ICDAbio Town Hall: Session 1_March 2020

– It’s a 11 o’clock so I think we should get going We have seven panelists ready to, sort of, steer discussion, and sorta working together with the attendee So we have 32 attendees and that could probably change over time, as well So I wanted to start off with saying a very warm welcome It’s very exciting to do this in this format It’s something that, at least, I haven’t tried at this scale before As you well know through our email communication we made the difficult, but we feel right decision last week to postpone the ICDA face-to-face meeting with the acknowledgment that a lot of we need to do, in terms of setting up the group, and meeting face-to-face, and discussing needs to still happen, but at this time, it feels like it’s better to postpone and cancel and do it virtually, given the current Corona Virus outbreak So we want to thank you for all your patience, and all your forthcoming, and all your positive feedback around this decision, so that felt very encouraging because of course it would’ve been much nicer to see you all in person So we’re trialing this format today and it’s, I don’t know about you guys, but I’m at least a little apprehensive to see how the discussion will flow and so forth, but I’m also excited because it might be something that we need to do over the coming weeks, or even months So together with you and your input, we will make it a success As you know, we will have two town halls today and that’s in order to try to accommodate time zones differences So I’ve seen we have a couple of call ins from Australia and other places, which is great because that was our intent, so Loic, I’ve seen you there, so welcome And then I also wanted to talk through, quickly, the Zoom etiquette, which Rachel and her team has sent out in the communications so if you look at the bottom there, you can raise your hand if you want to say something, and you can also use the chat page at the bottom here to suggest comments and, for instance Rachel has just told me I should remind everyone that you can ask questions and up vote questions during the Q and A that is coming later So you all have seen the agenda So, when I’m quite done here, Eric is going to kickoff and give you some general overview of ICDA Then we’re going to go in and discuss through the different recommendations, and then we’re gonna have a panelist sort of discussion that Carolyn and also, to a lesser extent me, will sort of moderate, and at that point we will welcome your questions and input as well The link to the recommendations has been sent in the agenda I’m happy to sort of put it in here as well, if anybody hasn’t seen it So I also want to extend big thank you to Rachel and her team for sort of putting this format together and for very quickly going from a fully organized and ready conference to go in Copenhagen, with kind hosting of Novo Nordisk, who’s also been super helpful and certain in his team, to sort of swiftly going over to this virtual format, so thank you for that So without further ado, Eric – Unmute – Uh um, – Here we go, now you’re up Now you’re on, yeah – Yeah Thank you Cecilia And let me add my thanks to Cecilia’s for all of the work that was done to set up Copenhagen, and then unwind Copenhagen and set this up on very, very, short notice Thank you to everybody who’s on the phone We now have 70 people on the phone, which is fantastic and one advantage of this format is I know we have a number of people joining who were not able to go to Copenhagen, and that’s great! So, let me just say a quick word, by way of framing, before we’re gonna turn to lightning overviews of the recommendations, and then to general discussion What is ICDA? Still worth emphasizing, what ICDA is and what it isn’t ICDA is a scientific forum to bring together people interested in this maps, to mechanisms, to medicine challenge From all around the world, many, many, different countries, many sectors, academia, and industry, and government, funders, and many, many more, to try to identify what are the most important things we need to do together, to solve this M to M to M challenge? To help facilitate that those things’ll get done,

and also to help convene the community to sort of monitor the scientific progress But what ICDA not, is ICDA is not gonna do the science itself, it’s not actually in charge of anything, ICDA doesn’t decide what gets done or not That’s gonna be up to the scientific groups, to the funders, to decide what they wanna do, what they wanna fund But the act of bringing together an amazing community that hasn’t really had a formal channel to try to distill the ideas and clarify the projects, I think the work that’s been done in the last three to four months by working groups, has shown how powerful it is to bring together a community to try to reach clarity about what needs to be done The purpose of this call is to look at those recommendations I know these recommendations, they’re not prioritized as this is the one to do first, or the other Because different groups may wish to do different things, and different funders may wish to fund different things So for all those reasons, the idea is to lay out “What are all the things that are gonna have to get done?” I think ICDA and all it’s members will have a very useful role in talking amongst the groups, talking to funders, til people understand what it would mean to pick up one of those recommendations and run with it And it might be that several groups together as is likely gonna be the case, wanna run with things, and I should emphasize, that in many cases, groups are already doing some of this, and it’s likely that they’ll be the ones who are running with it I think very little would be on the list, if it was a total vacuum Indeed, the recommendations grow out of work that is beginning throughout the field So ICDA is meant to be able to help facilitate those discussions, and then, I think, as things continue to grow, under perhaps this intellectual framework, to bring people together for scientific meetings, to talk about how it’s going So that’s just by way of background so people know what we’re trying to do We’re not in charge of anything at all, and yet a community that takes the responsibility together to clarify it’s goals, is a very, very, effective community So I’ll stop there, and I think our plan is now to go into lightning, and I think it really is lightning, descriptions of recommendation clusters, two or three minutes so that we can open up, everyone has got the recommendations and has seen them They’ve been available for at least a month So we’re not gonna go into great detail, but anyway, let me thank you everyone for joining, a 101 people so far on the phone Back to you Cecilia – Great, am I? Yep I’m on So then, I think we’re gonna go back to the agenda, and I actually think it’s back to us Eric (chuckles) for recommendation one, where we’re gonna discuss through the flagship project So just to add one thing to what Eric said, I think it’s really important also that everyone who is active in ICDA can of course, also stand up a project Because that’s something we have discussed, that a lot of scientists that are active in ICDA will stand up a project So one of the things that we are gonna do now, is that we’re quickly gonna do the lightning thing, where we go through the different recommendations Eric and I have been assigned to go through the flagship disease projects And for those of you who have read the recommendations, you will have seen that we have proposed a collection of flagship disease projects We’ll act as a test bed for it, like a pie pipeline construction to develop and validate reliable paradigms for how to go from maps to mechanisms to medicines, for any common disease Of course it will be cases in that sort of flow that are special for each of the diseases, which tissue type, which cell type, which particular mechanisms that will be mapped out, but we could think that it’s a reasonable thought that there will be sort of a flow that we will need to sort of map out We need to identify the cause of variants in genes, we need to figure out the cell types and tissues in organs Where those genes and variants act to affect disease? we need to map out the cellular pathways and mechanisms that drive disease We need to identify potential targets for prevention, detection, and therapy And any kind of tools that are needed for diagnostics

and therapeutic development So this is obviously really, really, you know a grand sort of stage, if you want, and I personally, love the executive figure, if you look in the recommendations, the overview where you will see that the flagships or the projects are, the ones that are sort of cross-cutting the sort of three themes And I think that that’s sort of on purpose, because again, it will allow us to flow And Eric do you wanna add something to my brain dump? (chuckles) – Yes, let me just briefly say, there’s of course already work going on, on many diseases And this is intended to kinda provide a framework, under which many such projects go along where we can think about, “What are shared infrastructures across them?” “What if some funder or disease area wants to go into new areas?” It tries to think about, “What are the common things that one would do, across diseases?” These things will flow from existing projects, for sure But I suspect we’ll grow (audio warbles) Some people said already, “Who decides what should be a flagship?” The answer is, “The people who want to do it, “and the funders who want to do it, “will ultimately decide that they want to do it.” It’s not like ICDA will decide what should be, you know what the choices should be But ICDA can clearly define, “What would constitute a meaningful flagship project?” And help as, “What might be the most efficient ways, “to stand it up?” Those are the kinds of things that you know, we want to have this for, and it was recommendation one, this is cross-cutting If we can do recommendation one, it becomes the forcing function that tells us, we really can make use of all the rest of the pieces to understand disease – And I think it’s really important to add champion in part, because somebody has asked us, “How would you work with existing disease consortia, for instance?” So, I think we have no intention in competing, it would make sense that, you know, somebody in an existing, or all of an existing disease consortia, would stand up a flagship process and sort of map it out I think there would be merit in doing an example, sort of flagship project, and sorta map out roughly what that could look like To sort of help people guide through that thought But I think it needs a champion, and it needs to then, go to funders for discussion Does that make sense? People? – Good, actually, we’re not getting feedback at this point, we’re doing lightning– – No, I meant to you, Eric (both laughing) – Oh, sorry! (audio warbles) to me – Okay – So let’s let others go through the lightning for the first set of clusters, and then we’ll be able to be open to, you know getting the questions that have already come in, and that are appearing through a window here – Perfect – All right – Okay, so if we are done with the flagship lightning, we should go on to Mark Daly, Ben Neale, and Cristen Willer about the maps recommendation And I think it’s Mark, who’s gonna go through this in the first session, right? – Yes exactly, and as long as nobody has muted me, and I can be heard, I am happy to do so Okay, a thumbs up means, I guess, people can hear me So the maps group, very ably chaired by Ben Neale and Cristen Willer, has been focused on, obviously the first step in this pipeline Which is, “What are the primarily resources that are needed “in order for us to build a comprehensive, “and fully transparent, “for the rest of the research community view, “of the genetics of human disease, “and genetic variation, in general?” And so we ended up with a few focused areas with respect to maps, and then a few others that I’ll highlight with respect to genetic resources, that are required So number two on your tour through maps to mechanisms to medicine, is quite obviously the critical importance of increasing population diversity of biobanks, that are focused on genetic analysis And I don’t think, I’m not gonna go through the justification for this, I think it’s obvious to almost everyone, probably at least almost 120 out of 120 people who are now on call, which is fantastic But this specific activity is that the ICDA recommendations, or course that funders need to really focus on emphasis and facilitation of supporting the construction of biobanks in under represented regions of the world, as well as including underrepresented populations

more fluidly in existing biobanks And working with the regional scientific communities to make sure that happens in all locations in the world The next point, point three on your map is that we would need to be in sync with that, to increase globally, and very substantially, the size and utility of biobanks focused on genetic analysis with really an ultimate aim of working towards, perhaps, something on the order of 50 million individuals worth of global diverse representation, but with a deep clinical and genomic workup of those individuals, as a resource for discovery and all of the downstream things that we’re gonna talk about We would hope that that, would in most cases, or many cases, be clinical data, from primary care, from EMRs, in order to get this completed real world picture of health as possible And that the funders should be supporting high up projects in these areas to help design, and evaluate, and expand existing biobank efforts all over the world And finally recommendation four, would be to support genetic analysis across biobanks And not by, you know, aggregating in one place, all the world’s data as some sort of uber project But the idea that has emerged, rather organically, over the last year is that, there should be a genetic analysis network, that fluidly allows collaboration, at whatever level it’s appropriate for data sharing, and taking advantage of advances in data sharing, and data security But that funders should really support efforts to create such a network that facilitates it’s meeting, facilitates federated analysis, and perhaps even, with respect to an early opportunity, that a global biobank network has begun, that then for instance you’ll get many others are very much involved in them, so hoping to support some of those meetings and activities So, the next section of section three of, over at the second half of the maps, speaks specifically to genetic resources that are essential So in addition to increasing the size and interactivity among biobanks, there are comprehensive resources that provide a critical starting point all of these activities that we’re going to discuss today, and for the next couple of years One is the need for comprehensive genetic, and genomic variation resource It cannot be understated how important it is that we have as complete a picture of human genetic variation across all populations as possible, this needs to be comprehensive, it needs to be emphasizing, especially, underrepresented populations, as in the case of the increasing biobanks, and we need to ensure, as much as possible, that there’s broad and individual level sharing when that’s possible, but also that there are allele frequency servers, and imputation servers, and other ways of representing non-individual level data that as many of us have come to know over the last decade, are becoming critical elements of both clinical, and research discovery in common and rare disease, on a day in, day out basis And so those foundational resources, and servers, and tools, need to be supported And then finally, part six, in a similar thing, you know, one of the motivating things that brought us to the table in terms of an ICDA, is really been this observation of great progress, in one sense, in the discovery of genetic variants associated to disease, on a disease, especially by a genome-wide association studies And that that has to be the launching point for all of the downstream efforts to better understand the mechanisms of disease, and ultimately develop new medicines And so it’s essential that we have, and significantly invest in the resources to accurately capture and curate all of the genome-wide association data that has been collected over the past decade, decade and a half of early and now, more matured genome studies These need to not only collect timeline data from individuals studies, but also work very closely with the most, sort of detailed consortium efforts that have taken place in many different diseases, in order to represent the best powered,

and most current, up to date, information, and to keep that up to date, and in real time for downstream mechanism and medicine communities that we’ll build from this, as well as, potentially develop other, as in the case of the allele frequency and genomics variation resources, other references that might be useful, for example with polygenic risk scores, and obviously, extensive discussion has already taken place, with respect to the EBI and the GWAS catalog that they have initiated So I will turn over to continue the section and on behalf of those of us here in Helsinki, at FIMM, and my colleagues who have been involved in presenting at previous ICDA meetings, Nice to see everyone – Great, thank you Mark So we are going to go over to Tuuli Lappalainen, Who’s going to discuss through recommendations seven to nine In a lightning way, Which represents the mechanisms session – OK thanks Cecilia, hi everyone So yeah it’s a pleasure to present on behalf of the mechanisms working group that is co-chaired by myself and Jay Shendure And Jay’s in the middle of the COVID-19 work in Seattle and not able to attend today unfortunately So as you all know, one of the key challenges in common disease research is understanding the mechanisms of how these variant associations actually contribute to complex phenotypes And here in the mechanisms working group, we are really focusing on the molecular and cellular mechanisms and then the physiological mechanisms are in the medicines part And we put together three specific recommendations to address different aspects of this challenge And this, of course, doesn’t include everything that needs to be done in this area, but these are some focus areas that we identified So, recommendation seven, which is creating a human genome regulation map, really focuses on node coding cis-regulatory elements, and variants, and better identification and characterization of those So here the idea is really focused on analysis across all human cell types, for the cell type, potentially cell state specific analysis to identify all cis-regulatory elements a little bit sort of alongside of what ENCODE has been doing Also, identify all cis-QTLs at the single cell level, about a certain effect size threshold, and for target genes effected by these cis-regulatory elements, based on experimental data, CRISPR perturbations, et cetera And then also, develop computational models that use experimental data to allow these kinds of inferences, even when we don’t have data, from experiments And then, also do sort of a functional inference, understand the functional architecture of these cis-regulatory elements, so that we can actually predict, or develop predictive models of variant effects upon gene function and gene regulation in cis And this recommendation as some of the others with the links close to some of the existing projects, that where we will need to interface with them, to continue and complement their work, especially ENCODE and Human Cell Atlas Then, when it comes to recommendation eight, this focuses on protein coding variants, which is of course a smaller slice of all the GWAS variants, but in some ways a lower hanging fruit, in terms of understanding their mechanisms, because the target gene is known and if the effect sizes are larger, and also coding variants are a tractable number of total variants, which allows comprehensive analysis So here the idea is to really sort of use all possible approaches, and ways to try to understand these variants, ranging from GWAS analysis in various biobanks, to various experimental perturbations approaches using isogenic genome editing, high throughput saturation mutagenesis, also model organism work for selected coding variants, and then various general functional assays, or gene specific functional assays And then also a key part is to develop and calibrate in PERD computation methods to predict coding variant effects upon protein structure, and function And then finally, in recommendation nine,

is sort of taking this kind of effects and system into an effect on cellular programs which is potentially a more challenging, sort of aim that we have, that’s something that is absolutely essential from getting from those molecular functions to actual cellular phenotypes, which is of course kind of an intermediate to getting to physiological phenotypes And here the recommendations that we have put forward are basically two-fold, so there’s one that takes advantage of existing genetic variation across individuals, so using samples from actual human individuals, or cell-like organoids created from those, analyzing how common variants, or rare variants or polygenic risk scores associate to similar phenotypes, such as single-cell level gene expression patterns and other cellular phenotypes And then also experimental perturbation approaches such as CRISPR, CRISPRi, to inhibit genes and then have readouts on the consequences of that And these will be parallel complementary approaches And I think I will end there, I will just mention that in all of these studies, where the idea is to use samples from existing human populations and cell-lines, there is going to be a lot of work Also to develop protocols and SOPs for the creation of biospecimens and cell-lines, and assays, and then when it comes to population samples from humans, a key focus area is to have some from diverse ancestries to avoid the European focus that we have had in these studies, thus far – Great, thank you Tuuli So, next we have the data cluster, cluster four, which are recommendations 10 to 12 When, where Ben Neale is– – Cecilia, this is Carolyn, I’m gonna cut you off, ’cause I think– – Yeah – Correct me if– – Yeah – Oh yes of course, – the plan is to pause now, for discussions, ’cause we wanted to, – Perfect – we knew it was a lot of information, so we’re gonna go ask now, this is Carolyn Hutter from the National Human Genome Research Institute in the U.S, and we’re gonna take you into, what is now, our first of two Q and A sessions, after which, Cecilia will take you into cluster four So, just so people know, what we’re really looking for, right now is just inputs and thoughts on these recommendations If you don’t see it on the bottom of your screen, you should see something that says Q and A And if you click on that you can enter in your questions You can also up vote other people’s questions and feedback With 127 participants we’re not gonna unmute everybody, but we may try to unmute some of you as appropriate to bring in different questions And what we’re looking for is “At the highest level did we “get these recommendations right? “What do people see as major strengths, “or gaps or questions that you have “as you think about the current recommendations?” And then as you think about what ICDA is doing, or shouldn’t be doing, you can also ask questions more generally about ICDA itself, and not just about the recommendations, if that’s one of the places that you’re wanting to sort of get some more feedback So I’m gonna sort of kick us off, I’m incorporating some of the questions coming in, as well as questions coming from people who put some stuff in last night And I would say, it’s interesting sometimes to see some of the overlap in questions, So I’m going to start with one that sorta was something, that I had along, incorporating with Paul Frank, which is ICDA really has a very ambitious set of recommendations to cover a lot of the areas on this maps, to mechanisms, to medicines spectrum, and what are the thoughts about, or the framework for partnering with identifying, integrating and working with overlapping stakeholders, examples include epidemiologic cohorts, existing efforts with the same aims, Paul called out Disease Specific International Precision Medicine Initiative, somebody in the online, talked about open targets, et cetera, So maybe Eric, you leaned forward so we’ll start with you – Okay – And this is sort of a question to any of the panelists who want to jump in – Sure, so I want to emphasize again, I mentioned it briefly, but it’s really important to say that we expect that most of this work

is gonna be done by groups that either already exist, or are standing themselves up So it’s more like, how can the ICDA help bring together and convene, but it’s not, in many questions, the work may be an expansion of what is going on by existing groups I think ICDA is trying to describe, what needs to be done, but I know that in many cases, there are very active, say disease focused groups, and it may be that they are providing the leadership for it there In other cases, I know there are diseases that haven’t been really the subject of great genetic focus, and they’re trying to figure out, “How do we mount a project?” And I think ICDA can be helpful to such groups, or to funders who want to see work in an area, in helping describe what it would take to do that But in the end, every one of these recommendations is going to come from initiative in the community and people taking leadership ICDA can help facilitate, but it’s not like ICDA can decide or can do the doing We can act as a forum for groups to gather to do it So I think ICDA’s prepared to work hard with existing groups to help make connections, help make sure that there’s access to infrastructure and tools, help make sure that the plans are fully fledged out, but again, it’s gonna depend on the initiative of the community – Thanks, do any of the other, Mark, did you want to add to that? – Uh yeah, I can expand on it, and also take David’s question as well, I think, you know, one of the key things to keep in mind is that, in response to both of these questions, is that as we think about flagship diseases, I think it becomes more obvious that we can be reminded that the focus is really not on the genetic discovery activity, and the focus of collecting the largest possible biobank, is primarily not for genetic discovery purposes, for common diseases, where genetic discovery is well underway I think it’s clear the flagship projects would be quite naturally led by, if they overlapped with a significant consortium activity already going with gene discovery, then the gene discovery aspect of that, would clearly be driven, or have a large contribution from those consortia I think, what we are trying to focus on is really that we aim that we can now see through in these flagship projects, initially, the trajectory all the way from the mapping process, which is well underway to an understanding of the mechanisms underlying what we’re mapping, and then all the way through to therapeutic hypotheses And so the biobank expansion, which as we do say, in your final point David, that at the aim would be 50 million in a more cohort style biobank and with the broad data would make the possibility that required biospecimens be important understanding of the full range of medical consequences, positive and negative, for findividual associations and for the global risk of disease, would be well understood And so far more than just the discovery activity, I think we really want to focus on “What is the full set of deliverables from genetics?” And then, “Do we have, not only the information, but also the biospecimens and the follow up possibility to carry that forward? – Thank you Mark And Mark, just in the future, if you’re referring to questions like you just did for David can you also let the group know a little bit about what the question is? ’cause I’m not sure that everybody can sort of, fully see the questions, particularly people who just dialed in, and didn’t use the WebEx – Great point, okay sorry, I had a Q and A thing up on my screen right next to my Zoom window, so I was presuming how they did as well, but, good point for people calling in can’t see the questions – I think, go ahead So another question that’s come in that’s been upvoted quite a bit is from Michel Naslavsky, and a huge apology to everybody and anyone whose names I mispronounce, but the question really

sort of addresses phenotypic harmonization So even existing biobanks are fully digital, the choice of variables may not be standardized, so it could be converted and adapted which requires a deep knowledge of the phenotype And so I wondered if somebody wanted to talk a little bit about both phenotypic harmonization, and I’m gonna expand this a little bit, to also talk about what types of phenotypes are really sort of, are we thinking about and are recommending within the ICDA to bring in and what types of things, in some ways, there’s just sort of a mention of phenotypes, sometimes clinical, sometimes hinting at environmental, but not fully spelled out in the current recommendations, where do we sort of see things landing for that? And I guess I’ll knock this over all the way, I see he just took a bite, to Mark, or anyone from the maps group, who wants to take an answer to that one first – Happy to take a shot, though I mean, I think this is an area where there clearly needs to be investments and then there’s not a quick answer to this I think in the proposal that we need to invest in the development of biobanks, this is certainly an essential part of developing biobanks, which is to figure out, what is it possible to collect? And how would we harmonize it with the remainder of the global activity? But it’s not one that I think anyone has a quick, or straightforward answer to, at this point – I would completely agree with that I mean I think it’s worth noting in recommendation four, we talk about both clinical phenotypes and other phenotypes, as well as, kind of phenotypes that have more, traditionally, been very difficult to capture, particularly things along the lines of progression, and outcomes that may be more available from electronic health records, and integration along those lines, but again, it is exactly as Mark says, that it’s not as if we have all of these phenotypes packaged and ready to go A lot of the work will be on the curation and harmonization on the phenotype side, alongside the curation and harmonization on the genotype side – Can I jump in for a quick second here as well? I think it’s really important to emphasize that having as many phenotypes as possible, including medical records phenotypes, but also environmental exposures, to the extent that those can be obtained, self report, I think UK biobank has shown the tremendous power of collecting a diversity of phenotypes So we could probably emphasize even more in the recommendations, the importance of seizing the opportunities to collect phenotypes broadly The second point I’d make, and here I look to things that Mark and Ben have done, is that there are both traditional ways of harmonizing phenotypes by making sure that one collects exactly the same thing, but I think the ICDA community can be a leader in also thinking about modern ways, like using machine learning There have been recent papers where phenotypes collected in totally different hospitals, got integrated by machine learning to figure out when somebody in hospital A says something, and somebody in hospital B says something else, this is what they mean together And then finally there’s genetics, which is, there’s a validation which only genetics can provide, that if in one country the disease was defined one way, and in another country the disease was defined another way, by looking at which loci come up as significantly associated, if they show the same sets of loci, then there’s a strong case that they’re detecting the same thing Not every last locus, but broadly so So, I think the ICDA community working together, could be very creative about the multiple different ways of harmonizing phenotypes that are now possible, given big data, given genetics, and I think we should, certainly if we’re looking to the future, be collecting phenotypes broadly, or more precisely, urging the projects that are stood up to collect broadly – So yeah, and I think, I mean to that note, I also think it’s important with some of these things to think about, what needs to be collected and thought about at the beginning, versus what can be done more retrospectively You can think about sort of something that passive collection could do, or you could go in and later get the information and then there’s other key, non genetic information that is really good to think about from the beginning, and engaging with the correct community to think about how to be getting that data I wanna switch now, there’s a question about how online combined with one of the questions that came in last night, so Inês Barraso was asking about

how to ensure sufficient engagement with the LC community, particularly thinking about, diverse ancestries that have been less represented thus far, how do you make sure that just coming in, and working, and efforts, with the local communities, and although not exactly in the same vein, but also I think related to this question, is a little bit about what does ICDA mean when you say “diverse?” And how do you, sometimes it’s unclear in the recommendations when you’re focusing only on ancestry diversity, or more broadly, on other activities such as socioeconomic diversity, et cetera I realize there’s more to those two things, and Nicki did point out that this is gonna be covered in the cluster six recommendations, I saw that a little too late, but I’m gonna go ahead and, since I’ve already asked it, put that question out now and I don’t know Nicki if you wanna chime in a little bit first? – [Nicki] Sure, and then, thank you Carolyn Yeah, we will be talking about that and our recommendations, which are on developing good policies for genetic studies, data sharing, and federated analysis, and then also promoting global equity And in these recommendations we talk to our consent processors and how we can make sure these are sound, and also how we can accurately store the consent data Because often these are not really properly kept currently, especially for secondary data analysis And then we also looked at, and our policies for, sharing datasets, et cetera, that we need to develop community engagement guidelines that are regional and local, or relevant regionally and locally, to ensure that the policies are inclusive And also something that’s not often flagged but, to address culturally accepted research practices So not all cultural views of cell-lines, in vivo models, bloods, et cetera, would be the same So I will be speaking to this a little bit more, perhaps we can, and equally with promoting global equity to ensure that approaches are globally inclusive for participants and researchers So I will be speaking to this a bit more in the next summary of recommendations I think maybe we can pick it up there if that suits everyone – Sounds good, thank you Nicki So the next question comes from Carl Anderson, both online submission and here on the chat, about why is the recommendation focusing on whole genome sequencing, rather than whole exome sequencing? Eric? – I think if we are making recommendations for the future, even the not very distant future, it’s clear that the cost of whole genome sequencing is going to be dropping into the range of $100 to $200 There was an announcement, so we wrote that somewhat prophetically in the white paper, in the recommendations, then in AGBT there was a first announcement by one group, that said they were going to be releasing a sequencer whose reagent costs were $100 So that probably translates into something a little bit under $200 total cost And I think there is every reason to think that this will drop to $100 I think at $100 for whole genome sequencing, even though I’ve been one of the biggest proponents of whole exome sequencing for the purpose of getting as many samples as possible, I’m sort of now at the point of saying “We really are in a world where we will cut over in the next several years.” The whole genomes, it will just become affordable It’s now reaching the point where it’s equal to or less than the cost of collection and all of samples And even in medical systems, for people who live 100 years, just to round, it’s sort of on the order of a dollar a year So I’m biting the bullet myself, which is a big change for me in saying I think we will cut over So I think that’s why we put it there, obviously it’s something that individual funders and groups should decide for themselves, but I think the recommendation was to look that way and think that way ’cause that’s sort of where it’s probably going – There are a few other scientific rationales,

so fine mapping is much better serviced by having comprehensive capture of common genetic variation This actually, also improves diverse population capture, so a lot of the arrays are built off of what we know about different populations, and we know a lot more about European ancestry individuals, we know about other world populations, and so there’s value there It also helps for structural variation in some other kinds of more complex variants, so I think there are good scientific motivations, alongside the sort of forward looking motivations that Eric just provided – I think Carl is raising his hand – Yeah, I was gonna say I see that you have your hand raised and we also did answer your question, do you have anything else you wanna add, Carl? – [Carl] Yes, I just wanted to – We can hear you – [Carl] I supposed I’m less convinced that now is the right time to (audio warbles) – So Carl, we’re having a little bit of difficulty hearing you, but I think your question was sort of about the timing of this, and is now the right time to be making, you know how does timing factor into this decision? – So I can channel Carl because I agree with his point on a scientific level and we talked a lot about this, which is, I guess, this, two things that I would add to this, one is, this whole genome sequencing for new biobanks in the first parts of the world, this is essential now because we need to have a variation resource, and imputation resource and so forth, that is comprehensive and deep you know in populations, and there’s no argument that we need that now The question of what we invest in as a community for the deep dives into disease, I think since those are already happening and are going to be funded by organizations interested in those diseases, that will be taken up on a disease by disease basis The point being that we expect the crossing over point to be sometime in the not too distant future, but you know, we will assess it as it comes – Thank you So there’s quite an active sort of chat in the question and answer about the importance of environmental information Given the timing, I’m not gonna sort of go into that in great detail other than to say, we’re keeping track of these discussions, and certainly, Rick, and Richard, and David, I think you guys really have given some really good feedback and considerations here, particularly about how to get the environmental information and what are the best ways to go about doing that And so I think that’s certainly something for ICDA to consider and think about as we move forward I wanna give sort of a last question for the session, before we go back into the asking coming from Hernan Dopazo, from Buenos Aires, who was really sort of asking about how ICDA can best support regions that are currently underrepresented in genetic studies, where science is also more difficult to carry forward because of resource limitations, and how can ICDA support these regions, groups, or communities to help properly develop an ICDA program, and reach that sort of goal that ICDA has scientifically? Cecilia? – So Nicki just answered, so maybe I think it’s gonna be covered in cluster six again, but Nicki do you wanna say something quickly to this as well? – [Nicki] Sure, I’m happy to do so So recommendation 23 is specifically designed to push forward promoting global equity, and to ensure that the work of those for, those globally inclusive first for participants, and for researchers So the ICDA is recommending active states to decrease the barriers to research in some regions, which is exactly what you’ve raised in this point And this can be through training, technology, and funding, so we’ve identified where work needs to be done It can be done working with funders to promote these global equity goals, as well as hands on training, and online training And then also securing equitable access to advanced technologies So working to ensure that pricing is fairly kind of pitched to not exclude sectors

of the research community So I’m gonna say all of that again in about four minutes time, (chuckles) but anyway, that’s sort of the overview – Excellent, thank you Nicki And on that Cecilia and Eric, I will kick it back to you now Cecilia, this is when you can go into cluster four (Cecilia chuckles) – Yes, so I’ll progress into cluster four, and ask Ben to talk us through the data related recommendations – Of course, thank you Cecilia So there are three core data recommendations that we’ve kind of highlighted in the near term The first, and perhaps, most complex among those is the idea of a shared data platform It is worth pausing here and noting that this is not a single centralized data set, or sort of server where all of the data lives, rather it’s a potential ecosystem of federated, computational environments that will allow for different data sets to reside in different places, respecting the sort of ethical and compliance and regulatory considerations for each data set But nevertheless there’s been a long tradition in human genetics of having these kinds of computational work flows readily available to many in the community, you can think of like the Haplotype Resource Consortium, as like an example of an online place where people can process data in a given way So that is like an exemplar to guide our thinking about how we want to make sure that the ways to process and analyze genomic datasets, can really be made accessible to as large a group as possible Recommendation 11, really focuses on this idea of a kind of a genotype by phenotype portal So we have the GWAS catalog, and the efforts that have come along with the GWAS catalog There’s a opportunity to kind of expand and enrich that kind of environment, as well as, expand and enrich other kinds of key environments and resources that are out there for the community, things like gnomAD and Bravo for allele frequency references, as well as you know the potential for thinking about other portals, such as what GTEx has set up, or some of those other ways of accessing genomic information and results for the kind of wider research community is really that the gist of recommendation 11 And then recommendation 12 really focuses on this idea of a handful of gold standard validation datasets And that can kind of come in two different ways of thinking about One is for you know data processing, so you can imagine key datasets that if you can process this dataset and get to the same answer, then you are now compatible with the standards that are being used more widely across the community And that has obvious potential value for ensuring things like functional equivalence And then on the other side, there are, you know, this whole M to M to M challenge is focused on trying to get from the genetic mapping, all the way through to the medicine And so as we start to develop gold standard datasets for different pieces of that overall pipeline, those gold standard validation datasets, should be made available as widely as possible, because they’ll help us develop the methods, and the approaches, and the computational tools, necessary to continue and expand this particular approach across as many different diseases as possible Thank you Cecilia – Great, thank you So after Ben we’re gonna go over to Unnur þorsteinsdóttir who is gonna talk through cluster five, which are recommendations 13 to 17, and represents the medicines group Hi Unnur – Hi, can you hear me? Are you hearing me? – Yes Okay, good Okay so, I’m part of the medicine group with Judy Cho, and Mark McCarthy, and we have also worked closely with the Pharma Council, and Mark is actually on both, in both groups And we have five recommendations that are tailored towards the research community and also to Pharma And our first recommendation is the development of functional assets for systematic related processes, for example atrophy in ALS, and we have discussed this should be focused on genetic pathways, that cross theses pathways, or if it should be to develop new platforms that are more customized to its disease Then is the creation of tools

to propel therapeutic development for high priority targets And in this respect we are talking about the development of antibodies, molecular inhibitors, and biomarkers, that are very time consuming to generate, and for high priority targets like, both the research community and pharma could step in there And we also see like a good avenue for this structural genetic consortium This actually has a, is actually a good path forward for a number of these things that we need to develop Then, there is the development and to develop and apply new methods for discovering new biomarkers of disease We discussed this a lot and there is sort of a new, sort of, we are seeing, new ways to do proteomics of plasma, and we discussed, and then there are like, also, proteomics of CFS, and there are a number of omics, and other omics, and imaging data that can be used as biomarkers, and in this respect, I think, for example, if we just talk about the obvious, the plasma proteomics, then folks like to use the plasma that has been collected through, in large biobanks to actually do studies on plasma proteomics, as well as to incorporate this into clinical trials That would use this from the start, like phase one, two, and three, to actually evaluate the pocket encasement and therapeutic response in clinical trials Then we discussed a lot how we can sort of use genomics to assist in clinical trials And in that respect we discussed a lot the fault and at risk scores that can actually increase the success of the trial based on selection into the trial And it can actually reduce the number of adverse effects, and the time to the enrollment, like you could use even the known biobanks for that So and this is actually, there are some, actually regulatory thinking that needs to be thought of because how this would actually approve with regulatory authorities, but this is actually a very important point that can actually help to reduce the cost of clinical trials which is probably the most expensive part of the development And then the last recommendation, is sort of linked to this, is actually try to ensure the responsible use of the polygenic risk score in medicine So I’m done. (chuckles) – Perfect, thank you Unnur And for the participants, keep the questions coming in on the side, and we’ll address them when it’s time for Q and A And we’re now gonna go over to cluster six, which we have already touched a bit upon, but that contains recommendations 18 and 23 And Nicki Tiffin is gonna lead the discussion on those – [Nicki] Thanks Cecilia Yeah, so very briefly, recommendation 18 talks about the policies for genetic studies, the data sharing, and federated analysis And it recognizes that we need policies and guidelines for data sharing and access These have to be globally relevant, inclusive, and appropriate, also globally And the idea is, or the recommendation is to collaborate with existing efforts, so we flag particularly GA4GH which has been very active in this area We certainly aren’t recommending that we try and reinvent the wheel from scratch, but rather partner and consolidate what’s out there, in a way that is relevant across the board So we’ve proposed a data compliance task force that would undertake this and could work

with national authorities and funders Also bearing in mind that their gestation varies, globally, so keeping all these in mind in building the guidelines As I already touched on, informed consent data permissions, also need to be addressed in terms of guidelines for some consent processes, and the storage of permitted data uses and secondary uses And also using standardized vocabularies for storing those permissions We’d like to also recommend that we in terms of people accessing data and become, and researchers becoming data users, that we could standardize the user categories to facilitate access to appropriate data sets So for example, if a researcher is labeled as being someone who’s an epilepsy researcher, then they would be able to access data sets, which have approved epilepsy secondary use So by standardizing our vocabularies of how we store consents and data permissions, we can facilitate data use And then policies for sharing data sets, the different types of data sets, that need clarity so summary statistics and meta data, are one such category We need clear policies about when these are open and when they’re controlled access summary data Policies around data for strengthening genomic data resources So this might be imputation panels, generating allele frequencies, or population They will aggregate control data to have control data sets Also policies and technologies for federated data analysis, that’s also been touched on briefly So this would be around the data sharing aspect of that Community engagement guidelines are very important, these are going to, community engagement practices are going to vary, globally, so these are guidelines to be able to be, regionally and locally appropriate and to ensure increase of policies, and to identify culturally accepted research practices And then, and that’s recognizing, as I already mentioned, that different cultural perceptions exist For work, for example in cell lines, in people in vivo models, even blood samples, can be culturally very differently approached So community engagement guidelines can help to be sensitive to others And then recommendation 23 is to promote global equity and as I mentioned, this is about being globally inclusive, not only to increase our global array of participants, but also to include researchers Active steps can be taken to decrease barriers to research, for maybe under-resourced through training, providing technology, and for directing funding appropriately to those regions So the ICDA recommendations working with funders to promote that kind of approach, and to promote global equity goals And this could look like undergrads internships, could be postdoctoral fellows that are held in other parts of the world, and long term projects, but then supportive of researchers to go back to their home countries, and undertake research there And then also hands on training and hackathons, and promoting the access to online training material, to extend the reach of these kinds of resources And then, yeah, to work, sort of advocate for more equitable access to more advanced technologies, genome sequencing, single cell characterization, computation analysis, and to try and advise on producing training and platforms that can accommodate limited things, like limited bandwidth, or technical capacity So those are the main points, thank you – Great, thank you Nicki So then we have the last tranche of recommendations, 19 to 22, where me and Eric are on the hook So Eric do you wanna start here? – Sure. I’m just coming over to this end So 19 to 22 are mean to acknowledge really clearly, that while many of the ICDA recommendations pertain to larger projects, creating resources, dealing with policies, things like that, it’s really important to say that we don’t know everything, or all of the scientific foundations, and it’s really important to have individual investigator initiated grants, and small group projects

that go off in entirely new directions to develop methodologies, and technologies, and new biological understandings of the genetic basis of common disease, and training programs, because one can sometimes fall victim to thinking we know how to do everything right now I think the other ICDA recommendations are built by looking at what’s going on and trying to integrate and distill them These are a clear statement to funders that lots of creativity is going to be needed, and we’ve tried to lay out those areas, and I think, in some sense, this is the most straightforward one to implement, because, you know, funders have been doing this, at least some funders have been doing this, and I think we’re saying that doubling down on the importance of the individual creativity and the small collaboration creativity, is gonna be crucial to the success I think the ICDA would be glad to help funders, if it’s needed to convene meetings about some of these topics et cetera, but that’s really the motivation for these recommendations – Great, so then, over to you Carolyn – Okay, excellent everybody So I guess a reminder for people who perhaps joined late, what we’re doing now is a question and answer session with over a 125 on the call, we’re not opening it to just everyone talking at once, so if you have a question please type it in the question and answer box, you can also up vote other people’s questions, or if you’re not able to do that, you can also raise your hand So before I go into the, a couple of the questions that have been coming in, and as hopefully some people are typing some questions in, Ben I have a question to you It’s a little bit more of a statement, than a question, the data recommendations right now, sort of as written, focused sort of on the data resources, data platform need, and then not as much of a sort of recommendations on the sort of data generators, and so, I feel, and others have noticed, that the recommendations could benefit from having more about sort of data being FAIR, machine readable, standards around that There’s a little bit of talking with GA4GH data flow et cetera, but do you sort of have some thoughts on where you see that in the current recommendations, or where that might be added going forward? – Sure, that’s an excellent question Carolyn So the FAIR principles are, I think perhaps more implicit, rather than explicit, in the data recommendations at this point in time I think it makes sense to make them a lot more explicit, so for example, you know, there’s a, you know, FAIR includes interoperability, and we talked a lot about federated solutions, and for federated solutions to work appropriately, interoperability has to be a kind of core component of that Similarly with the kind of accessibility piece, a lot of the data recommendations really turn around, trying to, in a sense, lower the bar for access, both in terms of how we think about, accessing individual level data sets, but also how we think about accessing certain, kind of core human genetic resources, such as imputation, or even variant calling from raw sequence data, as another way of thinking about accessibility It is very much focused on what we do with the data, and how we organize and coordinate and make available the data, rather than exactly what data is being generated And the reason for that is that the kind of data generation activities are gonna be much more naturally, sort of built out in the scientific projects that ICDA is recommending So you know, sort of, where a flagship is easiest, and genetic mapping, and where it needs to go in genetic mapping, should be tailored to each individual flagship disease, and that’s not really a kind of, what we do with the data is not the same as, what data sets we think we need to create, and how we think about getting towards those data creation aspects And so that was really the sort of remit, and the way to kinda constrain the scope of the data conversation Because a lot of those kinds of core principles and approaches, I think need to be shared so that we can really work together and go from maps, to mechanisms, to medicines, and I think that kind of going, linearly through those things, particularly starting from that genetic mapping point of view, and focusing and amplifying the importance

of understanding genetic variation that is, relevant to different diseases, and how that works mechanistically, is at least in my mind, a kind of major tenanting plank of the ICDA – Great, thank you I’m gonna go next to a question in this question and answer box from Vijay Sankaran, and Nicki, I’m gonna send this one to you And it was really sort of following up on your discussion of data access and can you sort of touch on how sort of recontact could be facilitated in the context of genotyped populations that are part of ICDA? – [Nicki] Sure – Nicki? Oh – [Nicki] Thank you, yeah So Vijay I think from my perspective probably, that point that I would raise is that, if informed consent are done appropriately, it’s possible to get consent for recontact And if the informed consents are properly stored, which should be fairly trivial to mine as to whether they are consenting to be recontacted or not So I think it speaks to the idea of properly curating and storing consents And I also can raise, and maybe it speaks a little bit to Carl’s question, that electronic health records can also be a great way to maintain contact with study participants So if we can keep an open mind to working with electronic health records and provisional health care, as a partner to the research and to clients I think that certainly within Africa that could be a very powerful way forward And allow us a more sort of longitudinal follow up of participants So those are just a few ideas, but I’m happy to follow it up further – Thank you I’m gonna back up now a little bit to Tuuli, so this is a mechanism question coming in, even though we’re not, we’ve sort of moved past your section And it sort of addresses the fact that there’s a lot of focus on human genetics and phenotypes, occasional mentions of animal models, but there’s also sort of gaps and holes in the overlap of animal human data rendering, currently rendering translational work less effective Do you have ideas on how ICDA could help to maximize the usable overlap between human and mouse work, and I guess a little but related on that, can you sort of just talk a little bit more about how animal models, this is a incorporated question that came in online last night, could also be used to validate findings – Yeah, we’ve had quite a bit of discussion about what would be the role of animal models in this work, and one of the challenges is being that, this sort of mandate that we’ve had in the mechanisms working group it’s really sort of like have comprehensive pairs of genome-wide large scale efforts, and some of the animal work is just kinda like, it doesn’t have that kind of scalability that we have like in our recommendations, try to avoid this sort of, like, single sort of approaches, but I think it’s clear that animal models do have a very important role in this, and they need to be part of this effort, I think it’s a fair comment that– – Tuuli we seemed to have lost you – Okay can you hear me now? – Yeah – Yeah, sorry Something’s weird about my microphone settings Yeah, so, I think that’s a good comment, I think that it’s also something that may be, animal models come more into question when it comes to the medicines working group? Since the cellular, molecular mechanisms are in some ways something that we will be addressing with human cell line models and such efforts I don’t know if Unnur or someone else wants to jump in when it comes to the medicines part – [Unnur] Yes, can you hear me? – Yes – [Unnur] Yeah, we have discussed that and you can actually set up with, an animal, like a high-throughput screening, or through you know, with CRISPR, or any other methods, so we did discuss that And I think that this will be part of the sort of functional assay to try to understand, you know, the processes that a particular gene, or genes are involved in – So Unnur, while we have you, I wanted to follow up with a question, it relates to one of the questions that came in last night

about recommendation 15 Says we sort of think about you know, there definitely is promise in the area of discovering biomarkers from disease, thinking about using machine learning methods et cetera, but one of the questions is right now there’s not really sort of systematic assessment of already-known studied biomarkers, and so as you think about this discovery, can you also think about ways to think about systematic assessment with biomarker associations, or clearer discussion of what types of information or studies designs are needed really for going to biomarker discovery verses association? And how do you think that one, particularly ICDA, might be able to contribute to such efforts – [Unnur] Yeah, I think that the genomics, and the other omics, are actually working quite well together But you need a very complicated machine learning mechanism to analyze all of these together and I think that this is gonna be actually critical now, with the, for example, with the proteomics platform from pharmalogic machine, 5,000 proteins and plasma is actually, it’s just a new era of, and you can look at the variants in the genome that affect the level of protein when you’re getting closer to the disease, and I think that, actually, you will probably see in the coming years, a lot of biobanks that gathered plasma, are now analyzing the plasma, and also this is gonna clinical trials, I believe So you’ll get a better understanding also from that area I hope I answered– – Thank you – [Unnur] your question. (chuckles) – Does anyone else wanna add on that point? – I can add just quickly also seeing Rory’s comment that we in the recommendation around clinical trials, I think we sort of you know, acknowledge that we’re not clinical trialists, and we have given a shout out to that Gates Foundation, Wellcome Trust, and also African Society, sort of initiative around clinical trials, which Martin Landry who’s here in the EBI, where I’m in as well, was spearheading So I think it’s a good point, but just to build on to what Unnur is saying, I think sort of we are aiming to liaise with others, sort of forums and stakeholders here that are working on figuring out some of the aspects (audio warbles) – Um, did we lose Cecilia? – Think maybe her connection just– – Yeah, we seem to have lost Cecilia – Briefly, yeah, – Just a teensy bit to the end of Cecilia’s point for Rory’s excellent question, I think– – so Eric I’m gonna pause you for a minute, for the people on the phone So Rory’s question, do you wanna just summarize it in a sentence, before you answer it? – So Rory’s question was, “While it’s wonderful that recommendation 16 thinks about how to make clinical trials smaller and more efficient, but maybe that’s not a good idea because it might actually miss the fact that a treatment applies to a much larger population Or by doing a smaller trial one might get a more limited evaluation of safety.” So balancing the idea of, is it really key to be doing the smaller trials? Maybe we should be finding ways to make it easier to do the larger trials And I think Rory raises a really important question that the current version of the recommendations just doesn’t go deeply enough into I think it’s really a complicated question and we need to say more about it There are certainly times when pharmaceutical companies want to do a small trial in order to get an approval in the limited indication, because then they’ll get money for it, which means they could now run trials to expand the indication So it might allow more trails to go on and more explorations to go on On the other hand, the point Rory raises, is absolutely right, it might not be the right thing And I think we need to embrace to positives and potential negatives of this kind of an approach, and my guess is that we’re, you know, it will be a mixed portfolio that we’re gonna need to think about doing both And as currently written, we don’t acknowledge that I think it’s just a little bit too much on the, “oh small genomic trails are such a great thing,” side, and so I’m really glad that he’s brought this up – It’s also I think worth emphasizing that this is really

a series of exploratory discussions about how one might design that What it might look like, and what some of the benefits and potential risks are And I think we probably amplified the benefits a little bit more than risks, and I think Rory is quite rightly calling our attention to the risk piece So this isn’t like we have a clinical trial ready to go that we’re gonna do This is more how should we think about it? What are the potential upsides and downsides, and really how would we do such a thing from a both scientific and regulatory point of view – Yup – Sorry, and I got cut off, but I was gonna say that I think it’s an important question to raise, because a lot of people have talked about, you know, PRS, and “Are they ready to go into clinic?” And I think we tried to address that with, “We should evaluate them in clinical trials, to see if they are, and what the potential risks are.” which is the question I think, we’re really trying to address – Great – Yep – [Unnur] I think we need to just keep our mind open for this opportunity or this avenue, and it doesn’t really apply to all trials, but at least maybe to some – Absolutely, and appropriately evaluate when it’s working and when it’s not gonna work, and what are the optimal settings for it, and what are suboptimal settings? – [Unnur] Totally agree – So I’m gonna change focus a little bit and sort of tie in one of the questions that came in online that was really sort of asking what are the opportunities to contribute to the white paper recommendations and are there working groups, and who is membership open to? And I’m gonna tie that also to, some of the feedback that came in earlier, about promoting training opportunities, or about training and thinking about the next generation of researchers And one of the things that’s discussed is, promoting training opportunities, but I also wanted to sort of ask the panelists, about what you think ICDA could do to promote early stage investigator involvement in ICDA itself? So two part question there – Well maybe the first one about who’s this open to, to have input into the white paper, the answer is everybody right now I think the purpose of releasing a version 0.9 was to solicit input from the entire community, anybody can be a member of ICDA, just by signing up And anybody can provide input into this and so, I think this has been an experiment, and I think we’re gonna try to keep this going Even when, in the coming weeks, we reach version 1.0 1.0 isn’t the end of the numbering system. (chuckles) I think there should be continuing opportunities for people to be raising questions to the working groups, to ICDA, and on a regular basis, we should be updating this We could think, and it’d be great, if people would write with suggestions of what are the best ways to encourage people to do it? You know, bringing together additional small groups of people to do it, especially with regard to trainees Figuring out how to get people in their early stage, career scientists, to feel empowered to make these recommendations I think what’s come from the questions we’ve gotten already, are that there’s a lot of really good ideas, and that we’re gonna want, the point of ICDA is to bring together the wisdom of a community So anybody who has ideas on how we can make that clearer to everybody, that this is open to all, and we’re trying to distill all this input, we’re very open to figuring out how to do that – And just to add to that, a sort of group of us have already started to discuss what we can do in terms of mentorship schemes, joint training programs, you know if we think about being a global resource, what’s most helpful in different parts of the world? Because what’s helpful for a trainee in the UK is, most likely very different from somebody in India, South Africa, or Brazil So how do we make sure that we sort of capture that? So we don’t do like a design of what helps somebody in, you know, the UK or the US, but more globally So at every planning we do, we try to sort of look at a range of diversities, and of stakeholders, and gender, age, you know, global representation, and so forth We can’t always capture it perfectly, but it is at the core and forefront of our minds and hearts,

from a planning basis Just wanna emphasize that – Great, thanks all So I do see there’s still some questions and comments that came in from Carl, and Sasha, and Loic These seem to be more, feedback than direct questions, and so we’ll take those into account, along with all the other feedback that’s been coming in today, as the group works Oh, and a late breaking thing from Rory, which I haven’t had a chance to read yet, but we will read and pay attention to But in the interest of time, I’m gonna send it now back to Eric, and Cecilia to sort of close us out with some next steps and conclusions – So, do you wanna go first Eric? Or should I– – I’ll go quickly, and then I think you can close us out I mostly wanted to observe that this experiment, we just ran today, with more than 130 people joining in, just on this one town hall, we have an attendance, sort of in the neighborhood of what the auditorium in Copenhagen was gonna be able to hold Just a little bit more there, so I think this is already an example that there are ways we haven’t thought of for how to on an ongoing basis, make sure that the whole community is engaged We’re gonna go back and take the list of questions that people have laid out, the discussion on this call, and use this to rework 0.9 and the white paper into a 1.0, which I hope we’ll get, I’m sure we’ll get this month, but already I’m so convinced that getting the community feedback, and this particular mechanism of a Zoom town hall webinar, which I never did before, is a great thing, and it points to how ICDA can do a better job than we thought about making sure it’s a global community, you know, distilling a path forward I’ll turn back to Cecilia – Yeah, I wanna echo that I’m a pro webinar person now, then. (chuckles) So I wanna thank everyone, I want to start to thank all the working groups for all their immense amount of work And also the community for all the input that you have given over, you know we have tweeted out the recommendations, people have sent in recommendations, to the ICDA office, or we have tried to sort of capture the discussion We have really sort of tried to massage these recommendations, with as much feedback from as many of you as possible And I think it’s really sort of been an exciting process over the last couple of months to get to where we are now So I’m excited to move towards version 1.0, and it is wonderful to see that so many people are engaging, and the questions about how, somebody asked how we choose the disease projects, and I think Eric and I tried to address that, saying you should champion them. (chuckles) So if you have a disease, you wanna champion, start to think about what a flagship project could look like and you know, we’re gonna come back with more discussions, about, when it’s appropriate, how to sort of move towards implementations that will obviously be the next step, but for now, focusing on the recommendation, it’s been super valuable to get all your input And also thank you to Carolyn for hosting the discussion so well today So I think we should close out here, and for those of you who want to, there is a second round of town hall in the afternoon, if you’ve now increased your appetite, and it will probably run even smoother, (chuckles) now that we know what to do, we’re gonna be here So we’re looking forward to discuss with as many as possible then as well So thank you everyone, also for calling in and giving us your time, and your thoughts – Thank you – Thank you – Bye – So we shall adjourn for now, and we’re back in, oh I don’t know, – Three hours – three hours for round two – Yeah, yep – Thank you everybody – Thank you. Over and out – Bye