>> Lisa Cordis: Hello to all of our IBPCR [phonetic sp.]
participants from around the world.
My name is Dr. Lisa Cordis,
and I'm one of the directors for this course
and I'll be serving as a moderator for this session.
In this panel interview today,
we will get to know members of our research team.
We've assembled a team of research professionals
from the US National Institutes of Health
here in Bethesda, Maryland.
And our team has a lot of experience in clinical research
and is hoping to share some of that insight with you today.
So, let's begin with introductions.
Dr. Apolo, will you please start us off.
>> Andrea Apolo: Hi and thank you for having me.
This is a great idea. My name is Andrea Apolo
and I'm a Senior Principal Investigator
at the National Cancer Institute.
>> Denise Francis:
Hello, thank you for having me. My name is Denise Francis,
and I'm a Senior Research Nurse Specialist
at the National Cancer Institute.
>> Elizabeth Ness: Hi, I'm Elizabeth Ness,
and I am the director of our Office of Education
and Compliance here in the NCI's intramural program,
and it's wonderful to be here.
>> Paul Wakim: I'm Paul Wakim. I'm a biostatistician.
I'm actually retired as of two weeks ago, I --
but before retirement, I was chief of the biostatistics
and clinical epidemiology service
at the NIH Clinical Center.
>> Robbie Kattappuram:
Hi. Thanks for having me. My name is Robbie Kattappuram.
I'm an investigational drug pharmacist
at the NIH Clinical Center.
>> Cody Peer: Hi. Cody Peer.
I'm a Clinical Pharmacologist at the National Cancer Institute.
>> Stephanie Wilmot: Hi, my name is Stephanie Wilmot,
and I'm a Clinical Data Manager Supervisor
here at the National Cancer Institute.
>> Lisa Cordis: Thanks to you all for introducing yourselves.
I'd like to further discuss the roles and responsibilities
of each of our team members.
And Dr. Apolo, will you please provide some insight
regarding how you conceptualize a study and also
the key responsibilities of a principal investigator
as you move a trial towards implementation?
>> Andrea Apolo: Yeah, so it's a great question.
So, how do we come up with the ideas
that we are going to then implement into a clinical trial,
there are many ways of doing it,
we take drugs that are active in certain cancers
and only apply them to other cancers,
we take two active therapies, and then we can combine them.
Or we can take an interesting molecule
that has shown a lot of preclinical data
that is exciting,
and we do first in human studies.
So, that's usually you know, multiple ways of doing it.
And that's usually more for phase one studies;
for phase two studies we take -- for phase one studies,
we're really trying to understand the toxicity
and the tolerance of the drugs for the patient
and what the best dose is that can be safely given.
And then for phase twos,
then we're really looking at efficacy.
And whether the drug itself or the combination works
in a particular group of patients.
And then for phase threes, then you really compare a drug
that has shown efficacy to the standard of care.
>> Lisa Cordis: Thank you for that answer.
Working closely with the principal investigator
is our research nurse or study coordinator.
Denise, will you please share with us
some of your day-to-day responsibilities?
>> Denise Francis:
So, the principal, the day-to-day activities,
let's start from the beginning for
when the protocol is approved.
I work with the primary investigator
and the research team to build that protocol within our system
to make sure all the checks are done
to make sure we get quality data.
And then once we start to enroll patients,
I work with the team to screen those patients.
Make sure they're eligible based on the eligibility criteria
of that protocol. And once they're eligible,
enroll them in the clinical trial.
And once they start treatment I --
in my job, we give them their treatment schedule
and work with the infusion suite
and any other ancillary teams that we need to work with
to make sure they get the treatment on time
and monitor them for any adverse drug reactions,
or any reactions at all.
And make sure they're safe while they're getting treatment, so.
>> Lisa Cordis:
Which is obviously our number one goal here.
Unfortunately, the principal investigator
and the research nurse are not alone in this process.
And we have a number of regulatory experts
and experts in human subjects' research protections
which help our investigators along the way.
And Elizabeth Ness is one of these regulatory experts.
Ms. Ness, would you please share how you provide assistance
to the teams conducting clinical trials?
>> Elizabeth Ness: Sure.
Myself and my office, we provide general research education
that's grounded in the regulations,
first and foremost. We also conduct our own audits,
audits of our standard operating procedures, et cetera.
We review monitoring and auditing findings for trends,
especially as they relate to human subjects' protection,
and good clinical practice issues.
We provide consultation,
really in any aspect of clinical research implementation.
Most of our consultations tend to be around informed consent,
specifically non-English speaking participants
as well as adverse events.
And you know whether an event should be reported
expeditiously to the IRB or to the sponsor.
We also assist teams with their monitoring visits
or auditing, or even FDA inspections.
This can include supporting their own educational needs,
or preparing or helping them prepare for the visit,
or even being physically with the team
such as with an FDA inspection to provide support
and additional information as needed.
We also, myself and my office, provide,
develop our own research specific policies
and procedures for our research program
that are consistent with our regulations
and with our other human research protection program
policies as well as other institutional policies.
We provide more granular detail
on how to stay compliant with the regulations,
we can develop corrective and preventive action plans,
helping to identify the root cause
and how to correct or prevent in the future.
And so, overall, in a nutshell,
we really are here to provide support consistent
with the regulations and policies for our research teams.
>> Lisa Cordis: Elizabeth Ness,
I don't know what we would do without you,
your team and your group really keeps us
on the straight and narrow.
So, thank you for all of your work
in compliance and regulations.
Next up, we have investigational pharmacists.
So, investigational pharmacists have unique training
and expertise specifically in investigational products.
And this is in addition to the standard training
that a traditional pharmacist would receive in FDA
approved drugs.
Dr. Kattappuram, what is the role
of an investigational pharmacist in clinical research?
>> Robbie Kattappuram: Sure.
I think that investigational pharmacists play
kind of a crucial role in clinical trials
by really leveraging our pharmaceutical
and clinical expertise
with kind of the administrative and regulatory functions
to kind of help drive drug discovery.
So, our primary responsibilities
are really to support the protocol teams
and then also to do management of the study drug.
So, really, this entails reviewing the study documents
like the protocol,
the investigative brochure, the pharmacy manual,
and also developing study specific
SOPs and drug information documents
and dispensing instructions.
We also provide feedback to the study teams
on their protocols. And even in some cases,
we can assist in writing parts of the protocol,
or some of the sections of the pharmacy manual as well.
One of the biggest things that we do is ensuring
that the investigational products are received,
are stored and dispensed in compliance with sponsor,
institutional state, and federal regulations as well.
So, this makes -- so we make sure that the drugs
are stored under proper temperature conditions,
we make sure that sterile preparations
of hazardous or nonhazardous drugs
are made under USP 797 or 800 environments.
And we maintain steady blinding as well.
And through all this, we maintain the documentation
for all things drugs, so -- because we also participate
in FDA and sponsor audits as well.
And in some cases,
the institutions also have a pharmacist sit in
on the IRB committee or any other institutional committee
to kind of give some insight as to upcoming protocols.
So, I mean, you can tell from this discussion
that there are a lot of moving parts to clinical trials.
And so, as the pharmacists, we really try to take over
that drug management portion of it
so that we can let the study teams,
kind of, do their other tasks,
so that we can also ensure Safe Medication Practices.
>> Lisa Cordis: Thank you so much,
you play a vital role to the team for sure.
In addition to the investigational pharmacist,
there's also a clinical pharmacologist
that's involved with clinical trials,
but in a very different role.
So, they're focused more on pharmacokinetics
and modeling, for example, Dr. Peer,
would you please elaborate on your involvement
in drug development trials?
>> Cody Peer: Sure. Thank you, Lisa.
The pharmacologist's job is really to analyze
both what the drug does to the body
when administered to a patient,
and also what the body does to the drug.
And so, each of these processes
combined constitutes pharmacology.
So, what the body does to the drug
is considered pharmacokinetics,
also called PK, what the drug is doing to the body?
Some change in, you know, some signaling pathway over time
that change is a dynamic change.
So, it's pharmacodynamics is that discipline, abbreviated PD.
So, a lot of PKPD studies are conducted in clinical trials,
and it's a pharmacologist's role to analyze that PK data,
that PD data, and ultimately answer two big questions
how much of a dose to give, and how often to get it.
Now another major reason we do pharmacology
other than optimizing the dose
is to understand patient to patient differences.
In other words, inter individual variability.
So, if you and your neighbor, for example,
both take the same dose of the same drug,
there's a good chance that the two of you
will have different experiences, whether that's from the intended
on-target pharmacological effects,
or from unintended off-target toxicological effects.
Now, the reason, in this example,
you and your neighbor might have differences in response
could be some pharmacodynamic reason like you
have different expression of the target receptor of the drug,
or it could be a pharmacokinetic reason
such as one person has a slower metabolism
of the drug in clearance,
which could be further due to genetic reasons.
So, with pharmacokinetics, the word pharmacokinetics
broken down is drug movement.
It understands the rate processes
of how a drug moves throughout the body,
how it's absorbed.
From the formulation, administered,
how its distributed throughout the body
and gets to the site of action,
how the body when it recognizes this foreign substance
tries to metabolize it and get rid of it.
There's a rate of metabolism and a rate of elimination
and pharmacokinetically, you can build them,
you can apply a mathematical equation or a model
to describe the disposition of the drug over time.
And in trying to understand
why some people react differently to drugs,
from the pharmacokinetic standpoint,
you can also factor in variables such as age,
sex, race, body size, body composition,
the genotype for a particular drug metabolizing enzyme
or transporter that handles the drug,
if the study drug is given with another concomitant drug
that might be affecting its metabolism.
If it's an oral drug,
are you experiencing differences in absorption without food,
or with a low fat or a high fat meal,
all of these things can be studied clinically and analyzed
by a pharmacologist through building models.
So, ultimately, you know, the personalization of dosing
is a goal of a pharmacologist,
that's not always achievable with a clinical trial,
but it's still the type of data we analyze and look for
and we want to make sure that the doses
we give in a clinical trial
are going to maximize efficacy and minimize toxicity
in a vast majority of patients
which gives the drug the best chance
of being approved by the FDA.
Might have been a long-winded answer,
but I really enjoyed doing this type of pharmacology work
and with oncology, especially that I work in the NCI,
oncology drugs are very toxic.
So, really pinpointing that optimal dose
that minimizes toxicity and maximizes your benefit really
is a crucial question to answer. Thank you.
>> Lisa Cordis: Thank you, Dr. Peer.
It's such an important role on the Clinical Research Team.
Another key role on the team is the statistician.
A lot of our investigators have an understanding of statistics
but really having the expertise of a biostatistician is key.
Dr. Wakim, would you please explain
how biostatistician works with the principal investigator
on the study statistics?
>> Paul Wakim:
Yes, the statistician is quite involved at the beginning
and at the end of the study,
I mean, that's the heaviest involvement.
And so, let me take those two separately,
at the beginning, there's, like two parts, connected parts,
the design of the study and the analysis plan.
So, the design of the study
starts with the primary research question,
what's the primary research question?
And what is the measure, the quantifiable measure
that will be analyzed to answer that question?
That's extremely important,
the most important part of a study.
So, sometimes PIs are pretty clear about it.
And sometimes they're exploring, they're just thinking,
and they're --
so the statistician in that latter case,
the statistician can help organize thoughts, thinking,
how to quantify, how to design, basically answer that.
Also, part of the design is the, like, urbanization,
and how many treatment arms you're going to have.
Do you do an observational study?
Are you going to do randomized trial?
And things like that? The sample sizes?
What sample size are we going to need?
So, that's the design part still, at the beginning, also,
at the beginning of the study, is the analysis plan.
So, the analysis plan is basically,
well, how is the data going to be analyzed?
And what's the best approach?
And all the details that are around the analysis plan?
Like you would have what if the assumptions are not met?
That, you know, like you thought the data was going to be normal
and now it's not normal, what are we going to do?
Or like, how are we going to handle missing values?
How -- what if we're doing a longitudinal study
or a cluster study, and we have correlated data?
How are we going to handle the correlated data?
Are we going to do an interim analysis?
All of these are part of the analysis plan.
So, that's at the beginning.
And of course, this is very close collaboration with the PI,
and the team, the whole team,
because it's a back-and-forth thing,
it's not just the statistician goes away,
disappears, and comes back, and here it is.
So, that's the beginning.
Then the study is conducted.
And then you've got the data's collected.
And then the statistician is, again, quite involved
in the, of course, the analysis of the data.
And it's -- again, it's an iterative process,
it's, you know, every time, you know, I do something,
I show it to the PI's, does it make sense,
does it makes clinical sense.
You know, it's easy for me to do the stat modeling,
and poof, here's the result. But does it make sense?
And sometimes the answer is yes, sometimes the answer is no.
And if the answer is no,
it doesn't mean that something was wrong with the analysis.
It could be two things.
One is, well, it's something is not quite right,
whether the analysis,
or maybe there is an outlier somewhere that's driving things.
So, if -- so we look into it.
Sometimes it's not what is expected,
but it is what it is, the statistician looks into it
doesn't see anything odd. And that's the way it is.
And it's sometimes you know,
you wonder, I mean, let's put it the way it is.
And then -- and let's be transparent about it,
even though it doesn't make sense,
let's be transparent about it in the manuscript.
I have to mention one thing that happens quite often
is there's a tendency with the PIs to say,
okay, why don't we try this? Why don't we try that?
What -- why don't we include this?
This is after the data has been collected,
the analysis has been in print,
and I don't blame PIs for doing that.
I wouldn't have done the same thing
if I were in their shoes.
But there's a -- there's this tendency,
you know, try this, try that, try this, try that.
And one has to be careful as long as we're transparent
in the manuscript about what was the plan
and what was not the plan, it's fine.
I mean, at the NIH, we're about exploring and understanding.
So, it's okay to explore and try things but statisticians
call it the fishing expedition, you know, meaning, you know,
if you try this, you try that, you try things enough times,
eventually you're going to get what you want.
So, one has to be careful about this.
And that's why a single study is not definitive,
I always say a single study is not the definitive answer.
And that's when meta-analyses are very valuable
because they collect several studies
and see if there is consistency in the results.
So, that's the -- at the end.
And finally, at the writing of the manuscript,
as a statistician, obviously, is going to write
the statistical methodology section of the manuscript.
The results, you know, typically the PI writes the results,
but the statistician --
I'm not talking about the discussion,
just the results, the fact --
the statistician has to review very, very closely,
the results section,
all the numbers has to have to be double checked.
And the wording, how the results are being presented have to be,
you know, closely reviewed.
And of course, when you know, the manuscript is submitted,
and reviewers are sending comments,
and if there are statistical issues,
the statistician is also involved
in the addressing of the reviewers' comments.
>> Lisa Cordis:
Thank you, that's very valuable insight.
Another member of our research team
that is key to our success is our data manager.
So, Ms. Wilmot, would you please share
how a clinical trial data gets collected,
and the role in the data --
of the Data Manager in that process?
>> Stephanie Wilmot:
Hi, everybody, thanks for having me.
The data managers are usually assigned
according to the branches that they're assigned to,
for example, the molecular imaging branch,
your oncology Branch, things of that nature.
So, what happens when data managers when they're assigned,
they're usually contacted by either Liz Ness's team,
or the sister contract, which is our central support contract
that consists of builders' protocol analysis,
these individuals are responsible
for building the actual protocol.
We attend, we are also invited again
from the beginning, middle and end.
So, we do attend the site initiation visit
when the protocol is presented to the scientific community.
And we start by working with Liz Ness's team
in either a preclinical data capture meeting,
or we work specifically with a research nurse,
and the PI in how the protocol is going
to be billed according to the protocol.
That usually takes place in various meetings
with the Central Support Program protocol builders,
and it's usually referred to as data specification testing.
This is extremely important.
And Liz Ness does a really good job of this.
And the research nurse, we all come together in a meeting,
along with the PI to see actually
what is going to be recorded in the case
reporting forms commonly known as CRFs.
Once this is done and the protocol is built,
then it's a process of communicating
with the research nurse,
usually with the Denise Richard --
Denise Francis, on specific protocols.
So, Denise will reach out and say, you know,
we have a patient coming in,
we're looking for the press enrollment
email with the patient information.
And usually what we do is the Data Manager
will wait for the nurse or we check the client,
the Clinical Research Information System,
also known as CRIS.
So, we check that for the first registration note,
we check for the research note, progress note,
various notes that incorporate the enrollment,
the history, the screening of the patient.
And we usually, once we are notified,
we have about 10 business days to enter that,
but we usually enter it a few days after
or right at the same time. Sometimes the Data Manager,
just to make sure for data consistency and accuracy,
we meet biweekly with a research nurse
to see if the data that is being captured
is reflected in the client in the case reporting form,
especially adverse events,
because data managers don't do calculations or attributions.
And so, sometimes when we read some of the notes,
it's best just for all of us to meet and have a conversation
on what actually is going to be recorded in the ongoing CRFs.
So, we follow the patient treatment cycle
according to the protocol.
We follow that along with a nurse.
So, it's a back-and-forth email, teams meeting.
And sometimes even chatting on teams, just to see,
especially if there is a site monitoring visit
or an interim monitoring visit that is coming up.
And we want to ensure that all the data is in.
Some of the patients according to the protocol,
according to the reaction to the investigational drug
have a significant amount of case reporting forms
that have to be filled out,
including waiting for attributions.
And again, we communicate consistently throughout the day
with a research nurse that is our point of contact.
And if something else comes in, last minute,
the research nurses that I've worked with over the years
are really good about either sending us a teams chat
or sending us an email
encrypted saying this patient is ready to go, and so forth.
We're also involved in working with the research teams,
once some of the data
is in periodically throughout the year,
there are certain reporting regulatory doc documents
that are needed continuing review,
FDA reporting, and also some of the research teams want
what is called J review standardized template reports.
If they're not available in the system,
the Data Manager will work with the team
and get those reports out as soon as possible.
And we also on our end, of this clinical data manager contract,
we do have our own review team that reviews the data
periodically to make sure that the data is going in,
according to data manager standard operating procedures.
Another thing that we do as well is we follow the patient
throughout the patient treatment cycle,
including offs, off treatment, off steady, follow up
and participate in all post IMVSMV* meetings
to ensure that what is monitored is accurate,
according to the protocol. And we also have a conversation
on how we're going to move forward with data
capturing if the study is either on hold
by the sponsor on hold -- and it's run its course.
And at that point, we do attend a post closure of the meeting.
So, we do a song and dance what I call with a research team.
But our main point of contact is the research nurse,
we really could not do it without the research nurse.
And then at the beginning,
when Liz Ness does that data capture meeting
in creating the actual CRF is extremely important.
Because she does have that history on what is needed
in those client reporting forms, and how it's going to pertain
to capturing the data for that protocol.
So, overall, we're very involved.
And we're just really happy to work
with a research team on this. So, thank you very much.
>> Lisa Cordis: Thank you, Ms. Wilmot.
So, I'm sure everybody has seen by now
that these clinical trials are such a team approach.
And each member of our team is so vital.
One of the most common questions
we actually get from our participants
is the background of our research team members.
So, I would like for anybody to share
that there are a couple people
I'd like to specifically call out to share their background
and how they got into clinical trials.
Dr. Apolo, do you want to share your background
and your history?
>> Andrea Apolo: Of course, yes. So, I am a medical oncologist.
So, I went to medical school,
and I did a residency in Internal Medicine
and then fellowship in medical oncology.
And from then I could have gone to practice
but I also have some lab research
and have always enjoyed doing clinical trials
when I was doing my fellowship
and participating in clinical trials.
So, I was, during my fellowship training in medical oncology.
I wrote several clinical trials
and became interested in running my own clinical trials
and asking questions and drug development.
And that's how I came to the NCI,
and I had the opportunity to do that.
So, medical oncology background,
and also lab research background.
And right now, I have a lab and I have a clinical team.
We do preclinical work, and we --
and then we also run clinical trials
for patients with advanced cancer.
>> Lisa Cordis: Thank you, Dr. Apolo.
Denise, do you also want to share your background
and your history and how you became a research nurse?
>> Denise Francis: My background is very varied,
I have a mechanical technology bachelor's,
and then I decided to go into nursing after 10 years.
So, nursing is my second career.
I was -- I started my oncology career at NIH
as a medical oncology nurse intern in 1998.
And I worked at the bedside,
and I worked outpatient in the infusion suite,
administering chemotherapy immunotherapy.
In those days, it was mainly chemotherapy
and some targeted therapies.
And then after a few years, I left NIH
and went out to the community
and worked in a community hospital
setting for like eight years.
And it was during that time that I became a research nurse.
And I came back to NIH as a clinical research nurse
a few years ago. So, I have a varied background
and I think it works well for my patients
and my interaction with my team
in that I worked with on the outside
with pharmaceutical companies,
and their clinical trials, and then work in here at NIH
with our own investigators sponsored clinical trials.
So, it's a plus-plus for me
to have experienced both areas, or both arenas.
>> Lisa Cordis: Thank you, Denise.
And a common question we get
is actually about our data managers
and how you become a data manager.
Stephanie, do you want to share with us
how you became a data manager?
>> Stephanie Wilmot: Okay.
So, my background again is a little bit different.
I started at NIH, December 2015.
Previously, I worked in Fort Lauderdale
at an 85-bed emergency room at Broward
at another hospital in Fort Lauderdale,
doing crisis --
that my training is crisis intervention in addiction
for co-occurring disorder. So, it worked both Psych
and in the lock lockdown facility for detoxification.
When I moved back to Maryland,
I transitioned into clinical data manager.
So, there was a training process for that,
as well as having a medical background
or access to interpreting medical records
and things of that nature.
So, currently, that is where my field is,
and I've been working at it since 2015.
And I think working in the emergency room
has created a lot of learning to deal with individuals
and learning to problem solve and troubleshoot.
Right there and then so that's one of the reasons
why I kind of enjoy working in clinical data manager
because everything every day is interesting.
And every day we're working with a team
and it's just amazing to see it everything come together.
So, thank you.
>> Lisa Cordis: Thank you.
Is there anyone else in the group
that wants to share their background and their history?
>> Cody Peer:
Yeah, Lisa, I can share mine, clinical pharmacologist
and how I got there,
a chemistry degree undergraduates,
and then I went to graduate school and did pharmacology,
but specifically what I did was drug metabolism.
Got well versed in drug metabolism,
and then did a postdoctoral fellowship in a pharmacology lab
and learned more about the mathematical analyses
that accompany pharmacology.
Realized that's a whole other discipline.
So, I went and got a master's after the PhD.
The master's was in pharmacometrics,
which is more of a statistical approach to pharmacology data,
and it incorporates not just the PKPD data
but incorporates more anatomy, physiology, disease states
and so you can really take
the numerical statistical approach to,
you know, pharmacology and pinpoint the dose regimens.
So, that was my track.
>> Lisa Cordis: Thank you, Dr. Peer.
I think it's really important to highlight
that a lot of us didn't get here through a traditional path.
At least I know I didn't. And many of you didn't either.
And I think that's important for our audience to remember.
What advice would you all give to someone
who is interested in clinical research,
but doesn't know where to start?
>> Andrea Apolo: I would say get in,
get involved with ongoing research and a team,
there's so many different ways to do that.
We have fellows that join our team,
we have post backs that join our team, postdocs.
We have medical students; we have at all different levels.
Get involved and see what do you like about it,
which part, you know, do you enjoy,
and how, you know, you would envision yourself
participating in a research team,
there's so much research to be done.
>> Denise Francis: I would say as a nurse,
not necessarily a research nurse,
but as a nurse, there are a lot of organizations,
if you're interested in clinical research
that you can take classes.
I am, I belong to the Society of Clinical Research Professionals,
SOCRA, S-O-C-R-A,
and they have a lot of training classes
that healthcare professionals and you don't necessarily
have to be a healthcare professional,
there are a lot of classes that you can take at SOCRA,
as well with more of a regulatory aspect,
not necessarily a clinical aspect.
So, you can take their classes and trade,
you know, their training sessions,
they have different conferences, that's one area to start with
if you want to get into clinical research,
and you're not sure where to start.
>> Elizabeth Ness:
Well, I think I'm just going to add to that, if I can,
that there are many master's programs and bachelor programs
now in various aspects of clinical research,
they can be regulatory, they can be pharmacology based,
they can be, you know, there's just all kinds
of bachelor's and master's programs out there.
And I think getting a feel for what that might look like,
and trying to connect with maybe an academic medical center
to see if they have any shadowing experiences,
which is what sort of Dr. Apollo
was referencing a little bit, I think,
is to sort of see where you can get your foot in the door.
And sometimes that foot in the door
can be from a data management perspective.
And you can work your way up to a clinical research coordinator.
I've had people from --
researchers from the labs want to leave the bench
and go into sort of the clinical aspects of that.
And, you know, I always say, you know, it is challenging.
But sometimes the data management activities
for a year, gets that foot in the door,
you get to know who's who on the research team,
and then can begin to carve your path
on the clinical research side,
after having been on the basic research side of things.
So, sort of a different perspective as well.
>> Lisa Cordis: That's great advice. Thank you.
All right. As we've all seen, our research team
is so involved throughout the protocol lifecycle.
Dr. Apolo, will you explain a little bit
about the protocol lifecycle
in terms of how a protocol goes from concept
into dosing the first patient?
>> Andrea Apolo: Yeah, and it's a --
there's a lot of different avenues.
And it depends on the protocol. So, the protocols can be,
they can be sponsored and funded in a lot of different ways.
So, this can be an investigator-initiated trial,
which is something that we commonly do here
at the intramural NCI.
They can be larger trials through the extramural NCI,
like cooperative groups or CTEPH studies.
They can be pharma sponsored studies.
And you know, these are all different ways,
but we have to communicate first,
you know, we have to kind of start the contracts
and see who's going to support the study.
And then we have to design the study, like we talked,
design it with the statistician,
meet, kind of, decide how big the study is going to be,
who's going to be the population?
What are the questions that we're going to ask?
What are the additional secondary questions
that we can ask and what about any scientific questions
that we can ask so that takes a lot of time
in terms of the contracts can take a long time.
And then the building of the protocol initially,
that kind of what kind of protocol it's going to be,
can take some time where I work very closely
with the statistician, I work with the labs.
I work with the pharmacist, you know,
all kinds of thinking about you know, do we do PKs?
How often do we do blood draws?
All of these questions that kind of come up initially.
So, once that is kind of established,
then we write a an LOI.
And that's the concept to present
to the scientific committee who then says,
this makes sense in this population,
this, there's a need, we should do this,
we should -- they support it, or they don't support it.
And then they also have really great suggestions
as to how can we make this study better,
maybe add another group, maybe don't treat for as long,
you know, they may have multiple different suggestions.
So, it goes through all these several committees,
it first starts off in, you know, your department,
then it goes off to the larger scientific community
within your institute.
And then after that, it, if you have to apply for an IND,
that's something else, which is really asking for a new way
to give a drug, you know, you're basically saying
I'm going to give this drug
or this combination of drug in this population,
and the FDA reviews that, and then it goes through the IRB
and the IRB's job is really to make sure
that it's safe to give to the patients,
and that we're doing everything possible to ensure
the safety of the patients within this clinical trial.
So, that process itself can take anywhere from one year
to three years just to get started.
And then once the trial opens up and starts enrolling patients,
then it depends on how large the study is, you know,
if it's a small phase one with 40 patients,
or if it's a large phase three with 800 patients,
you know, they can take anywhere from a year to, you know,
six, you know, five, six years,
maybe even longer sometimes
if especially if there's issues with accrual.
So, the process can take a long time.
And then once that is done,
then we have to analyze the data,
we have, you know, have to put all the data
together and meet again with the statistician
to talk about the data. So, it is a long process,
and it depends also on who's sponsoring the study
and, you know,
how large the trial is, how complex the study is.
>> Lisa Cordis:
Thank you so much, Dr. Apolo, for that great overview.
And thanks to all of our panel members today
and we hope the audience has enjoyed
getting to know our research team.
Thank you so much.