Geoffrey Ginsburg: Thanks, Dan, and the other speakers.
I'd like ask the four speakers from this morning, maybe, to come up to answer and field some
questions.
We have about 10 or 15 minutes or so for questions from the audience, and I encourage you to
use the microphones.
So, don't be shy.
But I will start, I guess, particularly since I know that we probably don't have Francis
here for the entire two days, I would like to just ask him, from the perspective of someone
who has led a very large and complex multinational project, the Human Genome Project, as you
think about the potential for this group to do maybe something in the genomics implementation
space at scale, what types of lessons learned, or I wouldn't -- I hesitate to call it advice,
but what sort of insights from that project would you want us to be thinking about as
we think about what we might do or might not do coming out of this meeting?
Francis Collins: I think it is an appropriate question, and
we have some experiences from the genome sequencing efforts, from HapMap, from now the International
Cancer Genomics effort, from the International Microbiome Project, to sort of see how those
kinds of models have been developed.
There are other things going on with rare diseases.
So, certainly, it would be appropriate, not just in my quick response here, but in a more
thorough way to look and see how those were structured in what seemed to have been successful
efforts, and which things maybe we could learn from and not make the same mistakes.
I think the most critical thing is to create a space where talented, motivated, energetic,
visionary people will want to come and take part, and that was critical for every one
of the successful international efforts that I've mentioned.
You want this to be a place where somebody really would not want to miss out on taking
part in such an effort because they know that the atmosphere, that the quality of the team,
that the consequences of what goes on are going to be something that you just don't
want to miss taking part in.
That being said, it will be crucial to have leadership of the effort that is truly international,
that recognizes the importance of having the contributions of all the participants really
clearly laid out and appropriately credited so that people don't feel as if they're cogs
in some machine.
And particularly for this effort, it's going to take maybe more in the way of sophistication
in managing all of the differences that exist in medical care systems across the world;
that was not such a serious issue, although occasionally it came up, in sequencing the
human genome or even in HapMap, but here, it's going to be a big issue, just in terms
of what kinds of access one has to specimens, to issues about policy and so on.
I would urge strongly that the ethic that the group adopts, which has served so well
for genomics, is this idea of immediate open access to the information that's derived,
because that becomes so empowering.
It is a little threatening at first for people who have not lived in that kind of space because
it has not been the tradition of medical research, in many areas previously, to be so forthcoming
and revealing, but it turns everything into a much more interesting and productive enterprise
to take that step, recognizing that immediate release of the data does not mean that the
producers of that data should have their contributions ignored, or neglected, or downgraded, but
that basically by making the data available, you're actually having the producers more
important, not less so and that'll be an important issue to consider.
I could go on a bit, but those are some of the main principles.
Geoffrey Ginsburg: Those are terrific responses.
Eric, you looked like you had something to add to that.
Eric Green: I mean, I think the only thing I would -- I
was going to immediately add was just the vehicles for communication.
And I think it may be even more important in this regard because -- I mean, Teri started
to allude to it.
I mean, I just think the complexities of -- that heterogeneity of health care delivery, I mean,
you know, genome project was very focused, goal laser-focused in some ways.
I think the concept of genomic medicine and how that gets implemented in different countries
and different cultures and different ecosystems makes it even more important that whatever
we do collectively, that there's just incredibly good communication if we're going to benefit
from collaborative efforts.
Geoffrey Ginsburg: Excellent point.
Alan O'Connor: Hi, Alan O'Connor, University of Maryland.
So there's, I guess, another kind of personalized medicine paradox related to the one that Dan
mentioned that I thought maybe the panel could address.
And that's one of a policy paradox: the fact that our U.S. health care system, we're told
that we need to be moving towards population health, healthcare systems taking on risk
for populations and the maintenance of their health, and I'm just wondering how you all
think about layering personalized medicine on this policy paradox?
Teri Manolio: Why don't you handle that?
[laughter]
Dan Roden: You know, Alan, I don't really have an answer
to that except that -- so there's this -- I'll be a politician and not answer question but
answer the question I think you asked, or the answer that I want to give, and that is,
there is this tension, as you know, between evidence-based medicine and personalized medicine.
People sort of argue that there's sort of two, you know, like the north and south magnetic
poles, they'll never meet, because if you have evidence-based medicine, you have evidence
across a population, and if you're interested in health population, then you ought to deploy
certain kinds of medications widely across a population, for example.
And personalized medicine has this individual flavor to it.
I don't think that those are actually as diametrically opposed as they appear on first blush, and
the reason I don't think they're opposed is because if we have evidence that personalizing
care results in better outcomes, then we ought to personalize care.
And the challenge, I think, to us in eMERGE and to everybody in this room is to develop
that evidence base, and it's really early, early days, number one; and number two, to
figure out which variants really are important for implementation in a clinical environment
and not.
And I think that's where the gap is for -- as I see it, but I think that those are not difficult
views to reconcile, except when it comes down to actually doing it, you have to have the
evidence.
And that's one of the things that we ought to focus on, I think.
Teri Manolio: Maybe I could just add, in that, you know,
I agree with everything Dan has said, and we are sort of trying to start a little smaller
and then getting bigger, and so populations are big and clinical care is a little bit
smaller.
But we didn't have time, and I'm sorry that we don't, to have Howard McLeod talk a little
bit about his PG program, which really is looking, as Dan sort of alluded to, across
populations at, you know, very big differences in drug metabolizing variants -- hope I'm
getting this right, Howard -- and making recommendations on a nationwide basis to say, you know, the
prevalence of the polymorphisms that really make it inappropriate for your population
to be using Isoniazid, for example, is so high in this population that it probably shouldn't
be a first-line drug.
So those kinds of implementations probably are possible along the road.
I think we're not quite there yet for a large variety of them.
Geoffrey Ginsburg: Dr. Alfalo [spelled phonetically].
Male Speaker: So -- thank you very much.
So as I understand from the Genomic Medicine I to V, the various American agencies found
it hard to work with each other, at least that's my understanding.
What is your vision for this international consortium?
What are we going to get out of this?
I mean, of course there is a basic question, which is -- or basic answer, we all are going
to learn from that, but what are our targets really?
Do you have anything set in mind for all of us to work?
Because it's going to be gigantic job.
Teri Manolio: Right, so I might ask Geoff to comment, and
he did -- he did review sort of what the outcomes might be.
My personal dream would be -- I'm sorry?
Would be an evidence generation project on a large scale because we can actually get
to the wide diversity of genetic variation, and if we can use some of the electronic phenotyping
tools that were described here, it can't be that difficult to try to get some phenotypes
out of the medical records that we're all collecting worldwide.
So that, to me, would be a dream, but I don't know, Geoff, you want --
Geoffrey Ginsburg: I would just say that we didn't want to be
very prescriptive going into this meeting about what the output would be, thinking that
our own provincial view of what the field looks like should not represent yours or any
of the diversity of people in the audience.
So I think this is one of our challenges for the next two days is to keep coming back to
what are the opportunities, and, you know, think about things that would have near-term
wins that could really be a demonstration that we can act as a global community to do
something impactful in this field, and then go beyond that.
I'm not saying anything very detailed purposely.
I mean, the kind of project that Teri alluded to, an evidence generation project would certainly
be something I think we would all rally around, though.
Thanks for the question.
We have time probably for two more questions, I think.
I can't tell how many people are in line, but we do need to also respect some of the
agenda, so let's go with Heidi and then Marc.
Heidi Rehm: So this is a question probably for Francis.
As Dan mentioned, and I think many of us believe, the implementation of genomics into medicine
is going to critically depend on electronic health care systems that we all employ throughout
our hospitals.
And, you know, being involved in the Partners Health Care implementation of Epic at the
figure $1.5 billion, and being on the genomic medicine committee for that, we are struggling
to even get family history implemented into an EHR environment, let alone all of the things
that all of us in this room want to do.
And my question is, what, if any, role does NIH potentially play in the, you know, the
EHR environment and how we interplay between, you know, private healthcare systems and other
healthcare systems, and the NIH that has such, you know, momentum in the space?
Francis Collins: So it's a great question.
And in the United States, in terms of the standards that have to be adopted by electronic
health records, much of this is overseen by the Office of the National Coordinator for
Health IT, and we have close and regular interactions with ONC about exactly how, in their various
phases of implementing those standards, they could be put in place in a way that is friendly
to research.
We have to be realistic about it, of course, because the main point of the electronic health
record is to help care be delivered.
And so if we layer too many things on top of that that really don't have much use in
the management of patient care but are purely research-oriented, there will be loud objections.
We've already experienced a little bit of that, but we are being given the opportunity
by ONC to put forward realistic standards that ought to be included as this whole process
evolves.
And, of course, it is an evolving process; what you see now is, thank God, not what you're
going to have in a few years if we continue down this road.
So, it is a great opportunity if this group, for instance, wanted to suggest things that
electronic health records across the world really need to have in place in order to deliver
good genomic medicine, I'd love to hear about that.
Geoffrey Ginsburg: Thanks, Francis.
Marc?
And short questions, please.
Marc Williams: Yeah, I just wanted to come back to the first
question about population health.
I think it's important to recognize that we do this already.
I mean, if we do blood transfusions, we personalize blood transfusions based on a variety of blood
types, and we treat that in a population manner but we use that individual data.
And I think the concept that needs to be thought about is one that Clay Christensen has brought
forward called "precision medicine."
That right now we're in an empiric period of medicine where we, you know, say, based
on a population, you're likely to respond to this drug, we're going to try it, and we'll
see if it works, or if it doesn't work, or if it kills you.
But he's envisioning a time where we will be able to precisely define diseases, understand
what the causes are, and then target those causes with drugs that are specifically designed
or work best in that, and that you can still use population approaches, but be very precise
about how it's done, and that principles that underlie that are mass customization, which
is why we can all get the laptop exactly that we want but we use mass production techniques
to get high reliability.
And that's the transformative reengineering of health care delivery that will allow us
to do that.
So I don't see this as a paradox at all, but it still does come back to the evidence generation.
We have to generate the evidence to understand how to realize precision medicine.
Geoffrey Ginsburg: Thanks, Marc.
Paul Lasko: Just briefly -- this is for Teri.
I was very ---
Geoffrey Ginsburg: State your name and --
Paul Lasko: Paul Lasko, Canadian Institutes of Health
Research.
I was very intrigued with what you had to say about education of healthcare providers.
This is a hugely important issue, and I wonder if your group has any plans to take that program
globally and engage international agencies.
Teri Manolio: Well, we would love to do that, and we'll
need some partners in order to be able to, and since we know you're right next door,
that's just good to know, but, yes, absolutely.
We're trying to make as much available as widely as possible, and we should talk more
about how to expand that.
Geoffrey Ginsburg: Great, and just let me add a comment based
on the previous question by Dr. Alfalo about what we could do coming at this meeting.
We laid out the working group's activities as a menu of potential ways to expand into
an international community.
Sukhdev Sinha: Thank you.
I'm Sinha from India.
I was thinking about the whole vaccinology area.
My question here is that impact of genomic medicine in future in the immunization program,
whether it could have some impact.
And second point, actually, which I would like to flag here, that in India, we have
a couple of new institutions that we have launched long-standing Indo-U.S. relationship.
So, we'll be interested particularly in some educational and training programs.
Thank you.
Geoffrey Ginsburg: Thank you.
Teri Manolio: In terms of immunization, I'm aware that there
is some work that the CDC has done.
They initially started looking at smallpox, I believe, and then at some of the flu vaccine
reactions because there are some really devastating reactions to those vaccines.
Some work is beginning, but it's discovery work that needs to be done, and I don't think
there's enough of it, personally.
Francis Collins: You know, it's intriguing, recent observation
about narcolepsy being a side effect of immunization for influenza in Scandinavia with a particular
batch of the vaccine, and that's just a snapshot of maybe the way in which genomics and vaccination
may find some opportunities to work together.
Geoffrey Ginsburg: Thank you.
Last question, Dr. Hubbard.
Tim Hubbard: Tim Hubbard from Genomics England.
This question of coordination bodies, a lot of potential of coordinating across the globe
is data exchange.
Now this other entity, the Global Alliance which has recently been set up, you know,
it's obviously not completely the same thing, but, you know, if you had something new, there'd
be a lot of overlap between them.
Have you considered how to work with that?
Francis Collins: So, I'm glad you brought it up, Tim.
I think not everybody's aware because it's a new arrival on the scene, but it certainly
should be on the table for this meeting.
The Global Alliance for Genomic Health, GA4GH, as it has now been rechristened, is an effort
to try to establish standards by which large-scale genomic datasets related to human medicine
can find their way into a shared data format, probably in the cloud, to allow investigators
to gain access to such datasets, and to make inferences and provide insights that might
otherwise take a long time by trying to be sure that formatting is thought about, that
privacy and access is thought about.
This group now has a series of working groups that are pretty -- rolled up their sleeves
trying to come up with standards.
There will be a meeting in London on March 4th to see where we have gotten to.
It is an international effort.
Certainly while you might think of this as sort of on the mechanical side, if we don't
get this part right in terms of how data finds its way into an accessible place, then a lot
of the rest of our dreams as far as the research opportunities and their clinical implications
will be impeded.
So I think many of us have been quite excited to see this arrive.
Many institutions, more than a hundred have signed on; probably many of you in this room
have institutions that have joined this GA4GH.
But certainly something that needs to be watched closely.
The next year is going to be critical.
Eric Green: We were well aware of the relevance of that
-- the Global Alliance, and this meeting, and, in fact, the organizers of this meeting,
we extended an invitation.
It just didn't work out schedule wise for some key people, but anything coming out of
this gathering should clearly somehow make sure there's good connections with the Global
Alliance.
Geoffrey Ginsburg: All right, well, I really want to thank our
speakers and our panel for laying the groundwork for today's and tomorrow's meeting.
We're going to take a short break, probably about 23 minutes or so.
We'll try to be back here at five after 10:00 to keep on our schedule.
See you in a few minutes.