern
University, Feinberg School of Medicine
and the dedicated and extremely talented team at Galtier Health Sciences
Library and Learning Center, who regularly make magic happen
through our resources, services and spaces, and whose work I will
briefly highlight a bit later in my remarks.
I also want to call attention to the design on some of my slides,
which reflects the design of the current strategic plan underway at Alnylam.
This active effort
builds on an incredible body of work at the National Library of Medicine,
accelerating biomedical discovery and data powered health.
It is indeed a bright future for libraries as research partners.
Dr. Lindbergh's impact is impossible to quantify
across biomedical informatics and library communities
through information standards, technology trends, a deep dedication
to interdisciplinary partnerships and thoughtful engagements to impact health.
His influence will be felt for years and years to come.
Perhaps the most remarkable is that much of his work was happening
during the relatively early days of the Internet, which Dr.
Lindbergh himself called an intellectual Wild West.
Today's foundational resources, such as those shown on the front page
of the National Library of Medicine website, which are shown on
the left like PubMed, ClinicalTrials.gov, Medline plus and more
were once new and unfamiliar, and as they were launched,
they offered access to medical information like never before.
A great example of that is shown here where we see Vice
President Al Gore with Suzanne McInerney, coauthor of Info Medicine.
David Lippman, who was the director of NCI at the time.
Harold Varmus, the director of NIH then, and Dr.
Lindbergh.
In the image, Vice President Gore is demonstrating a new system
developed by the NLM called PubMed, which simplified
searching for online medical information by researchers and the public alike.
The flexibility of PubMed and the ease of use prompted Gore
to make those remarkable comments we heard earlier in the video
in which the vice president said
making information like this freely available on the Web
maybe may do more to reform and improve the quality of health care
in the United States than anything else we have done in a long time.
I've thought a
lot about what to share during my remarks today.
Eventually, I came to the realization that I can likely never do a truly fitting
tribute to the legacy of Don Limburg and his lasting impact on libraries.
As as a research partner, I decided that perhaps I will just
contribute to the discussion with a few thoughts and experiences
that build upon the idea of libraries this research partners .
I'll also share the story of how I entered the world and found
a thoroughly invigorating professional home in libraries.
I cannot imagine a better place to be, and I am grateful to the champions
at NLM, such as Dr.
Lindbergh and Betsy Humphries and now Dr.
Brennan and so many others for their role in helping me find my way here.
Several years ago, I read Dr.
Lindbergh's lecture, The Modern Library Lost and found in which he present,
which he presented at the seventh International Congress
on medical librarianship in May of 1995.
There are a few passages I'd like to share with you today during my remarks.
First, he shares that the system of connections between computers
and their users has remade our world even more than the computers themselves.
He goes on to write.
Suffice it to say that
the spirit of voluntary cooperation and helpfulness within the library
and the medical communities permitted the work of NLM to be fruitful.
And here's the great section.
The Human Network, in other words, preceded
the electronic network, as it always must.
If useful services are to result.
Indeed, this human network
depicted as the puzzle pieces on the right of community
and capacity building, provides both a strong foundation, as well as momentum
for health sciences, libraries to partner, lead and champion .
Exciting efforts to translate and advance what we think of as a knowledge
network of data and resources in extraordinary ways.
This remarkable synergy between the human and knowledge networks
reminded me of a quote attributed to Aristotle,
where he communicates that the whole is something besides the part
in this case and the case of libraries, its research partners .
The whole is something much more impactful than the sum of the parts.
Indeed.
What?
I'm sorry.
Can we go back a couple of flights?
Okay.
As is the case for many of us
who have served in research roles in health sciences libraries.
My first major connection with the National Library of Medicine
was through training.
I joined Washington University's Becker Medical Library
as a bioinformatics test in the summer of 2006.
I just graduated with a biochemistry degree the year before,
and I was searching for something that would allow me to build programing
and connect with people in more of an infrastructure support role
rather than a discovery role that I might have as a postdoc.
I was able to quickly find training opportunities
at the National Library of Medicine, such as the Field Guide Workshops
and the CBI Advanced Workshop for Bioinformatics
Information Specialists, which is affectionately called Novice.
A five day intensive training program held at CDI,
which helped me get up and running to do my own workshops
and to be able to partner with researchers through consultation services.
I also found an incredibly supportive community of practice through a network
of bio information specialists at different libraries across the country
and through these novice leaders and an alum such as Renato Geer and a few
example papers of the work of this group are shown on the left.
For me, this is one of the most meaningful examples of the power of Dr.
Lindbergh's human network that NLM made possible.
Many of us have gone on to work together on various research
projects, outreach partnerships and more.
This focus on people continues today in a variety of ways and alarm.
For example, if we look at the Learn page today at NCBI,
we can see that it supports both end users and other workforce roles
who engage, use and support these resources.
A great example of this is the NCBI Virtual Outreach Event Series.
This series expanded online outreach to a worldwide audience of people
who use NCBI resources for biological and biomedical research,
science, education, clinical applications, and much more.
These virtual outreach events included a wide range of activities
such as interactive workshops, webinars and even codified.
Another great example
currently underway is the NIH Comparative Genomics Resource, or KDR,
a multi-year
National Library of Medicine project to maximize the impact of eukaryotic
research organisms and their genomic data resources to biomedical research.
The National Center for Biotechnology Information and as part of an alum, leads
both the development of this initiative
as well as the important work of engaging genomics communities.
Ultimately, the CCR project will facilitate reliable
comparative genomics analysis for eukaryotic organisms
in collaboration with the genomics community.
The CCR project intends to achieve several impacts that will benefit
research in the genomics community, which are listed here on the right.
Community Collaboration.
Again, that human network is critical.
The CCR feedback from the genomics community will inform
improvements made to and CVI data, tools and interfaces,
as well as help to guide new developments in these areas .
Moreover, KDR will enhance the NLM or and CDI health content
with community supplied content such that the sample metadata
and gene functional information and other types of resource information
like DAG to further empower scientific discovery.
My first meeting of Dr.
Limburg in person, as Teresa shared, was at the medical informatics
course in Woods Hole in 2007, another incredible human network program.
This course was launched in 1992 by Dr.
Limberg and Cathy Norton, who served as the director of the Marine
Biological Laboratory and the Woods Hole Oceanographic Institution Library
and Archives, who was a real information and technology trailblazer as well.
The course was designed to bring together medical doctors and librarians
who were in a position to be change agents in their institutions.
When I attended the course, I was now
one year into my job as a bioinformatics assistant, back her library.
I thoroughly enjoyed this training and consultation role on
campus building partnerships and programs for our research community.
But I was uncertain about this job long term.
While I was at the course, I had the chance to explore new ideas,
meet incredible people in the medical informatics community
who are shown here on this picture.
And I know there are a lot of familiar faces in this photo
and really think about my career and what might be possible.
During one chat with Dr.
Limberg, I had a chance to ask him about this.
I asked him if he thought I could make a career out of this,
and to be honest, I think I didn't really believe that a field of work
so interesting, supportive and fun could actually be a career for me.
His reply.
Why not this?
And why not?
You go for it and you won't regret it.
And I don't regret it.
After the medical informatics course, I crossed paths
with him at AMIA meetings and on campus at NLM through the Blair
Grant Review panel, and without fail he would ask me how I was doing,
what work I'd been up to, and how things were going in Missouri.
I appreciated his support and kindness.
Since that time, I've come to realize that everyone has a special Don
Limburg story that he was able to connect with so many in such a meaningful way.
It's a real testament to his legacy.
Looking back, my experience in the context of John's
human network of community and capacity building has set
a remarkably collaborative tone for so much of what I do today, both local
and national community and capacity building initiatives, catalyzing
new partnerships and projects, and helping me push against my own biases
and assumptions about data and methodologies in ways
that might not have been possible without this nurturing environment.
I also had the opportunity to think about putting data to work in new
and exciting ways not only for health care, research and education,
but also administrative workflows, knowledge dissemination and discovery
evaluation and continuous improvement and even understanding meaningful impact.
All of which has provided a strong foundation for our work at Northwestern.
The Cultural Scientist Librarian Learning Center, which I'll refer to as
Galtier, is a next generation fully integrated information
knowledge management hub for Feinberg School of Medicine.
Galtier provides dedicated support for the research, education and patient
care activities at the Feinberg School of Medicine in McCarter Medical Center.
Got Her is uniquely positioned as a unit within Northwestern
University Clinical and Translational Sciences Institute.
Are New Cats, the only relationship of its kind?
This relationship facilitates important synergies across research,
clinical and education priorities on campus.
We are actively involved in a wide range of research activities and partnerships
and cultures, such as an alum funded project with the Center
for Health Equity Transformation, which has catalyzed a partnership
with the Chicago Public Library, Chicago Department of Public Health and the Health
Sciences Libraries at the University of Chicago and the University of Illinois.
Chicago, a clinical informatics training program
with the Northwestern Medicine Enterprise Data Warehouse, a clinical information
program to support health care and a robust, systematic
review service across Feinberg School of Medicine,
as well as extensive partnerships and activities
with Northwestern's Institute for Augmented Intelligence in Medicine.
Beyond research activities,
we take our core library mission to heart every day.
This means a few specific things.
We intentionally focus our human network, including our community, community
of users and the culture library team.
We provide targeted and dependable services, resources and innovations,
and nurture inclusive action through our practices, collections and spaces.
We foster integrated partnerships and collaborative collaborative action.
We support professional development of our team, encouraging
and celebrating their professional growth and accomplishments.
And we advance our deep commitment to knowledge, equity and access
to make our library and collections welcome, accessible
and inclusive.
Our team has catalyzed enhancements
in library services and spaces to support strategic priorities and advancements
in information structure, aggregation, retrieval and application.
They are responsible for catalyzing remarkable enhancements in our clinical
support services, educational programing, special collections,
special projects, open science, research impact and so much more.
The blocks on the right highlight different departments at Alter Library,
which support an extensive range
of spaces, resources and services, both physical and virtual.
In addition to these departments, we also have two specialized cores
the Metrics and Impact Core
in the library's Department of Research, Assessment and Communications,
which supports evaluation, benchmarking and strategy needs across the enterprise
and the data lab.
A high tech data core for training, one on one consultations
and community building around informatics and data science.
The modern university library is not just a steward
of information, it is a partner in creating new knowledge.
Over the last several years, we've initiated a variety of programs
to align our library's priorities with our greater collaborative mission
and set a course for the library as a 21st century research partner.
To demonstrate the role of the library is a research partner.
I would like to highlight just one timely topic area to show how we leverage
the synergies possible through the human network of our user, community
and library team and that knowledge network of data and resources.
In this slide, we can see data sharing activities map to a few of our departments
in the library, further highlighting staff
library team expertize on this important research topic.
The culture team is a very collaborative one and works
often happens in cross-departmental collaborative working groups.
This is something we're working on now as a collaborative effort
to establish the resources and services, expertize and workflows needed to meet the
NIH data management and sharing policy, which goes into effect in January of 2023.
The Digital Systems Department provides expertize
for the creation, development, maintenance and support of technologies and culture.
Library accessibility is also advanced through the information systems
themselves to ensure that they meet accessibility standards and principles.
Digital Systems Houses The Data Lab, which includes
support for the entire research data management pipeline.
We are also enhancing our systems infrastructure as contributors and core
developer partners on the embedding our open source community
to build a turnkey next generation solution for digital repositories.
The Department's Data Lab provides consultation and training
for all stages of the research data
lifecycle and links the researchers with the university experts at cores and
other research facilities that can serve any complex needs that come in.
The Department of
Research, Assessments and Communication provides expertize in building metrics
and alternative metrics, information visualization for research, assessment
and advisory services for increasing the visibility
and accessibility of research in a digital environment.
Scholarly communications and digital scholarship,
including our repository, is a critical aspect of the preservation,
dissemination and re-use of research.
The Research and Information Services team shown in that light turquoise
block meets the educational, clinical and research needs of our campus.
Research and Information Services coordinates all reference
activities and culture as well as our Liaison Librarian program,
which pairs librarians with department centers, institutes and programs
to enhance communication, collaboration, and the effectiveness of our library
in supporting campus education, clinical and research needs.
The Collection, Management and Metadata Services
Team provides rapid and reliable access to resources.
The department's cataloging and metadata services are core to the way
we describe and make discoverable our resources and the care
we take to be aware of and address biases in our information systems and practices
not only in the past, but today as well.
Across these activities, we see the power of
integrated human and knowledge networks.
In listening to the comments of the earlier speakers and panelists,
it's clear that anything is possible when we focus our investments and time
and resources on a vibrant ecosystem that supports the evolution of resources
and data with the human community and capacity building component.
We see this in Dr.
Lindbergh's remarks at the end of this passage.
The modern library's evolution during the next ten years
do seem somewhat more clear.
More sophistication will be expected both of the user
of the information and of the librarian who arranges for it.
In this respect, the modern library will be ever more interesting.
It is critical that we keep an open mind and unfailing optimism about
what is possible when we work together to realize the vision that Dr.
Lindbergh had of the library as a research partner.
As we look to the future, we
will continue our keen focus on research, education and clinical priorities
and will grow in ways that reflect the evolution of our campus and mission.
Areas of effort will feature human and knowledge networks working in synergy
to produce new strategic partnerships and the evolution of our research services
and resources to harness this work to power innovation and discovery.
While various priorities and opportunities will emerge over time,
we will work to be nimble and continue to prioritize actions to support
the role of the library as an active, open and transformative
research partner.
I'd like to invite everyone.
There are a number of really amazing resources that have been made available
by the National Library of Medicine, and we're really just
such a pleasure to go back and reread in preparation for this.
And I wanted to include those here
and and I'd like to thank you for your time and attention. And
I'm excited
to hear the remarks from my fellow panelists.
Thank you.
Thank you, Christine.
One of the things that you talked about that really resonated with me is how
the human network that Lindbergh referenced lives on through those
speaking here today, those who are attending, as well as how
Lindbergh really leveraged the human network synergies to fill social stage
creation of interconnected systems to improve health across the world.
So with that, thank you so much for sharing your experience
at Northwestern.
Our second panelist this afternoon is Philip Morrow
Payne, PHC from the Washington University in Saint Louis.
Philip is the Janet and Bernard Becker, professor and director of the Institute
for Informatics or IQ at Washington University Saint Louis School of Medicine.
Philip serves as associate dean for health information
and Data Science and is the chief data scientist.
He is internationally recognized as a leader in the field of clinical
research, informatics and translational bioinformatics, as well as in the fields
of clinical research informatics and translational bioinformatics.
His research portfolio is actively supported by a combination of
in Katz and 11 NCI grants and contracts,
as well as a variety of awards from both nonprofit and philanthropic organizations.
Today, Philip is going to speak about
integrating informatics in the Health Sciences Library, creating
a digital hub for the contemporary academic health science.
Philip Great.
Thank you, Theresa, for the introduction.
And I have to admit, I'm a little daunted by the prospect of following Dr.
Holmes, who I consider to be a good friend and colleague.
So I will do my very best to continue
the sort of high bar that she set with her presentation.
So I'm really excited and honored to be here
today, and I appreciate the invitation.
Like many of the speakers at panelists today, almost
every aspect of my career can be traced back to the influence that Dr.
Weinberg had.
And I'll leave a few remarks about that towards the end of my presentation.
So don't worry.
If you haven't heard me speak about that, I will touch on that topic.
But what I do want to talk a bit about is the efforts that are underway here
at Washington University in Saint Louis to integrate our Health Sciences Library
with our broader data, information and knowledge enterprise
in support of the School of Medicine's multiple missions.
And you may note that I, unlike some of my fellow panelists, am
not really a traditional medical library professional.
In fact, I have trained and spent the bulk of my career as an implementation
and only recently stepped into a role where I took responsibility
for the strategic direction of the library.
So I think I'll bring a slightly different lens to this and hopefully one
that makes sense with the broader theme of today's sessions.
So I want to start.
Well, I've already missed one of my slides.
I want to start with a quote.
And many people have provided quotes today.
And I think in part, that is because Dr.
Lindbergh was so voluminous in his contributions to the knowledge base.
But this particular quote from Dr.
Lindbergh's swearing in ceremony as the director of the NLM
in 1984 was particularly prescient, given what I wanted to talk about,
because really the theme here in this quote is that the role of data,
information and knowledge in modern medicine was only going to increase,
and that as a result of that,
the fields of informatics and library science were inextricably
intermingled and central to the future success of the Academic Health Center.
And really, health and wellness more broadly.
And I think one of the true testaments to Dr.
Lindbergh's leadership is that he recognized this well before.
I think almost anyone else in our field, with the exception of a few
other key individuals who have participated today
and have also made remarks really fully understood.
So as I mentioned, I want to start by just saying a little bit
about the Becker Medical Library here at Washington University in Saint Louis.
And actually, Dr.
Holmes did a nice job of providing a little bit of a sneak preview of that,
given her prior affiliation with our organization.
But I think one of the things that's interesting about the Dr.
Library is that it really does have a long history
of working at this intersection of informatics and library science.
The library is very sort of senior in its lifespan
in that it was established in 1911 and actually is one of the oldest
and most comprehensive libraries west of the Mississippi.
For those of you that know me well as an individual
who grew up on the West Coast and then went to school on the East Coast,
I suddenly found myself as a midwesterner and therefore can make almost
any reference in sort of correlation to the location of the Mississippi River now.
But at the core of this
long history of bringing informatics and library science together
was a relationship that began in the early 1990s with the NCBI,
where the Becker Library was deeply engaged in the development
and dissemination of a number of critical tools and data resources
that tackled fundamental problems in the biomolecular sciences.
And it was actually because of that work at the intersection of Becker and NCBI
that a core information technology
and Bioinformatics Support Unit was created in 2000.
And the goal of creating this new unit was really to provide
a front door to critical resources that would enable this modern
knowledge enterprise in a research intensive academic health center .
And in particular, the group was quite focused on areas that you see enumerated
here, such as genomics, research, computing and knowledge management.
Not surprising for an institution
that also housed a large genome institute and a sizable clinical
as well as translational and basic science enterprise.
It was also interesting
that with the foundation, this group within the Becker Library,
there was a clear acknowledgment
of the fundamental interdisciplinary nature of this work,
in that there was a faculty advisory group that spanned both the preclinical
and clinical domains in the medical school
that came together to provide strategic guidance to this new unit.
And one of the important
aspects of the unit, when it was created
in 2000, was that it was meant not only to provide services,
but also to invest time and energy in workforce development.
It is an interesting sidebar, actually, that Washington University was also
one of the very first institutions to receive a training grant
from the National Library of Medicine when that program began, as well
under Marc Fritz's leadership at the time at the university.
And I think that speaks again to this commitment to workforce development
and the intersectionality of informatics and the library in that space.
And I won't read the other details here, although they emphasize that like everyone
in today's session, I had at least one embarrassing picture or magazine cover
showing people dressed in sort of late
nineties or early twenties apparel holding
shockingly large computers that were high tech at the time.
But nonetheless, there has been this very lengthy
and intentional approach to building bridges between scientists
and informatics and technology professionals that has been based
in the Becker Medical Library since the very beginning of such efforts.
And now I want to sort of
engage in just a little bit of time travel and fast forward to today in the role
that I'm in and sort of how
that's reflected in the evolving mission of the medical library.
And this is really the story of how we've created this new unit,
which we call the Office of Health Information and Data Science,
which I lead in my role as associate dean here at the School of Medicine.
And I won't bore you with the details, other than to point out in this timeline
that the development of the Office of Health Information and Data Science
has been relatively short in duration as compared to the lengthy history that Dr.
Library and actually dates back only to 2016 with the formation
of the Institute for Informatics or ITU at the university.
And now today we've really created an integrated academic
home for informatics, research, practice and education.
We brought that group together with our bio statistics and data science teams,
as well as research computing and data infrastructure and the Becker Library
in order to create an integrated unit that really spans the full spectrum.
Back to that theme, from data to information to knowledge.
And this has really been a major change
for our institution for many who know WashU.
We are, as I often affectionately use the phrase, pathologically decentralized
in that we enjoy building very robust silos of excellence across our enterprise.
And we've been very successful in driving critical advances in basic and clinical
and translational research for decades in that mode of operation.
Yet there was also a clear recognition by our leadership
that in these critical areas of data, information and knowledge,
we really needed something that was purposely built to be horizontal
and cross-cutting and really support all of our mission areas,
which is where this office becomes really the hub for that work.
And you can see here, our mission
very clearly is to bring those pieces together
and in fact, create the infrastructure, the workforce and the scientific
discoveries that really will drive precision medicine and our ability to
improve the quality of health and health care locally, regionally and nationally.
And certainly Saint Louis and the surrounding region is a microcosm
of the challenges that face the national health system here
in the United States, and thus is an ideal testbed for many of these initiatives.
This is sort of that the abridged version of what
this office means in sort of practical reality,
which is that it houses a informatics unit that spans the spectrum
from translational bioinformatics to clinical informatics to population
health, a rapidly growing biostatistics and data science
research unit, shared educational and workforce programs.
All of the fundamental structures and functions that make up the Becker
Medical Library, as well as all of the research,
computing and data infrastructure
that sits under what we call our Office of the Chief Research Information Officer.
And we see this as sort of the template for a next generation academic home
that again is
quite horizontal in its nature to achieve all the goals I've talked about.
And you can see a number of the research highlights here, but I would point out
that almost every one of these research domains,
which also involve practice in terms of services and practical tools,
have been in some way supported or enabled by the activities of the Becker
Medical Library.
So there's deep integration across all of our research teams,
as well as the services and training programs that we offer
to our medical school curriculum as a function of this tight
coupling of the Becker Medical Library and all the other units
that make up the office.
We'd also
be remiss if we didn't talk about educational programs,
because as much as we would like to believe
that we can recruit every single person to Saint Louis that we need in order
to tackle these large and complex problems, we simply cannot do that.
And so we're very committed to growing a workforce
locally that works at this, again, intersectional space.
And we do that in traditional ways that many of us are familiar with,
but also in equal measure in what we believe are quite innovative
ways, such as K through 12 outreach and engagement and a very,
very robust regional internship program that brings in trainees
who get experience in the Becker Library, in the Institute for Informatics
and in our Research Computing Services Group all at the same time.
And of course, all of the other components that you see enumerated here.
But the takeaway is we're very committed to building the pipeline
of future trainees and exposing them early and often to the fields of library
and information science, as well as informatics and data science
and training a workforce that can work in equal measure across all of those areas.
And that also leads to the services that we offer.
And I want to draw your attention
to the role of the medical library in that regard,
because one of the key roles and perhaps the most important role
is that our library serves today as a digital hub for our campus.
It's providing practical training in all of the tools
that our researchers need only to survive
but thrive in a modern, data intensive research environment.
And this is a critical role
that I think the library is uniquely suited to fill in, that their
sort of capacity as an impartial and central hub for the campus,
not connected to any particular disease domain or basic science domain,
but rather focused on these data, information and knowledge
related activities, makes the library a trusted partner for delivering
this type of training, as well as access to these services and capabilities.
And increasingly, what we've done is positioned
our library as the front door or onramp to all of our informatics data
and knowledge management services.
And I'll say a little bit more about that in a moment.
And so that really leads me to the final part of my remarks
this afternoon, which is really how are we innovating sort of
going from that history of the initial establishment of the Dr.
Library and its very early leadership in informatics to this new structure
with the Office of Health Information and Data Science
to sort of looking forward what comes next for our organization
with this structure and means of operating?
So first and foremost, when we talk about the future of the library,
we talk about it as a hub for what is increasingly,
if not essentially a digital knowledge enterprise that characterizes
all parts of our teaching and learning research and clinical missions here
at Washington University and with our partners at BJC health care.
And that means in addition to the collections and knowledge resources
that we provide today, we also are increasingly focused on
creating what we call centers of excellence.
Some of them are areas that might be familiar to many of you,
such as our Center for History in Medicine,
which, in addition to providing access to all of our archives
and other historical documents, serves as the official historian
of the medical school so that we can learn from the prior
history of the research and educational and service activities
of the lengthy history of this institution.
We also recently created a new Center for Health and Science Communication
with the explicit goal of helping to train our scientists
and practitioners to better communicate their work with the general public.
And I think we can all acknowledge that the trust gap between the general public
and academic medicine has never been greater than it is today.
And one of our key roles and responsibilities is to help address
that gap and bring those parties closer together with shared understanding.
And then, of course, in a way that's similar to some of our other peer
institutions, we have a deep investment in growing our evidence synthesis review
service to truly help our investigators navigate increasingly complex
knowledge resources as they pursue their research endeavors.
As already alluded to before, we've also established
the library is our onramp to informatics and data services.
And this is really about how do people come in and find those services?
Because by and large, our investigators, our trainees,
our practitioners don't necessarily know what services or capabilities they need.
And it's unreasonable
to expect that they would navigate the myriad of resources that are present.
What we really want to do is provide, and I think Dr.
Holmes referred to it earlier, is white glove service
where human experts help our investigators, our trainees
and our clinicians to navigate these myriad resources.
And importantly, again, we provide a number of emergent platforms
such as our expertize, profiling systems, and then our institutional data
repository,
which we've stood up in conjunction with our new data management services
to help our investigators navigate the new NIH data sharing policies
and embrace a culture of open science and sharing here at our campus.
When we think
about future directions for the library,
we are now increasingly focusing not just on the medical school,
but also the campus writ large.
And we've just launched a program to initiate a ten year
digital transformation program for the university,
which brings many of the lessons learned from the formation of the Institute
for Informatics and the other components to the rest of our campus.
We're also increasingly looking at how we can expand our digital collections,
and particularly those that are relevant to just in time, information and knowledge
needs at the point of care and expanding that to our entire health system.
So in conjunction with BJC Healthcare, we want to provide these just in time
knowledge resources to practitioners across all 14 hospitals
and a 300 mile catchment area, including both rural
and community hospitals and academic tertiary care centers, really
sort of democratizing access to these knowledge resources.
We're also using libraries of hope for navigating.
How do we provide new modalities of support
for all of these data, information and knowledge management needs?
Given the sort of evolving
nature of our hybrid workforce in this post-pandemic time period,
and then also providing new tools and resources
to increase utilization of public datasets and repositories
that are increasingly central to research and innovation endeavors.
And then finally, in a little bit
more sort of pragmatically, we're looking at the space
that physically makes up the home of the library and ascertaining
how does it truly become the hub for convening and team science
activities across our increasingly geographically distributed campus?
So I'll just end with a slightly embarrassing picture, but
one that I think is apropos of my comments about my own personal connection to Dr.
Lindbergh.
And this is a picture
actually from a location at the University of Missouri, Columbia.
Our key partner in both our TSA Cancer Center programs and located
just a little bit less than 2 hours from where I am today in Saint Louis.
And the first time I visited shortly after coming here to Saint Louis
six years ago, I went to Columbia and I had the opportunity
to see this display, which is in recognition of the
Donald Abe Lindbergh Award that is given each year
to excellent faculty in the health informatics program at Mizzou.
And it was sort of a prescient moment as I looked back upon
the impact he's had on my career.
And that impact has been multifold.
There are certainly a geographic and sort of
institutional affiliations that tied us together, including the fact that Dr.
Lindbergh was a Columbia alumni when he received his M.D..
And I was fortunate to train in informatics in the Department
of Biomedical Informatics at the College of Physicians and Surgeons.
Certainly the connection here in Missouri,
I would not have had the opportunity to come into the field of informatics,
if not for the fellowship support that I received.
And I remember fondly the many convening events of the annual entries, including,
I think, and perhaps most importantly, many of the social events that Dr.
Lindbergh helped to organize,
even though we were all quite intimidated by him at the time.
And then when I sort of fast forward in my first academic leadership role
at the Ohio State University, when we were fortunate enough
to receive a T 15 training award during the final site visit, Dr.
Lindbergh, as well as Dr.
Korn, came to Ohio State to visit us and talk about the program they were planning.
And I always remember because Don had a very dry wit at times,
we showed him space that we had for our students
to engage in collaborative and team science.
And as we showed him the space, he looked at me and he said,
You just created that space just for this visit. Right?
And it was because he could smell the fresh paint in the room.
And that was entirely true. And he left it at that.
But I think that was apropos of his sense of humor.
And then I think perhaps most importantly to me, I had four years
of having the good fortune of serving on what at the time was the work,
the standing study section of the film.
Actually, Dr.
Holmes and I were on that committee together
for a period of time, and perhaps the best part of those meetings were what
I refer to as the family dinners with the study section, and Don and Mary,
where we really got to hear sort of his view of the history of the field.
And then lastly, I'll just share that most recently, I had the opportunity
to help lead a strategic planning process for the American College
of Medical Informatics, which included thinking about the history of that group,
which we've all heard about earlier today, and how it might evolve
to meet current needs.
And this is towards the end of his life.
And Don was so generous with providing his sort of historical insights
and knowledge as I navigated what was a very politically tenuous
process of sort of reshaping the future of me.
And I was immensely thankful for his willingness to share his time
and knowledge.
And I will always remember that very fondly
when I was doing that very critical work.
So I'll just say, like many of us in our field,
Don has been a giant in the field of informatics, hugely impactful
and has shaped my view of the world, which I hope what I shared with you today
is manifest in how we're bringing our informatics and library teams together.
And I'll just conclude by saying I think that this is consistent
with Don's vision for this intersectionality of informatics
and library science and medical libraries.
And I think it's only appropriate that
that would be happening here in the Show Me State where Don started his career.
So thank you again for the time.
And I will turn it over to our moderator and look forward to our
other panelists comments.
Thank you, Phillip.
I have reflected to you on how, in many ways, the whole
Don Lindbergh's journey in informatics really started in the Show Me site
at the University of Missouri and the deep connections
at the University of Washington in St Louis
and how that has propelled informatics forward.
Additionally, I think that Don's leadership
of the National Library of Medicine and how he encouraged the
organization to fund research in informatics
and in training programs I think is especially insightful.
And one of the things that I found especially meaningful
about what you're talking about is the libraries
and particularly librarians, because it's librarians who do the work
, really have the ability
to serve as this impartial and connected hub, bringing trusted partners together
across the university as being engaged in team
science and advance our research.
So thank you so much for.
I do have one more thought that I want to share.
I think that apparently we need to create a compendium of non Lindbergh quotes
that would inform future generations that might be welcomed by many.
Our next speaker is peace.
Awesome, Williamson.
She has her MLS and a master's degree in Science.
Peace is the Associate Director of the National Center
for Data Sciences for the Network of the National Library of Medicine
at the New York University Health Sciences Library.
Pieces Expertize includes data sciences,
scholarly communication and outreach and libraries.
In recognition of her research piece
received the 2021 Texas Women's University Hallmark Alumni Award, as
well as the Medical Library Association's 2020 ident George Eliot Prize.
For an article she coauthored, the Audie George Eliot Prize
recognizes the most effective article in furthering medical librarianship.
As an active educator.
Peace Teachers, Research Data Services and Libraries at San Jose State
University and Public Health Informatics at the University of Texas at Arlington.
Today, peaceful address, expanded expertize and emerging specialties.
Role of librarians embedded in each stage of research.
Peace.
Thank you so much, Teresa.
I don't know if I need to take control.
Okay, I have control.
Wonderful.
Okay.
Thank you so much for the invitation and for the opportunity to speak today.
I'm really excited to be part of this panel.
I think that it represents numerous perspectives
and really all of the roles that medical
libraries can touch and all of the fields.
Dr. Holmes and Dr.
Payne spoke from perspectives of Biochemistry and Informatics.
As someone who did not know Dr.
Lindbergh personally, I'm here to provide insight into how his vision
carries on into current and future developments in libraries.
This computational focus of Dr.
Lindbergh and now Dr.
Brennan came in advance of many of the clear examples of its need
and its impact, as evident during the COVID 19 pandemic and beyond.
I like to challenge us
in libraries to continue to investigate and engage in
metacognitive processes where we evaluate where our field is heading
with a focus during this presentation
on data librarianship.
Dr. Lindbergh created programs that changed fundamentally
the way that biomedical information is collected, shared and analyzed
through all of the computational changes he oversaw at the library.
He still valued primary resources and original documents and the stories
they told.
In an introduction, he wrote in Hidden Treasure in 2011,
he wrote that speedy computer access to information is truly wonderful.
Yet there are times, especially when we ask
why or how a discovery or a belief arose when we need to see
and hold the original intellectual work in context.
As a data librarian, I often emphasize the importance
of the domain of expertize in addition to the data literacy
that's necessary for understanding broad trends.
You cannot have one without the other, and it is incredibly important
to have that expertize partnered with the
interpretations that take place under Dr.
Lindberg's leadership.
In a limb, embrace the Internet, enabling the public
health providers and scientists to gain new
or improved access to medical literature via PubMed and PubMed.
Central ClinicalTrials.gov and Consumer Health Information on Medline plus.
He played an integral role in the establishment
of the National Center for Biotechnology and Information,
which we've talked about numerous times today.
But I'm going to talk about how that leads into the current roles
of data librarianship as we move forward in discovery.
My focus
today is mostly on the topic of open science. It's
something that I champion and something that I'm incredibly passionate about.
And I believe that a lot of the developments of Dr.
Limberg and the in Ilim have led toward the advancement of this aim.
Open science is the
natural way, a natural way of this movement.
And it focuses on transparency and accessibility.
Research aims, methods, materials and processes should be made
as openly available as possible, which include open licensing.
Open as defined by open knowledge.
And 2005 involves a standard which will
which allows for reuse and remixing.
However, in order for open science to occur, it involves
a combination of infrastructure, policies and guidelines,
incentives and tools in addition to resources, skills and effort.
Librarians are natural partners in this endeavor, as librarians
are leading the open movement alongside many other scholars and activists.
The open movement seeks to work toward solutions of many of the world's
most pressing problems in a spirit of transparency,
collaboration, re-use and free access.
It encompasses open science, open government,
open pedagogy, and much more participatory processes.
Sharing of knowledge and outputs and open source software are among its key tools.
The specific definition of open as applied to data,
knowledge and content is set out by the open definition.
And with these aims, many libraries are actively transforming
by increasing their capacity for supporting the open movement.
The librarian is active in the effort toward advancing open computing,
data driven biomedical research and open science through expertize
in information organization and information literacy.
Now some data to back up my claims.
Open is clearly something that's influential.
We all know this with the current pandemic.
But even prior to that, we saw evidence of that where open
openly published research had increased citations.
Increase of use not present on
this slide are also more accurate representation
and how it's being portrayed in news articles.
We also see that the field usage
as evident in the SNAP score is higher for research that is open.
And this is really kind of more obvious as you think about
when the entire article is made available and open and people are much more able
to understand what occurred and be able to replicate it.
In addition, we call it a movement because we are moving in that direction.
As of
2019,
25% of research being published has been published, open access
and all of the research that can possibly be study
using on paywall data.
So what is open mean and was involved?
Let's take a look.
Here is a very simplified
view of the research data lifecycle,
and we see how libraries are active partners here.
As previously mentioned, open science involves an investment
of resources, support and effort at multiple levels,
and they exist at each stage of this research data lifecycle.
In this picture, to simplify data lifecycle, you can see
planning, acquiring, structuring, analyzing and sharing data.
Libraries have developed services and built infrastructure at many,
if not all, stages of this process.
If we look at what
this process looked like traditionally,
it involved a great number of proprietary tools.
These are often commonly used for open publishing with a shift
in the end at that sharing stage.
However, many of these tools come at a significant cost
that are all cannot afford and work within tools and environments
such as utilizing proprietary file types and statistical software
that does not track the actions that are taken
and can advertently be inaccessible to others
and make reproducibility more difficult or impossible.
In 2005, Dr.
Lundberg and Betsy Humphreys wrote in the future, journals are still
an important vehicle for disseminating peer reviewed research results.
But many individual articles have electronic lives of their own.
Much scientific information is available free over the Internet.
Thanks in part to earlier efforts to make information
about clinical trials and government funded research available to the public.
So many sources.
Electronic information required paid licenses in this hand.
After he and Ms..
Humphreys began to highlight efforts toward open resources
and digital libraries to inform resource researchers and the public.
As researchers shift to open science
methods, new processes and products are necessary
for transparency and accessibility at each stage.
Looking at this simplified model again
with some some examples are many of open
tools, software, file types, etc..
At each stage
we can see there's a lot involved in the movement toward open science.
Unfortunately, the true integration of multimedia
information is still either not simple or cheap, says Dr.
Limberg.
Technology that supports ready online access
to full text, picture, sound, video, etc.
continue to evolve quickly.
And technology companies derive more income from selling services
than from selling hardware, which makes it less of a priority.
A library back in 2015, which was what he was looking at
as far as ten years in the future, continues to be the logical
entity to manage this complexity on behalf of the institution,
to make decisions about inevitable and substantial expenditures,
to adapt information services to new realities,
and to provide essential user training and support.
Again. This was something written by Dr.
Lindbergh in the New England Journal of Medicine in 2005.
And you can see that that rings extremely true as we
look at this model and open examples of each stage
and think about the entire environment of the open movement today.
As data have become
easier to collect, analyze and re, analyze,
store and share, and as processes toward open science become more complex,
there is a growing demand for data literacy skills, data technology
and infrastructure and process implementation and research.
Libraries, particularly research and medical libraries,
are expanding service services to support these practices,
particularly services for research, data curation and reuse.
In this context, I describe data curation as incompetent, encompassing,
managing data throughout research, and the process of making data fair
or findable, accessible, interoperable and reusable over the long term.
Libraries are now building open platforms like repositories and data portals,
teaching classes on use of open software, and more
librarians are partnering with larger resource providers to simplify
and make easier the process for their researchers and using their resources.
For example, I live in Texas.
We have the Texas Advanced Computing Center,
which has storage options, cloud computing and statistical services
in which research data librarians assist researchers in making use of.
Research Data
Services or RTX for short have become a critically important topic
for academic libraries, medical libraries and research libraries of all kinds.
With the average our one classified university employing a range between 0
to 10 librarians with an average of two data librarians per institution
assessing the data services being offered in RL member libraries.
Some researchers in 2018 placed them into the categories
of information, access, support, technical support
and personalized consultation console consultation.
Sorry, and these describe the acts of providing the information,
the technology and in-person assistance
to be able to work in this new landscape.
Many libraries have information placed online or in places
such as the data management planning tool or dump tool for short.
But they are limited and the consultation category
due to a number of factors which could include the number of them.
Again, mentioning that the average have two per institution.
Working with all of the researchers in one institution is quite an undertaking.
The the
financial aspects of the infrastructure and more.
In addition, the focus has been on the preparation
and the final curation of data, where fewer librarians provide
support for data, acquisition, processing and analysis.
However, that is shifting.
So I'll talk a little bit about each stage
and we'll circle back into kind of again looking at the future of libraries.
So thinking about the planning stage, in addition to data management planning,
librarians can advise on components of a good protocol
and assist with pre-registration.
We also work with colleagues across campuses to develop guidelines
and make resources and services more clear.
This includes working with research offices, I.T.
departments, information security, innovation
and commercialization offices, and more.
Together, we work to communicate across these offices to make requirements
clearer and more consistent to researchers while providing services
to support their work.
Librarians are collaborators with specialized skills.
We are able to help researchers across this lifecycle from reviewing
data management plans to assisting with data sharing and publishing.
We do this by helping researchers one on one during consultations
and by holding workshops where we teach data different
different data analysis and visualization tools.
Depending on expertize, librarians can provide guidance on best practices
for designing data collection tools, particularly surveys
to have well-structured data at the completion of their collection.
And as I mentioned, we've provided significant amount of training
on software programs and other tools for data collection for secondary data.
Librarians have awareness
or the ability to find data sources that may be useful for research.
And we assess researchers in the process of submitting requests
for applications to data service data sources, including projects.
And data that you may be familiar with through your local health department.
Other data sources like the Inmarsat data and so on.
Some libraries also
kind of exist within the center of the data lifecycle,
including working to help researchers and structuring their data
and analyzing them.
I mentioned the idea of creating workshops,
online tutorials and tools and helping people one on one, consultations
with data structuring, database design, and also working with analog
analytical software and research methods.
Two decades ago, Dr.
Lundberg stated, If I read and memorized two medical journal articles
every night by the end of the year, I'd be 400 years behind.
Adam Marcus stated in Dr.
Lindbergh's obituary in The Lancet, This was a statement from two decades ago.
So imagine how wide that gap is now that millions of articles
are published each year.
And we saw this ramp up even further with the COVID 19 pandemic.
His career focused on applying the power of computers
to medical research, discovery and information access.
As a researcher.
He led the development of A.I.
systems, and he wrote that the flood of patient specific data generated
by large scale prospective normal cohort students presents special problems.
And I don't want to skip over the problems that are involved
in a lot of these processes and the amount of commitment
that it takes to be successful in moving toward this movement.
Not pictured, are they?
Numerous in alarm products and data sets?
I only had so much room in that life
cycle picture, but a lot of it all.
Work focuses on metadata such as the Unified Medical Language
System, Daily Med Committee plus and and and so on.
Before the UML, databases lacked common terminology,
and these systems have numerous uses for information sharing,
compilation of evidence and interoperability.
This is a key area of leadership coming out of the SPL
as librarians can and are helping usher researchers
path standalone data sets toward fair data and interoperability.
Hopefully the taxes on take small in the slide.
But I also wanted to point out
some other areas of support that libraries are offering.
I think these will only grow and intensify
with all of the memos and policies that are currently coming out.
But some of these include helping researchers find where to publish.
Funding article processing charges for open access
initiatives with the idea that funding you on the front end
with a one time charge to make your article permanently public
where you're saving that library the funds of continuous subscriptions
in order to maintain access to those articles.
Assisting with copyright and helping researchers
navigate their copyright agreements to possibly
have their articles open as open as possible,
not just their articles, but also their data sets,
and then assessing the research impact on the back end.
I don't want to forget to
point out that librarians are researchers as well.
We have a number of domains, specific expertize,
particularly in medical libraries.
Many of us have, as Teresa mentioned, I have a kind of public health
background and others have backgrounds in biology,
chemistry and so on.
We also have our initial focus,
which is around information literacy and information access,
information organization and now scholarly communication
as that field grows.
With all of this.
I hope this helps you look forward toward where libraries are going,
opportunities for libraries, and the legacy that Dr.
Lindbergh has set by focusing on computers
in medicine and in librarianship.
You can also see this legacy, carry on with it in a lab and continued
R&D with Litecoin Common Data Elements
and Advances in Medical Research, Description and access.
Again, thank you so much for having me
as a speaker and I look forward to your question.
Thank you.
Peace. That was excellent.
And I really appreciate that.
And in listening to what you said and I see some common themes from science,
data science, team science, collaboration,
open access through science
solving problems, how librarians can serve
as a partner in the research enterprise.
And from everything I knew about Don Lindberg, this really reflected
his vision of the future, where librarians are collaborators
and connectors and the research.
Ecosystem.
Before we move on to other questions, I do have a question for piece,
which is with the new.
Announcement of the White House
Office of Science Technology Policy.
Last week that the embargo is going to be removed
and that there's going to be a focus on sharing of data.
How do you foresee librarians working in that space,
or how will it change the practice of librarianship?
Yeah, that's a great question.
Thank you for asking.
For those who are unfamiliar,
the White House just released a new memo
which include included basically four large changes
to the previous memo
and that there are no more embargoes.
So any research that's being published
from federally funded agencies
must be made immediately available by deposit in
acceptable repositories.
And that includes not only the article itself or the
the publication itself, but also the underlying data
as well as the metadata describing kind of the researcher
and just making some of that research process transparent.
In addition to that, all federal funding agencies must now adopt these policies
when the previous memo was only to the largest agencies.
So that includes agencies like any age, which was not originally included.
This promotes equity and access to research.
It increases trust in the research that's being participated in.
And it makes sense.
Taxpayers are funding this research
and that research should be made available for any use.
We also saw the importance of this, of course, as I mentioned, numerous time
and public health side I have too is during the COVID 19 pandemic
where the access to information allowed for the speedy
creation of things like vaccines and understanding of
this virus.
So what is the role of medical libraries in all of this?
Well, I'll be honest.
I'm already hearing from medical libraries in terms of what this means,
not only this new post up memo, but the NIH policy
that is coming into place in January
as these policies and memos
work toward motivating researchers toward openness.
They are looking to their libraries to support them
as they engaged in the changes necessary
to be able to foster that.
Not only the researchers, but I mentioned that in my presentation,
also the institution as a whole.
I worked when I was a data librarian
with a number of nonacademic units
to create policies within the institution that aligned with these federal
federal policies and memos to also create infrastructure that made it easier
and to look at the software and tools that we have available
and how can we make them as seamless as possible
and as focused on reproducibility and openness as possible
in order to do that, that it can be things like teaching how to make use of
tools that allow for reproducibility,
saving an open file type,
and depositing in these repositories that are being recommended
by recommended federally.
So I think there are a lot of opportunities for libraries
and it's a matter of getting engaged in this process
and also looking at the leadership coming out of the alnylam.
Thank you. Peace. That was excellent.
So we do have a question for the panel.
Then I would actually ask each of you to answer that, which is what
other frontiers and opportunities do you see for your institution?
So we'll go back to the order that we started,
which is Christy Holmes from Northwestern first.
Sure. Thank you.
So for me, I mean, I think your sky's the limit.
It's been a remarkable day to hear about all of the ways that
that we see intersections between
data and informatics
and research activities and the people that not only
do this work, but the people who benefit from it as well.
So the thing that's making, I think me most excited these days
is the role that libraries can play in equitable access to research.
So taking advantage of not just technology but social strategies, you know,
working with people, engaging in railways, partnering with communities,
community led research activities so that we're really making
the most of these incredible investments by American taxpayers
so that it's not of perhaps
as technologically
strong of an area.
I don't see a lot of, you know, huge
work to build technology or
data standards necessarily.
But I do think that it's something that requires intentional action.
So it's something that everyone agrees is a worthwhile activity,
but it's really hard to be intentional about it.
And so that's something I've been thinking a lot about these days, and
I'm really excited about the work that libraries are playing
to help to advance this this work and in many different areas.
Right. Thank you, Christine. Philip.
Yeah.
So I, I will give three concrete examples that I think actually are just emblematic
of some bigger themes.
So I think you heard all three of us talk about in different ways
the critical issue of communications and in particular
how we equip our various constituencies in our academic health centers
to more effectively communicate with the broader public.
And I think that's a unique role that the libraries and our institutions
can fill, certainly at our institution and an area where we really want to lead,
because we believe that the trust gap
between our communities and our researchers and practitioners
is an impediment to achieving sort of critical goals around access ,
affordability, equity and improved overall population level health.
And it starts with being able to communicate
and get people to sort of understand and have a sort
of shared framework for the current state of the art in health and health care.
So that's one big area.
I think the second area and I alluded to this is how do we better help
our investigators specifically in the research arena, navigate
the myriad of large public data resources that are available?
And at the risk of sounding like I'm making an editorial comment,
I'll say that, you know, the natural tendency of funders and researchers
alike, when given the opportunity, is to create yet another data set.
And the question is, you know, are we fully leveraging the very expensive
and very sort of voluminous data sets
we've already created before we create yet another data set?
And I think that begins with helping people, people
to understand and discover what resources are there,
how we can augment what they may be doing at a laboratory or clinical research
or population health level, and then bring those pieces together.
And again, I think it's a unique role that the library can fill.
And then the third, which is much more aspirational for us, is that,
you know, we have a very large health system
and we all know that, you know, health systems are increasingly aggregating
and creating larger and larger networks of both ambulatory
and inpatient facilities.
And we have really just this incredibly diverse
workforce of individuals at all of our facilities
that need access to just in time contextual information sources.
And we believe that those individuals will benefit greatly from the expertize
and capabilities that a medical library brings to the table in terms of delivering
the right information and the right time, place and format and of note.
That's a critical intersection of informatics and library science.
And so we're really focused right now.
Like I mentioned earlier, we've got 14 hospitals over a 300 mile
catchment area and they're not all tertiary care, academic health centers.
In fact, that is the minority of sort of the beds and employees in our system.
And so the question is,
how do we extend the reach of our medical library
to meet the information needs of those individuals
where we can see direct impact on not only education and workforce
development, but patient outcomes and quality and safety and value of care.
So those are sort of three big themes that we're particularly focused on in terms
of sort of frontiers and opportunities that we really want to pursue.
Thank you, Philip.
So peace.
The question is to you as well.
And I don't know whether you want to put on your internal Center
for National Center for Data Services or one of your other hats.
So, again, what other frontiers and opportunities
do you see for your institution?
Like an institution?
Yeah, just thinking generically.
I think just to add to something that Philip said
about kind of always wanting to create another data set is the idea
of the massive amount of information that is currently existing.
And kind of going back to what we know about human subjects research
and the idea of respect for persons and thinking about
honoring people's participation in our research,
whether it's a survey or something a lot more involved
or even just making use of their our data.
This is something that we need to remember.
And I think that also drives
our aim toward the open movement of rather
than kind of recreating every time we're making use of what already exists .
And I think libraries can help drive that.
In addition, I think that there is so much to develop
in terms of linked data and interoperability making use of.
There is some talk about machine readable
data in the new oh step memo,
but you know, just thinking about more than kind of.
Static datasets and how we can build infrastructure for that future.
I also think that there is a push pull between
participant and patient privacy and confidentiality of their information
and scientific advancement and how to respect that, particularly
as we think about marginalized communities and
who is involved in the research and who is involved
and kind of as the researcher and as the patient and participants,
I think that libraries have a lot to to develop
and to explore in terms of moving this forward in a
in a way for discovery, but also in a way that respects persons.
Great.
So the other question that's come in from the audience is Dr.
Payne explained one focus of his institution, among
others, is to be the history of medicine.
Can you please describe how this focus fits with and contributes
to the contemporary mission of Washington University St Louis?
Yes, sir. It's a great question.
I would begin by saying I'm a little bit of a history nerd, so
fundamentally, I'm always excited about our Center for History
in Medicine and the archives collections and the other activities of that group.
But I would start by saying, you know, we recently went through a process
of refreshing our medical school curriculum,
and we really found that there were three essential themes that weren't reflected
in our current curriculum that we wanted to embrace with that refresh.
One was really preparing our providers
to be more humanistic and more able
to serve as advocates for the patients and communities that they serve.
The second was to incorporate public health competencies
into sort of the core competencies of practitioners.
And the third, quite, I guess,
sort of
constructively for us was to incorporate digital health
and informatics and data science as sort of another core competency.
But from our perspective, you know, being able to prepare
future practitioners that sort of embrace the humanistic side of medicine
and that are able to advocate for the communities that we serve , begins
with understanding the history
of how those individuals and communities had been served in the past,
and that history is both positive and negative.
And our Center for History Medicine both provides
sort of the tangible artifacts and the expertize to help people navigate
in sort of a given domain so that all of those knowledge resources,
but also , as I mentioned earlier, serves as the official historian
of our medical school to speak to sort of the role that we've played.
Again, you know, both positive and negative, because I think we all have
sort of, you know, dimensions of the histories of our institutions
that we look back at.
And in a current historical context, you know, requires some deeper analysis
and understanding.
And so that is a central role of that center.
And we also want to support both trainees and faculty
that want to make the history of medicine part of their scholarly endeavors,
again, reflecting that humanistic angle of the field.
So when you put it all together, you know, the value of histories
is the history nerd in me is being able to learn from prior
sort of positive and negative lessons and then transpose
and understand that in a current and contemporary context.
And that's exactly what our center does on a daily basis.
And it also is a sidebar has the the distinction
of being very poppy for the fact that there are a couple Nobel medals there
that on occasion you can go and actually hold.
So if you are so inclined and you're in Saint Louis, we can arrange that as well.
That's awesome.
So peace or Christi, do you have any thoughts on that as well?
I think, too.
And so actually we have a number of really important
partnerships that flow through our special collections.
It allows us to be able to ask questions and investigate topics
in a much more nuanced and I think engaging way
than simply a report or a discussion topic.
And so one resource.
The National Library of Medicine
that I'd like to highlight is the exhibition program,
and that's been a really tremendous opportunity for us to be able
to catalyze conversations on our campus across a wide variety of topics.
And so this exhibition program,
it's really fantastic.
There are resources that travel around the country
that are banners and other kinds of exhibit materials,
and you're able to set it up in a way in your space, whatever that is,
that provides a weight for the attendee
or for our patrons to be able to look at this content in new ways.
And then we supplement that
with materials from our special collections
that may look at that topic from a historical perspective.
We also then use it as an opportunity
to catalyze conversations that perhaps
may be related to the topic in the in the exhibit .
And so it provides a really I think
it's a
setting, an environment to ask difficult questions to
to perhaps ask ourselves how we're contributing
to some of these topics or conversations, how are we advancing
what's happening on our own campus and in our community in meaningful ways?
And it's been a great catalyst for networking, too.
We have a number of conversations and partnerships that have started
as a result of conversations that have started from those activities in the past.
So we're delighted that this program has started again
from the National Library of Medicine, and we'll look forward to hopefully
being able to bring one of those exhibits to Northwestern.
Thank you for hosting.
And I can echo what you're saying, because when we bring those exhibits
and we do programing around that, that allows us to contextualize
the history of medicine in Richmond, Virginia and across the country
as a unique learning opportunity for many of our users.
So with that, I would like to thank the panel
for sharing their knowledge and experience.
I very much appreciate your contributions to the session
this afternoon, and I am going to turn things back over to Jeff.
Thank you very much, Theresa,
and to all of our panelists, outstanding presentations and a great Q&A.
Really appreciate your time and your engagement with us on this wonderful day.
And we are going to take another break or 15 minutes.
Our proceedings will pick up around 5 minutes to the hour.
So please come back and join us for our last two presentations of the day.
Thank you very much.
Welcome back to the 2022 Lindbergh King Lecture and Scientific Symposium.
My name is Jeff Reznick.
I'm chief of the NLM History Medicine Division.
And it's been my distinct privilege this afternoon,
all day to moderate our proceedings.
For those of you who are just joining, please use the live feedback button
under your video stream to send questions or comments.
We're going to continue with our program.
And in so doing, it's my great pleasure to introduce Betsy
Humphreys, who is with us, to offer her reflections on Dr.
Lindbergh's leadership and scientific legacy.
Betsy, retired as deputy director of the National Library of Medicine
in 2017 after serving in that position for 12 years.
Throughout her 44 years at the helm, she took on many responsibilities,
including serving as acting director, where she was responsible
for all of the library's activities, ranging from program development
to evaluation to policy formulation.
Betsy contributed to the development of the NIH and HHS policies
on health information technology, public access to research results,
and clinical trial registration and results reporting.
Her earliest accomplishments at the NLM included automation
of internal operations, leadership of intelligence, library operations,
division, where I work, and direction
of the Unified Medical Language System, UML Large project.
And very notably, Betsy recently co-edited a very important book
entitled Transforming Biomedical Informatics
and Health Information Access, Donn Lindbergh and the U.S.
National Library of Medicine, published this year by iOS Press.
Welcome back to the great to see you.
And I'm going to turn things over to you. Thank you.
Oh. Okay.
Thank you, Jeff.
This has been a great symposium, a really interesting day, of course.
I love hearing about
the wonderful things that people have done with data and services.
I enjoyed seeing people who were helped early in their career
by training opportunities that NLM provided.
And so it's a great treat for me to listen
to people, many of whom are my long term friends and colleagues.
So I've enjoyed it a great deal.
I think the Dawn would have approved of a program that began
with a focus on patients and included so many stellar people who were benefit
have benefited from MLM support services and training programs.
It would also have resonated to the recent comments
about needless creation of new datasets, respecting research
participants contributions by enabling re-use of their data
and the value of history and and of anyone
traveling exhibition program, which is really part of his legacy.
He was a tremendous.
He was a
tremendous contributor to an Olympic history of medicine programs
along multiple dimensions, including really
integrating the onsite exhibition program and really pushing traveling exhibitions.
So he'd be glad to hear that people are still using them
and enjoying them.
Having listened to everyone's comments
about Dawn's outstanding qualities as a leader and a person,
you know that I was beyond fortunate to have worked directly with him
for all of his 30 plus years at the National Library of Medicine,
and to have had the advantage of him
as a mentor, a great boss and a good friend.
And because of the latter, also
because of all these roles, really also
becoming a great friend of Mary Lindbergh
and knowing his family.
I think that it's obvious
that Don was a great boss.
He gave
people who worked for him,
myself and others, challenging opportunities.
Resources.
Lots of running room.
Good advice.
Back up when things get sticky and
and plenty of limelight.
Don started many things.
And if you came along later,
five years later, ten years later, 15
years later, you might have said, well, what did he have to do with this?
I, I see.
You know, Alexis, Betsy, I see David Lippman or whomever.
And it's because that he got things started.
He delegated and he gave a lot of freedom.
And he didn't need to be the front person for the things that he turned over.
He was very interesting in what he spent.
His personal time are very
judicious.
He had a particular.
View of looking
at each activity and seeing whether
the direct participation of the director of the National Library of Medicine
could make a difference.
And in a lot of areas, that involved
making underserved populations
realize that no one was serious
about working with them and helping them, or encouraging
leading lights in the fields who were headed to retirement
to deposit papers where they would be taken care of.
And in coming up
with great ideas about how technology could be used in a particular program,
he would be passing off great ideas and focusing on some of them.
So that was another aspect
of his great leadership.
Like. Dr..
Carney this morning, I'm going to start by reminding you
about 1984.
In that year,
train searchers, primarily librarians, conducted less than 3 million
searches of an album database and paid their fair share
of the commercial telecommunications costs to reach into one's computer system.
They searched Medline and other bibliographic
the source chemical
toxicological and cancer databases.
The Libraries Network managed by NLM, the library network managed by NLM
probably filled about nearly 2 million requests for full text journal articles.
Although it would be a few years before Dr.
Klein could actually count them.
In 1984, all the index citations
and abstracts were key de novo for the Medline database.
Some of the data in the factual databases were received on magnetic
magnetic tape from other federal agencies and organizations,
including the Chem Abstracts Service actually,
and NLM licensed Medline to other US online
database providers and had formal agreements with the Pan American Health
Organization and the governments of 13 countries to facilitate, facilitate
access to Medline outside the US.
By 1984.
Standards like this with very heavy use.
Now imagine that you are very familiar
with that picture, Beetle, and you know all about it.
But just before dawn, Lindbergh arrives as director,
you are kidnaped by aliens and taken to another galaxy.
31 years later, they decide to punish you by returning you to Earth.
Knowing the NLM of 1984
and being apprized of the general tremendous expansion
in world worldwide, access to advanced computing devices and the Internet.
What would would strike you as most of the most surprising
aspects of intelligence services in 2015?
I think it would be what was entirely new and had no precursor.
In 1984,
my comments are going to center on
how expansion of intelligence scope from 1984
to 2015 occurred and the role of Don Lindbergh in making it happen.
Excuse me, Betsy.
Yeah. Hi. Pardon me. It's Jeff.
We're not seeing your slides advance.
And you do have control. Yes, but that's.
That's that's because it's not ready to be advanced yet.
Fair enough. All right.
Sorry. We just.
I failed 1 to 1 in presentation by having so much to say
about before I advance my slides, at any rate.
Thank you.
At the time Don retired in 2015,
I first encountered Stuart Kaufman's ideas about the adjacent possible
and their application to institutional innovation.
Kaufman theorized an additional contributor to evolution,
quote, It may be the case
that biospheres on average
keep expanding into the adjacent possible.
By doing so, they increase the diversity of what can happen next.
This is a good metaphor for expansion of Alan's programs, services and influence.
If you have a broad view of what's adjacent
and what's possible, as Don Wennberg clearly did.
Well, now I am trying to advance them.
There we go.
So I want to.
Talk about
why Don Lindberg came out and
he came with a purpose.
He in turn, he he looked
at the opportunity of an alliance directorship.
And realized that NLM was in a position
to really accelerate the applications of advanced
computing and communications to patient care
and biomedical research.
And he thought that he was a person
who could really make this happen.
He was attracted by the existing
and Elim Foundation
that he could build upon.
The mission he loved
and frequently quoted is. And.
He was aware and because of his previous experience
at NLM, which involved
serving on the board of scientific counselors for the Lister
Hill Center and also serving on the block, which we've heard
discussed by previous
speakers, the grant review committee.
He knew that
NLM had a really multidisciplinary staff
with.
And multidisciplinary programs that covered the gamut
the services, the educational program, research and grants.
So this was a broad way.
Many different ways he could influence what he wanted to have happen here,
which is the application of computers to health
care and biomedicine .
He was proud of the services that ILM already had.
They were excellent.
They were regularly updated, and for 1984, they were very
frequently used.
And he was very enthusiastic
about the NLM network.
Because of his experience.
As someone in institutions
to work members of the network.
He was very admiring of the
capabilities of medical librarians.
One can sort of understand why one of the medical librarians
that he was very familiar with was Estelle BROADMAN,
who was director at WashU and a real pioneer in library automation.
He. I first spent
time with him when it came by giving him a tour.
Somebody asked him if he would like to see
the current state
of automated systems that were used to build and alarms databases,
and they were among the systems that we were in the midst
when he arrived of redeveloping and trying to improve.
And he responded.
Nothing would please me more.
And I was given the role of giving him the tour.
I immediately discovered some things that
you all know, too. If you knew Don.
He was interested in everything.
He was fascinated
at looking at the online indexing system.
Of which he was very complimentary
and he asked
questions that I thought that I realized later
were questions to desire to find out whether the users of the system
had participated in designing it and whether it had been developed
in an innovative way.
Because as far as he was concerned, that was the only way to develop
a good and useful system.
ED of
when the users and then make the improvements based on real use.
One of his famous quotes is systems that get used to get better.
So he was very interested in that, but he was also interested
in the fact that the Cataloger who was showing him the catalog system
was working part time at home.
This was in 1984 and NLM was the first was doing an experiment.
We were the New Age experiment about flexi placed, you know, working at home
some days or whatever.
So he was fascinated by that and he was perfectly delighted
that NLM had been in the forefront of that
as we were actually in the forefront of a lot of things.
So I learned about a lot about him on that trip, on that tour,
and he immediately asked me as he asked everyone
when he was thinking about something and he met somebody new and he wanted
some, you know, he just would ask, well, what do you think about this idea?
So he asked me, what did I think about the UI M.S.,
his idea, which was very sort of inchoate at the time.
But I said, well, we
have a little minor project that sort of is in line with that.
And you said, Oh, what was that?
And I said, Well, we have a project to map
the medical parts of the Library of Congress
subject headings to the medical subject headings, which is the
we used it in a room and he immediately said, This is music to my ears.
It was not long after that that I was on the M.S.
team, but.
He arrived with visionary ideas.
Moving ahead on them.
Was going
to obviously require a substantial increase in an arms budget.
And the list of his initial priorities
he brought really reflected this.
You see them here along with cryptic notes on early progress,
which went ahead pretty quickly, as you can see. The.
The health community,
the health care community for as far as he was concerned, the general public
and the Congress
needed to become more aware of and eliminates programs and services.
The Board of Regents was all on this page already, so they really supported this.
And in a very fortunate coincidence, an alum was to celebrate
its 150th anniversary in 1986.
Dorn saw this as ample justification for special events and expanded publicity
much more than an Olympics in planning, I should say, before he arrived,
and much of it was sponsored
by the newly established friends of an alum, which he was
no enthusiastic about that.
That new organization, which also I think
was created in 1986.
Now, to make an important difference in justifying increased resources,
the library needed a long range plan with compelling goals.
You've heard a lot about it and you've seen it.
The board was in complete agreement
with this priority of Don's as well. And.
Dawn was absolutely clear that the plan should reflect the ideas
of a very broad, multidisciplinary,
narrow range of NLM.
Current and potential users, partners
and stakeholders.
As it happened,
about 200 people participated in the five panels that contributed
to the development of the long range plan for 1986 to 2006.
A number of them
were from many different disciplines were part of Dawn's
existing personal network to refer back to remarks in the last panel.
Donald West King was one of these.
Like Donald King, many
participants became strong advocates and allies
for involvement for the plan and ran around,
as you heard, heard before,
seeking and listening
to ideas and opinions from a wide spectrum of sources
and enlisting them as allies was a hallmark of Don's leadership.
To quote him, No one has a lock on good ideas.
They come from everywhere.
The great idea to establish and CPI it.
An alarm arose in the panel planning panel on factual data,
which included one future and two former Nobel Prize winners.
One at least Josh Lautenberg,
was a long term colleague of of Dawn.
The overall 1986 plan
raised some topics as requiring more focused plans.
Dawn considered two of them to be especially important.
The specially focused outreach panel chaired by Mike DeBakey,
another previous colleague of Don's, advocated expanding the mission
and funding of the Library Network to promote online services to health
professionals not affiliated with institutions and medical work
that had medical libraries in 1999.
In 1990, Don made outreach to expand the use
of all alum programs and services and alum wide priority.
And it was one that was highest priority for him
till the day he left the National Library of Medicine.
Also in 1990, a special planning
panel on electric electronic imaging chaired by Dr.
King, I should say, endorsed the production of the visible human datasets.
And provided a blueprint for the project
in 1990, Don believed in the importance of imagery
in understanding biomedical concepts and data.
To Don.
The increasing availability of personal computers in offices
and homes was a golden opportunity to expand and alarms directly as a group,
to use this group to help professionals
by providing an affordable way to search Medline to answer clinical questions.
He was particularly, again, particularly
concerned about physicians practicing
outside of institutions with medical library services.
Less obviously pneumonia, less resources he envisioned would be the first in a line
products designed expressly for system developers and informatics researchers.
In 1984, the problem they were designed to address, namely the differences
in terminologies and codes used in disparate electronic
biomedical databases,
was a problem that Dawn saw,
but very few others did.
And then, in response to recent reductions in anyone's extramural budget
not unrelated to acrimonious interactions with publishers in the information
industry, Dodd's initial priorities included the grant budget
improving increasing it and improving relations with publishers and
the information industry.
There were many heroes in the best start to Don's tenure
at NLM, including great advisors, strong advocates, etc.
supporters in the Congress
and terrific on staff, both existing and newly recruited.
But Don's visionary ideas.
Ability to inspire. And.
Action and newly
and uncanny judgment were essential.
Throughout his career, Don made inspired decisions about what to do
and when to do it.
A shining example was his
decision to aggressively
pursue the establishment of NCI as the highest priority
coming out of the 1986 long range plan.
I should add that Don
also made great decisions about what not to do in that category.
His first and best was refusing Ken Smith's offer to step aside as
deputy director.
The establishment of an CPI
at an ELM in 1988, with the function shown here,
an initial budget of 8 million had a tremendous positive impact
on biomedical science and on the scope and effect of integration of mental health
services, as you heard from many speakers.
It made sense, as stated by the planning panel because, quote.
At the time.
The problems of scientific research in molecular biology
are increasingly problems of information science.
I think they still are.
However, the establishment
at NLM was by no means inevitable.
I am sure that the advocacy
of Josh Lederberg, Alan Maxim, another Nobel
Prize winner, and Richard Roberts, who would become one,
was extremely helpful
in overcoming the skepticism in the scientific community
that a library was a reasonable home for this responsibility.
And of course, in addition to bringing the scientific community
on board, Congress had to understand the need for it.
You could see, Don, immediately, immediately
into recruited Dan
Macy's, who was an NCI branch chief, who had served on the panel
that made the recommendation as director of the Lister Hill Center to help
NLM scientific visibility and credibility in biotechnology information.
And he was ably assisted by Denis Benson, who was already working in
Lister Hill at that time.
Parallel efforts,
which involved another NLM employee, Frances
Humphrey, Howard Hubert Humphrey sister.
The succeeded in educating Claude Pepper on the importance
of creating the center in the short window be cut
before the expected 1000
fold increase
in molecular biology data became.
By the time.
By the time Congress acted to establish NCB
in November 1988, Alnylam had a higher profile.
An initial set of microbiology research tools and was adding sequence
data tags to Medline citations, the latter being Don's Idea and
instruction to the indexing operation.
Dawn quickly hired
Dave David Litman to lead the new center once the law was passed,
and Jim Astill actually arrived in England shortly before.
David.
And of course, as I said, Dennis was already in place
and CBI was up and running
in 1989, early in 1989, and designated to assume
full responsibility for Gene Bank in 1982.
In the 1990s.
And Sally gave us insights to this and you heard from other people as well.
NLM embraced the Internet and the web browser and reinvented
all of its services.
It was this was not an easy thing to do.
It was inevitable.
As soon as the web browser appeared, every other interface was obsolete.
And issues and problems that you had been struggling with in the past like
nothing was really platform independent and designing
products to be loaded on machines as we were with grateful meant
and having to have a mac version of the PC version. So
the web browser was nirvana for service developers,
but we had a lot of services, so they all had to migrate and we had to
deal with.
Something that is not common today.
We had to make sure that all our existing users could make a had
an Internet connection and be had a Web capable workstation.
Now, of course, we're used to the fact that the.
Users having new devices means that the system developers
have to develop new services, not that you have to ensure that people
have the right equipment to use your service.
This change obviously enabled the things
that have made a huge impact on the world.
It enabled us to,
first off, and one of the earliest things
was to really make our historical resources
beautiful, gorgeous special collections,
pictures, movies, etc., accessible
to remote users in ways they never were before.
And this was something that was actually a big, high priority for Don.
As I said, he loved
the he loved
the historical collections.
The biggest thing I don't have to go over was except to tell you
that it was important to orchestrate.
The. Announcement
of the free med line in such a way
that there would not be any blowback from.
Others in the information industry about unfair competition
for the private sector and this, that and the other thing.
So consequently,
as Don said, I figured I was pretty bulletproof.
I was up there on the on the stage with Harold Varmus,
with the vice president and with Senators Harkin and Specter.
So he figured that
he was not going to get any blowback and he really didn't,
although this was a seismic and.
Upset in the access to information.
And of course once we saw
how the public was searching Medline the issue of.
But is Medline really going to be helpful to them
for many of their issues, which is gaining an understanding of basic concepts
and getting something that is not written and specialist few
people in library operations.
My predecessor, Alison Cogliano,
saw this one coming, so
a group was already put together to
develop a prototype of what became Medline.
Plus, as soon as we saw that the as Don saw
the level of public use of Medline.
This seemed like the next step.
And he was delighted because he would have always liked to serve the direct
the public.
But before the internet and the web browser, he didn't have a way
of delivering services that would be useful to people.
This is a very high level explanation which you already know.
And I'm not going to run through this about the fact
that by 2015 life was totally different.
And the time he retired, everything had expanded.
You've heard about it before.
You didn't hear so much.
But the active outreach program that NLM had was enormous.
The national the network of libraries had doubled in size because it now included
public libraries, community information centers and other partners,
as well as health sciences libraries, to help people understand
what was available to them for it and to actually become aware of it.
People don't use things if they don't know about them.
Many people say, Oh, you just discovered on the web.
Maybe a little harder now with so much stuff on the web.
Not as hard then, but a lot of people didn't at that time,
you know, didn't necessarily know why they should be on the web
or why they should be looking for it
and where they should go for health information.
So the outreach was really important.
And of course,
Medline began the avalanche
in terms of free data
available.
And there were.
Many more channels of access to data application
programing interfaces, download sites, integration of data across systems.
This is all made possible by these technological advances
that you all know about as well as I do. And.
NLM also worked on organizational arrangements and public policy
and trained more people that could contribute
to all of this, as we heard from some of them already today.
It was the interaction of all of these things, working on all of them.
They actually cemented and expanded them around
influence. So.
In this next set of slides I'm showing you are old slides.
This is what life looked like in 2015,
and you can see that a tremendous amount
had happened and much more has happened since and will still go on.
It's very interesting if you look at this little place
where it says PubMed citations back to 1940s
to the present, back to 1940s was also done.
But he initiated the project to go back from the sixties,
which is really where our automated data had started in
and convert the indexing
pre sixties indexing.
And of course the fast connections
were the payoff from the addition of data to analyze services.
What we just saw in terms of access to the literature
was huge and valuable and maybe our greatest contribution or is.
But on the other hand, you if you look back to 1984, it's in a straight line.
From there, it really is.
It's just doing it better with the with the technology that's available.
The creation of NCB
was a total different thing for album and it had huge benefits,
including the tight integration
and access mechanisms for all of these kinds of data.
I, you know, we could wonder whether this would have happened
if then CPI had been created somewhere else.
It probably wouldn't have had it happened as quickly or as smoothly.
Maybe it wouldn't have happened at all.
I don't know. But it's a huge
it's a huge legacy of that one decision.
Now, it's interesting to look at clinicaltrials.gov,
because the origin of clinicaltrials.gov was not a decision by anyone.
By John Lindbergh.
It followed the following sequence of events
in 1988, and ILM asked the staff what we could do
to serve AIDS researchers and patients better.
They said the top one would be to create AIDS baseline,
a focused, bibliographic database of AIDS information.
We did that in 19.
At the end of 1988,
in the same legislation that created NCI,
there was a requirement to build new AIDS resources for the community.
AIDS drugs.
AIDS trials. So.
I h everybody
looked at that requirement, which was HHS was all involved and everything too.
And they said, well,
and all of a sudden it's line and they have all this other database,
they should build the AIDS trials database.
So we did that.
So fast forward
in 1988, 98 for check in
1997 the.
The. Congress says builds clinical trials.
Soccer.
And Harold Varmus.
Who has this assignment?
Looks around.
Some progress is being made.
People are talking about it, but nothing is happening.
And in 1998, he sends Don Lindbergh an e-mail
and he said, Don, I want anyone to take this over to do this.
And you have the experience.
You've done well with AIDS trials.
So you take this on and please get back to me
immediately and tell me who on your staff is going to be in charge of this.
And Don shortly responded, Alex and Chris.
So then you end up
with the situation of alum as clinicaltrials.gov.
And as you see here,
we go down there, and ten years later, there's now a new requirement.
I think what's
interesting here and what our returned person
from the other galaxy would also find remarkable
was the extent to which NLM databases
and services were tied into
requirements for the research community.
Where in fact,
people had to use our services
because of what was.
Had been laid down
by legislation, public policy, and what have you.
This was a major change.
And then you get to an honest vocabulary portfolio.
I could give you a very long list of things that were acquired
as a result of this.
How this happened, it, Don, was essential
to this ending up being an initial priority.
And not only was it essential for him to get this
started in the direction for us to move ahead on this.
It was actually essential that he stayed as long as he did,
because this was also
quite a distance adjacent possible when we started, and it required
steady support and interest in this direction for this to happen
. I think.
That it is the data.
The NCB is genomic data.
The clinical trials, data and analytics
for in the standardization of electronic health data.
It is those things.
Which.
Are different in kind from what was going on
at the National Library of Medicine in 1984 and an alarm
that certainly Don Wennberg had a lot to do
with all of those directions.
But in fact
he would have been delighted and alone.
There is a connection between ANL and services direct used all the time
between Medline Plus and others,
and it is enabled by all of that work and standards.
But in the end,
what Don was really interested in was helping people.
And he focused
a lot of his own personal time on.
Trying to make
services and information more accessible, more usable,
and more useful to the whole community. And.
Trying to get more people
in that community into the business
of working on information systems and information delivery.
So I think that that is really a great part of this legacy.
Thank you.
Betsy, thank you very much.
We've received a number of comments during the course of your presentation
and one of them rings especially.
True.
And I'd like to just share and it's a quotation
that's been attributed widely to a variety of people
over the past several decades, but it applies here and I want to share it.
And then a follow on thought.
The comment is the Dr.
Lindbergh and his leadership of the National Library of Medicine
embraced the idea that the only way to predict the future is to invent it.
And I'd like to.
With respect to your your comments and those of earlier presenters say
we can extend that, saying the only way to predict
the future is to invent it, which is what he did, and to plan for it
with a distinctive appreciation of the past, combined
with embracing experiences and challenges and opportunities.
And to your very point at the end of your presentation,
being supportive of people all along the way colleagues, peers, students,
all who can contribute to the to the public service mission.
So thank you for allowing me to reflect in that way.
And thank you very much for your your presentation.
It's good to see you.
See you too.
Likewise.
So for our closing remarks this afternoon on this great day,
so many great presentations, we have a distinct honor before us.
It is my
pleasure to introduce Christopher Lindbergh.
Christopher Lindbergh is the grandson of Dr.
Lindbergh.
He is currently a senior at Portland State University in Portland, Oregon.
So he's joining us, obviously, from the West Coast.
His interest in photography and the outdoors
echo those of his grandfather.
In fact, as I understand it from Mrs.
Lindbergh, when Dr.
Lindbergh loaned Christopher his camera during a visit to Plymouth, Massachusetts,
when Christopher was about two and a half years old, Dr.
and Mrs.
Lindbergh were astounded at his excellent eye,
and they could see that Christopher had immediately taken to photography.
Indeed, he has grown to become what I understand, to be an avid photographer.
So it's therefore very apropos for Christopher
to close our proceedings today to help us see even further how his grandfather
exorcized his own eye to lead the world's largest biomedical library.
And in so doing, as we know,
leave a remarkable legacy of service to science and society.
Christopher, a warm welcome to you from all of us
at the National Library Medicine, the NIH.
And thank you for joining us today.
I'm going to turn it over to you. Thank you.
Thank you, Jeff, for those kind introductory words.
It's so great to see so many of you.
Betsy Can Smith, Claire McDonald's.
Jeff I like to take this opportunity to thank you personally
for all your hard and tireless work the last few years, putting this together
and making sure that we were able to finally get it done.
And I'd also like to extend that to the media team today
for making sure everything is done so smoothly.
Yes, as I say, this is no small feat.
I would have loved to have seen all of you
in person back at the library, of course, but
health risks demand .
Otherwise, we convene remotely.
Despite my initial disappointment at not being able to see you all,
I realized that again.
Like all of you, I agree 100% that my grandfather would have loved
the fact that this was still happening remotely and had an avenue to,
you know, collect, connect globally and make sure that this was
a nice.
Pathway for information to be exchanged and for all of us
to get together again after being apart for so long.
That was one of his main goals in his career
was to make public communication and make certain information
available to the public, as is perfectly exemplified
by his efforts with Medline and Medline, plus all those things.
He was someone who truly wanted to help people like feel and to further
the betterment of mankind, genuinely.
And there are many people like that throughout history who do as good
a job as he did and as are and are,
as in in close proximity to us as they do them.
He saw into the future of medicine and knew that the storage and transfer
and application of information
was going to change and knew that computers were part of the answer.
In a chapter of the recent book that Betsy
and Robert Logan have put together and put so much work into.
There's an excerpt that he says
Journals on the shelf will become too remote for immediate decisions.
And I think he was he was spot on and saw that coming a mile away
and that he assumed that computers would soon be potentially essential.
And I think by, you know, our our remote convening today,
he was on to something.
He loved his time at the library as as
I did as well the short time that I was there.
And it was truly the passion that fulfilled his life.
I was privileged to see this process firsthand from behind the scenes
as my time spent with him at the house was matched
in my early years to the time spent in the office.
He was the same person in and out of the office.
We all knew the same person.
Always cool, calm, collected from door to door.
He moved.
He loved every minute there, and I truly don't believe he ever had a bad day
in office or in his time at the library.
As I watched parts of the library grow and change,
the library seemed to watch right back as I grew up and
got to know everybody and they got to know me and see me
grow up and go through my processes.
And I was for a while an annual fixture in the mezzanine
every summer, which in itself was a great pleasure.
And I look back as
some of the greatest times
that I will ever get to experience.
These are, of course, among core memories of my childhood,
as are as are the people who were at the library at the time
previously mentioned Betsy Clam so many more
that I that I would love to mention and personally thank and extend gratitude
for for all the all of the time and
and kind energy that they have given me over the years.
I believe that I saw the library in its golden years,
both because of my grandfather's influence
and, as previously mentioned, the people who worked with him at the time
who he had handpicked and trusted and personally believed in.
And these are the part of the part of what made the team so special.
These people are part of what made the process and his time there so special.
The group of doers and accomplished years that followed and supported him.
And that he supported and followed right back.
Again, people like Betsy
Humphrey and Robert Logan are.
On our end and incredibly
special to the Lindbergh family and will forever
be held in the highest regards in our hearts and in
have put in so much fantastic
work into the book the last few years and making sure that we all can properly
remember
him and remember ourselves with him.
And the EP
and the organization of events and exhibits throughout the years
made the library a place that was enjoyed as well as respected.
And I think that was, again, one of his one of his driving goals for the library,
not just to be an intellectual powerhouse,
but to be a place that was inviting to everyone and made people want to learn
and want to come and explore and investigate.
And, you know,
things like the murder rooms and and the costume parties.
And, you know, when when David Nash had the Frankenstein mask on, you know,
these are all things that were just so fantastic and so great that
wouldn't have happened otherwise, I feel like.
And this was how he conducted himself,
a combination of well-rounded comedy,
as has been previously stated and constant commanding respect
not of people, but of the situation and how he handled handled things.
These also seem to be
recurring things in our adventures.
For example, 4th of July, one year at the Government Printing Office,
followed by several hours of lost driving in the city or boat
trips up the Potomac for the weekend, complete with towing up rock.
We one time we towed up a rock that was so big it took four people
and three different watercraft, two on wedge from the anchor.
And, you know, seemed seemingly.
Random elements of hilarity
that were seemed only
to to two part to perfect for the scenario,
you know, two to perfect.
So even an absurd
situation is just always had command of the situation.
And I saw how far this reach was
and how far his respect followed him on numerous trips that we took together.
One such trip to Alaska for the Native Voices.
When I was, I think, one of our favorite trips we ever took,
and I had never been there before.
My grandfather
was finishing up the work on that exhibit, Native Voices, whose traveling
adaptation would reach over 20 venues across the country in the following years.
Here we were met by Ted Mala, who facilitated our numerous bookings
and appointments and is one another of many, many people that I was able to meet
and be around and learn from and have been lucky to call my friend
ever since.
The hospitality and accommodation was second to none.
And I had experiences, like I said, that I may never have again that were so rich.
And these range from
salmon fishing in the rain to long nights
talking, you know, over several rounds of drinks with whoever was there.
And they were the kinds of conversations that had no destination or direction.
And I think sometimes these are the richest forms of conversation.
And it was rare that you would have a conversation with my grandfather
and not have learned something that you didn't know before.
And my relationship with him was similar in nature.
And I always had a tremendous respect for him, which came from the usual
familial, familial structure, but also in
his inherent way of commanding the room.
And there is never a lack of conversation.
And rare was the occasion,
like I say, where you would walk away not having learned something.
He had piles of books cresting the armrests on both sides
of two separate armchairs in two different rooms of the house.
And he had just had an ever growing intellect and thirst for knowledge.
This gave him the ability to entertain a conversation with anyone about anything
in a way that made them feel included without
looming an intellect or making you feel less than or uninformed.
I never felt condescended to or spoken down to,
which as I grew older, I came to realize was a true testament to his character
and himself as a person and all people.
Consistency and understanding were cornerstones of our relationship.
Some of his hobbies became mine and my endeavors
were always a priority and were treated as such and vice versa.
We both shared a love for cinema and film that stemmed from photography
and grew into something we learned we just loved doing together.
One Christmas, I remember we were all staying up for the New Year's,
for the ball drop, and we were channel surfing waiting to pass the time.
And until this time, my grandfather had never waste,
you know, wasted time with television.
And he saw it as just that, a waste of time for the most part.
And that night, though, we stumbled
upon Turner Classic movies, and this was a soft spot
my grandfather didn't know he had, and he was instantly hooked.
And if you're not familiar, it's just old, older movies
from anywhere from like the 50, 6070s, eighties,
you know, spaghetti westerns and things like that, and James Cagney movies. And
he's here.
He loved it. Right, right from the jump.
So we watched the nineties.
The first film that we found was the 1966 adaptation of Fahrenheit 451,
followed by a couple of Cary Grant movies.
And we became so infatuated with the films that we missed the ball,
drop the whole event and watched until about four in the morning,
which was shocking.
It was absolutely unheard of.
After the end of each film, I would go to turn off the TV,
and before I could reach it, he would say, Well,
hold on now, hold on, see what else there is.
And we would slide right into the next movie,
and then we would get right through that one.
And it just went on and on and on. Analysis.
I feel his first introduction to television
and you know, after that he like he loved the Westerns, the John Wayne's
and all those great things whenever, whenever he had the chance.
But it was never a form of entertainment that he stuck it out or would seek out.
That being
said, this has become one of our favorite things to do together.
Our love of photography helped me
grow a passion and practice that has become a business.
As you can see, I'm in a partially finished studio
for green screens and media production,
and I have been running a multimedia production business
for about the past year and hope to scale into a successful brand.
After the practices of my grandfather and his photography,
in addition to myself, Rob Logan and I have joined forces in attempts
to digitize and preserve
that vast collection of photography, which includes prints and digital copies
and amassed images from my grandfather's extensive travels.
These will ideally be the next installments
in the Lindbergh legacy and will hopefully be available
on the Internet as these recordings will be in the next year or two.
He shared these experiences with my father before me
and I hope to share with my family in the future.
Looking back, the things that stand out as core
memories are seemingly simple in nature.
But the older I get, I see them differently
and with a more refined understanding.
For example, the fact that my grandfather taught me how to swim in the backyard
pool of the house in Maryland, which I'm sure many of you are familiar
as a child.
These are some of the best days in your life.
Sunshine Pool Toys.
Visiting the grandparents for the summer.
It's all sublime.
This is how I remember this memory for years.
But now, with the prospect
of planning family for myself, I have a whole new level of respect
for my grandfather and what he was able to accomplish in that moment.
What was a simple afternoon of poolside fun to a child
was the result of years of hard work, accomplishment and commitment.
And the satisfaction of teaching your grandchild to swim in your own pool
alongside your beautiful house is a whole a whole worldly accomplishment in itself.
Accomplishment
was simply second nature to my grandfather.
His effortless control is something I look up to to this day
and try to restore in myself.
He managed to master so many facets of his life
in so many areas that it seemed daunting by comparison,
but he wouldn't see them as such and would simply advise you to do your best
and to do what's right.
And oftentimes they are one in the same.
Somehow some parts of me found it
somewhat difficult to organize this collection of words, mostly because
it seems stems from wanting to accurately and appropriately represent him
and remember him, as everyone here has done today, in so many beautiful words.
But it's really the finality of this event.
And although this is the final ceremony, I remind myself that it is
far from the last memory of the legacy best left behind.
The National Library of Medicine is forever
changed and influenced for the better, as is the world.
I extend a tremendous thanks to my grandfather for being the driving force
for our family and our surroundings.
And with that, I offer my closing statements and I thank you guys
all once again for being here, for organizing
such amazing tributes.
And I hope to see you as many of you soon as I can.
Thank you very much.
Christopher, thank you very, very much.
Your reputation, as I understand it,
from your grandmother as a photographer has
is incredibly, wonderfully obvious.
Your keen eye and keen ability with words
is fantastic. And.
I share your thoughts
respectfully, and I appreciate them both professionally.
Having known Dr.
Lindbergh myself for 7 to 8 years, maybe a decade,
but also personally, if I may so publicly say
the beautiful way in which
you articulated your memories of your grandfather is
unique to you
, unique to your memories.
But it's universal at the same time.
And I thank you
both professionally and personally for their wonderful, wonderful remarks.
And very respectfully, of course,
and with your remarks, I want to thank you very,
very much for your time and our communication for today.
And I look forward to our own the crossing again soon
and know that we're here to support you.
And we wish you all the best in your studies
and certainly in your business and on your own path in life.
Influenced so wonderfully by your grandfather and his leadership
of the National Library, Medicine and Science and society
and all that we've learned today from these wonderful proceedings.
Thank you very much.
And you really likewise, Jeff.
Thank you so much. Thank you. Welcome.
So with your remarks, Christopher,
and all of the wonderful contributions today, we're going
to conclude this special and outstanding program
that we've had the experience of of watching and being a part of today
on behalf of the entire National Library Medicine,
which I've had the great privilege of representing today.
Thanks to everyone for their contributions, and especially,
of course, to our keynote presenter, Dr.
Isaac, for his enlightening and thought provoking presentation.
Thanks again to the friends of the National Library Medicine, the NLM,
for their co-sponsorship of this event and for being such wonderful friends
of the NAL
and the world's largest biomedical library located on the campus of the NIH.
I'd also like to thank, along with all of you who are watching
and all who contributed today our outstanding and Elm communications
and media teams for their time and their outstanding talent and our
mutual support for such a long time to realize this wonderful event.
Each and every one of you on these fantastic.
It's been a pleasure working with you.
And this program is a testimony to Dr.
Lindbergh's leadership and scientific legacy.
And it's also a testimony to our teamwork and representation of the world's
largest biomedical library to the global public.
And, of course, thanks to all of you for tuning in near
and far for our watching our program today.
The archive proceedings will be available soon.
As I and others have mentioned, they will be available permanently
and freely to anyone in the world with Internet access,
and it will be in the Nature Video Cast Archive.
And for everyone who registered for the program, you'll receive word
when those proceedings are freely and permanently available.
Thanks once more, my colleagues and I appreciate your tuning in
and we look forward to keeping in touch. Thank you.