 So let me give a little bit of background for the next thing on the open session agenda. And it relates to our training program, and there was really a confluence of two things that led me to want to get a little bit more input about our training program. One, I found it very interesting that almost from the very first event associated with our Genomics 2020 strategic planning process, we heard significant input about the genomics workforce and our training programs. It just came up repeatedly, almost at every event, is training, training, training, more so than I guess I had anticipated going into it. So that was one thing I thought was interesting. Lots of ideas started bubbling up. And then a second thing was, as always, lots of attention at the leadership level, NIH Institute of Center Directors looking at various metrics and various reports about NIH's overall training investment. And at about the same time that we were kicking off our strategic planning process, I happened to be at an Institute Directors meeting where they reviewed some recent data about the NIH's training investments in different ways with different measurements, including an indication of what each institute was doing in terms of its investment. And what I was struck by was the fact that our overall, and you're going to see the data, I'm sure it's going to be in one of Wendy's slides, is we're below average. And there's a lot of historic reasons for it, but it was striking to me, especially in conjunction with hearing the early strategic planning events stronger than expected outcry about the need for more training. So I thought I wanted, I just thought it would be very useful to get additional input about this and really look at it, especially with the eye knowing that we were going to be publishing our new strategic plan, that maybe it was time to take a critical look at our overall investments in our training portfolio and our extramural research program. And so I asked a small group to be convened out of a council, I called it a task force. Wendy Chung agreed to co-chair it with Jeff Struyne, who is familiar to many of you. Jeff had just recently retired as a long-term program director of the Institute and had a lot of familiarity with a lot of things in our extramural program. And so it was willing to come back and be helpful in co-chairing. And Jonathan Pritchard was another member of the council table that I asked to serve on it. And then there were a few others that were added, and Wendy's going to show the roster of the group. I gave them a Herculean task of like, I wanted this quick, like six or so months, something like that, because I really wanted to be able to act on this. And I also wanted to make sure we were acting on this in a fashion that was highly synchronized with the new strategic plan. And so Wendy is here today to give the report of this task force. And I mean, the humorous thing is, when I gave the charge to the group, there were a number of things I said, but I never thought this would come out of my mouth. I said, make some recommendations on how to make us average. And as you'll see, that really is all, and usually we're so far above average at anything an HGRIR does, but this was a situation where if we could just be average, we'd be so much better off. And I think it's really important for us to get there. And so with that as a backdrop, I will turn this over to Wendy. Thanks, Eric. So as Eric said, I'm really speaking on behalf of the task force. And the members are listed here. I want to special call out to a couple either current or former council members, John and Pritchard and Carol Bolts specifically, and all the NHGRI staff that were so helpful in terms of coming up with our recommendations. As we were doing this, I actually am quite thankful to Eric that he gave us a tight timeline, because we had to work on this aggressively, but we got to get it done and move on. And this will be the efforts that started out last summer. I'll be showing you some of the data that show where we have been, but also where we hope to be growing in the future. As we did this, I'll show you what we did, but largely by a series of teleconferences, we tried to get input both from ourselves, but also largely from the community. So we looked at the current NHGRI training portfolio, looked at all of the strategic planning meetings that had been going on, as Eric said, and that was very much a theme that came across with all of the town halls that we saw, took the strategic plan from the ISCC, and then did a semi sort of informal way of doing this, had a series of questions that we put out to the community, and amongst the task force members surveyed 30 individuals who we thought knew pretty well what the scope of the landscape was. As you'll see, this included individuals really from the breadth of who represents human genomics and brought that information back. For those of you who may be listening, thank you for those of you who responded, and many of you actually represented your entire institutions as you gathered data, and so this was quite helpful to us. We then presented this at the last council meeting and got valuable input from council, and all of this is put together in what I'm going to present today. This was what Eric was referring to in terms of seeing all the different institutes on the x-axis here. Let's see. I think this projects. You see the different institutes, and then I'll just point out here, NHGRI, shown on the y-axis on the left is a percentage of the budget that's going towards training, and then on the x-axis in red over here, or rather y-axis here, the absolute dollars spent. Unfortunately, in our minds, as Eric was saying for NHGRI, both in terms of percentage as well as absolute dollars were definitely on the lower end across the other ICs, and especially given how much this field is growing and changing, we thought that was really an issue in terms of thinking about this. Shown here is breaking down now in terms of the total dollars, how the training budget is spent, and again looking at the total amount, this is 17.3 million for FY18. Exactly half of that was going to T32s. Relatively small portion going to F awards, a decent portion going to K awards, and then as some of you know within the LC sphere, some of this is done within training centers, the Centers for Excellence for LC Research, and then specifically, and I'll get to this again for some of our underrepresented objectives, DAPs and diversity supplements accounting for a portion of the funds as well. So again, this is how the funding at least currently is broken down. So through many conversations, we thought about this and wanted to make very clear that there are several guiding principles we think are very important, and specifically for genomics, especially as we think about this. The first is that we believe that we really need to make sure that we have an inclusive and diverse community of leaders that are doing the science in this. This is incredibly important in terms of the leadership that's actually doing the research and also making sure the participants are represented, and to be able to get participants represented, we think we need their voices also in terms of the research that's being done. This is especially important because there are some underserved communities who have been slighted and really not been included in a robust meaningful way, and so that's a very important value in our recommendations. The second is that in terms of diversity, this is really very much a team sport, and so we really need to be able to train individuals to speak across the divides in terms of the different sciences and be able to understand and see the connections, and it's much more multidisciplinary than many other sciences are, so that definitely comes across in terms of our recommendations. The third is that this is very much a rapidly changing field, and so unlike the way we have many other efforts in terms of training, we need to be very nimble. We need to be able to adjust and be able to develop new curricula on the go and be able to deliver these in mechanisms and modalities that might be somewhat nontraditional, and so we're urging people to think creatively in terms of how to be able to deliver this. The communication streams, what will have greater impact are likely to be things we believe that are going to be online. We think of them as modules, so things that can teach specific concepts but then be repurposed and used by many different learners, not necessarily just NHGRI sponsored trainees, but really used across the space of data sciences, different ICs, different clinicians, but being able to use those as bite-sized bits of information that can be updated and iteratively revised as new data supports that. So thinking about that, that's and we'll get into this in a bit, there may be creative funding mechanisms to do that. We thought about R25 funding mechanisms to be able to develop this curriculum, and then again, a robust way of dissemination for this information. Maybe Twitter accounts, but anyway, a robust way of being able to get this information out. Another fundamental value we have is in terms of data access. We believe it's very important to be able to have data democratization, have these data available broadly to everyone internationally in the community, and we need to be able to train therefore investigators to use the highest data standards and data semantics to be able to get good data used by the greatest number of individuals possible. Within this, we believe that there's obviously a lot of foundational knowledge that's necessary for this. We did restrict our recommendations to thinking about individuals not necessarily starting, for instance, through K through 12, although we believe that's very important. There are other NHGRI and other resources that really should be covering that territory, but one of the things we appreciate, especially when it comes to, for instance, having a diverse and inclusive trainee community, is that sometimes we may have to get people up to speed, and so being able to think about whether they're boot camps or other ways of being able to get people just in time up to speed in terms of some of these foundational, analytical, mathematical, computational skills, computer programming, it may be necessary to do this in intensive courses, and again, for people to think about that as they develop training programs. Okay, so here's the bottom line. When we think about this in terms of how to be able to get ourselves up to average, we do realize that this is going to take some learning and it may take some iteration. So we thought about this in really two different chunks, a first five years and then a second five years, but the second five years being informed by the experience and the data derived from the first five years. So immediately, increasing by approximately two to three percent for a total of six percent, the extramural budget over the entirety of the five to denier period broken down in terms of the first chunk being about six to eight million dollars, the second chunk being two to four million dollars. I will say personally, I favor the upper end of that in terms of being able to get to where we need to be. And again, that would be informed by the learnings in terms of as we go along with this. In terms of thinking about how to break down that increase in the budget, we did think about within the pipeline of training where we get the most return on our investment. And so thinking about this and looking at some of the data, the farther you are along the training pipeline, the more likely you are to actually stay in the field and stay in the science. And so we thought about disproportionately putting more of the dollars into, for instance, K awards, F awards, individuals that are clearly highly motivated because they're writing their grants. They're individually showing us what they can do, but also realizing that there definitely is value, for instance, in T32s in terms of setting up an environment of learners in a specific area. Also realizing that we do need to increase the number of underrepresented minorities and so having an important component of that. So in terms of breaking this down, we thought about doubling the number of F awards. And if you remember back to that pie chart, the F awards are a teeny tiny sliver at this point. And so doubling that in total dollars is not that much, but it does increase significantly those opportunities, increasing by 50% the DAPS and the K awards and then by 17% the T32s. We did think about the T32s and whether or not that's mostly put into, for instance, new institutions with new T32 grants or being able to expand the size of current T32 grants. And we came to lean on the former that is hopefully having more institutions that would have training programs, but realizing that there needs to be a critical mass. So they need to be of sufficient size to be effective. So all of this all told $5.5 million in terms of that increase. In terms of thinking about this, we also thought about all the individuals who have basically declared themselves to be very much interested in the genome, but may not be contributing as much as they could be. And perhaps that's because they need a little bit more rigorous or formalized training and how to support that. We're not prescriptive in terms of understanding how that should be done, but realizing that we do think that's an important group of individuals included amongst this, for instance, are individuals that are on the clinical side of things. So for instance, the individuals who are in training programs as laboratorians for ABMGG, molecular genetics and cytogenomics training programs, genetic counselors, nurses, nurse practitioners, LC researchers, but those individuals who already have a large knowledge base, but being able to get a little bit more rigorous in terms of understanding how to do this might be able to make much greater contributions. And again, we're not prescriptive in terms of what those training programs should look like, but that there should be funds set aside for that. In a similar way, there are many individuals that are more junior data scientists. They may not necessarily be in a tract to get a PhD, but they may be very, very much able to contribute in terms of bioinformatics, computational work. And so those individuals, again, being able to have training programs specifically for them that are not necessarily doctoral level, specifically calling out within that group, the underrepresentation of women as one group within that group that some individuals may not realize are underrepresented, but within this particular group are an underrepresented group that we hope to enhance. With this, as I said, we thought about being able to have some sort of modular training programs. I described a lot of this earlier, but again, thinking about something like an R25 mechanism, boot camps, summer training programs, again, we're not being prescriptive in terms of thinking exactly how this should work, but opportunities to be able to have a more creative, more flexible, more nimble, and more widely disseminated training program. Within this, one of the things that we definitely wanted to do, we believe in being data driven to make some of these decisions. And again, the idea being that the second half of this needs to be based on decisions and looking at whatever data can be gotten. And I realize it may be limited, but based on the first cycle. So that as, for instance, these grants are being evaluated, that they need to have very specific milestones, data metrics, being able to assess what the impact has been. And even though it may be short term impact, being able to see how many learners are touched, how widely this is disseminated. And ultimately, as Eric was saying, be able to long term track the career trajectories for these individuals, so that ultimately these can inform the best strategies going forward. So as a first step to this, this happened to be happening in real time as we were thinking about and going through this process. But the opportunity came up for NHGRI to sign on to an FOA for what's called the Mosaic. This is one of these kangaroo types of training programs or training grants, a K99 going to an R00. And so on the basis of what we had been talking about within the task force, the decision was made for NHGRI to go ahead and sign on to this FOA. Again, I think a good idea in terms of doing this, but to enhance in terms of a diverse workforce specifically within this group. So I'll be glad to stop there and take any questions. Thank you, Wendy. That was terrific. We'd love to hear feedback from council Sharon. Wendy, thank you for all the hard work that your committee did. Two thoughts. One is that the core concepts, which I think are very interesting, seem to be more from the institute's perspective as opposed to from a trainee's perspective. I'm not sure how the core concepts would translate to trainees thinking, oh, what are they trying to develop? Obviously multi-disciplinary researchers and things like that. But are there ways that we can really encourage trainees to enter genome sciences and be aware of the K and Fellowship Award opportunities? Because one of the issues is to get more grants into the pipeline. And the other is you brought up the ABMG fellows. So I'll just raise it. Of course, there's a dearth of funding right now for LGG fellowships, and there's an enormous applicant pool. So there are many labs that are certified but can't actually fill because they don't have financial support. So did your committee consider not just supporting curricula, but actually potentially half funding or something to help with this kind of log down? Sure. So for the trainee's point of view, we could go through each one of those guiding principles, but I think the point is to be able to really train trainees to be able to think about all of those and how to be able to instill them. I think in terms of how to get the right people, get it in front of the right eyes and to be able to stimulate people, I do think personally that this starts very early on in the career process. But hopefully we and all of us out there can be guiding people in terms of just raising awareness of these opportunities are there and to be able to beat the bushes in terms of that if there are more funds that are available. We did very specifically and I can testify that you're absolutely correct. I think the current number has probably run about 100 to one or 50 to one in terms of applicants for every slot that's out there. We have many talented people that we unfortunately turn away. There are some tricky things having previously been a fellowship director just to be able to get through all the requirements. You really don't have time to do research during, especially now that molecular cytogenomics is combined. But what we are hoping is that these training spots would offer an opportunity for instead of if you did two years of clinical, for instance, if you wanted to add a third or a fourth year for doing research, that you could use this and be able to then keep those individuals and get them onto a research track that if they were for instance afterwards to take a faculty position would be able to start a research program in addition to I'm sure probably signing out cases for part of their time. So it doesn't quite cover the clinical training part of things but I hope would help those training programs in terms of fertilizing the soil that they've got for people extending onward. Trey? Yeah, thanks for that presentation. And I think this question may be a question for program rather than the committee you chaired. But what is the plan for how this 6% will be achieved? So presumably 2% has to come out of some other funding programs. Is that just going to be across the board or is there some other expenses that are targeted? I'm happy to take the first pass if I don't do well enough I'll ask division directors to weigh in. I mean first of all we you know it's all these things are easier to do when you get increases because you don't have to take it away so but we're gonna I think you already heard we can jump start some of this almost immediately this year and you know and then and then handle it a year by year basis. I mean I mean that's you know we're not you know the as always you know if we can get continual increase like we got the last few years it's so everything is so much easier if needed I think we would have to sort of identify taking it from somewhere. Also we discussed this morning that the K awards are already split right so they're not in the training budget they're split among the different scientific programs. Yeah but I think when we when we tally everything up I mean you do it not by streams you do it through databases so I mean what you're seeing the data for is grabbing it from anywhere what really is training. Yeah I mean to that point the way we for people watching in the open session who don't come to the closed session we do we have a budget specific for our training stream which is not equivalent to the numbers here because this was looking at the mechanisms in the K awards so if we have an increase in K awards right now those would then be competing within that streams space against other activities in those streams or we can continue to provide increases to specifically our training stream of funding or or cross things with an idea that we would earmark more of it in for training. So there's sort of different ways to come but we are hoping through increases to do this more from directed increases than from sort of that's my tap hand motion I guess. Rafael and then Hal. Thanks Wendy that was really good. I want to share an experience that I encounter often in trying to increase the pool of students in genomics and also data science and it's that I get asked very often what after people finish an undergrad or take one of one of the online courses that we offer what do I do next if I want to become a data scientist or work in genomics and often the only thing I can think of is do a PhD or do a master's the problem is that doing a PhD takes can be free with fellowships but it takes five years so it's quite a risk if you're not going to like it you might spend a lot of time wasted and the other problem with a master's program is that there's no fellowship so you end up paying tens of thousands of dollars. So you had a point number three up there that I think relates to this which is what I would suggest is that we think of ways in which you can have a transition period where at the end of it it's short like a master's and at the end you have something you have some certificate or a master's degree and then you can decide if you if you go into the PhD I think that that would help at least for me it would help me answer that question when people ask me what should I do next because I I just don't feel right telling them come and pay us $50,000 to do a master's degree with us or even if you're not sure take the risk of doing a five-year PhD. Right so I think that's a great suggestion Rafael it is exactly what we had in mind for number three here which is that we thought about things that were smaller more intensive but you know not a PhD type of thesis in terms of doing this but that there are a lot of data scientists a lot of talented people who could benefit from that. What I would add to what to what you're you're suggesting is that there's something at the end that they can use to attain an employer. So you know we've we thought about exactly as you said a certificate I have to be honest I don't know in some circumstances I've seen that gets not be taken all that seriously in other circumstances they have been I think that'll depend on the credibility of the program and sort of the prestige that goes with that but yes I do think there should be something in terms of an achievement that someone can be able to put on their resume as a result. So I'd also like to thank you and your committee for excellent work. I'm questioning the goal of achieving the mean especially given the introduction that the compelling introduction that you gave testing to the urgency especially in our field especially now. So I'd feel more comfortable if that was based on a functional assessment of here's what we need as opposed to here's what would make us credible in the eyes of others. Given that many corporate entities are thriving based upon people trained in our field I'm wondering if there is a missed opportunity for corporate partnership in funding training programs. So that's that's a great point. So number one I just want to amplify that there were several members of the task force that also fell towards being more aggressive in terms of the time the funds that were going into this. I also thought that we were thinking we need to be realistic though and get some data to see how effective this was so that's somewhat what our upper limit to this. Number two and I should have said this earlier is that we think of a success not necessarily staying in academic medicine per se in terms of the trainees but we really think about continuing in genomic sciences whatever that whatever roof that might be under. We had thought about and actually I'll come back to Sharon's point in part we had thought about corporate sponsorship or ways of doing training even to the point of ABMGG fellowship programs in terms of how we might be able to get people to sort of jointly put into the pool in terms of doing this. I'm going to defer this to Eric but I think it gets a little bit complicated in terms of mixing funds for this. I don't know if this would be separately trying to think about how corporations would sponsor be able to do this but I think at the end of the day many of them directly benefit from what we have done in terms of growing these folks up and so I don't know if that would be on an individual institutional basis or if there's some more centralized way of doing this. I just can imagine it gets complicated bureaucratically. I mean Hal I mean let me ask you a direct question I mean I think it makes total sense to see if there's industrial interest do you want NIH in that conversation or would it be better served to keep us out of the conversation because I mean and I think this is all interrelated with what Wendy just said you know and I don't know there's a lot of complexities associated. I mean first of all we couldn't do any of that but we have we have a fundraising you know the foundation for NIH I'm not sure how realistic I think this has come up in other scientific areas and I'm not sure how well this would go if NIH is in the conversation but that wouldn't stop professional societies institutions from pursuing this separately. I don't know. Sharon are you on this point? Yeah I mean first of all a lot of the current fellowships do have industrial funding because many of what the many academic labs are now jointly owned certainly the Baylor Fellowship is is sponsors include our diagnostic partner. I think what we're talking about is not what I was talking about was not so much like a complex discussion but for example if half of a slot was paid through not that dissimilar from the T32s that help support the physician trainees and medical genetics that might really encourage other diagnostic companies to be willing to pay half a slot. We need additional funding sources for these trainees that's just very clear and so I do think some of the testing companies that are not a training site themselves do actually contribute to some training programs. I'm not as familiar with that but that's what I understand. It's certainly something the ACMG probably has more familiarity with but I do think really thinking of some way of helping to fund the training slot. These are our genomic diagnosticians of the future is pretty critical right now. I mean if tenable I think having NIH at the table could make a huge difference. I think you have leverage to apply. I think that you could democratize the process. I mean now there are some very large very wealthy diagnostic labs who you know can get the ear of corporate sponsors much more easily than others. I would favor the model where NIH is at the table if possible. Fundraising is I mean you know this is all theoretically doable. It's a you know and there's a way we can do it but it's not us. I mean it's the foundation but it is not it's not a it always sounds really good going in and it also gets really hard really quick but maybe this is a fertile enough area that I'm not being optimistic enough. I mean I think it's also to NIH's benefit. I mean if you can get sponsorship for that aspect of your funding mission you'll have more dollars to spend on more conventional pursuits. Jeff did you have a question? Yeah and I think it's related to this discussion whether work is related. I wonder whether you had the opportunity to think about what the genetic force might look like as time goes forward. What are we training folks for in 20 years? Got that so far. Yes what's the genetic force like workforce likely to look like in the future? What are we training people for and do you feel that the recommendations that are largely general sort of at the funding level are sufficiently flexible to deal with any significant evolution in the workforce as time goes on and perhaps related to that too is the question of training physicians in genome science which I think remains a serious challenge. Yeah so I'm not sure if you were thinking mostly the latter in terms of that I think certainly what we were thinking is that everyone's going to be practicing to a certain extent or using genome sciences and we've got to be able to lower the bar to entry and it's got to be information that's in and so I'm going to take clinicians sort of in using this hopefully in their daily lives that it's got to be delivered with information that's just in time and bite-sized pieces that's not overly complicated that they can really be able to I call it news you can use but information they can be able to immediately practice and you implement potentially that's even things they can use for instance that are delivered through the EHR in terms of decision support at the time and that's what we were getting at in terms of those bite-sized modules with the workforce for the next 10 20 30 years and that that's really all levels of medical professional providers doctors physicians assistants nurses unit counselors our workforce in terms of that backing up a step from that I think they're going to be also you know I think the other big group we thought of our data sciences that that's really going to continue to be the engine the driver I think ultimately of individuals with quantitative background software engineers data scientists in terms of doing that I have to be honest I don't know that I could project 20 30 years I think I'm good if I can project five years at this point but but I think it's a lot of those individuals who are going to be powering this and again I think it's something that they're going to need more intensive programs it's a very different training paradigm for those folks and again if there's anything I think we work worry about is that being able to get individuals to the point that they can even enter that that there are some individuals who might have been disadvantaged in terms of where they started from that we might need to level set to be able to get the diverse workforce we're talking about and represented in that community but that we should be willing to do that and be able to help in terms of leveling that field and getting people that may have come from a biology background that was not so computational but have really remarkable skill sets to think about again about those cross-disciplinary bridges that can be made yeah this is an interesting discussion I think you know when you talk about what the future jobs look like here you've got an interesting a couple of things going on today is one is you've got this huge blossoming in academic medicine academic centers and research in order to bring this all to reality and particularly in the data science area many of the people that are really really good data data science also have other opportunities for example in silicon valley they can go to google they can go to facebook they can go to these kind of companies where the economics are very very different and so you know I think you've also got an economic issue here and how to motivate you know how to get the right people and then the imbalance of economics between these these different activities yeah no I think you're absolutely right and I have definitely observed the economic difference I think it's people I just guide them as people who are mission driven who are really driven because they have some passion for this specifically and I do think as I said sometimes those are people that are not coming to this thinking about solely being data science and agnostic about what data set they look at but they come in because they have a passion for some of the medical and scientific questions and and I think to be honest those are some of the people who end up staying the longest and making really significant contributions Carol bolt on the phone did you have anything you wanted to add no I think I think Wendy did a great job summarizing I will point out that when we reached out to our peers we did make sure that we included representatives from industry to sort of test the waters in terms of what the needs are there and we were really not focusing on kind of the 30-year horizon this was really what can we do in the next five years where would the investment be that could have the biggest impact in improving the number of of qualified individuals in data science and not just putting money into the traditional avenues such as the the phd type programs as was discussed earlier but but really sort of opening up and and thinking about how to invest in novel ways as well so all of the questions that have been raised are really good ones that that we did discuss and the recommendations that are coming out of this were really focused on what near-term impact highest near-term impact we could have by by bringing NHGRI up in terms of the amount that it funds in data science thank you and Jonathan Pritchard you were part of this team as well did you have any comments no I think that was a great discussion thank you I don't know I need to ask thanks for the presentation Wendy okay well once again thanks to Wendy and Jonathan and Carol all the members of the team and Jeff screwing all of you from but we will you will be hearing from us as we move forward from these recommendations to implementation you give us some important things to think about so thanks again all right we're going to take about a 55 minute break let's resume here with the open session at one o'clock and for the council members your lunches are going to be brought in okay thank you all