 Okay, so it sounds like they're tag teaming, and we have Howard McLeod from the Moffitt Cancer Center, and Surika Muth, I'm not going to say your last name correctly, I'm sorry. My last name is Mahasri Munkun, so it's so long. Anyways, you can call me Surika Muth. From the Time Ministry of Public Health, thank you. So we are tasked with seven questions, and it's about the key gaps, and what we send at once in clinical implementation of genomics, from a co-genomics, we'll be having to get this likelihood of contributing to re-education of preventable causes of stem-intensed key barriers, resource, and recent development, and what is the most promising opportunity in the next five years, and what is the evidence-based need to implement the screening testing and what alternative to the last prospective clinical trials, and it seems that the co-action is overlapping in somewhat, so we did the survey sending the co-actions to the working group participant, which is about 20, and I got nine responses, and somebody is in the most promising opportunity in the next five years from the pre-survey. One interesting question that keeps coming up is about how to recommend testing in the admixt population, where the prevalence of the admixt only is worrying between race and ethnic, and this is going to be more complicated in the next generations if we have a half Chinese, half Caucasians, and a lot of mixings in the population, how can we going to be reliable recommendation based on race or ethnic, and the next promising thing is that we should develop the low cost from a code genetics essay that can be included in the state on national health program, because in the cost-benefit equation, we can do two things, like lowering the cost of testing or increase the benefit of the testing, so the one equation that Thailand did is that we provided the test as $30,000, and then it's become the cost-benefit equation become good in Thailand setting, despite the fact that we use the test of one quality at just life years, $4,000, comparing to $100,000 here, or $50,000 in Singapore, and the next thing is to include the genotype data in the medical records, how we going to implement this testing in the clinical electronic health record setting, how to include the interpretation of the next generation sequencing data, and two of the test drug that we think is promising is the test based on the commercial gene, HVB-1502 and HVA-3101, and the alofrino HVB-5801, and we received several comments that these tests should be implemented in the high-risk populations, and we should have an impact study to study the impact of these testing on the prescription pattern and the behavior of the one who are receiving the test and the one who provided the test, and there is interest that in piloting the pre-emptive testing in some hospitals. So it should be no surprise that the people who are willing to actually answer the survey are also willing to come with their thoughts during the meeting itself, and so there are some overlaps in terms of that, and what I've summarized here, or what Sir Khamenei summarized here is some of the discussion, we had a very vigorous discussion over the two-hour period, plus there was a subgroup of us that had a discussion over the 45 minutes that we spent on the wrong bus trying to get back to the metro center, but we now know a lot more about the NIH campus, so please talk to Dave or Dave or Matt if you need any directions on the campus. So one point that was brought out is that these are iatrogenic events, and unlike some of the other events that we care for, there is an extra bit of responsibility that falls on us because of who caused them. These are not things that are occurring out in the wild, these are things that are occurring because of an act within the branch of allopathic medicine that we most all practice. And so there is this moral obligation that's maybe even you consider above some of the other obligations that we have, and so as we implement, sometimes it won't be just about cost, but there will be also about this principle. Another thing that came out is that it's really hard to think about implementing or for that matter doing a lot of the basic research, we really don't have a clue what the burden of the problem is. We know the cases, and those of us who have managed some of these cases will never forget them because they are indeed a motive, but we really don't know what the frequency is in most countries, including the one that we all happen to be in at this moment. And so there's some basic landscape definition that is needed. We haven't even seen a study of whether the HLA alleles replicate in Asian Americans, for example, a study that you think would have been done, and I was happy to see who was Steve, I think, showed some data that the Canadians have gone down that route. So I guess we could say North America has been done. But the idea that there are some really simple straightforward things that could be done, well, not simple. There are some straightforward things that could be done to help us think about how to apply things in this country. We are way behind Thailand in terms of understanding the problem. It was brought out by Matt and others, what's really going to move the needle? And genetics by itself is not enough. And really we can't think of this as a genetics problem, but rather a clinical problem for which genetics can be an important contributor. And almost every successful example on the pharmacoside has included organ function and body size in this and that, in addition to genetics, in order to really hone things down to either divert to a different drug or a different dose or whatever it might be. And so there's some work that needs to be done in terms of defining that before implementation can be really more straightforward. The downstream implications of changing therapy also is needed, and Dave Morgollis and others brought this up where are the alternatives better, the same, worse? I mean, what are we diverting people to? Are we diverting them from Heathrow Airport to Baghdad? Or are we diverting them from Heathrow Airport to Paris, which is not necessarily a bad diversion. So the idea of where we're going needs to be more clearly defined. And that really came out in Dave Vincenzo's talk and others. This focus on one gene, one drug will rarely be favorable economically. And so we need to be looking at panels or other approaches that could face that. If it's really almost setting ourselves up for failure, if we go down the economic route, to look at the cost of doing one gene. When you really, it's a very similar cost to do an entire panel. And then you get to amortize that across the panel. The next thing is really we don't have a lot of data on how people will behave when faced with data such as a risk of SJS-10. And so there are examples that could be done. We put one of them there where we could survey patients, maybe through the advocacy organizations. There are loved ones, the general population. And try to look at differences in the way one would respond to this kind of risk. Because we just don't really know whether we're doing the right thing or how to do the right thing. It's also a bit of a changing atmosphere in the United States anyway for who bears the extra cost of this atrogenic event. And frankly, in the past, the incidence of a severe event such as SJS-10 has, if anything, been economically positive to a health center. And because they get the money that comes in for the management of that patient, even though it was an atrogenic event. And so with some of the movement towards more of a bundling of care or a lack of payment for atrogenic events, suddenly the focus becomes a little bit clearer for an individual health system or an individual polyphysician practice to try to get it right the first time. And so I think we need to focus a little bit more on who currently bears these costs because they should be the ones that would be our partners to help solve them. And then it was brought out that there are qualitative methods, rather, that have not really been clearly defined from the patient. And if we want to talk about that more, we'll give more goals and others to go further. But that we really haven't been looking at patients, at their responses, how things would be in terms of trying to implement these things. And then the last little thing, I put a little space between it because it's not really implementation. But it was brought out that currently most of us in this room have decided to have on our driver's license or whatever the document might be to be an organ donor. And with that, we've pledged to have HLA testing done on ourselves after we die. So it was brought out, I won't name names, but Alan Sholdiner, brought out that maybe we should be doing the HLA testing now, benefit from it for these other aspects and be ready for our organ donation when that time comes. And there's some problems with that. We don't want people going and hunting down people with the right HLAs in order to get that kidney. But there's not enough hotel rooms and ice baths in Las Vegas to get all those illegal kidneys done. But the idea that we could be thinking about some other ways of benefit of this data now and later was, I think, Alan's point. And certainly in terms of implementation, creative things like that, where we may get it for a number of reasons, but it would also benefit the prevention of these types of syndromes. It was really the point that he and others were making. So I think I'll stop there. Maybe Oat could open it up first, if it's OK with you, to other members of the committee to fill in the blanks that I circumvent and I inadvertently left. So Dave, Dave, others, Mike? If you're a bone marrow donor, I think you get your results now rather than one at a time. Right. All right. General questions or comments? So I was wondering if you could elaborate a bit on the admixt populations issue you had said you, you know, early on you felt, yeah, that that was an important topic. So what would we need to do in order to address that? Well, I think my take on that was that there was still some worry that when you found a marker for a population, you found it for that population and its relevance across to other populations is not known. So the admixture element, one of them is it's going to be harder, even harder to label people in the future because we're going to be admixt. And then there was also the idea that the existing admixture is different, you know, 1,000 genomes is nice, but it's only a very limited set of the population in the world. And so, you know, even the data like, you know, Manir, I can't remember what Mike, what you called it, was unsettling, I think, was the term you used. When Manir presented that data with the Italians, you're like, oh, you know, what are we going to do? So there's a lot of need in terms of trying to understand, is there five different markers that cause SGS-10 and carbamazepine around the world, and we found two of them? Or is there one, and that we found two tags in different populations for that one, or, you know, what, you know, so there's both of those issues. So it's less about admixture in an individual and more about ethnic diversity? Yeah, you shouldn't say less about, because that was definitely part of the discussion in terms of future generations. Well, you know, what will you call yourself, you know, so. Thank you, Dave. Yeah, a very nice presentation of what we're doing. Can you come a little closer to the mic? Be consistent with the, that's way too loud. Even I don't like that. Although my kids might. To be consistent with the first group, many of these studies and many of the things we suggest that could become part of studies that would be done as a large national cohort system or a large national registry, these would all be compatible with studies on individuals who have disease or family members who have disease as well. So it would all fit nicely into what was sort of being proposed by some of the individuals near the end of the first presentation. Cynthia? Yes, I think Elizabeth raised that it's the interpretation of the data that's so critical. So was there any discussion about, you know, training of individuals or even a medical specialty that would become the interpreters of all this data? So that wasn't a major feature of our discussion, although it is a real issue. I guess maybe there was, part of it we had such a vigorous discussion about the points that we were on. And part of it is the hope that Elizabeth will figure it out and we can just use her approach. But I do think that, although we didn't discuss that, we did talk a little bit that you didn't capture here about the uncertainty and both the communication of the uncertainty and also doing some of this work in the presence of uncertainty, both about some of it coming from the rareness, but some of it also coming from other aspects of the disease. So I don't know if you or someone else from the group wants to elaborate on that a little bit more. Yeah, thank you for that. I don't, but just because I don't know how to. So one of the things that did come up also, going back to this issue of what's the frame of reference for a certain demographic group, that currently people self-identify. They say I am Chinese or I am whatever. Over time, it's gonna become more confusing as people are, as the genetic drift is increasing because of globalization. So one of the challenges going forward, if there are different markers that come from different populations as founder markers for risk that will eventually get mixed together, is actually how to do a snapshot that's a objective snapshot of the genetic background of that individual. So the question is there from a genetics perspective, for geneticists, when they say this genome has this complexion, what actually are the, what are the markers of that individual from the point of view of where they all came from? Is there a measure, a genetic measure in the genome that gives the frame of reference other than I'm African-American or I'm Chinese-American, which is very, I mean, African-Americans all over the place genetically. So again, it's a very arcane point of reference and it needs to be replaced with something more modern. Any other comments or questions for this group? Oh, go ahead. One of the things I spoke about my participation in this group, thank you, was talk to the victims of SJS. It's a wealth of information, how it's impacted them physically, economically, especially the family members and the ones who have had children and they would love to talk and tell you what their circumstances are and that hopefully could provide something that would provide everybody here with something that could move forward, whatever it is that you have in mind. That's our hope. And like I said, we're available if you wanna talk to these people. Thank you. And thank you for your help at this meeting. I mean, there have been some of the comments you've made have really been enlightening in terms of some of the problems that we've kind of been focusing on, do you get it or not? And then you've really highlighted a lot of the longitudinal aspects that have been kind of invisible. I think Maneer had his hand up first. Maneer and then Mark, yes. Yes, I just wanted to comment on the pilot study. You've got a bullet point there. So for 31-1-1 carbamazepine, we've done a patient preference study. We've done discrete choice experiment and basically, let me just read out what to answer. So the odds of preferring an anti-epileptic drug decreased by 99% for every 1% increase in the risk of severe ADR. This is from patients and some patients were willing to sacrifice a degree of efficacy to have the drug to be more safe. And so they would prefer to have a genetic test than not to have a genetic test. And I've got data in terms of how much they'd be willing to pay to be able to prevent an adverse drug reaction. So great. And so Mark, just Dave, being stressed since you were one of the people who brought that up, do you want to respond to that point before we move on a little? No, I think that'd be incredibly useful in a lot of different ways understanding how to best implement programs, et cetera. Mark. Great, I wanted to respond relating to the patient perspective and contextualize it. And I don't know if this came up with the discussion or not since I was in a different work group, but NHGRI is funding an economic analysis of HLA 1502 and Stephen Johnson syndrome through the University of Florida IGNITE group where we're trying to develop an economic model that would have a certain degree of generic quality so that essentially that curve that David showed, people could plug in a discrete set of things like a legal frequency, cost of an episode, cost of the test, and could basically get a rough idea without having to have a degree in economics to say, is this something that we should consider doing more work on or not? And as part of that, we're using some standardized methodology that had been used in Thailand to determine the impact on the patient. And so I think if that's a direction that you wanna go, what I would recommend is that we, again, use that sort of standardized approach that's always been used in some of the economic modeling and do that more broadly. And it sounds like we have a group that would be willing to probably contribute data that would be highly useful. Yeah, yeah, that's great. Oh, go ahead, Mike. Just have a question and a comment. Are the... A little closer to your microphone. Are the IGNITE programs testing for these alleles? I'm not aware of any IGNITE program testing for carbamazepine, but maybe Florida is. We locally are looking at implementing some of the HLA things and Elizabeth could talk more about that. Goes back to sort of a fundamental question. I think we as a society haven't really committed to the fact that screening patients for these types of factors is important from preventing them in the clinic. And I think with all of these research proposals, we really have to keep that in game in mind. I mean, we can throw a lot of money and come up with new biomarkers, but if clinically it's never gonna translate, I think we have to sort of take pause and figure out what it's going to take to deliver these types of tests in the clinic. Mark. Yeah, we have to have the answers before we can implement. Implementation is simple. It's dead solid simple. We implement pharmacogenomic stuff all the time in the clinic, but if we don't have the data about whether it's worth it or not, then it's an opportunity cost. So I could instantiate an HLA testing algorithm for carbamazepine today. I'm not confident that there would be much value that would accrue to the healthcare system, my healthcare system in central Pennsylvania if I were to do that. And so I can guarantee you that if I get an answer that says this is really going to work, I will turn it on. And I think there are a lot of systems that could do that through clinical decision support, enhanced electronic health records, guidelines that are computable, all those sorts of things. We're moving into an era where that is not gonna be the rate limiting step. I think one of the big hurdles again is with established drugs. If you get a new drug where the test is bundled with the drug, there's gonna be much less of a problem. You're not gonna have those barriers. People will just be considered to be part of prescribing the drug. I think every drug that we know that's established, anasothioprine is another example, like how many people are doing TPMT testing? It's not that it's not effective. It's just that it's not ingrained in us. And with established drugs that physicians have prescribed for years without a test, it's then hard to implement a test. I mean, we used to do G6PD screening on every HIV patient, whether or not they were gonna get prescribed DAPSone. And the cost of that test compared to doing one lifetime test of 5701 or 1502, and also how much is the test itself in the capacity of the total lifetime health cost of the patient? I mean, that's something we also don't consider. We can do seven metabolic screens, 10 CBCs. It's just goes on and on and on and who measures the cost effectiveness of those screening tests, screening tests which may have no utility whatsoever. So Dave Vinstra. I'm sorry, if I can just respond real quick. Okay. It's usually a life care planner who will go in and speak to the victim and measure out everything down to the last bit of Kleenex. And that's how it's measured about how long it will take and how much medical care it will take to sustain this person and give them what they need for the measure of their lifetime. So if that helps, we have that data, but that's important in the way she's talking. Yeah, that could be very helpful for refining some of these evaluations. I mean, I don't think there's a major issue here on cost effectiveness. So there's an issue, but we're not seeing signals from the market, from the payers that they're highly resistant. I mean, you saw some of those policies. So I think we need a little bit more data. We've already got people doing some modeling work in the US. We need a little bit of US relevant data for that. We've got some good, basically this conjoined analysis stuff. It's a tool for marketing actually. It's really helpful to understand how people will perceive things. So we have nice bits of data. I think some of the other issues are around having a practical, easy to use, rapid turnaround kind of issues. So I mean, I just voice a word of encouragement that from the value side, my sense is that in certain populations that are obviously more likely to have these variants in the United States, my guess is that it's gonna be a good economic value, especially when you plug in these costs, these patients that we're hearing about. Anything else? Okay, well, we'll go ahead on now to the working group three.