 Well, what a perfect complement of a Q&A session to follow an excellent synoptic presentation and that brings us to something that's been mentioned multiple times and that is as seen through the lens of eMERGE, this major national initiative which looks like eMERGE raised to the next level and no better presenter than Steph DeVaney who is the heart and soul of all of us and its predecessor label, the Presidential Precision Medicine Initiative and we're very pleased to have her come and expand our context for the importance of the methods of eMERGE and the opportunities to accelerate this national program. Stephanie. Thanks again and nice to see you and so many familiar faces, I thought for sure Rex was going to scoop me when he started answering questions about all of us so grateful to solve stuff to talk about. So I have only 15 minutes, I'm going to blow through a large amount of content but hopefully more of this conversation can happen throughout the day. We do have, I will double down on Rex's comments about the infrastructure that's been built and the lessons that have been learned through eMERGE certainly did help set the path for all of us. So we're really grateful and there's a ton of overlap here in the room in both awardees, investigators, folks at NIH that we work with closely, members of our advisory panel, Maryland and even folks who helped us really build the blueprint for this large research endeavor that we're launching just now. So just as a reminder I'm not going to do too much overview of all of us because I think there's some familiarity in the room but our intention is to build a longitudinal resource with all different types of data on individuals that hopefully last for, hopefully last for many decades and we really are interested in making sure that we reach a diversity of people. So one of our major focuses is on reaching communities that have been underrepresented in biomedical research and maintaining them as participants over the long term. So engagement and retention really important to us and then also diversity of researchers. So building the data set that can be used and utilized by many different types of researchers, not a small challenge. So some of the areas I think where there are opportunities for convergence between the two programs and then some places I think where we'll learn a lot from a merge, you'll learn a lot from us and we can share and swap. I'm going to walk through each of these. So first of all just sort of the basic, we are building a very large data set. You guys have a very large data set. We will have EHR data and genomic data and ours in addition to other types. So this is a real opportunity to expand the data set for understanding many things, just a few of which are listed here, pharmacogenomic genotypes and drug response, actionable genes and variants, genomic medicine implementation studies and of course something that I care deeply about LC and policy research. I think there's a real opportunity here to use all of us and take some of the stuff that you guys have already learned in a merge and advance some of these really important ethical, legal, social issues research. So just a little bit about, while we're talking about data types, just a little bit about all of us, our core baseline of data that we're pulling together right now and the participants that have already joined and over the near term is asking everyone to go through a number of surveys. We have three surveys at the outset and we'll be deploying four more as over time so that participants are slowly answering more surveys digitally. We will be asking everyone to share access to their electronic health records. They'll be undergoing physical evaluation and we're collecting blood and urine samples to run genomics but as well as other assays. Ultimately we plan to incorporate mobile and wearable technologies and environmental data in addition to a number of other data types. We like to show this visual at the bottom to make the point clear that right now we're building version one of the platform but we really do intend to add data types over time as technologies evolve and as we understand with the science of the community needs or what types of research questions could be answered on a program and a sample set of this size and scale over time. So individuals can enroll either through a health care provider organization or as direct volunteers from any internet source. Here's a map of our health care provider organizations. A lot of overlap with the merge as you can see. I'm happy to answer any questions about this at any point. And of course right now what we're thinking about is how we're going to start to build out our genomic data set. We have an expert panel that has just finished their work and we'll be hearing their report over the next couple of days. Eric Green was very helpful in that process helping us to figure out what are the different options we could undertake as we think about ultimately doing whole genome sequencing on a million people but where do we start. So just a quick thing on our data access because this came up when Rex was talking and moving to a cloud based platform. So all of us research program is going to be our data set will be in the cloud from the start. We have we are developing we just just finalized our data access policy our framework for how researchers will access the data. We it's a researcher based access no data removal tiered access approval for developing a data passport model which I'll talk about. And we really are interested in broad access. So how can we make this platform usable by many different types of researchers. So essentially what happens is we will have all of the data in one place in a curated data repository researchers will ask for access from a board that are a committee that we have in internally to the consortium. And then once they get access as a researcher they can then launch a bunch of different studies. We'll be doing studies specific review. So a researcher can come in and launch three different workspaces or however many workspaces they want. They'll have to get really clear about what they're trying to do with that data so that we can post it publicly. We have to do that according to the Cures Act but also one of the things that we're really relying on to make sure that researchers abide by the code of conduct is transparency. And so the extent to which the public can see what researchers are doing with the data we think is is really important. There's just a real quick visual of our data tiers. We will have a public data set that will be aggregated data that will be open to anyone anywhere anytime no log in required this is a little bit like how the census does it. Then we'll have registered data set which is which is a little bit higher risk of identifying participants and will require a data use agreement identity verification ethics training and approval again researcher based not study based or question based and then control data is is going to include genomic data and some other higher risk data types again researcher based so once you have access you can sort of launch as many studies as you'd like to. So the next thing I want to talk about is innovative methods for integration of different types of health data for research. So as we move forward we're learning a tremendous amount from what you guys have already done with electronic health records. We also though need to collect EHR data on participants who come into the program from their smartphone or from their public library from a website and we don't necessarily know who their provider is and we don't have a direct relationship with their provider. And so we're going to have to get on the EHR front as well as other different other data types we're going to have to get pretty creative and build technologies in order to incorporate those data types. I think that this could ultimately be a place of interest between the two programs We have I'm going to talk a little bit about sync for science as well as data aggregators and different things that we're piloting to try and get EHR data in on our direct volunteer participants. But also we're interested in claims data. We have just been funded by the PCOR trust fund and a collaboration between NIH and CMS to deploy sync for science like technology on for claims data so that people who have Medicare Medicare beneficiary claims data can agree to donate that data to the all of us research program or really any research program that that will be available for the research community broadly. We're looking into getting data from pharmacy managers directly so that we can get a sense of what prescriptions are filled on participants genetic testing reports with the Office of the National Coordinator has started a project called sync for genes which will begin to help with genomic testing information and and there's there's many other different types that could be added to this list. We're starting to think about all different sources of data we'd like to bring in to the program. I think one of the big questions for us will be how are these data coming in? Are we are we relying on our primary consent and then and then pulling the data from the back end from these organizations or are we going to be entering more of our participant mediated situation where the patient says I want to share my data from shareships or I want to share my data from Medicare. And that's a really important we really like that model because it creates a it creates the situation where the participant gets to control their data and I think really puts pressure on some of these organizations to free up data that is that is the right of the person to access and share for research. So just real quick on sync for science and I'll take a moment here to give Dan this is a shout out for for I think pointing this term perhaps and and this is really important. We got really excited about this project because this is truly participant mediated EHR sharing and so both relies on a HIPAA right of access and also technology to get the right data and the right form of formatting to our system. So the way that's for science works is that our any of our participants who joined directly not through a health care provider organization that we're funding but directly from their couch can go into their their patient portal and say yes I want to donate my go through all the agreements and then say yes I want to donate my data to all this research program and that data will then come into the data and research center in the form and format that we would want it to come in and so that it can be added to our data set. We are partnering with four major vendors to to build the technology epic a clinical work center and all scripts have all contributed greatly to this and they will be deploying the technology at 14 pilot provider sites starting in the next month or two so we'll get a real test of how well this is working with the patient controlling the data flow. The another challenge we have that I'm sure Emerge has had to I'd love to hear more about this that the day and other large cohorts is engagement and retention. So we are because we're trying to reach so many people we're really thinking about both getting folks in the door but then how do we retain them and this might be it's a different scenario when we have folks coming in through a relationship with a provider and there's a real strong relationship between that provider and their patient base and it's very different when we have digital digital participants and we understand that falloff could be quite traumatic. So trying to think about you know how to engage people digitally I listed some some things here that we're doing we are we're really interested in participant feedback we have a lot of surveys usability testing that we're deploying all the time and we're trying to get in the frame of mind where we can get participant feedback and make changes to the program pretty rapidly. But we also are working with federally qualified health centers we're going to learn a lot about how to work with their populations. We have a new community engagement partners that are helping us to be sort of trusted intermediaries between a certain population in our program and hoping to build engagement and trust that way. But one of the things I wanted to talk about here with this group because I think it might be of interest is also deploying some digital engagement tools the different ways that we can use our digital platform to keep people interested in the program and sharing data with us as well. Some of the things that we've been thinking about and our team here at Vibrant I think PJ is here somewhere in the room has been helping us along with the Scripps team to think a lot about what different types of things we could deploy through our app that would both give the data the scientific community data and also keep people engaged in the program and give them something back for participating. So here's just a couple examples we'll continue to refine this over time interested in any thoughts from folks in the room here. And then and then finally speaking of returning things back and giving back to our program we have made a promise from the beginning of the of the build of the precision medicine initiative which is now still a thriving initiative but this one piece of it which is now called all of us about returning information and promising to our participants that we will both return information and even specific results raw data to participants. So this is a big task as you all know you've been doing this for a decade. We we imagine there will be areas where this will be pretty simple and really just requires building up the technologies you can see over here on the right. We will be ultimately giving people the survey data back and showing how they compare within the broader demographic and just a nice interface. We'll be giving individual access to their EHR data so they can see what actually we have on them what came from their EHR and what data we have claims data any other data that comes in that they share with us individual research results which I'll talk about in a second of course ongoing study updates aggregated results scientific findings all of the things that come out of the study will want to share back with our participants and then opportunities for them to be contacted for other research opportunities especially as we learn more over them on them over time and if you consider what what other studies they might be interested in so genetic results we had a workshop in March which many of you stuff I think you're losing your mic am I you maybe oh it's probably too far down have people who nailed to hear me yeah I wish I saw it was just the last minute or two thanks Sharon thanks Mike I had another slide in this so return of results you know for us we have so we have just begun thinking about how we're going to return results to participants for us we you know this is going to be quite the challenge and you guys have done a lot of work here I think we at this March and at this workshop in March we agreed that we should start with the ACMG 59 pharmacogenomics that it sounds like Emerge has done a lot of work here and we certainly will benefit from the clinical decision support and some of the patient resources that you have already developed we would love to you know start this journey with you and learn and share and share lessons learned across both of the consortia because I think this will be one of our greatest challenges and could be quite resource-heavy and then finally electronic phenotyping and Rex talked a ton about this I mean we have you know we have none of this we really are going to be able to take advantage of the well-validated and public phenotypes that Emerge has developed right off the get go and that's a huge running start for us and for the researchers who access the data and then integration of genomic findings into EHR for clinical research and care we are not anywhere near this point but really look forward to learning from you all on how to sort of complete the cycle from research back into care and then finally this is my last point I just wanted to expand upon my point earlier about how we intend to add data types over time we are really interested we set up the core data set based on the ACB working group report that helped with sort of the blueprint for our study and also what we think people might want to have on hand but we want to work with the scientific community to understand across all of the different domains what are the types of data that would have the most impact on as data set of the size and scale that would be common across many different research questions so that we can maximize the impact of the different data types we add to this large piece participant base over time and so we'll be holding a workshop in March to start to talk through some of those use cases and understand what's most beneficial and hope to include researchers and participants in that as well this just shows how we're breaking up the workshop to talk about all of the different all of the different scientific topics that we think this program is right to help understand and so then just briefly where we are we've enrolled I'm sure this number has gone up Josh could probably give us the latest numbers as of today but at least 4,600 participants have gone through the full protocol at about 60 sites we're going to continue to ramp up between now and winter we're in beta phase you can only join with a code that's invite only at this point we're going to be ramping up to over a hundred sites that will be enrolling participants and hopefully around 10 to 15,000 participants with the guests so that we can launch this spring and open up the doors believe that's it thank you Stephanie question microphone oh yeah so good question his question was why will we have any restrictions on data access when we open the doors so we we the data resource actually will not be available to researchers when we open the doors it's really just for just for participants to join we expect to have the researcher portal open sometime later in the year well we have did okay fair enough you want the substance so we when we do open the doors I imagine we'll want to do some sort of beta testing phase but once we have opened the doors to researchers broadly the access process will be the same for pretty much anyone we'll ask them to go through a code of conduct to validate who they are and then and then go through approval and that should really be the same process for everyone we are running into a little trouble because we're hoping to enter to integrate citizen scientists and that's trickier because at the controlled data level where we have some more of the high-risk data types we want to have an institutional backing and it's it's hard to uh that's that's a challenge we're working on is there a way that we can get institutional organizations to validate citizen scientists so that they can get access to some of the deeper data but we haven't figured that piece out yet but so not no no real no major restrictions unless josh join sorry I'm fine okay well I think she's first thank you um two questions one was I heard you in talking about the access is going to be researcher based as opposed to project base but also emphasize the transparency of the description so I like the researcher based because it can be a pain in the butt to go back and sort of do everything but at the same time there's the transparency so how are you gonna combine those things that if a reader comes up with another project that they have to make sure to report it or how does that work yeah and then a separate question is the sync for science is awesome and if it works yeah um and in theory if people can sync to your model then someone with cerner data could sync out for your model and then sync back to epic and is anyone looking at that as sort of a solution to interoperability I don't know if you um yeah I'm probably not the right person to answer that question although I think I I love how you're thinking um but on the first question um which was data uh transparency and access so we uh yeah so it's all uh researcher based when a researcher starts to opens up a new workstation just where sort of where they'll pull the data that they want to use to answer a specific question we'll ask them to get pretty clear about what they're trying to do um and we both we need to post that publicly uh and we want to and then we're relying on the panopticum which is a new word I've used and love using now I just learned this um to uh to help look across these different data uses and uh flag stuff if they think some researcher is acting outside of the code of conduct so because we're not doing a study by study review we're really losing that opportunity to look at some of the research questions and we don't want uh we want to be sure that there's uh there aren't a whole bunch of studies going on that either violate our code of conduct or which will also be public or uh you know get into some sort of stigmatizing uh area that could cause problems for some of our communities that we're hoping to be able to trust with so uh at that point if somebody flags something we will have our board uh be able to review those studies so which is why we're leaning so deeply on transparency sorry oh sorry um two quick things I think it's certainly right did you want to respond to that that was okay okay um each workspace can be attached to a bunch of people and so the descriptions in a workspace a computational you know place where data and analysis will happen um uh you know it can have many people attached to it and that has labels so anyone that works on a common project will be in that same place with the same descriptions of what the project is um and that's sort of the mediation and any group of projects uh any individual can be on a whole bunch of different projects with a whole bunch of different clusters of people so it's all driven by the workspace connection that's clear and yes we are thinking about inter EHR and intra sites and all that kind of stuff collaboration with science um it's it's based on smart on fire and sort of the growing fire descriptions and so so you know you could imagine that and it was always envisioned because i'm sure dan would would say as well as you know a 350 million plus you know experiment not just a 1 million you know or 10 million or whatever you know all of us in the team in the year is there anyone else yeah you're okay so um you know another thought the you know the literature would suggest the um decision support directed to the patient can be very effective actually effective in activating the patient to subsequently activate their their doctor so i wonder if the sync for science resource might allow a patient citizen patient if you will to suggest their data set or their assets be linked up to decision support services from both public and private sources blackford that wouldn't have anything to do with the PCORI uh patient facing cds the thing that you lead would an interesting idea thank you for that we we haven't thought that far but i appreciate that my question was sort of a follow-on to that uh in in the return of results activities i didn't hear anything about returning the results to physicians how our physicians out of this loop or we hope that they're not and uh you know these are some policies that we're going to be developing with the healthcare organizations that we're so closely linked to that are the help those in this program with us but we haven't fully defined that whole process so this is something that we're working on you know we certainly want to have all of that defined by the time we start running genomics at least because that's really going to be the first or individual level results that will be returning to people i i think i'm out of time dan's gonna maybe grab me at a break i'm at zero minute yeah so if you could ask your questions if if stefanie's going to be around for a little while you could ask questions directly