 So then, moving on to give you more of an overview of the genomic medicine working group, which was the sort of the grandparent of this particular effort now telling you about a working group of you. So the advisory council has two major working groups that I'm aware of, one of them you just heard from before lunch and now this one. And just to remind you who is on it, so this is the group and then Eric and Laura and I are sort of the ex-officio folks from NHGRO. The GMWG was set up about four years ago, shortly after the strategic plan was released, to help us in charting this area, particularly to evaluate and implement genomic medicine and review progress, identify research gaps, identify and publicize key advances. We decided we needed a series of meetings. We actually weren't sure it was going to be a series, but we knew we needed at least one and figured there probably would be others to help us explore this area and also learn who is doing this work, bring them together and form more of a community of effort. Facilitate collaborations and explore models for long-term infrastructure and sustainability. So as I mentioned, we've planned a series of meetings. These first three were in rapid succession in the first year or so after the strategic plan was released. Again, mainly to kind of develop collaborations and get people aware of what each other was doing and not duplicate what each other was doing, because there was a fair amount of siloing and duplication. Our fourth meeting was focused specifically on physician education, because I think everybody recognized that that was an area that needed to be addressed. Our fifth was trying to develop federal strategies. That was one that the gentleman you're going to hear from next managed to make it through for a period, and really asking our other agencies what should we be doing together in implementing general medicine. The global leaders meeting that I mentioned to you previously, in October we held one on genomic clinical decision support, and the report for that has gone in for publication. And then this most recent one in June was really kind of an overview. So the working group members said, you know, something that would be very helpful would be for us to take a step back and look at all of the programs all together and see how they fit together, where they could fit together better, and what the gaps might be. And just to kind of give you a feel for what's come out of these meetings. So our first meeting actually led to a separate workshop a few months later that we called ClinAction, and from that the clinical genome resource, or the ClinGen, was born. And so that was kind of a direct descendant, basically of that first meeting where people were saying, you know, got all these variants, we don't know what they mean. We all sit down in the room and try and hash it out, and it seemed to us that if people were doing that in separate rooms in 20 or 30 or 100 places around the country that we could organize and coordinate that effort and get it done much faster. The Emerge Pharmacogenetic effort also came in large part out of that first meeting where we recognized that Pharmacogenetics was a ripe area and that we could be working in one of our large consortia to be able to implement it rapidly. Our second meeting was on collaborations and that led to our Ignite program where we really are trying to take centers that are expert in this area and then try to have them disseminate to centers that really don't do genomics at all, so family health clinics, community health centers, military, VA, other kinds of places. Our third meeting involved payers. We really wanted to work with payers to understand what kind of evidence they needed in order to be able to support this kind of reimbursement for these kinds of tests. Our fourth on education led to the Inter-Society Coordinating Committee that you've heard about a few times since at this meeting. And the fifth one, I have dotted lines here not because I didn't want to imply that our fifth meeting produced CMS FDA or the Air Force, but what they have a nose, what they did produce were closer collaborations with those groups in looking at ways that we can share information and collaborate to improve implementation where it's appropriate, not just willy-nilly. The fifth one also led to a trans-NIH working group within NIH. This is something we discussed with the Institute leaders at one of their strategic planning forums and they basically said, you know, we need to also know, everybody needs to know what's going on within NIH and it was that group that we drew from when we put together the SGS10 planning group. Our sixth meeting, which was the Global Leaders Meeting, led to a global consortium called the Global Genomic Medicine Consortium, or G2MC. It is jointly hosted with the Institute of Medicine and it will have another meeting in Singapore in November and there are a series of areas that groups are collaborating in and also working with the Global Alliance for Genomics and Health, which is much more of a research effort, it's more of an implementation effort. You've heard about that before, so I won't go into it much with limited time, but out of that group came the SGS10 meeting that you just heard about. Our seventh meeting in clinical decision support led to a much stronger collaboration with the Institute of Medicine Genomics Roundtable and there was kind of a plan hatched for a soup to nuts program in Genomics Clinical Decision Support at our meeting that is now being implemented in the Genomics Roundtable, so that's very exciting. And then our eighth meeting was just held in June. The objectives of it were, as often is, kind of where are we going sort of meeting, so reviewing our portfolio, identifying gaps, identifying related programs among other centers and ways that we can work together, research needs for ourselves and our partner agencies to pursue. And then we always try and one of the reasons that we do these programs as large collaborative programs is that they can have an impact on the field and sort of pushing it forward or pushing in a direction that no single investigator can have by themselves no matter how good they are. And then examine potential methods for assessing the impact of these programs. So we decided to kind of focus on the six programs that are the major genomic medicine portfolio parsing. You've heard these described before, so I'm not going to go into detail about them, but they're here. And our undiagnosed diseases, newborn screening, clinical sequencing, emerge the IGNITE program and dissemination and then the ClinGen resource. And then we also had a series of related programs that we wanted to hear from and have members in the room, some of them in the very basic realms, some in informatics, as you see here with GSIT, ENCODE was there. Representatives from the ILM, Ron Tave-Wolf, some from the NCI clinical trials that are genomically driven, et cetera. So a large number that we tried to bring together and see where we had the opportunities. And then we asked for summaries from each of them. This is one from the clinical genome resource. It's basically a summary that describes who's involved, what the mission or the objectives are. Here's another one for newborn sequencing, a third one for the centers of menelium genomics. And in these we asked for just two pages to describe the objectives, what the funding period is, the working groups, the resources and tools that they've produced, publications, obstacles, and the approaches to meet those obstacles. And all of those are stored and available on the website for this meeting, which if you search Genomic Medicine 8, or if you just go Genomic Medicine Activities, the website for the meeting will come up, and then you can find these meetings summaries. And we're still referring back to them. They're very useful to have. One of the things we asked them to do, as I mentioned, was to identify their objectives. And then we kind of looked across them to see what their objectives, particularly in the focus programs, that are really quite common across them, because we would expect them to have some that would be in common. And as you might expect, these are very closely aligned with the goals of our division and the goals that the Genomic Medicine Working Group has outlined for itself. So integrating genomic data into patient care, incorporating actionable variants into the electronic medical record, particularly with using clinical decision support, educating clinicians and patients, assessing the outcomes, defining and sharing how best to do this in best practices, promoting interactions and collaborations, translating implementation outside highly specialized centers. And while this is Ignite's special role, actually several of the programs are doing this currently. There were also some that were pretty much targeted or unique to a given program. So the UDN is very heavily emphasizing improving genomic diagnosis and facilitating research and undiagnosed diseases. But Insight and Seizure do a little bit of that kind of work as well. Only Insight is looking at newborn care. Electronic phenotypes are something that is unique to Emerge, but is needed by all of these programs really. Identifying variants related to complex traits are showing a few of them as well. Pharmacogenetics is pretty much the domain of Emerge and Ignite. Looking at penetrance is pretty much Emerge alone. Standardizing clinical annotation, assessing actionability with mainly Insight and ClinGen, and then creating genomics-enabled learning health care systems where we can actually improve care in a real-time way. Something that Seizure and Emerge and Ignite are really focusing on. And we also identified barriers that face multiple programs. Lack of an evidence base was one we knew four years ago. It's one we have now, and it's probably one that will be with us for as long as we're in this area. The need for common data elements came up repeatedly. It's something that we want to try to encourage across the programs. Assessing the frequency and impact of variants, particularly in ancestrally diverse populations. Something that is a particular problem. And as Eric mentioned earlier today, that Ben's had an entire workshop on focusing specifically on why is it so hard to get information in ancestrally diverse populations when we must have it. Rapid evolution of evidence on variants. So how do you deal with the changing levels of evidence? A variant that you thought yesterday was benign. Now, a report comes out, and it looks like, oh, it might not be so benign. A few more reports come out, and well, gee, it's pretty clearly pathogenic. How do you deal with that in relating to patients and clinicians? The current limited usefulness and interoperability of clinical decision support systems. So you build it in one hospital system, and it works, hopefully, in that one hospital system, but nowhere else. Regulations that impede return of results have really gotten in our way, in many ways, with the research efforts that we're doing. And we're working with our colleagues in the regulatory field to try to address those, but that's going very slowly. And it is having an impact both on the research and the clinical care. Need for cloud computing is growing as the sequence data grow. So does the need for better ways to manipulate the data and transfer it to move it around when you do. Reimbursement policies and regulations, I mentioned earlier, I think, and a particular need for a bedside back-to-bench research. So how can we stimulate that virtuous cycle where we find something at the bedside and can take it back and really investigate it? We set up a series of panels. These were the panel areas, and we asked them to then address a number of questions. How important is this topic in this area? What programs do we have addressing it? What are the gaps? What could be the synergies in the training opportunities? And then we asked each of the Genomic Medicine working group members to lead one of those and very much appreciated their efforts in doing that. There were a series of recommendations that got a lot of discussion. I may be heavily discussed as a little too strong, but I tried to pull out those that seem to be recurring just to kind of share them with you. And again, sorry not to have gotten these out to you sooner. They are in the report, and we'll post these slides so that if you want to refer back, you'll have them. But generating evidence was an area that everybody agreed was something we needed to do much more of data sharing and improved phenotyping, particularly standards for phenotype description that you could use from model organisms to humans so that you can go back to the bench when you've seen something at the bedside. A lot of interest in patient-oriented ontologies, so ways that patients can enter information on what their child has or what they have, what their symptoms might be, and that could still be translatable in ways that cases could be picked up around the world and linked together. Identifying and carrying out innovative studies, particularly engaging basic sciences more actively in planning our programs because we don't have that voice at the table very often when we have this table, but we need you to speak up more in terms of how we can do the science better. An interesting idea was to add family history to a large-scale sequencing effort so that we might end up with 20,000 people who had both a rigorous family history, not one that took weeks to put together, but something using some of the more up-to-date software tools that can be done relatively rapidly. If you had that on 20,000 people with their sequence information, imagine what you could learn about the added value of family history and how you need family history information to interpret particularly in rare sequence variants. Studying the impact and consequences of changes in variant annotation, facilitating implementation commons was something that was very attractive to a number of the groups putting tools into a common place where people could then use them and share their experience using them. Health disparities, and again, we discussed some of these last week and you'll be hearing about them more, but looking at specific health disparities, research questions related to genomics and implementation, developing dedicated programs for non-European ancestry populations and increasing patient engagement, education and training is always an area that is needed, potentially joint training opportunities or best practices for clinician education. One of the things that we did with this meeting was to take, we had about 50 recommendations and we thought, well, why don't we ask people to sort of tell us what their top 10 is? So from the ones that I showed, I pulled out about 20 of them to report to you, but we then through our, Duke University was working with us on this workshop and so they sent out a little survey and said, just tell us what your top 10 are and rank them from one to 10. And then we kind of averaged those just to see which were those that tended to come to the top and you'll notice that up here there are a couple that are really quite popular and then there's maybe a little bit more of a shelf down here at 10 or 11. So I just pulled these out to show you what the top ones were. And the top number one was measuring outcomes of value to patients, clinicians, payers and then a whole list of other stakeholders. So regulators, et cetera, et cetera. How can we learn what outcomes are important to these groups so that we can add them to our studies it couldn't, it might not be very difficult to do and produce information that is much more useful to them. The family history tool came in second to us at 3.5, identifying types of evidence to collect and share across programs, accelerate rapid genotype phenotype explorations. One of the big concerns was that a lot of these explorations take a very long time and if you have a sick baby in the neonatal intensive care unit or if you have someone else who is really quite desperately old you don't want that process to take months or years. Suggestion was made to consider cooperative sequencing groups to gather information about sequencing much like the cooperative oncology groups that the NCI has funded at the, you know basically the budget of this institute many, many times over per year. So we couldn't do anything quite that grand but at least something to consider. And then a number of others that I just sort of show here facilitating coverage through evidence development identifying payers needs something that we are really struggling with. You know, what is it that payers really want to see? Not that we're trying to get everybody to pay for these things. We want to understand what is appropriate to be paid and what isn't. And so how can we learn what evidence to generate for that? Post-marketing studies, similar to pharmacovigilance studies but for genetic testing. So can you kind of gather information from people who've had genetic tests on what their outcomes are and how they use that information? Some agreed upon nomenclature, variant definitions and allele identifiers that will help us with some of the trading information back and forth like the pharmacogenetics star allele system which is very cumbersome and very difficult to work with. HLA is another area where nomenclature is a major challenge. Are there other ways to work on that? Computable guidelines to put into clinical decision support systems. Clinical trials of the added value of whole genome sequencing to more limited testing. So the question that we're doing in Emerge right now, we can afford basically a 100 gene panel and if we did a whole genome sequence compared to what would be the risks and the benefits we might identify a whole bunch of stuff you don't know what to do with and you just run up costs without any added benefit. On the other hand, you might find somebody who's at risk for carbamazepine toxicity that you didn't know and they might be about to get that or a related drug. So our plans for follow up immediately are to engage basic scientists. This came up over and over. We need basic scientists at the table and involved in developing our programs. So we've had a lot of emphasis on this sort of pathway from the bench to the bedside and we really need to go back and be sure that the function is explored and other things are explored in the laboratory. Areas that seemed like they would benefit from this included phenotyping that was compatible with model organisms to promote that kind of research. Variants on myclature was one function to help us with clinical annotation. So those are the things that we are going to pursue and that will be sort of a focus of our ninth meeting which will be held next April. Pursuing infrastructure needs, there were a lot of suggestions that were really kind of infrastructural, develop knowledge bases of what's going on in genomic medicine, a variety of other things. The implementation of commons, common data elements, those are things we're going to have to struggle with a bit because they don't really seem to lend themselves necessarily and we would welcome your advice to funding opportunities where we say somebody develop common data elements or increase patient engagement in that. But they're things we need to think about a bit. And then comparative effectiveness research, I may have put this on anticipating the next talk to come but we did hear something that would be very useful would be a whole genome sequencing versus targeted panels. Another would be whole genome sequencing with or without family history and large enough numbers to be able to draw some conclusions. So these are the people that were involved in putting this together and many thanks to them. And then back to you. So we welcome your comments on our recent activities and advice on the priorities that we've outlined. And I've asked Carol Bolt and Howard Jacob to comment. Carol, do you want to go first? So of course these are all very broad ranging giant areas of activity that were discussed and outlined especially at the last genomic medicine meeting. And we've talked a little bit on our phone calls about how we can most effectively work together to move forward genomic medicine. And I think that, I think there's a number of things in the priorities that came out and we're still discussing whether those are the right priorities. So really interested in people's comments about whether or not they feel like the ones that came out of the survey. Which I forget, Teri, how many people responded to the survey? It was a small number. So we had about 88 at the meeting and 35 responded. Yeah, that's always a challenge, right? We hold these meetings and then you ask for feedback and you get feedback from a very small number of people and that ends up being your recommendations and priorities. So part of the benefit of bringing it out to the group like this is, is that a bias sense? Is there general agreement with these priorities or not? And just with respect to the planning for GM9, you want me to comment on that as well. So as Teri said, one of the themes that emerged a number of times during GM8 was this integration of basic science and how that can effectively promote and advance genomic medicine. And it goes back to what Eric was saying earlier this morning about the fact that we have all these variants come out in these genome sequencing projects and we don't know their biology. We don't know what they do. And to effectively integrate that information into genomic medicine, we have to functionalize them. And so this virtuous cycle that Teri had the slide on that, we want GM9 to kind of focus on that virtuous cycle. How can we better integrate, especially the arc that goes from the patients back into the model organisms and how we develop the models themselves, right? When we talk about models, that means so many different things to so many different people and even being able to communicate effectively about what a model is and what it means is important to do. So that's going to be, currently that's going to be our focus for GM9. Howard? Howard, did you want to talk? Yeah, so I think that's a great summary. I would only add one additional point to what Teri and Carol have mentioned, and that is that connection at the basic research level. We need to also be able to do it, and Teri did say this, but we have to do this much, much faster because as we're doing more and more of this clinical sequencing, it's right at the edge of care slash research, and we're finding these variants of uncertain significance. So not only do we need to think how to functionalize it, but how do we do this fast enough to provide information back to the patient or to the physician in order to try to affect care? So that's all I had to add, but I thought it was a good summary. Great, thank you. Comments from the group? I just want to echo what Carol said. I mean, I think that we've spent GM1 through 8 on sort of looking at other communities, and as we were planning for GM9, it was one community that we really haven't engaged, and that's our basic science colleagues and everybody around this table, from the most clinical to the most basic, recognizes that the potential for that virtuous cycle functionalizing, I like that word, variants of uncertain significance is a huge problem, and there are many, many other, I'm sure, opportunities that the clinical data sets that we're generating should offer to the basic scientists, and there are other things that basic science should be offering to us besides just telling us whether a particular SNP is functional or not, and that's why we have to have that interchange. Just, it's a great comment, and this goes back to what I was talking about in terms of models. So we're used to thinking about models of understanding the basic biology, but there's also model systems to look at therapy outcomes, right? And so those can be completely different models, but we tend to lump them all into the same thing, and I think this meeting could help us start to tease some of those things apart so that there's really good communication. And I might note that we have that scheduled for April 19th and 20th, I believe, that's a Tuesday and a Wednesday, I think, in 2016. Not quite sure if it'll be in Bethesda or if it's in a more central part of the country, but we would hope that folks will put that on their calendars, and Eric, I know you'd love to come to Bethesda, so if we have it in Bethesda, you'll be there. Yes, we hold it in Houston, you won't be there. So great. Any other comments? Great, thank you very much. If not, then I'll go ahead and introduce our next speaker, if that's all right.