 Okay, welcome back everyone. We're now going to have a concept presentation by Lucia Hindorf, program director at NHGRI. There are actually three concepts being presented under CESAR 2, so there'll be three separate discussions, discussion vote, discussion vote, discussion vote. And then we'll have a discussion vote on the investigator initiated program announcement which has a set aside of funds associated with it. So before I get started, I'd like to acknowledge the contributions of several of the CESAR staff, particularly Jean, Dave, and especially Carolyn and our outstanding analysts, Ellie and Alex in the back. Can everybody hear me? All right, across the spectrum of genomics, a central feature of NHGRI programs is that the human genome has brought people together to answer critical questions about how the genome works, and then to ask even better questions than the ones we started out with. In the past several years, NHGRI has established programs to make inroads in understanding how genomic information can be used to improve human health by applying genomic technologies to healthcare settings. NHGRI's first major foray in the clinical sequencing occurred in 2011 when the Clinical Sequencing Exploratory Research or CESAR program was funded to explore the use of genome sequencing in clinical care and identify challenges and opportunities across varied clinical contexts. Dr. Rodin's presentation nicely described the study organization and recent progress, but just to remind you, a key characteristic of CESAR was its three-part focus on first, a clinical genomic study in which patients and practitioners were recruited, second, a second project was generated, analyzed, and interpreted sequencing data, and a third project focusing on return of results, and in which there was an overarching focus on the ethical, legal, and psychosocial implications, which I will abbreviate as LC. Throughout CESAR, these parts worked in an integrated way. From the beginning, CESAR was organized around a consortium model with integrated, highly coordinated efforts, as symbolized by this formal garden. Sites were able to learn from one another as they implemented clinical workflows for genome sequencing, and over the course of several years of working together, they've written papers that have helped establish the evidence base for clinical utility, including a number of best practices and recommendation in areas as diverse as pediatrics, tumor, electronic health record integration, and variant interpretation, including a number of professional society guidelines that you heard about in Dan's talk. It's also true that when CESAR was initially envisioned, the many flowers bloom approach was also fundamental. So within the basic project structure that I described, and blessed gators had the flexibility to refine their sites' focus on clinical settings, on research methods and approaches, and on site-specific expertise that could drive innovation in key areas. Going forward for CESAR 2, we will likely benefit my balance of both approaches. In Dan's talk, we heard a number of key recommendations from the CESAR and Beyond workshop last fall, and it's worth taking a step back to juxtapose them with the NHGRI strategic plan, which shows an increase in density around the science of medicine and effectiveness of healthcare domains through 2020 and beyond. So as part of the advancing of science medicine domain, we heard recommendations to increase participant diversity along ethnic, racial, socioeconomic, and underserved lines, and to continue to focus on interactions among patients, family members, practitioners, and clinical labs. As part of the effectiveness of healthcare domain, recommendations included assessing the clinical utility of genomic sequencing, and the setting where clinical utility is still being assessed. We need a shared evidence space in a similar way that the relevance of genomic medicine to different healthcare settings beyond academic medical settings was also raised as a recommendation. And as CESAR data have been used to inform and refine practice guidelines in very interpretation, to continue to use stakeholder input to inform and refine future clinical sequencing data is important. These recommendations form the basis for the three proposed aims of CESAR 2. The first aim is to generate evidence to determine the clinical utility of genome sequencing. The second aim is to research the critical interactions among patients, family members, health practitioners, and clinical laboratories. And the third aim is to investigate the feasibility of exchanging genomic, clinical, and healthcare utilization data within an existing healthcare system. So let's take the first aim. Clinical utility as defined by AC and G and others is the likelihood that genomic intervention leads to improved health outcomes. Broadly speaking, this includes diagnosis, treatment, management, or disease prevention that will benefit a patient or his or her family members. Assessing clinical utility is inherent to understanding how genomic information benefits human health, and is thus already an indirect focus of many NHGRI programs. However, there is not yet consensus on what measures of clinical utility to use for decision-making. Decisions on reimbursement, for example, tend to use a much narrower definition that do not rely as much on the value of a diagnosis. So we're not just talking about an evidence gap, but how we think about evidence gap. A second aim of CESAR relates to identifying research opportunities at the point of the clinical encounter where patients and family members, practitioners, and clinical laboratories intersect. A number of research opportunities could be envisioned in this space, and I'm just going to list three as exemplars. There are many, many more. For example, the patient and family measured, family centered measures of utility, exchange of phenotype information, variant interpretation and disclosure, and characterizing this cascade of genomic information. This latter finding refers to the process that occurs when a genomic finding ends a diagnostic odyssey. It can often begin a cascade of additional medical and other consequences as well as implications for family members. I would like to note that these topics leave room for flexibility for investigators to propose research topics that are relevant to their particular clinical setting, again tying back to the balance between the consortium and site-specific efforts. We imagine, as was true for CESAR 1, that the rich integration of LC will continue throughout each of these domains. As I've mentioned, promoting interactions among these groups is critical, but so is doing so in the context of the health care system. Related to the health care system, a third aim of CESAR 2 will be to investigate the feasibility of exchanging genomic clinical and health care utilization data within existing health care systems. This is an area in which the spectrum of clinical settings across CESAR, for example, and healthy and diseased individuals or in pediatric and adult populations or in academic or community settings, those differences lend themselves well to an effectiveness approach, which study real-world settings compared to an efficacy approach under highly controlled or idealized research settings. This is really to get around the problem or to help ameliorate the problem of having silos. So genomic data are often siloed from EHR data, as was described in a joint paper between CESAR and Emerge. Clinical data can be siloed in research databases or patient registries. And health care utilization data are often siloed in systems related to billing. Data exchange to unify data across silos is important to being able to accomplish the first two aims of CESAR. For CESAR 2, that we propose that this be implemented iteratively with an individual health care system. The idea being that a genomic finding that shows some sort of benefit for patient care might be useful for other subsequent patients. But this works best if the system can iteratively incorporate and learn from that initial information. Many of the challenges of implementing this model are likely to be institution-specific, so that's why we're proposing this aim for feasibility. Existing standards, however, and common standards across consortium sites will be strongly encouraged wherever possible. To enhance the applicability of evidence that CESAR 2 generates beyond specialized medical centers, we are going to rely on two key components. The first we've heard a lot about today, it has to do with the topic of diversity. So here we will rely on increasing participant diversity as well as including clinical settings outside academic medical centers. CESAR 2 will deliberately engage stakeholders, such as professional societies, payers, regulatory agencies, and patients, all of whom have a stake in the type of evidence that CESAR will be generating. Such buy-in will generate evidence and best practices with a high likelihood of adoption, as well as keep CESAR 2 outward looking and cognizant of other efforts. So if the program is successful, we will be able to bridge the how we think about evidence gap and say that we did this work intentionally, including diverse individuals and stakeholders. Okay, so now we've covered the why of CESAR, let me transition to how we plan to do this work. So we're proposing a series of three RFAs, and also a program announcement with CESAR side, which, as Reedy mentioned, we'll talk about after the RFAs. The clinical site RFAs collectively have similar goals and will study 10,000 diverse patients across CESAR 2. Each site will recruit, sequence, and disclose results to patients within the context of the healthcare setting. We would expect sites to include comparison genomic modalities to evaluate the clinical utility aim, for example, comparing co-exome to gene panel. Existing data would be permitted with caveats, or for example, existing sequence data could be included as long as investigators could demonstrate that they were addressing all three aims. This might be also an opportunity to encourage partnerships with other existing resources that have diverse data, which will be important in just a minute. It will be crucial to establish multidisciplinary teams as well. So investigators will be expected to include a broad degree of research and clinical expertise to integrate LC throughout the three aims to foster a collaborative environment where idea and data exchange works well within sites as well as across them. And then also sites will propose ideas for stakeholder engagement, whether that's having stakeholders as co-investigators on grants, or as members of advisory panels, or steering committee meetings, or other ideas that investigators may have. Okay, so we've heard a lot about diversity today, and I want to be clear about what I mean about participant diversity. For this presentation, I'll be referring to race or ethnic, socioeconomic, or underserved distinctions. Each site will be addressing one or more diversity-focused research aim in these subgroups. For example, looking at differences among them in the disclosure and interpretation of genomic results, differences in disease presentation diagnosis and healthcare implications, novel methods for healthcare delivery and challenging underserved populations in other relevant areas. We're proposing two RFA's with different thresholds for the percentage of participants from diverse populations. The first RFA, which we're referring to as general clinical sites, will be strongly encouraged to recruit 25% or more of their participants from diverse populations. The clinical sites with enhanced diversity have a higher threshold of 60% or more. And the rationale for splitting out the two RFA's is twofold. First, it gives us the flexibility to assign a separate review panel for the enhanced diversity sites. And it also addresses what we know to be logistical and practical challenges in recruiting and retaining individuals in challenging settings. And so the second RFA is proposed to have an up to a 20% increased budget cap to help investigators plan for those challenges. Okay, to get the sense of what is possible in a program of the size that we're proposing, we did some thought experiments and power calculations for individual sites. So keep in mind that part of the goal of CSER2 is actually to define and assess relevant measures of clinical utility so the exact measures are not known, these are just the examples. So if you take the 10,000 participants that are assumed across CSER2 and you divide by nine, which is the midpoint of the range of the number of sites we're proposing, you get 1,100 participants per site. Assume that they would come from a spectrum of real world clinical settings, adults and children, for example. And that each site would be well poised to look at disease-specific analyses or site-specific measures. So for example, a site could look at the difference in disease diagnostic rates comparing cold genome sequencing to standard of care. So with 1,100 participants, there would be 80% power to deduct a comparison of 25% in cold genome, which is a diagnostic rate that's seen in CSER2 and elsewhere compared to 18% or lower in standard of care. So that's an absolute difference of at least 7%. A site could look at whether the actionable finding rate differed between whole exome and panel testing. So it would be powered to detect a comparison of 45% in whole exome, which was the rate from the paper that Eric mentioned this morning, compared to 37% or lower in panel testing. So that's an absolute difference of 8% or more. I wanna stress the importance of doing this across multiple sites. We could then compare each of these kinds of analyses across, for example, adults and children, across disease A, disease B, different ethnic groups, et cetera. We also looked at what would be possible in a sample size of 10,000 participants across the consortium. So recognize that sites might maybe comparing different sequencing approaches, but we could aggregate analyses across clinical settings and even among subgroups. Such outcomes might include rare outcomes that could be evaluated consortium-wide, as well as the standardized or aggregated measures of clinical utility that I mentioned before. So 10,000 allows us to, for example, look at the secondary finding rate in whole eggs compared to standard of care. And here, 10,000 participants will be powered to detect a comparison of 4% in whole eggs compared to 3% or lower in standard of care. So an absolute difference of 1% or more. We could also look at subgroups. So if you wanted to look at the actionable finding rate and how that compared in adults versus children with whole eggs in sequencing, this sample size would be powered to detect a comparison of 45% in adults, compared to 41% in children. So that's an absolute difference of 4% or more. Speaking along the lines of CSER2-wide opportunities, one key component of this is going to be this coordinating center or the CC. We're going to continue to need scientific and administrative coordination to facilitate CSER2 efforts, for example, aggregating data, to disseminate resources and best practices, to respond to opportunities to which CSER2 could uniquely contribute. So it's hard to know about them in advance, but they could include things like professional society guidelines that are either being developed or have just come out. Coordination of stakeholder engagement will be crucial. And this is not to displace what any of the individual sites would do, but for example, if there were multiple cancer sites, it might make sense to coordinate outreach to AACR or ASCO in a more central way across sites. And then finally, we would rely on the CC to organize steering committee meetings, working group and stakeholder meetings. Okay, so now let's take a look at the table again with the proposed budget. So for the general clinical sites we're proposing an annual budget, that's about the same as what the current CSER sites are being funded at. The diversity sites, as I mentioned, would be given up to a 20% increase budget cap, and the coordinating center is proposed for a slightly higher budget than they have now to account for increases in stakeholder engagement, increased expectations for stakeholder engagement, as well as an additional consortium meeting. I should note that we are seeking support from other ICs for co-funding and have had some very encouraging discussions. So where possible, we hope to have some buy-in from other institutes. Okay, so one other thing that I wanna talk about is we've discussed that why and the how of CSER2. So I wanna take a step back and see how CSER2 fits in with the landscape of other genomic medicine programs. So the implementation of genomic medicine has a number of bottlenecks where challenges and opportunities across fields lend themselves well to a consortium approach. So you see some of them here. As I've described today, the primary focus of CSER2 is in determining clinical utility with the lesser emphasis in these other areas that you see here. However, genomic medicine program, other genomic medicine programs have a unique primary focus in each of these other categories. So for example, ClinGen focuses on variant curation to speed the identification of clinically relevant variants. VUDN focuses on diagnosis and clinical evaluation to end the diagnostic odyssey. Ignite focuses on clinical decision support and dissemination in tests with established clinical utility. Insight focuses on newborn and pediatric populations and Emerge has a unique focus on estimating penetrance and also a unique focus on EHR derived phenotypes. These programs are also doing cross-cutting work in a complementary yet distinct way. One feature of such complementary programs is synergy without duplication. So for example, CSER's primary focus will be assessing the clinical utility of genomic sequencing more broadly whereas Emerge is focusing on the penetrance and clinical consequences of actual genomic variants. CSER2 will focus on genomic tests with clinical utility yet to be established, as I mentioned, compared to Ignite, which is focusing on genomic tests with established clinical utility. CSER2 will focus on clinical sequencing in adult and pediatric patients compared to EnSight, which is focused on sequencing in newborns. And then a central feature of CSER2 will be understanding and managing the diagnostic uncertainty and the uncertainty in clinical utility, whereas UDN has a much more primary focus on ending the diagnostic odyssey. Okay, so now we've kind of taken a look at why and how CSER and looked at how CSER fits in with the other genomic medicine programs. I'm going to show the three CSER2 aims here briefly before we move on to our discussion. We do have a number of questions or topics for discussion where we'd like council input, the first to which we'll surprise nobody is the definition of diversity. So historically, NHGRI has focused on race and ethnicity to broaden inclusion in our programs, should we take this opportunity and consider a broader definition that includes low SES and underserved populations. Second, the data exchange aim is currently phrased as a pilot or feasibility aim, should we have stronger expectations or say more about expecting common standards. And then I think general feedback on the balance between site-specific and consortium goals would be welcome. So we have four discussants assigned to lead off the conversation, Bob, Dan, Shanita and Lucila. So why don't we start with Bob. So we've had prior conversations and the current document and then also the slides that CSER showed. I think we've reflected to a large extent some minor changes that resulted from our conversations. So fundamentally, I think CSER itself has been a successful program and it makes sense to continue the clinical sequencing exploratory, whether you wanna call it exploratory anymore or you wanna change that name a little bit. I know I like CSER, it just has a certain ring to it, but whatever. I think the key issues here are ones that I think Lucila's done a good job of addressing, which is how does CSER fit in with all the other acronyms, the ignites and the emerges and the insights and the clingens and all that alphabet soup. And I think that there is an attempt to strike a balance between synergy and overlap, synergy and redundancy. I think you have to have a little bit of redundancy in order to have any synergy at all, but I think that the synergy is greatly enhanced compared to the redundancy. So I think you've said it just about the right way. The other issue you mentioned is about data exchange. And I fully recognize that it is so much easier. It's hard enough, at least I have from personal experience, it's hard enough trying to get your own institution to do certain things when it comes to clinical studies, particularly when it's involving effectiveness research, in other words, real life settings as opposed to artificial efficacy kinds of research. And then expanding that to make multiple institutions try to hone to some basic goal, I think is much, much harder. So I do recognize that I think there is value. And if I were a CSER2 investigator, I would want to be able to focus on my institution, which is hard enough to get anything done. That said, I think having not a pilot or feasibility but an actual commitment to interoperability and standards I think is absolutely essential if this is ever going to become more than just a little boutique effort in a small number of institutions. And then finally, in terms of diversity definition, I think my main comment there is that there's a lot of people who are underserved for reasons that have not to do with race or ethnicity per se but have a lot to do with geographic dispersion and also educational and economic, some more of the SES. And so I would encourage containing that or combining that into a diversity definition along with race and ethnicity, which is obviously a major, really, really important area. And then actually, as you were speaking, Lucia, something I didn't bring up before but it just occurred to me is that somewhere in here some investigation of the obstacle of fear about insurability probably should somehow play a role in here. Despite Jenna, there's still a fairly high worrisome comments about life insurance and other sorts of insurance that Jenna doesn't really cover. And I know Robert Green has told me that in some of his work he's been just shocked at how often worries about being able to get life insurance has entered into decisions about wanting to participate, not just in research, but also to even participate in any kind of using sequencing that's gonna unveil things that you can't predict before you do it. So I just thought I would add that as a little tick to put in. But I mean, all in all, I think the concept is a good one. I think it's something that needs to be done. It should be done and will synergize with the other programs. Thanks. Should we move on to Dan? I really have very little to add. I'll make two points. One is that when I first started to think about where CSER belongs, first joined their advisory board and where CSER belongs, I thought, well, it really seems to me to be almost congruent with Emerge. And that is absolutely not the case. CSER is the place where the healthcare system interacting with an individual patient starts to take legs, whereas Emerge is population. And the only place where people think about what individual subjects, how do individual subjects react to this kind of information in terms of emotional reaction as well as healthcare reactions is in this initiative. So I've become a pretty strong proponent of this through watching them and through thinking about the problem. The second point I'd make is something that Val raised in an earlier discussion. And that is the idea that the field is now mature enough. Five years ago, 10 years ago, the idea of doing any kind of sequencing in a large number of people and making head or tail of it was something that needed to be driven by some central authority because nobody really had any sense of how that would work. I think we're now in a position where the sequencing is not the major challenge, still is a challenge, but the application of it becomes a challenge. And so I think to confine ourselves to thinking that everybody at NHGRI has the best ideas or the only ideas in that large investigator community out there can't contribute, some really unique things is a mistake. So I would argue strongly in terms of the investigator initiative. So I think the concepts that you presented them are really responsive to the issues that were identified with diversity in the ongoing user programs. I think that's a really great, the approach your team has developed is really responsive to that, I would like to see it included in there. I would also support a more inclusive definition of diversity, one that considers race, ethnicity, geography, as well as other characteristics. And I think going back to the issue of diversity, I really am supportive of the inclusion of diversity centers. And I just wondered what your thoughts were about ensuring that there's sufficient interaction between the diversity centers and the other centers. I think that's a great question, and it's a good one because we didn't have, oh, okay, no, that's okay, I couldn't help maybe having two mics would get feedback, but yeah, well, you can hear me if I, okay, this is better. So we do, so okay, so we did, we didn't have, I was just about to say, so we didn't have room to get into this in the concept clearance, but we do imagine them as being essentially the same sites except for the distinction of the 25% and the 60%, other than that, the goals would be the same. So they would be very complimentary. I wouldn't see any other distinction between them. So they would work together. Let's see, you still have? Yeah, as for the questions, I would say all of the above, they're all important, and I would support all of them. The one thing that it's still a little confusing to me is that slide that Emerge is not any more dealing with clinical decision support, because I think it does to a large extent still, and I think that's the major strength of synergizing because to my understanding, Emerge is converging to a standard in terms of electronic health record and so on, so it would be better to have both follow the same standard to the extent possible, and then also use the lessons learned in Emerge and particularly at clinical decision support is hard, and it's hard to implement on the commercial vendor systems that we have out there, but try to push the envelope towards that direction. As I mentioned before, I think the secret is how to get the RFA right, so that the greater than 25%, greater than 60% is well-defined, and there is a rationale for what's expected and how it is monitored, because it will be hard to monitor this over time, right? And again, as I mentioned before, I think the R01 concept is very important, the investigator initiated, but I would say that it could be broader than what was presented in terms of seemingly too prescriptive and it has to be the variance that's the Caesar bound and things like that, so those were my main comments. Okay, thanks. I take all of those points. I will mention that the figure that I showed did show, I think, that primary emphasis on clinical decision support and dissemination for the Ignite program, but the other programs also have an emphasis in that, I think Emerge would also say that it's doing clinical decision support. Caesar, even current Caesar has a little bit of that. Yeah, do you want to come? I think because it's come up a couple of times, we are going to have a separate discussion about the investigator initiated, so I don't want to, a couple of people have mentioned that and I just want to point out that we will be discussing that more. Comments from other council members? So if indeed the two programs are going to be that coordinated, I guess I'd still encourage you to reconsider having two RFAs, one with 25%, one with 60%. That's just bothering me as a precedent that the institute's going to follow. I just don't think that's the way to promote diversity within the studies. There's just something about it that's bothering me, particularly if we expand the definition of underserved to include socioeconomic status, et cetera. It's just bothering me that we're going to have these two sets of RFAs and if we did that across every program, I just think it's a slippery slope. That's one kind, and then I'll be quiet. And then the second is, I actually didn't have many questions until your presentation, that your power calculation, and I apologize for picking up Powergate, it assumed that there was 11,000 people. That was across all of Cesar, right? And I doubt if there's a shared single hypothesis and method across every site that you're going to do a unified power calculation. I realize that's quibbling, but on the other hand, I would just avoid the inclusion of power calculations. It's bad enough that the investigators have to do them in their grants. I would hate to see council have to do formal power calculations if they were to finish. I will say that, so I completely take your point about the measures being different. I will say in current Cesar, for example, the Cycle Social Outcomes and Measures Group, even though they're all using different instruments, there are sort of aggregate measures like, is there patient harm being done? That can be aggravated across, and it was that sort of general measure that I was referring to, but yeah, I take your point. And then I think about the RFAs, I think it's a good point as well. One thing that I recalled from our pre-council, kind of concept development discussions was, some individuals, I think, were concerned that even a single threshold, say 60%, would be challenging to me. I think there were some concerns that that just might not be feasible. And I guess I welcome council input and whether that threshold, if we were to pursue a single RFA, would be too high. I think that was one of the reasons why we decided to keep them separate was to provide an incentive for some studies to go higher. I think we could have gone either way. Yeah, I'll be quick, but I think that it's very laudable. And I don't think it's out of the realm of possibility that people will be able to guarantee that kind of percentage. I also, I just wanted to say, I think this makes very clear that you're not talking about the ancestry populations here. You're really focusing on disparities populations and that that's not just race ethnicity. It includes a number of other features which have been already mentioned. So I think that's awesome as well. I would very much support that. So just to get your thinking on this, there's two ways to handle a question like how do you define diversity? One is to wrestle with it and put it in the RFA. And the other is to open it up to the applicants, which gets messy, but you get interesting ideas that way. Well, I think it opens up muddying the waters again. And I just think, I think you've got a very clear mandate with this, which was not accomplished in season one. And so I would advocate being even more specific about the kinds of things Jim mentioned, which we had seen as falling down in our, despite our best efforts. So I don't know, sorry. Well, I feel really strongly about it. I asked a question. See, I wanted to comment. You put something in there about the coordinating center being responsible for helping to disseminate information to professional societies and to try to bring them on board. I just wanted to add that there are probably two or three other critical bodies that it would be terrific to try to coordinate with. One is the Blue Cross Blue Shield Technology Assessment Group. And the other is the Molecular Diagnostics Tech Assessment Group out of Palmetto, which is one of the contractors for Medicare. Other comments from Child Health? Not me. Oh, sorry. Well, Regina, why don't you identify yourself? Your microphone is not on. Okay, so hi, good morning, afternoon, actually. Yes, my name is Regina James, and yes, I was at Child Health, but now actually I'm at the National Institute of Minority Health and Health Disparities and just kind of listening to the discussion around diversity definition. Just wanted to kind of put on the table that there is an official diversity definition for NIH, so it doesn't necessarily have to be adjusted. But I did want to just share with you just the definition of Minority Health and Health Disparities Research in Education, which is based on the public law, just to kind of keep this in mind as you're thinking about populations and the health. So, despite notable progress in the overall health of the nation, there are continuing disparities in the burden of illness and death experienced by African Americans, Hispanics, Native Americans, Alaska Natives, and Asian Pacific Islanders, compared to the U.S. population as a whole. The largest numbers of the medically underserved are white individuals, and many of them have the same healthcare access problems as do members of minority groups. However, there is a higher proportion of racial and ethnic minorities in the U.S. represented among the medically underserved, and this is based on the public law 106-525. So, with this discussion that you're having around, focus on race and ethnicity, whether you should or shouldn't, what is the definition of diversity, all those are really spelled out, and I guess the real question is, what is the research question that you're really trying to get at, and not necessarily trying to change the definitions? That's it. So, I think we're ready for a vote, and we'll take them one at a time. We need a vote for each one of them. So, can I get a motion to approve the concept as defined in the document and explained here by Lucia for the first, the clinical sites, motion to approve, second, all in favor, any opposed, any abstentions, okay? Thank you. I know further questions, so you don't need any clarification about the other two, right? I heard a full discussion. I'm just gonna march through them. So, a motion to approve the second concept for the clinical sites focused on diversity of participants, a motion to approve, a second, all in favor, thank you, for the coordinating center, a motion to approve, second, all in favor, any opposed, any opposed, any opposed? I'll do the IC.