He would be going a little low, and it's been a long day. You've been talked at. So we purposely had the next panel consist of two of the most introverted human beings I know. No, no, I got that wrong. Two of the most extroverted human beings that I know. So there's absolutely no way you will have an energy lull for either of the next two speakers. And this is a panel on creating medical breakthroughs. And the first speaker is the clinical director for NHGRI, Bill Gaul. And he's going to talk about success through traditional pathways, creating a new drug for now pending FDA approval on the specifics you'll see on this first slide. OK, but this is all business, so I'll try to stay all business. OK, so one of the things that the NIH does well is to create experts in rare diseases. And the NHGRI is a part of that, too. And this is a cystinosis, and this is a recessive disorder with the liver. And it's due to the genetic transport of the cystine out of lysosomes, which are intracellular organelles. As a consequence, the cystine, which has the low solubility, crystallizes and destroys the cells. So it is legitimately a lysosomal storage disease, but not of the classic type. We have an enzyme deficiency. In this case, it's a transport deficiency. So you can see some of the crystals there. Now, patients are normal at birth, which is really characteristic of many lysosomal storage diseases. Then they get kidney disease. They grow poorly. They have photophobia because there are crystals in the corneas of the patients. And that's going to be pertinent a little bit later. Need a renal transplant around age 10 by the natural history. And then have all sorts of other complications because, although the kidney transplant takes care of their renal disease, it does nothing for the other organs that are involved in this accumulation of cystine. And so they have muscle disease, pancreatic disease, retinal disease, et cetera. Well, there is a treatment for this. And it's a sustain, which is given orally. And it's this very simple molecule, which you see here. And it reacts with cystine in a disulfide interchange reaction. And while cystine itself can't leave the lysosome because of the genetic transport defect, the two products of this reaction can leave the lysosome. And therefore, you can deplete cells of cystine to an enormous extent, like 90% or so. Clinically, this retards the renal deterioration. It enhances growth. And it prevents virtually all of the late complications of this disease. So that when we studied 100 patients who were between the ages of 18 and 45, one third of them had died. And the average age was 28 years. And all the complications that they died of were essentially ameliorated by treatment for a certain number of years with oral sustaining. So oral sustaining was approved by the Food and Drug Administration on August 15th, 1994. And efficacy had been shown a few years earlier. But while the sustaining orally helps all those systemic problems, it doesn't help the corneal crystals. And why is that? Because sustaining and the circulation doesn't reach the cornea because the cornea has so little circulation. So these are the crystals that you can see in the cornea of individuals with cystinosis essentially untreated. And the patients have squinting of their eyes. And if this is constant and long enough, it's called blepharospasm.  Well, if you deliver the sustaining by eyedrops, in other words, topically, right to the cornea, you can dissolve those crystals. And this is a demonstration of that in a three-year-old treated for about a year or so. So before and after. And in a 20-year-old, the haziness that's attended to those crystals is also removed. And the cornea is clarified by those crystals. So what we did was to establish a library of the severity, in other words, put a number on how many crystals were there by creating this library and then comparing every individual that we had to this library to put a number on that person's density of corneal cystine crystals. And when we did that, we determined the natural history. And this is really pertinent because the Food and Drug Administration repeatedly asks for natural history data when they're asking, when you're trying to tell them that an intervention with metal words, they will say, how do you know that this wouldn't have happened without your treatment? Well, natural history data will tell you that. Here is the natural history of cystine crystal accumulation in the corneas of 171 individuals where each dot represents one individual prior to any treatment with topical sustaining. And you can see that over the course of the first few years, there's a huge accumulation of those crystals. This was because we were able to use the library we established. Well, if you treat with sustaining eyedrops and these are given, we recommend every hour while awake and we ask that they be given about 10 times a day or so. After eight months, you can see that there's loss of some crystals in the upper left, I guess. And after 25 months in the lower left, you can see that you can clear almost all the crystals after 12 months in the upper right, et cetera, et cetera. So these are before and afters for the crystals. Here's someone treated for 16 months in the upper left. And the crystals are gone. They're basically before and after. And it's true that you can get rid of these crystals regardless of how old the patients are. So dissolving crystals from the human body, pretty remarkable thing. We didn't know it would happen. And here are some other examples, even out as much as 20 years and longer for these individuals. Okay, so in fact, if you were to plot this and give the score before and after, you can see sort of a raindrop pattern superimposed on the natural history curve, which is that sort of asymptotic curve. And this is basically how you can get rid of the crystals. Okay, so the timeline for this was we demonstrated these data in the National Eye Institute and the Child Health Institute, which is where I worked before. We showed that in 1986 and published it in the New England Journal, continued to provide these eyedrops to patients under a protocol despite the fact that we actually knew that it was working. And so we had to have the IRB sort of work with us on this. In 1995, Sigma Tau Pharmaceuticals picked this up as a sponsor. And over the last 15 years, it's provided drug to the NIH Clinical Center Pharmacy so that we could give human use, it's just aiming to our patients for the eyedrops. They've also been working on preparing the clinical data to the FDA and submitted it on March 3rd of this year. They put in a huge investment in this. In 2000, we published the Natural History Data, which is very helpful for the FDA to compare the effects of the sustaining. And Sigma Tau has just submitted this and the FDA is fast-tracked. And right now at this moment, the NIH records are being inspected by an FDA inspector who came on Thursday. Yeah. And it's gonna be here for 10 days.  I don't know why anyone would take that job. No FDA members in the audience, I should. So, okay, go ahead. Just report us. Are you with the FDA? Well, are you an inspector? No, I'm not. Then you're okay. Okay, so I'll shake your hand. So, what are the points to be made here? Clinical research is a partnership. We needed the investigators at the NIH who provided their data for free to the company. We needed the patients who provided their eyes for free to us and the pharmaceutical company, which made a huge investment. The FDA cannot approve a drug unless a new drug application is filed. So, do people blame the FDA for not approving this? Yeah. But there's nothing to approve. So, for 24 years, nothing to approve. You can't blame the FDA for that. Knowing the natural history is critically important. And there are some pharmaceutical companies that address this niche market. For the big companies, they want something to earn, let's say at least 200 million a year or something of that sort. For a niche company, it only has to earn a few million a year. So, it's earning some money. So, Sigma Thar Pharmaceuticals is one of those companies in my experience and really that's all I've got to say. Our other introvert is Chris Austin, who wears several hats at NIH, one of which is head of a facility called the NIH Chemical Genomic Center. And well, there's others, but I won't even go through them. And you have a slide? 47 slides, somebody just said? Oh, yeah, this is small. This is the two hour version. Okay, so, Bill just gave you a wonderful example of both the joys and sorrows of doing the kind of translation that we're talking about. And so, what I'm gonna do is give you a sense of if you generalize that to the whole genome, what happens, try to make it as streamlined as possible. So, this is the world that I live in. I was in Pharma, I was at Merck before I came here. And this is what I worried about then, is what I worry about now, which is that this is really in my mind, this is the question for our era in biomedical research. That is, we live in a very paradoxical time, right? Where thanks to Francis and Eric and his buddies, we now have our parts list, otherwise known as the human genome. But during the period of time that the genome was sequenced, actually, this is the rate of new drug approvals from FDA and it's either staying flat or going down. And what you're not seeing is here is that during this period of time, spending in the public sector and the private sector tripled during this time. So we figure spend triples. Productivity goes down by half. That means during the years that it took to sequence the genome, our productivity per capita per dollar went down by five sixths during this time. Now, sometimes I blame this, correlation and causation in Francis, but this is not causative. There are lots of reasons for this and it's a different talk. But to the degree that science informs drug discovery, really the question for our era is how to translate this into this efficiently. And to give you a scale of the problem, it's a massive problem. That is that whether you ask yourself from the point of view of the total number of targets encoded by the human genome or the total number of diseases that affect the human family and ask yourself what percentage of targets or diseases are worked on by the entire drug development enterprise, public and private, the answer is about 5% in each case. So about 95% of targets and 95% of diseases are not worked on by anybody. And if you've ever had a rare disease or orphan disease, you know what I'm talking about here. Okay, so before I tell you what we're doing about this, I'm gonna throw some acronyms at you. So the NCGC stands for the NIH Chemical Genomic Center, that's the center that I run. The MLI means Molecular Libraries Roadmap Initiative. Trend means Therapeutic for Rare and Neglected Diseases Program. RAID is something called the Rapid Access to Intervention Development Program and CAN means the Cures Acceleration Network, something that just passed. Okay, so how do you make a drug in six easy steps? This is it. Going from here to here, takes currently about a billion and a half dollars, 15, 20 years, but you can really divide it into six steps here. And so what I'm gonna tell you is, one of the programs at NIH that we put in place to do this, and then I'm gonna tell you a little bit more about them and then come back to this at the end.  They're identifying massive numbers of targets in the cancer genome atlas. And this is really the role of NIH Basic Research, including what we're here to talk about. This is a little slide you may not see it, but that's Ari Petrinos and Francis and Greg Venter at the White House 10 years ago, which is what we're here to commemorate. But that's just the beginning. What you then gotta do is you gotta create a testing system for activity of that gene. Then you gotta test hundreds of thousands of chemicals on that target. And over the last five or six years, an initiative to do this at NIH, work that was traditionally really only done at this scale in pharma and biotech has been put in place at NIH through the Micah Libraries Roadmap Program and the NCGC that I run as part of that program. And then there's this new program called Trend, which works at this part here. So then we're making medicinal chemistry modifications of what came out of the screen here. There's a picture of the robot in our place. And then you make enough modifications that you can find a compound that's safe and efficacious for the disease model in an animal. And then you make some other modifications to make a compound that you hope is safe and efficacious in a human. And then you go to FDA at that point. Okay, so what is the center that I run? And I just wanna give you this as an example to sort of reduce it to practice and make this real as it were. This is a center up in Rockville. It's about 80 people now. About 90% of the folks came from pharma and biotech because this is where the expertise lives. It's a completely collaborative center, that is to say, and you heard Bill say this, this translation, translational drug development is a team sport. It cannot be done by any individual no matter how good their individual capacity is, their individual discipline. This requires biologists and chemists and informatics people and robotics people and pharmacologists and all kinds of things. You gotta work in a team. It also requires people who know how to do drug discovery but also people who know diseases or targets. And so our place works with about 130 different collaborators all over the world who have disease expertise or target expertise and working with their expertise and ours. That's really how this really works. And we work on those big blobs in the Venn diagram or the pie chart of neglected targets and diseases. So we're taking two approaches. If you take this linear diagram here and you change it to a Chevron diagram for drug development as you've probably seen before starting with a target ending up at FDA, the conventional approach and we're taking this is to screen about 400,000 compounds and then develop increasingly efficacious compounds through medicinal chemistry. It takes 10 years, 20 years. The other approach which we're taking which we hope will be faster is this idea of repurpose all the known drugs. So what the idea here is that you take all the drugs that have been approved by FDA or other regulatory agencies worldwide, put them into a screen which frequently can be primary cells directly from patients. And then if you're lucky enough to find something which works in this screen then you can repurpose the compound and back into clinical trials in as little as one to two years because the drug has already been approved and it can be used for a different indication. Okay, so just a couple of examples. This is a repurposing project for a disease called even pig type C. It's a lysosomal storage disease. You heard Bill use that term. It's an enzyme defect. It's a genetic disorder. The gene was identified over 10 years ago but we still don't really know what it does. We know it's a transporter out of, out of cholesterol transporter out of lysosomes but beyond that we really don't know. These are actually two girls who were affected. They're identical twins who were affected by the disorder and actually they're cells. We don't know which cells they are but their cells are actually at our place and we're actually testing them among about 30 other patient samples. And so this is a rare disorder. It's one in 150,000. It's a horrible disorder though. These girls untreated will be dead probably by about age 10 of a combination of Alzheimer's disease and Huntington's disease. And so what we're doing in this project is we're working with both extramural investigators at Wash U and Einstein and intramural investigators at NICHD and at the Genome Institute. Bill Paven actually was one of the people who cloned the gene back 10 years ago. And the purpose here was to find a current drug which can be used to repurpose foreign PC. And we identified a drug doing this and don't worry about what the details are but these are cells from kids with this disorder. They were biopsied at the clinical center by Danny Porter, brought up to our place and then stained for cholesterol in their lysosomes and you can see all this red stuff is cholesterol in lysosomes.  And so this drug is now, we're actually designing a clinical protocol right now. Okay, this is a neglected disease. Neglected disease known as their tropical parasitic diseases. This is a classic one. It's just a somiasis, affects about 250 million people worldwide. And this is a collaboration with an extramural investigator at Rush in Chicago who identified a new gene in the genome of schistosoma which he thought would be a good drug target. This is a slightly enlarged view of this worm that causes this. This boy has schistosomiasis. He looks like he's about nine months pregnant here but this is all liver and spleen full of worms. And he will live like that 20, 30 years. It's a good parasite, doesn't kill its host. And so we worked with David to screen our large compound collection, perform the chemistry that I talked about and then identified a potential drug that does this and don't worry about the details. But what you're looking at here, this is a paper that we published a couple of years ago where this is a normal liver of a mouse and this is a liver of a mouse infested with schistosomiasis. I don't know if you can see this in the back but all these white things are worms and it's about six times normal size. But this drug, if you treat the mice with this, who are infested with schistosomiasis, their livers shrink down to nothing to normal size. And if you take the worms out of the liver and you put them in a dish, they float around like nice, healthy, disgusting worms here. And if you throw the drug on top, it kills the worms and they shrivel up. Okay, so what I've told you is that there is now a pipeline in place at the scale that pharmaceutical, the best pharmaceutical companies have to go from drugs, from genes to a drug. Now this is, I don't want to make this sound simpler than it is, this is still exceedingly complex and a lot of what we're doing, actually a large amount of both the NCGC and TREND are devoted to improving the paradigm and novel technologies to make this work better. And so this is actually what it looks like. This is the simple diagram. This is what it actually looks like. So this is the Chevron diagram here at the top and this new organization called the Center for Translational Therapeutics is a center that we've just started. It's officially within genome, but it's also within the office of director that puts this integrated pipeline for trans-NIH drug development all together and it has everything from RNAI screening down here to repurposing and technology development in the middle. And what is gonna be superimposed on this in ways that we're still determining is the Cures Acceleration Network. That is a program that you're probably aware was authorized in the healthcare bill, but there was no money appropriated to it. But it will be superimposed on this whole process in some way. And the point I wanna make here is that there are now in place pieces of this pipeline to do all the steps that we talked about, but also including a very tight collaboration with the FDA to try to get over some of the issues that Bill talked about. Some of the issues that are simply miscommunication or lack of communication issues. And also a large component of paradigm and technology development. It's very clear that this problem, like the genome project itself, cannot be solved by brute force with the technologies we have now. Right, there are 7,000 diseases that affect the human family. If we work on 10 diseases at a time, and I do this until I retire, then we're still gonna only cover about 100 diseases. And even if we had 10 centers would do that, we're still only gonna cover 1,000 diseases. And so this is very much like what was said at the beginning of the genome project that, well, gosh, don't start the genome project because we don't have the technology to sequence the genome. Happily for all of us sitting here, that was not the decision. The decision that was made was to say, no, this is very important for us to do. So we're gonna start it with the technologies that we have, we're gonna put 25, 30% of the budget in the technology development to improve the mapping and sequencing that needs to happen. And that demand, necessity was the mother of invention. And that demand pushed the technology development to way beyond I think what any of us anticipated in terms of DNA sequencing. And so we're doing the same thing here. And so that is it. Thank you. These two speakers or participants are open to questions. Reader Rubin, USA Today. Doctor, I was really struck by how long it's taken to get to this point with the eye drops. And was that because the FDA was asking for 15 years of natural history? And if so, especially talking about eye drops, it just seems a little like overkill. No, the FDA wasn't asking for that. They did want the natural history information, but that was present in 2000. This was, first the company has to pick it up and then the company has to take all the NIH records and put it into decent shape, you know, frankly. And so that took a lot of time. But it's also true that the company wanted to make sure it looked good to the FDA. So they actually, in my opinion, and other people's opinion, wouldn't have had to do such a good job. But their reputation was on the line.  And that's why they were reluctant to submit this in the year 2001, 2003, 2005, 2008, et cetera. Tina? I've, in fact, I can tell you that in 1994, the FDA, on two occasions, called me up asking me when we were gonna submit it. Of course, you can't really publish that. The FDA would be pretty pissed if they heard I said that. Go ahead. I'm Tina Say with Science News Magazine. I was just wondering how the basic scientists that NIH has always traditionally funded view these efforts to get into sort of drug development which has traditionally been the purview of pharmaceutical companies. Are they upset that funding is being directed that way? It's a really, it's a good question. I think you hear a spectrum. I think there has been, let me put it this way, when we started the earlier phase of the pipeline back in Moico Libraries back in 2003, there was actually a lot more objection to this in terms of whether it's appropriate for NIH, whether it's outside of scope or not. I have not heard that about trend, interestingly. And I think the reasons perhaps are two. One that I think basic scientists, I trained basic genetics so this is what my training was but so I can understand it. I think the basic scientists have come to realize that looking at therapeutic applications of basic science is not only a very fulfilling thing to do, but also has some great science incorporated in it. I think the feeling was incorrectly that this whole translational pipeline is really not science, quote unquote, that the real science was in the basic side but the other problems were sort of cookbook steps. But as that community has gotten more and more appreciative of how difficult the science is in translational drug development, I think it's taken on a new respect perhaps. I think the other thing that people have come to appreciate is that from a taxpayer in Congress standpoint is very clear that the funders want to see that is Congress and the taxpayers want to see a tangible outcome of at least some of what NIH does and that means diagnostics or treatments for real people on Main Street as it were. And I think the average scientist has begun to see that to maintain the funding of basic research, some amount of NIH investment has to go to that translation as well. I should also amplify what Chris was saying. First of all, so far we're dealing with rather small amounts of money in the grand scheme of NIH funding and there are political realities. When Francis talked a little bit about this and Chris extended a little more this new thing called the Cures Acceleration Network. This is a creation of Senator Spector in particular but has other congressional support. The original vision for it was to set up a separate government agency to do this and people at NIH argued and successfully argued that this would be a mistake, that the decoupling of these activities from the basic science engine in separate government agencies would actually lose some important synergy and so that's why it's sort of under the umbrella of NIH. If this happens the way it's expected to happen or at least the way it was designed to happen it'll be fresh appropriation of money. Remember Francis talked about how the that the Cures Acceleration Network has been authorized but not appropriated. So the hope is that there's new money that will flow into this and that's when the real money will hopefully happen. I mean then the goal, if things go well would be a substantial amount of money. So this wouldn't be necessarily taking away from basic science. It would be augmenting the basic mission of NIH. Other questions for these two? Okay, we will move on. Thank you Bill and Chris. We're doing pretty well. Okay, our next panel is and our last panel is on testing and privacy. What do people want? And the first speaker is Jones Scott and I just heard talk right here. Where's that Scott? You're gonna put another one in first? Okay, we're gonna load up all three. Okay, I'll let you do that. And Jones is gonna talk about what do people want to know about the genetic information and she'll be presenting some preliminary survey results. So in five minutes what do people really wanna know? And actually it'll be some preliminary focus group data primarily. So I was charged with sort of talk about what are people gonna do with the information that is coming out of all of the research that you've been hearing about today. Now I'm a genetic counselor by background and so most of what we know about how people respond to and their interest in obtaining genetic information really comes from years and actually decades now of testing for very specific conditions and very specific settings. So we've been doing newborn screening as mentioned earlier today since forever. Not quite, but a long time. We've been doing prenatal diagnosis since the 70s. We've been doing carrier testing for decades and then a little more recently we've been doing predictive testing but primarily for highly penetrant and relatively rare conditions. And that's where the body really of our scholarship exists and what people want to know and what they do with the information. But we really now are moving into a whole another area with a whole lot of different kinds of genomic information and the question is what is it that people want and how are they gonna respond to it? And let's talk very eloquently about from the clinical perspective who wants this information? What kind of information do they want and are there different types of genomic information that are valued differently by people? So in my mind I could see getting genomic information about your tumor to make treatment decisions is gonna have a very different response from an individual than doing for example, pharmacogenomic testing to predict which particular drug you may want to go on or should go on versus testing for common variant for variants that predict risk for a common complex disease like diabetes or heart disease but there's a relatively rare risk or low risk associated with it. To ancestry testing or for genomic information that you can get about whether or not you have a propensity to be a weight lifter versus a sprinter. So these are all different kinds of genomic information and how people view these kinds of information are obviously gonna be very, very differently. And what's the informational needs that they have in order to decide what kind of testing is appropriate and whether or not they're interested in it and then what's the effect of the setting and how it occurs. So there's a lot we don't know and there are though some groups who are trying to fill in some of that data unless I told you about the project that he's involved in when they're looking at what people want to get and the results of Suzanne's gonna be talking about study that she's been doing and I'm gonna be sharing a little bit of some of our studies. So currently there's still pretty much if you're gonna get genetic testing the maturity is still gonna happen within a healthcare setting today. There's relatively few that are doing broad sort of genome wide kinds of testing but it's still pretty much in a healthcare setting. More and more that however there is the ability to get information in the direct to consumer market and we know very little about who's getting those types of testing and what they're doing within information. Now hopefully later on in the summer I'll have some data to share with you about that with funding from NHGRI and with cooperation from with Decode, Navigenics and 23andMe. We've been surveying direct to consumer customers and have just closed that survey so hopefully we'll have some data soon as to who's getting that kind of testing and what they may be doing with it. The other area or the other way people are accessing this kind of genomic information is through large cohort research and there are a number of them going on around the United States. These are just some of the settings that have initiated prospective large cohort studies where they're inviting large groups of individuals to participate mostly by an opt-in, a couple in an opt-out method to provide samples that are linked to electronic medical records to do wide genome studies. Most of these are not giving results back so the example that Les talked about today is unusual. Coriel project however is looking at giving results back to people and a few of the other groups are sort of investigating it. Now one of the questions that has come up and Terry talked about this earlier this afternoon is whether or not there should be a U.S. based prospective cohort study sort of like the equivalent of the UK Biobank. And a couple of years ago a group got together at NIH came up what would be the ideal design if this were to occur and at that time the design document that was developed looked at enrolling about 500,000 individuals that would be representative of the United States and as many as 30% would be households that would be recruited. You'd collect DNA a lot of medical information and then follow them over for 10 years and all of that would go into a database located at NIH or some respective place working with them and then that database would be available for researchers to access and study whatever particular condition. So it was this in mind that we were funded through NHGRI to get sort of an initial temperature taking about well should you build it and if you build it will they come? And so we did what we call the first public consultation project several years ago to get the sort of initial feeling of should there be a large US cohort study in the United States and would people actually participate? And what we found was that yeah it should be built and yes people said that they would come and as a matter of fact a lot of people said you know I mean this isn't going on already because they saw it as a very valuable resource to help understand disease betters. 84% in a large survey said it should be done and 60% and this was across the majorities of all demographic groups said that they would be willing to participate. The interesting thing that we heard though when we were doing we did a whole series of focus groups and we did this large survey is that people were very interested in getting results of research that was done on their sample and data if they were a participant. And we told everybody that they would get the results of that initial exam that they had but as we described this database people said I wanna know if there's some researcher out there who's studying cardiac disease or diabetes or whatever and I happen to have one of those variants I would wanna be able to get access to that. And 75% said that they would be less likely to participate if they weren't able to get those kinds of results. And we asked them in several different ways you know whether it was a treatable or non-treatable and people were just interested in general. So in order to follow that up in more detail because we were asking a whole ton of things around people's attitudes about having a large US cohort starting everything from do you want people knocking on your door to recruit you to these kinds of things about research results. So in order to explore that more in depth we are currently in the middle of a project of a two year project to go into more detail to understand what is it people think that they would be getting and what's the value of some kinds of this information. So we just completed this fall and winter 10 focus groups eight in person and two online and we did that specifically because we wanted to recruit social networkers to see if they have different attitudes particularly around privacy issues but which was another area that we were looking at. And so that's some of the information that I'm gonna share with you today. So what we did is we walked through people very clear cut examples of the types of information that they could be faced with getting and queried them about that. So we wanted to know did the availability of a treatment make any difference in people's interest? And the examples that we used were colon cancer where if you are identified of being at risk there could be surveillance enhanced surveillance in order to detect or something for which there isn't currently treatment like Alzheimer's. So did the availability of treatment make a difference in what people wanted to know? Did the level of the risk make a difference? So does it make a difference if you went in the example again we used was colon cancer and Alzheimer's did it make a difference if you went from a lifetime risk of 5% for colon cancer to a six or 7% risk or do you only wanna know if the risk is 10, 20, 30, 40, 50%. So does the level of the risk make a difference? Does it make any difference of how medically relevant the particular condition? So we did ask about what would you wanna know if you had a propensity for sprinting or weightlifting or premature graying or some other factor. And then we also spent a great deal of time after going through all these examples of talking about the limitations of some of this genomic information. Information changes over time as we learn more and more research is done. People, researchers may not know exactly the meaning of a particular finding and how much do you really wanna know about your genome. And what we found through all of these focus groups is very similar to what we heard the first time people wanna know and they want information about themselves. And what impacted had the least effect on whether or not they wanted to know was the availability of the treatment or the level of the risk. Now there were some people who didn't wanna know. I don't wanna know, bup, bup, bup. But the majority of the people said they did. And in order to participate they would want that opportunity of being able to get results back. And it didn't matter if the treatment was available and even small amounts of risk would be important to them or to know that they weren't at risk or they are at a lower risk. Now again, that wasn't everybody. Some people didn't see the value or the utility of that kind of information. So we heard things like, you can worry yourself to death about something you can't do anything about. So I don't wanna know. Or 1% change doesn't tell me enough to really do anything. But for the most people, for the majority of the people even that kind of information was very important for them to have. And I thought that the participant that Les had earlier in the earlier panel today to talking about his experience with getting back a result for something he didn't really initially motivate him to come into that was a very telling and would have been very much what we would have heard in many of our focus groups. So the things that we heard from people is that even if there wasn't available treatment there's always something you can do. And people have a great deal of optimism and interest in having information. It could motivate health changes. It gave them a sense of control that at least they knew something about that information. They could follow up on it, participate in research, follow the literature. They could prepare themselves for whatever it was and it was important information. So even though with the lack of an available treatment and even if the risks were low. But there was also this sort of underlying pervasive feeling at the sense that it's information about me. It's me. It's my genome. It's me, me, me. And I wanna know about me. Somebody else out there researcher knows about me. I should know about me too. Where we saw people begin to really sort of question and really where the values about what's important and what isn't is when we started talking about well how certain does the information have to be before. And here's where we begin to see people having different levels of comfort with certainty and uncertainty. So we gave people examples of how either a result may not be necessarily known like it's a gene change in a gene we know causes colon cancer, but this particular change, gene change hasn't been seen before. Or just that information as more research is done, the risks could be higher or lower than what you originally thought. And it's interesting people sort of expect information to change because they read it all the time in the newspaper. Today wine is bad for you, but tomorrow wine is good for you a little bit. And eggs are bad now, but eggs are now good. So people are used to getting or sort of attuned to this changing risk information that they get in the media. And so there's certain level of expectation, but not everybody's comfortable with it. So I don't wanna know if you're not 100%. If you need to do research, it's gonna take you five years, come back five years, tell me. I don't need to know before then. And a lot of people said there needs to be a certain level of certainty around what's given. But again, a lot of people sort of understood the nature of the research endeavor and that information changes and changes over time and people's level of comfort around that is very different. So in general, what we were hearing is very similar things to, I think what Les has experienced, what's been in CLEASAC, and maybe we'll hear about Suzanne's experience with her project, is this very intense interest in getting genomic information back. The one thing I will just say one word about privacy because in the course of our discussion, we asked people about concerns around privacy for participating in these large, donomic databases. And basically, there's sort of this prevailing sense of, privacy just doesn't exist anymore and you can't promise privacy. But the concerns are really about how information could be used against them, either in health or insurance, which we've been hearing for many, many years, but also interesting people make the connection of if you're in a database for identity theft. We did most of these focus groups around the fall, which was right when Gina became finally enacted and we described Gina to people. And unfortunately, it did little to reassure people that they would be protected. So we've done, I think, a pretty good job of sort of heightening that level of concern for people and there wasn't a lot of reassurance that that in fact might protect them. However, that being said, I will take this as a shameless opportunity for self-promotion and say that with some funding with the Pew Charitable Trust, we and the Genetic Alliance, whom Sharon Terry was here earlier and the NICHPEG, which is the National Coalition for Health Professional Education and Genetics, have recently produced educational materials, both for healthcare providers and for the public around what really Gina does and doesn't do. And these are now available interactive sites on both of those, all of those particular websites. And so with that, I will conclude and leave it to the next one. Okay, our next speaker in this panel is Suzanne O'Neill, who will be discussing some results of a new study, which I was just told has been cleared for press release and there are press releases in the back and copies of the paper in the back as well. So I told you this morning that there was gonna be news story and this is it. Now everybody went to the back table and all walked away. That's okay. I didn't say free cookies, I just said a press release. My gosh, you think they were giving away money back there? You can tell who the real reporters, because the other ones are just sitting on the real reporters are all hurting them. Okay, so I'm going to talk about something slightly different than what the title and the program says that I'm going to do. It says I'm going to talk about how test results impact health decisions and that's not exactly what I'm gonna talk about today. No one in this particular part of the study got test results. So the data I'm gonna talk about today come from the Multiplex Initiative, which was a multi-center prospective observational study mounted by the Social Behavioral Research Branch of the Genome Institute and the Henry Ford Health System. And very briefly, this initiative targeted a common diseases, which are located on the top of the slide there. They're all known to have behavior risk factors and they affect both men and women. Began with a baseline survey, which I circled and read up there, with a large and diverse group of healthy, insured individuals who are all part of the Henry Ford Health System, numbering almost about 2,000 participants. And at the end of the interview, they were offered the chance to move forward to a study website to get more information and to receive genetic testing for several common markers, which would confer relatively low risk of disease. And while the initiative will answer any number of different questions, such as who gets tested and then what do those people then do with this information? Does it influence their health behaviors or their interactions with their physician? That's again, not what I'm gonna talk about today. I was a postdoc at the time that the Multiplex Initiative was coming underway. And so what I really wanted to know at that point was what does the general public think about the value of genetic information and what role could play in improving their health? So what are they thinking about prior to any kind of offer of genetic testing? Because these beliefs and preferences will eventually impact what they do with any type of genetic information that we give them. So I used data collected at the very beginning of the study in the baseline survey to get a sense of that. So this was before anyone had had the opportunity to be offered genetic testing or to receive results. And I wanted to know a few key questions. What I really wanted to know was how people saw the balance of genes and behavioral risks like poor diet and smoking as the causes of disease. Did they tend to overvalue the role of genetics in their health? And likewise, I wanted to know how people valued receiving health information based on genetic information or health information that had a more behavioral bent. And was there one type of information that they valued over another? There has been a lot of concern about the public overvaluing genetic information while ignoring lifestyle changes that typically will help us to improve our health. And as different people have talked about today, there are very few data to actually address that concern. So I wanted to take a look at that. And we also wanted to know what role our risk factors play in these outcomes. There's a great deal of literature. I'm a psychologist by training. And there's a lot of literature that shows that when people are given risk information, they do all kinds of things to distance themselves from the information or distort the information to make it less threatening. And so do people do that based on their risk factors? So do people with a large number of behavioral risk factors or people with a family history, do they try to distance themselves from any type of risk information that would be relevant to them? And what we found was that actually, when looking at the group as a whole, so again looking at the almost 2,000 people who took the survey, people had a very balanced view as to whether genes or behavioral risks would cause disease. So in the red was their thinking on a scale from one to seven, the degree to which behavior would contribute to disease. And in blue is what they thought the role of genetics was in causing their disease. And as you can see across all eight diseases, behavior was seen as more contributory than genetics with lung cancer standing out as being seen as very behavioral. And a lot of the other diseases being seen as a much more balanced contribution between behavior and genetics. And we also found that there was a significantly greater interest in learning about how health habits would impact disease as compared to learning about genes. Though there was a strong interest in both types of information with interest in learning about genes being a little bit over 50%, 56% and then interest in learning about health habits was actually up at 67%. So almost two thirds of the sample said I'm very interested in learning about how health habits impact my overall health and what I can do to change that. We did find one somewhat troubling thing. As participants behavior risk factors increased, they tended to attribute the causes of many of the diseases to genetics and to be less interested in health information that emphasize their health habits. So it seems that those with the greatest need for behavior change are at the most risk for devaluing behavior change information. It may also be that those at risk have tried standard behavioral advice in the past with no success or that they're so inundated from all different sources, whether it be from the press, from their family, from their doctor, that they are fatigued from hearing the message and therefore just wanna tune it out and go the other way. So we may be able to use the novel information that new genetic data give us to incorporate into our health communications to reengage these individuals. If that fits with their belief that diseases are caused more by genetics, maybe that will pique their interest and cause them to tune back in to any kind of health information interventions that we have in the future. On the upside though, we also found that family history seems to be an effective motivator of health, could be an effective motivator of health behavior change or interest in health information. Those with a family history of disease were interested in both different types of sources of health information. So people with a family history were more interested in learning about their genes than people who didn't have a family history of different conditions and those people were also interested in health information that emphasized health habits. So it seems to be a motivator to pursue information to try to improve their health. And so I tried to keep this pretty brief given that particularly we're toward the end of the day but just to make a few final comments, we're fortunate to have these data because they are population based the way the sampling was done. It was a very large and diverse sample of people we don't usually get into our studies. Most of these types of studies that look at how people think about disease are done within more select groups of individuals who either are already impacted by disease or have a strong family history of a certain disease. And this let us see how the population as a whole thinks about genes and behavior and their health. Also people who actually move forward for testing might think a little bit differently. They may have a certain way of thinking about it and that's part of what moves them forward to get testing leaving behind the rest of the population that we don't usually get a good sense of. And so the key now is to use the information from this study and other similar studies that are going on like what Joe was just talking about to start to spur new behavioral research into how to use all of the genetic advances that we've talked about today to improve our behavioral interventions and to encourage people to change their behavior and to be sure that we're communicating properly. Thanks. And our last speaker in this panel is Laura Rodriguez who's acting director of NHGRI's office of policy communication education. She's gonna talk about what are the responsibilities to the public in genomics research. Okay, so thank you all for hanging in with me. I know I just wanted to tee it up very nicely for you. So I'm gonna try to go through this a little bit today and honestly, I struggled a bit with trying to think about how to pull this together because I think the responsibilities here vary a good deal and genomics is an incredibly broad field but also when we're talking about genomics in the public it's an incredibly broad area to think about as we've heard about today because there are so many different ways in which genomics can be applied to the public and the receptivity of the public for the information also varies as we go. So if we're just trying to focus here for this panel, sorry, the first two questions that were posed were thinking about what do the people want to know and then also how will the people use what they know about their genomic information and first of all I think that people here is incredibly nondescript. I think we've heard today throughout the day about people as the general public, as groups, we've heard about them as patients who want to know what's wrong and want to know how to fix it and we've also heard about them as research participants in the different ways that you can come to be a research participant in the different frames of mind that you might be in throughout the course of that. I think Sharon Terry didn't mention this today but I've heard her say in other settings too that when you're talking about healthy individuals who might be participating in research or might be considering their interest in genomic information, you can also just consider them the pre-diagnosed and how much you can change your attitudes and preferences and values over what you want to know about your information and how you might use it just based on the point and time at which you're trying to receive the information which can have a drastic effect. And so all of that then goes to what are the responsibilities that we have sort of if we're going and speaking from an institutional perspective or as policy makers for the government in terms of what do we owe the public? What do we owe individuals, groups, et cetera in trying to conduct the research and trying to move the research forward and again bring about not only research to advanced understanding but also to inform public health to move us along towards personalized medicine, which again they're all very different things and have different questions to be asked and different parameters around which to think about what the responsibilities might be in each of those settings. Again, we've heard a little bit coming through even in the scientific talks earlier this morning about the questions for protecting participants and having to check in with IRBs and informed consent and other forms of protections for the public which again gets to our responsibilities. What do we do to protect their interests or them as individuals, their privacy, their confidentiality, et cetera, as we are learning to use this information and learning to understand this information. And again, thinking about this in many different contexts from the traditional study of looking at a particular gene that may have run in a family for some particular rare disease versus in a large cohort study where we're generating enormous amounts of information about an enormous number of people and putting it in a database and sharing that information with a large number of researchers. Again, there are gonna be a lot of different kinds of protections that you would wanna put in place for different situations. So trying to put these pieces together, of course, they need to start with the science. And so again, defining the science in different situations, we'd have the research aims and objectives for what you're trying to accomplish with a given project or a given sort of area or discipline, again, personalized medicine versus a longitudinal research study. From a public perspective, we're talking and even from a scientific perspective, thinking about all of the different findings that are coming out. We've heard about that before and what the public's and individuals' reactions are to getting different findings of why I'm being good for you one day and not good for you another day and how do you interpret that and take that in as an individual or as a research participant. The different perspectives and agendas going into research itself, we heard from Sharon earlier about her experiences going through as a parent and learning about how just the culture of research and how it was about competition and it can depend on what you're trying to get out of the research in terms of how you're thinking about doing the research and how you're putting together the study design. And then there is of course the fact that science is always moving forward and so trying to keep up with that and trying to construct policies and to move forward responsibly in a sense of perpetual motion where the technologies are changing, the cultural conversation around the technologies are changing and what does that mean? So then, layering on top of that, there are policies and procedures which of course can start with just what are the laws and regulations about how we're going to do research or how we're going to move personalized medicine forward into the clinic and those laws and regulations that definitely do not move at the same speed that the science and the technology do. So trying to conduct the research or move the genomic science into the clinic forward in a different context where the laws may be outdated, the principles that may have been put in place 20 years ago just don't seem to quite fit for what we're dealing with at the present time. So we can then try and construct guiding principles for how we're doing this, what are the ethics involved with what we're thinking about and how again, where are we thinking about the individuals about who we're moving forward in the science, whose data are contributing to the science and that we're learning from. And again, in genetics, not unlike other fields of science or when you're dealing with large cohort studies or longitudinal studies, you are dealing with more than one individual and in some cases we're talking about definable communities or populations and there are cultural aspects that come to bear on this which also have to be taken into effect and where we also have some responsibility to those community expectations in terms of what are they going to get back from the research, but also how do they feel about genetics and genomics? What does their genetic and genomic information mean to them as a community, not just even as an individual? And then finally, trying to add in the implementation of the research program. How do you take all of these different bits of information around policies and the science going forward and create a system that is transparent and that is balanced of all of these different concerns going forward so that the research can be done in a responsible way and talking about shared responsibilities between investigators and policymakers but also the participants and the general public going forward in terms of what their expectations are and how they're participating in the overall process. Some of the particular issues just to put them out there, I think we've heard about most of these throughout the day that we're thinking about if we talk about privacy which Joan mentioned a little bit in confidentiality, what does that mean? We're talking about genomics and we're talking about whole genome information. There are questions around that being an ultimate identifier. Are there ways to de-identify it to protect the individual, to protect their information when you're sharing it broadly across many different investigators with whom individuals may have had absolutely no contact or have no idea that their data's even being used in these different ways? How do we respect the wishes of the individual in terms of how their data are used at the time and going on into the future so that we not only respect that individual but also sustain the public trust in what we're doing because again if we are not able to sustain public trust in the research, it will also taint the outcomes of that research and what the public feels about how to use that genomic information in their healthcare in the future and in society. There are questions around informed consent, what does that mean? It of course means something different to different people at different times and again as Sharon also mentioned, we hear what we hear and trying to understand what that is and how to control for that so that people do have a meaningful conversation and a meaningful understanding to them at a given point in time when they're enrolling in research or when they're making decisions about their healthcare is something that continually evolves. Questions around returning the results we heard from Joan just today that individuals to participate in these studies really want to know what their results are because it's part of them, it's information about them and they think they just want to have it and what they do with it is up to them. There are many people that I respect on both sides of this argument, again looking back at the laws in some cases, it is illegal to return information from a research study to an individual and people are struggling with that as we go forward and hold sequencing information as they find things that they think could be actionable or could be informative or may just have personal utility and there may be nothing that could be done but it's something that an individual might want to know again about themselves and how do we reconcile that with what we're doing with our ethics which are value based and individual based in what we're doing again between both the researcher and the participant and of course then how to provide responsible stewardship of the research program as all looking at at a macro level not just even at the individual context in terms of designing the programs that we're going to go forward with. All of this of course is as I already mentioned in the context of changing public perceptions and changing technology so we have other ads that come up comparing decoding your genome to getting your oil changed. We have direct to consumer marketing which brings genomic information into a social context, something that is fun, something that is to be shared, something that's about who you are, not just about your health and then also others that are promoting it as knowing yourself a little bit more deeply in lots of different ways that you can market this. There's also one where again, this is not just about you but it's about your family and what level of information it's not just for health information but it could be about sports information or all kinds of other non-medical uses and people making decisions for others around the genetic information and what they're doing with it. And again coming back to thinking about what this means, this particular clip, looking at the intimate secrets that are hidden in your DNA that could be stolen and that concept of privacy and the ultimate identifier and what that can mean to you as an individual. And then going back, as always, to the people that we talked about before and what the people are at different points in time, whether they're a research participant, a patient, or a partner in the entire research endeavor or in the healthcare setting and what their values are and what they're bringing to the table. There are different organizations that the patient advocacy organizations, organizations such as Sharon's, the genetic alliance that come together as umbrella groups to try and empower patient groups in what they're doing. Also groups like patients like me and the private access which came up earlier which are trying to band together and again empower people to make choices about who can see their personal health information and how it can be used if they want to try and participate in research and they want to put their genomic information out there. So participants are becoming much more active in this area and making much stronger statements about what their choices are and it's not being run as it used to be more so from an investigator oriented perspective. So we come back again to trying to put the pieces back together where we are again from a science perspective looking at trying to balance potential benefits with potential harms which again are very difficult to define and can vary very much depending on what perspective you're looking at trying to make sure that with the science there's this we're balancing the hope versus the hype another thing that Sharon mentioned as a patient which I think is very important and I hear a lot about looking at the policies and procedures in terms of the protections that we put in place and the questions that we ask ourselves around informed consent and our respect for the autonomy of the individual or of the group in their participation and in their use of genomic information trying to collect data as done and as less as doing to understand what people like or prefer in different situations and then to try to balance that between general public trends versus individual choices and again trying to implement programs in a way that can be responsive to changing technologies and changing discussions and also that is again transparent and has shared responsibility in what we're all doing. This panel is open to questions. Yeah, hi, it's Sudarsi from the Gracie. So were these people in the study actually tested or were they just asked if they would be willing to be tested? No, they were eventually they could eventually about 15% of the almost 2000 were tested but in the data that I talked about today and that's in the paper that came out today, those people for as a whole weren't tested and at the time they were asked the questions that I talked about today, they didn't even know that they would get the option for testing. It was just. I guess what the data I'm trying to get at is was there any resistance to like having blood drawn or was it inconvenient to go to the clinic or doctor's office or? I'm not sure because there was like there are a lot of these studies relatively low uptake and there probably were a number of different barriers. I don't know if they specifically asked, went back to the non-testers and asked them what their barriers were but for this specific study, my guess would be one, it could be blood draw as a barrier and also to be sure that things were being done in a very ethical manner and that things were being explained to them. The participants had to go to the clinic to get tested. So again, having the time to be able to go to the clinic could also be a barrier. So were there any questions you asked them about alternatives like these direct to consumer genetic tests are offered via the internet, did you say? If you had a direct to consumer genetic test where you could just give a cheek swab or something like that, you'd be more willing to do it than say blood drawn at the clinic. This study did not and actually the years that the data were collected was back in 0708 and it was right when 23andMe and the other companies were just starting to come to market when the data were being collected. It was free that. Yeah, it's the landscape even since the data were collected has really changed. Other questions for this panel? I think we're winding down. Okay, I wanna thank these three. I think the goal is to end on time. People are helping do that. So I, as you heard from the last speaker, I represent the bitter end. So, and I was asked to make some closing remarks and also to set a little bit of a context about the future of genetics research as it pertains to an ongoing planning process that the Institute is currently winding down in fact. In many ways, this is what you experienced today. On the one hand, I think you heard a lot about the exhilaration of genomic advances of late.  We covered a lot of territory and a lot of small bites. They were very intense, five, 10 minute presentations. Each one of the presentations is, you go to professional meeting, it might be a whole session of three hours. At the same time, it's gonna be daunting. It's exhilarating but it's daunting and this analogy of this tsunami type wave is really reaching across genomics left and right. In fact, just a few weeks ago at the annual Cold Spring Harbor meeting on the cover of the abstract book actually, they stole that same analogy. In fact, three of the speakers you heard from today is actually featured in caricature form in one of the boats that's about to get drowned by the wave. The truth of the matter is this wave, if you will, is as much an opportunity as anything else. And the Genome Institute in the field of genomics loves opportunities. We take on huge challenges. It's just the way we like to do things. And in fact, as an institute, we have a history of strategic planning processes that go back to our origins. We were created initially by the National Institute to Health to carry on the NIH's lead effort in the Human Genome Project.  And the truth of the matter is I could tell you, I was a post-doctoral fellow at the time when the genome project started. I was on the front line of the genome project when it began. And we had absolutely no idea what we were doing at that time. We had absolutely no idea how we were gonna do this audacious thing of sequencing the human genome. But what we did know is that we better figure it out. And so, with the genome project from the beginning, and our institute specifically, was into strategic planning. And in fact, you can see, as soon as the genome project began, we started a strategic planning process that yielded a five-year plan. Two years later, we went through and we redid that plan. Two years later, we went back and redid that plan again, practically. And so, or a few years later, it was sort of these rolling five-year goals as the technology changed, as sort of the horizons changed.  Needless to say, when the project concluded in 2003, we recognized that everybody was gonna be asking, well, what are you gonna do next? What is the future of genomics with a sequence, the genome in hand? That is why in 2001, 2002, we carried out another planning process that yielded the vision for genomics research, which is in the front pouch of your notebook. And as Francis alluded to, and if any of you look at that document, you will see some of it's fantastic, because it's been accomplished, some of it's fantastic, because it's still stuff to be done. We recognized it was time to launch another strategic planning process. And so we did so a couple years ago, and now we are winding this down. This time, we've made this thing much more open and transparent, in part because of our ability to put lots of things up on the web and solicit comments. So if you wanna read about our planning process, I would send you to this website. It had a number of elements. We've done a number of workshops, as we always do, around topics that we thought we needed more in-depth discussion and strategy about. We also had this web-based feedback around a series of white papers, the four topics that we had white papers about. And again, you can read these white papers are shown up here. We took advantage of a huge network of advisors that the Institute has to sort of strategize with and to talk about and think about what sort of the next phase of genomics research gonna look like. Lots of internal discussions and the synthesis are actually going on now. Since I was named director six months ago, I've even gone out and done a couple of town halls out of few places to try to capture community input. And then really just in several weeks, early next month, we're gonna have a finale meeting where about 200 leaders in the field are coming together in the DC area and are going to critically evaluate a draft version of this new strategic plan. It's like bringing in 200 peer reviewers, if you will. And they will rip it to shreds as they did in 2002. And that's great. And then we will put it all back together and this new strategic plan will be published in December of this year is our goal. And so this is something I wanna tell you about because I'm hoping in December you will talk about it. This will be a very important blueprint for the future of the field of genomics. It's written very broadly of which a subset of that vision will be what NHGRI specifically will be tackling and having as its fundamental goals and programmatic mission. What you may ask me as this sort of, is this being done in isolation just as one institute? Well, no, not entirely. In fact, as you might imagine with new leadership at the top of NIH, which is where we started today, we are doing this also within a context of what is looking in the mirror at NIH as Francis Collins is making all of us do. And if you didn't see this, I would point you to this early 2020 paper where Francis articulated what he thought was some of the most important opportunities for the NIH's agenda more broadly. In fact, if you look at them, we fit very nicely. In fact, we heard about many of these today in one form or another. But there's one subtle thing, and if you're gonna ask me the question, what's gonna be different about our strategic plan in genomics at this time than it was, say, in 2003, you can start to catch a hint of it by simply looking at what is being looked at NIH-wide, where the notion of health, the notion of medicine, the notion of treatments and diagnostics is coming much more to the forefront around NIH. In fact, Francis also recently commissioned a nice brochure, a more general public brochure, this is the cover of it, that really sort of highlights some of the great things that are going on at NIH. And notice that once again, the emphasis is on health, while basic science is the engine for much of what we do. I think increasing attention is being paid on the application of basic science discoveries to improving health in the United States and worldwide. It is therefore within that context, I can tell you, that we are thinking critically about not just understanding how the genome works, which is much of what you heard about today, especially in the morning, and unraveling the complexities, but extending what the institute has traditionally done so well and start to push out into frontiers of actually influencing the way medicine is practiced. And the notion of the phrase genomic medicine, which actually came to the forefront even before the genome project concluded, both in the popular press and also in the scientific press is just becoming increasingly common language around NHGRI, and I guarantee you, will echo considerably within the strategic plan that we unveil later this year. Now, genomic medicine, by that I mean healthcare, tailored to the individual based on genomic information. Other phrases are used to describe this, whether it's personalized medicine, individualized medicine, precision medicine. You heard elements of it today, certainly, in various settings, but it is basically taking advantage and knowledge of a genome within the context of an individual patient and changing the way you treat that patient clinically. Now, what I can tell you is that what I think, if you would ask me to show you one slide, that is sort of an organizing principle for the institute and where I think our strategic plan is going to go when we publish it later this year, it's gonna look something like this. We recognize that our foundation, our history, our basic core essence was the human genome project and the things that have come out of the genome project in terms of understanding how the human genome works, but our ultimate mission is actually to somehow influence the practice of medicine by using genomic knowledge of individuals, and that realization is gonna require a whole series of steps, many of which you heard about today because we understand what some of those steps are, but I would contend some of which we probably haven't even defined yet, but that is what I regard as sort of a core mission of what the NHGRI needs to do in the coming years. We were successful as an institute providing international leadership and participation in completing the goals of the genome project. I would like to believe we're going to be successful at realizing genomic medicine someday. I would contend the institute must do this if we're truly gonna fulfill the promise of why we sequence the human genome in the first place. The truth is I would actually contend, and I think the strategic document will echo this, that a central component of our future mission, indeed the whole field of genomics, future mission, must be to foster the maturation and practice of genomic medicine, and I am convinced you will hear this coming out of our planning process. This is a different kind of an set of activities. We've tiptoed into it and we got up to about one o'clock today I would say or so, maybe about 1.30 hearing from individuals at our institute that have sort of started to tiptoe into human subjects work and population studies and some human genetic studies, but I think what we're really going to start to shift and what will be new is getting closer and closer to patients, closer and closer to the bedside and really influencing the way that medicine is actually practiced. I will tell you quite candidly, it will force us to stretch as an institute. Not so much in the intramural program with people like Bill Gaul and Les Beesick or who you heard from. We've been doing that in our intramural program for a number of years. I think where the stretch will come will be much more in our extramural program, in our grants portfolio and some of the activities we are doing in other parts of the institute. But indeed I can tell you this is going to be a change but I think a very appropriate, and it's not a wholesale change, we won't lose our origins. We'll just be stretching into this new frontier of genomic medicine. Now why is it, why now? Why didn't we talk about this in 2003? Why didn't I say, ah, not my first year as institute director what I want to make such a stretch. What's special about now that really makes it very clear that we need to be sort of expanding our horizons? Well, you've heard all day probably the answer to that. You've heard bits and pieces of it. I would tell you that I think the driving aspects of it is the technology advances we've seen in the last five years. I think if we hadn't seen those, I don't think we would quite be creating such a situation to allow us to really push into genomic medicine. And I like to show this picture because it's not just one technology, it's not just two technologies, it's not just the next sequencing platform or the one after that. It's as if you're at an airport, you could sort of see the next 10 planes about to land over the next 30 minutes. Indeed, it's the next suite of technologies. Many of them are figuring out better ways to sequence human genomes. They are ones coming that are gonna land and be on the market in a year and a year and a half and two years. There's no doubt that the pace of these technological advances absolutely are going to make the generation of human genome sequence not rate limiting. And because of that, you can just start to imagine all of the projects that will spin out of that as we begin to sequence, not dozens of human genome sequences, but hundreds, thousands, tens of thousands because the technology is absolutely driving this. Another fun way to think about this, what is the difference? We're here to talk about what's sort of changed in the last 10 years. If you sort of think in very real terms about what has changed in the last 10 years, is you just, and you heard all this, but I'm just sort of summarizing it in a different way, hopefully a way that it will pick you up energetically, it'll end it on a very nice note, is if you just ask the question, how many human genomes can you sequence for $10 million? If you go back to 10 years ago, which was sort of the history why we are here is what happened 10 years ago versus now. 10 years ago, this guy was in charge of the NHGRI, and for $10 million, you couldn't even get an entire human genome sequenced, okay? If you fast forward to 2010, 10 years later, what's different between now and then? Well, there is a new institute director at NHGRI, that is me, and for those same $10 million, you get two to 400 human genomes. This is what I would regard as an upgrade. And so the fact of the matter is, this has changed the face of genomics, and the technological advances are going to continue over the next 10 years, and you come back here at 10 years and you'll have to look at 2,000 of my faces instead of just 200 of them. Okay, that's the positive attribute, but I want to also be real, because I don't want to make you think that genomic medicine is going to be easy, and you heard about this from several of the speakers, but I will just summarize it in two slides. There is a reality, and the reality is, every single time you break down a bottleneck, such as sequencing human genomes, you progress down a pathway closer to genomic medicine, but you instantly then encounter the next bottleneck. It is sort of the tradition of genomics. You break throughs and then bottlenecks. This is a breakthrough, but the truth is, this is the bottleneck. You heard about it, it is very real. There is an absolute computational bottleneck. In genomics, actually it's in all of biomedical research right now, genomics is one area, I think in sort of other areas of cell biology with imaging, there's other similar computational bottlenecks. It relates to hardware, of simply having the hardware in place for the scientist to process as much data. It's with the software, all the tools to analyze this huge amounts of data.  The metaphor is absolutely applicable. Just capturing that data, pushing it down pipes, and then being able to analyze it is huge. And let me remind you, there are simply not enough trained individuals who are currently working in our field to be able to help us through this computational bottleneck. I was asked earlier, is NIH concerned about this, looking at this? Absolutely, NHGRI is being looked at quite seriously. It's helping to provide leadership to figure this out. It is not just a bottleneck for our institute and our grantees, it is absolutely a bottleneck for all of NIH and quickly becoming for all biomedical researchers. But even if we crack this bottleneck, even if our pipes get wide enough and our servers get big enough and our processors get powerful enough and our software gets cool enough and we have enough people to help us get through all of this data, we will then face an informational bottleneck. And I think last piece of it started to echo some of the things of what it is like. Because when you have these fancy schmancy sequencers that are spewing out all this sequence data, even when you get past the bottleneck, you end up with lists of variants for an individual patient, such as our one individual ClinSeq participant who you heard from, whereby we'll have a list as shown here in orange of all the variants, there'll be 1,000 millions of variants an individual will have. And then sifting through all those variants to figure out which ones are actually relevant to that individual is going to be huge. And the information about which of those variants is relevant is currently a bottleneck. And I can tell you with somebody who originally got into genomics because of interest in diagnostic medicine that this is just going to be a huge bottleneck for a long time as well. That just because we can get lists of variants for all these ClinSeq patients or any of these patients, really understanding which of those variants are relevant is going to be a massive challenge. Gonna require lots of very good studies and lots of new analytical tools we're gonna have to figure out. But that's okay, those are the kind of challenges that all those of us in genomics love to have. So the take home message with this then is that data generation, I don't think is going to be at all limiting, I think computational bottlenecks, informational bottlenecks, and maybe at the other end of the pipeline starting most upstream, just samples and getting individuals enrolled, cohorts developed and so forth. It's gonna be those extremes that are gonna be the rate limiting ones. But I think you're gonna read and hear a lot about how the Institute and the field are gonna try to tackle that when we come up with our strategic plan, which you will see later this year. So I will stop there. I will thank all of you for participating today. I'm happy to take any questions. And then I don't know if there's any other logistical things Larry needs to tell you. So any questions for me at the end of the day? There's somebody moving towards a microphone. Hi, just wondering about that last point you made. Is this coming paradigm shift of the informational bottleneck kind of trickling into the schools of medicine and schools of nursing, all the healthcare practitioners who are being trained now are they getting any sort of sense of this? So the short answer is no. I mean, because I don't wanna paint that it's a perfect world. This is absolutely something that our strategic plan will discuss. It's something that many people at our Institute are now working on and many people in the field. And even thinking about, so clearly every level of education one can imagine starting with the general public going right to K through 12, right on up to health professionals, physicians, genetic counselors, nurses, physicians, assistants, and so forth. And what's the best place to sort of invest your resources? All of these things are being looked at. We at the Institute have a suite of things that we are doing but a much larger effort is absolutely going to be needed. There is, you talk to anybody at medical schools and they complain about this, that they recognize that changes to medical school curriculum does not happen quick enough for a tsunami like what's gone on in genomics over the last 10 years. So it's something we absolutely do need to be addressing and we regard that as sort of a fundamental aspect of genomics is gonna have to be education and training. Thank you. Is my Red Sox fan gonna ask a question or you're sneaking out? He's gotta go. Okay. Well, he's an American League fan which is the Lesser League but we won't go there. Any other questions? Okay. Well, Larry, are there any other questions? Okay. Well, on behalf of the Institute, thank you all especially those who made it to the bitter end and I was the bitter end and we greatly appreciate you participating. If you have any feedback, I am quite sure that Larry Thompson, his team would very much like to hear from you. We do this for you. And so we would love to hear if you have suggestions on how to do this, how to do it better or what other topics to do it on. So thank you very much for your attention.


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So what is it that I have against nano? What is my problem with the nano text editor? People really want me to answer this question This is something that has been constantly asked over the years of me doing this YouTube channel for one thing I spend a lot of time covering really extensible text editors like Vim and Emacs and I really never talk about Nano when I do talk about nano. I'll be honest I don't necessarily talk about nano in a good light, right? A lot of people are like, hey, man, what is it? What is it that you have against nano?  Where does all this built-in dislike for nano come from? And you know, I'm just gonna go ahead and say this these people that imagine that I hate nano They're not imagining it. I really do hate nano as a text editor now that that being said There's nothing wrong with you using nano as your text editor. If you want to use nano keep using it Right, you use the software you want to use. I use the software that I want to use We all make these personal choices as far as the software we choose to use and if nano is working for you Keep using it for me. I'm gonna go ahead and tell you I've got some things against nano that really bug the hell out of me Probably my biggest issue with nano is with any text editor whether it be nano Vim Emacs It really doesn't matter to get the most out of any text editor You really need to learn all the built-in functionality of that editor You need to learn all the already assigned key bindings to that editor right to get the most out of it to learn how to really Navigate around a document quickly and make those edits, you know Much faster to really speed up that process you need to learn the key bindings and nano has a lot of key bindings already assigned to it Many of you nano users actually don't realize just how many key bindings there are in nano There's an extensive list of key bindings available to you matter of fact I should actually link to like a nano cheat sheet of all the key bindings that are built into it There's a lot right so there's a learning curve to nano just like there is with Vim just like there is in Emacs You have a lot of learning to do up front. You need to learn all those key bindings You need to get used to all those key presses those strokes, right man Here's the thing with nano that learning curve to learn all that stuff It's not worth it because nano at the end of the day. There's only so powerful There's only so much you can do with a very basic plain text editor like nano work with Vim and Emacs Yes, there's a huge learning curve. You got to learn all these key bindings You got to learn of the plug-in system You may have to learn how to write in Vim script or Lua or Emacs list if you're using Emacs You're gonna have to learn some stuff But it's worth it in the end because of what those editors ultimately can do what they can become With you being knowledgeable and how they're scripted and you know with nano There's a learning curve to nano and that learning curve just isn't worth it also with nano just like with Vim and Emacs There's some basic plug-in functionality available.  You've got your nano or C file, right that you can play around with You know change some settings, but then at the end of the day, there's only so much Extending of nano you can do the sky is the limit with Vim and Emacs as far as Extensions and what you can turn those text editors into Emacs can practically become a full IDE Hell Emacs can practically become its own desktop environment You can extend it to that kind of capability where nano at the end of the day is really just a very basic Plane text editor. There's not a lot of plug-ins out there It's just a few you can only do so much with the config file even turning on things like basic Syntax highlighting and things like that, you know, it's just not great Yeah, it doesn't have the kind of capabilities that both Vim and Emacs for example have so really that's my only gripe is When I get into nano and try to do anything in nano it's got these weird set of key bindings that are not standard as Complete different set of key bindings and you would use in something like Vim or in Emacs or even plain text editors Like G at it or K right nano has its own weird set of key bindings that you have to learn It's just not worth it. That's that's really my complaint is it's uncomfortable to use and I don't want to learn it I don't want to waste time learning it just because at the end of the day I just don't think that that is time well spent for me nano is not a Endgame text editor, right? That's that's not ultimately where you want to end up as far as your text editing Software of choice, right? I think where you want to end up is something like the Vim or Emacs Nano what nano is really good for and what I might would use nano on occasion for is if I need to make a quick edit I really quick simple edit to a config file on my system or a machine I remote into SSH into a machine and maybe nano is the only editor on that server And I don't want to install another editor on that server just to make a really quick 5-second edit to one config file, right? I'll just use nano for that. Why not? I I can make it work for something really simple if I'm not, you know If it's a situation where I don't have to spend a significant amount of time in an editor nano is fine for those tests But where nano really falls apart is if you're going to do a ton of writing a ton of programming a ton of scripting Creative writing whatever it happens to be you're writing your your latest novel, right? Mano is definitely not the best tool for a job like that That is where tools like Vim and Emacs and those really extensible text editors That's where they shine because they have so much more functionality available for you for whatever task you're doing You've got all these thousands of plugins available to help you programmers and developers or your creative writers or whatever It happens to be that you need that text editor for they can make that happen where nano at the end of the day It's just a very basic piece of software and where some of my Obvious dislike of nano comes into play you guys sometimes see it on camera You know, I spent so many years using Vim and Emacs, you know I find nano it's just it's so damn frustrating when I end up in nano on In a virtual machine if I'm checking out a Linux distribution and nano is the only editor on it or or whatever It happens to be if I end up in nano for some reason Then I have to try to figure out the key bindings for nano and again Nano's got this weird set of key bindings that nothing else uses it It's a complete set of key bindings unlike any other program. You've ever used and that's part of my hatred of nano You know, I have nothing against, you know, good new nano the text editor Yeah, again, you guys that want to use it you can for me every time I end up in it You know that that frustration builds because it's because I'm a fish out of water at the end of the day I'm just not used to it and that's the problem a good analogy is when I end up in nano compared to you know Vim or Emacs, you know when I'm in nano, it's almost like I'm typing with both of my hands tied behind my back Right, like that's how clunky and slow and frustrating I find nano So I hope that answers some of your guys questions as far as what I have against nano Right, but some of you guys are even asking questions like what do I have against nano users?  If you're worried about what other people are doing you've got some issues to work at any sane and rational person Really isn't concerned about what somebody else is doing with their life Right, so I have no problems with nano users and when I talk about nano in a negative light I'm not talking about people using nano right some people think when I say a piece of software is not right for me I dislike a piece of software whatever it happens to be that I'm somehow Taking a shot at the people that use that piece of software and like using that piece of software That's not the case at all. I'm just speaking my personal opinion and many of you guys want my opinions on this stuff So I'm happy to give them, you know like on this video. I'm very straightforward and honest I just don't like nano and it's not you know that you shouldn't like nano Nano's just not the right tool for me for 99% of what I do with my text editing. Peace guys