I'm not really going to bother introducing myself. All you need to know is my name's Rahul. And I'm here to tell you that if your history sucks, it does. Now before you guys go up in arms and like my good history does not suck. Well, here it is. What do I mean by your?  And when I say git, I mean like git that we normally use not in the story files because he didn't name it after himself after all.  Absolutely everything.  You will find out eventually.   Right?  Or you don't explain what your commit tries to achieve. You just tell me what I could already find out from the diff, which need not be human readable, by the way.  Again, nothing to do with what your commit actually does. Or Is this a PG-13 event?  I don't know why people like to do this and I mean, I have examples for all of these things, right? Ignore the hashes they generated by me because I couldn't be bothered. But the commit messages are rephrased from actual projects on GitHub. I will not name any of them and I have removed most, I pretty much removed any identifying characteristics of the way people type. So you will not know where these are from, but I assure you they're from somewhere. So you have stuff like increment each element of the list by one. Why thank you captain? Obvious. I could have done a git log-p for that. Or something like semi-colons are good. Sure. Semi-colons are good, but semi-colons might be bad. And what are you actually trying to do with that commit? I don't know. Now you have other guys who are like, not everyone can pick the blue button and get bananas. Okay, but what does your commit actually do? It doesn't tell me anything. And then you have to use a story. As a commit, I can merge master into master and infuriate dot dot dot because you are not supposed to have a shot log beyond 50 characters. There's a reason this is there, which I will show you if I have time. Otherwise, I'll show you afterwards once the event is over.   Great. Thanks bug fixes. Oh, that's amazing. Or you mentioned a GitHub bug issue without summarizing it. Well, a context switches are expensive. I'm looking at your git history in my terminal. Now I need to open a browser, go to GitHub, find your project, find the issue number, realize it's closed, all that work. And of course, there's the other thing, right? Sourceforge, everyone used it. Everyone used issue numbers on Sourceforge. It died. Google code. Everyone used it. Everyone used issue numbers on Google code. It died. Now you're using GitHub issue numbers extrapolate. This does exist in the project, right? Obviously in standard git log format, that is new. This is old. Fixes number 42. Many, many years later fixes number 42. Wait. Do you mean the same number 42 or never mind? Let's not go there. If you have this amazing thing, it says bug fixes. Great. It fixes bugs. You look at the log and it's like 500 lines are changing. Like I don't know what bug this fixes.    You think this doesn't matter, but when you're looking through a really long git log, it it really does matter. And you don't have consistent punctuation. Sometimes you have a dot at the end. Sometimes you don't. Sometimes you have colons in the middle of somewhere. Sometimes you do bug fix colon. Sometimes your B is capital and you don't have a colon.   You have things like fixed bug, fixed bug, fixes bug. We'll fix the nation of the universe at some point. And you have like capitalized it. Capitalized allow the nation of users are non-capitalized added password security fix. Again, the tensors are not Like what what tens am I supposed to use? There is an answer to this always use imperative present tense.   And so you end up with like fast fast fast AFDF things or As I mentioned earlier You have emoji in your commit messages. This is something that honestly github has Holy shit, they're responsible for half of it Because until recently Most people could not read the emoji in any way in that get logs But no now they can and so you have something like this amazing commit message, which is like If I remember correctly smiley face in medical mask Point a finger right point finger right index backward and pile of poop would be the actual unicode reading of this And then you have this which is someone who realized they fixed a bug that they were supposed to and they're really angry That yes, I get that it works. You don't need three of those besides that's about commit message anyway Right and that again is more face rolling. Hi guys And then like you have like well the warcraft references and commit messages and then you have this one nice commit message at the bottom I Had to put this in there because I was going insane just looking at this list of stuff You're bad at formatting as well not not only can you not write commit messages? You're bad at formatting. You see this This is Vim. It's the best text editor around Emax is a similar to Vim Now when you use Vim to write a message and it's too long it gets cut off The color there shows you same way second line blank lines If you derp and herp and you write in the black line it highlights in red for you again all these things are there for a Reason there's a lot of parts of git that rely on you following this form I think correctly if you don't I will show you what happens Just There is more to life than commit messages Right. Let's talk about graphs because graphs are pretty See if this graph this is in history Yes, most of you have seen something that looks like this big history though.  Well angular is a bit big project look at what angular does Granted they have a singular branch floating around here and there And I did pick the best part of angular show you but nowhere absolutely nowhere do they have anything even close to this Right. I searched for every line that contains either a vertical bar and have forward slash or a backslash No, JS twelve thousand lines Angular eight hundred lines.  The first one is but merging is easy now when you say but merging is easy What everyone else here to say Is I can't be bothered to read about my tools Okay, fine Then some of you are like well, but the commits remain logically separate if you merge and you leave the branch floating around, right? I mean, I might merge the branch into another version some point and Then when you say that all I'm hearing is I'm bad at writing commit messages And I'm gonna merge things will you know the ad have much conflicts all over the place And also what is that cherry big thing you speak of I don't have a ladder and we don't have cherry trees in Singapore Of course you also have other reasons where people give me why they have such bad good history like well I'm working with this person That makes it a shared history, right? I'm not supposed to override shared history When you say that what I hear I Think things are black and white. They can only ever use merge or rebase. You can't ever like you know Perhaps rebase a feature branch right before you merge it. No, you guys have never heard of that clearly Of course, you have all these people like but I work in a really big team you see and like Merging is hard, but not as hard as rebasing. I mean, I don't have to read my commit 700 times when I rebase 700 commits a y You're abasing 700 commits Be when you say that all I hear is the base is too hard and we have no time Also, we don't have this guy called a repos to it Which actually a lot of people don't have which is also why your history sucks Nobody should ever be able to merge into develop even after code review except one or two people do it And obviously when you have a small team of people up to maybe 10 20 people really depends on how big your team is and how many Develop branches you want to have but seriously people shouldn't be allowed to push into a branch other than their own feature branches Their own dev branches The moment you have a serious branch It has to be one guy doing it so that you never have a conflict because that guy just pulls your stuff He rebases he merges he pulls your stuff.  That sounds perfectly fine in which case help me Obi-Wan You're only home Help is out there Talk to someone who knows a lot about get they will tell you how to do things the proper way without having bad history Of course, you have also these this class of people is the best class of people ever some of them are trolled Some of them really believe in it. They're like, but I really like merging willy-milly And randomly capitalizing my commit messages And using emoji in my commit messages pile of poop And not following the 50s or a 72 rule Which by the way was the length of the lines you're supposed to follow first line 50 characters second line 0 Third line onwards 72 Vim auto wraps that for you Most sane editors auto wrap that for you, but you can override it and a lot of people do I Mean that's fine. If you want to do all these things you want to randomly capitalize on all that stuff Hurry on go ahead and do what you want to do just don't expect that they just don't let me get near your rapper because I'll just Murder you or something and don't expect sane people out there to work on your projects Because the biggest problem with having really really really bad history Is if I'm trying to find out the commit that caused the bug if I'm trying to do a get by sect Which I think a lot of people don't talk about enough When I have a merge in that in there that makes the bicec really annoying Of course, you all have also these people like bicec, but why would I want to do bicec? I've see I for a reason.   Bye I only I want thing to add to that He can't 26 September submit talks vote for talks attend ticket sales opening next week


What's going on guys got Kyle here with Layton sports cards, and we are ripping this is three boxes for Vincent G Got one twenty twenty two elite basketball. We've got one twenty twenty two a revolution basketball And we've got one twenty twenty two twenty twenty three Panini prism giraffe picks basketball We'll start with the draft picks then we'll move on Good luck Vincent Let's see what we got. I think we are gonna be full guys. I think we are gonna be full Let me change the let me change the logo or the top here. I think we are full guys Thank you guys so much for keeping me busy today We'll have more group breaks tonight with Sam. It should be some more personals as well tomorrow. I believe I believe Alright, it's good luck Vincent on this one I'm gonna start with the Giraffe picks hobby. Let's do it. Let's see a palo See a palo out of each box. That'd be cool. Good luck looking for four autos Got a David Roddy on the base Our first silver is gonna be Trevor Kiehl's the Knicks rookie there and Our first auto is gonna be purple cracked ice of Doran Sebron Doran Sebron penmanship auto there that is number to 99 We've got Jayden Ivy hyper rookie blue cracked ice Isaiah Thomas bad boy Isaiah Thomas to 99 Jabari Smith Instant impact is Tari eason on the silver Jabari Walker and Shaden Sharp base. We got a silver Jordan pool our second auto is gonna be a Isaiah Brockington out of Iowa State there on the hyper auto Those are not numbered on the hyper Pat Ewing hyper rookie Caleb Houston hyper for the magic Paul George Silver is Kennedy Chandler and Looks like a base auto coming up is gonna be Grant Golden Out of Richmond there Sensational six base auto Bryce McGowan hyper Red is Jaylin Williams. This is Jay will for the Thunder. They got two Jaylin Williams is the 299 There's a hyper widescreen of chat nice check there Baji and Jimmy Butler last pack of the draft picks got silver Dominique National pride Nicola Joe, uh, Jovic. I just Serbia Serbia on the fly. I thought it was Serbia and Our last auto is gonna be sensational signatures auto Musa Diabata. That is the Clippers rookie on the hyper auto not numbered out of Michigan Hyper Orlando Robinson Jerry West and we've got a tie-tie Washington that is orange pulsar Tie-tie Washington number to 49. That'd be a variation as well Bill Russell throwback Chet and Clyde Drexler All right now we move on to the elite four-year Vincent. Good luck See if we can find a pin pal auto in here empty Good luck. Good luck Guy rents a 99 Deontay Murray die-cut Kate Cunningham That VV orange tray man Joe Ellen bead. I don't know if Joe. Well is gonna be able to do it against Boston, man. I Think they figured it out. God spellbound rookie or sorry not rookie spellbound. There's the R in Anthony Edwards Spellbound Edwards. There's a power formulas debunk on the die-cut power formulas of Steph Tatum. There's a orange Grayson Allen Grayson Allen was not my favorite player when he was at Duke man. He was always tripping Florida State players It's always for a state for some reason. It's just turned around trey young there for no reason at all It's a 49. We got a class of 2022 auto tie-tie Washington rookie yearbook auto Is red to 49 nice color match there for the Rockets It's high-tie during base there. There's a star status of Yanis Morvettes acetate This is the Mantis Sabonis glass masters He is man. I think he led the league and rebounds us here right Sabonis kind of surprising He was killing it man Kings just couldn't get it done unfortunately got purple to 49 Rudy Gobert. Here's a rookie of Nicola Jovic You get two rookies per box in the lead. There's an orange rookie of tie-tie Washington There's a Zion orange spellbound die-cut The I in Zion. I think could be the I on Williamson. I guess I think it's Zion though It's kind of weird how sometimes they use the last name sometimes use the first name on those There's an orange clink a Pella veterans Power formulas AD had a nice game last night against the Warriors Warriors got blown out last night, man They were up at one point like before half and then it just got out of hand got out of hand quick Things really escalated Full throttle full throttle there Trey young orange Bruce Brown body healed more veterans Acetate here. They like to stick This one is going to be Luca Donchich on the elite deck Acetate there's an instant impact auto this time. It's going to be Larry Johnson impact impressions Larry Johnson on the auto for the throwback Hornets that Hornets team makes me think a space jam immediately Those old Hornets jerseys. There's another rookie. It is going to be Blake Wesley second rookie there and veterans Alright Vincent got one more box for you. It's the 22 23 revolution basketball Good luck. Let's see what we got see if we can get a galactic out of here You get a galactic case hit work events Williams on the front is Trey man on the Sunburst number to 75 Had a Trey man to ten in the last box kind of wild Last two numbers have been Trey man. We got a supernova Luca There's a Jeremy so on on the groove rookie not numbered groove Veterans woman rookie. There's a groove of Zach Levine. There's a shade and sharp shockwave rookie Nice rookie there for the Blazers. We got a astro of Deontay Murray the Franz Johnny Davis. There is a fractal Christian Coloco rookie or sorry That's cosmic to 99 99 on the rookie Coloco. There's a rookie revolution Jake. LaRavia a Mike Conley astro Yeah, I got you Luke. I Gotcha. I got Pete up next then Stefan and then Luke and then Michael s I Got Pete up next with some archives won't take too long and then I got Stefan and Then Luke and then Michael. There's an astro rookie Johnny Davis. It's packed. Good luck Vincent. I got you Luke. Good luck I got you. We'll get going here soon Astro Anthony Simons and looks like an auto It is gonna be a rookie auto Jabari Smith, Jr. Nice hit there Vincent Last pack of the break base auto Jabari Smith Very nice one there Autos are about one every other box in a revolution. So very nice hit on the rookie Jabari Dame and Kawhi on the back. All right Vincent that will do it for your three boxes of basketball there Thank you so much. We'll get them right out to you


How long did you train to be in John Wick? Oh, you took my question, you asked me.  How long have I trained? I trained for seven days, like, but only 45 minutes.  Well, I need to do, like, my moves with, like, with trainers there, you know, first time without, without Keanu, and after, like, last three times with Keanu, and we practice together. How'd you get the call? How did you get that call?  Bobon is right here sitting next to me. No, they say, give me the nicest guy over here. No, yeah. Yeah, that's more like it.


Good. Okay. So I modified the title a little bit. I just found out this morning that I need to leave this evening, and so I figured that I would give you my entire input in this 20-minute section since I won't have time for dialogue, and since I wasn't in the previous session because I was rearranging flights. Sorry about that. So just to summarize, I think a key issue at this juncture for us all in terms of implementation of genomic medicine is implementation science, and this one slide kind of summarizes the points that I'll make that really we need for major investments if we're to go from our current stage of pioneering genomic medicine into the early adoption phase. So this is where we're at under, you know, at least from my standpoint, that we have been innovators and now we're starting to recruit early adopters, but we're very, very far away from seeing generalization of genomic medicine in routine practice. And so the strategies that are necessary, business logic has taught us, are quite different as a pioneer and an innovator from an early adopter from getting into the large majority or the early majority. Different strategies and approaches are needed. I'm going to focus on one homogeneous setting where I think genomic medicine makes sense today, and it is timely to talk about scale, and that is NICU and PICU, neonatal and pediatric intensive care units. Essentially, those are homogeneous setting, acutely ill infants, many of whom will have genetic diseases. This is the outlook for California, 35 million residents, only a total of 47 units that would need to be converted to genomic medicine to deliver genomic medicine to that entire population in this setting and affecting about 30,000 kids per year. So not something that's outlandish in terms of could we potentially do this within the next year or two. It's actually quite tractable, only 47 units. The economics are very favorable for implementation of genomic medicine in this setting. These are charges that are quite outdated, 2009, so six years old, and reflect level two through level four care, and at least initially, genomic medicine for neonates would be limited to level three and level four, where charges are going to be on the high end of these numbers. So the idea of implementing genome sequencing or exome sequencing at scale really would be a rounding error. So let's just look at the data for a second. Nothing like data. This is a unique area of need for genomic medicine. I know that the president's focus is heavily on adulthood cancers, but really if you think about genetic disease burden, the greatest genetic risk, obviously, is that conception, and then it sort of erodes exponentially through birth, and then it has a massive uptick again, because suddenly this human being has to operate without mom's accessory organs. And so with this massive uptick at birth, again, of the burden of genetic disease, and then again an exponential decay until we hit somatic mutation time late in life. So this really is a place of huge genetic disease burden. So let's look at the data. There really are only two published papers that I'm aware of that really look at whether we are ready for prime time in terms of delivery of genomic medicine in this setting. The first, just from last month, genetics in medicine, a group out of Melbourne, Australia, 80 infants, singleton exome sequencing delivered to them, and then all standard conventional testing. And the diagnosis rate, 58% by singleton exome versus 14% by collapsed all conventional tests. That's cytogenetics, arrays, fish, sanger sequencing, that sort of stuff. However, the time to diagnosis was 134 days, which clearly is not relevant much for NICU care. But despite that, there was a 19% change in management, so somewhat paradoxical. Second study is ours, which was funded by NHGRI and NICHD, excuse me, 35 infants in a single level for NICU. Amazingly enough, exactly the same rate of diagnosis. We got there the hard way with trio genomes as opposed to singleton exomes. Still not sure how they managed to get that with their singleton exomes, but hey, they must just be smarter than us. 9% by all collapsed standard methods. So again, very clear-cut improvement in diagnosis. We had troubles getting timeliness as well, not so much, but it was taking about 26 days for us on average, or actually it's the median, to enroll a baby. So they had to go through this series of steps where the diagnosis was not apparent. It raised to the level of a genetics consult, and then there was dialogue and eventually ascertainment that this baby might benefit. Despite that, though, 37% change in treatment, that's overall, that's not 37% of the 57%, that's 37% of the 35 kids. And so really, I think that we're here today in terms of our technology, that I don't know exactly where we're at on the curve, but I do think that in terms of short read sequencing, we pretty much are good enough to think about deploying this very broadly. Let's just look a little bit at what clinical utility means for a day 49 return of result. And the critical thing for me is this column here, quality-adjusted life years added. So you can read the numbers as well as I can. 17% palliative care guidance, one life saved, one patient in whom a NICU stay was expedited by a month, and two patients in whom major morbidity was avoided. And then we can add some sort of estimates of what the yield is in terms of quality-adjusted life years. Sorry. But really, if we look at something which is possible probably today, if we had ascertainment at birth, and then let's say a seven-day turnaround test, which could be quite feasible, we would achieve 94% diagnosis prior to discharge instead of 37. And just looking at the numbers based on our historical data, a 31% palliative care guidance, unlikely that we would change that one life saved to more, but possibly, but certainly we would increase the number of folk who had a prolonged NICU stay. So I think even with the data at hand, although I can't do statistical analysis on this and show statistical significance, the data is starting to become compelling in terms of there's a mature opportunity here, which we ought to consider realizing. So I just took a new job. I'm seven months there. We're starting from scratch with a brand new research institute in 2016 that exists to deliver genomic medicine to this hospital, which is the sixth largest children's hospital in California. This is our catchment area. It's about 4 million people. And so I'm thinking about these bottlenecks and problems a lot incessantly, in fact. And from a practical standpoint, how do we implement things at scale that we know are highly likely to work? We've done some modeling in terms of, again, quality-adjusted life here saved. How many sequences we would need per year to get us there? And you can see the numbers are quite remarkable. This is based on fairly conservative estimates and based on the published data in terms of diagnostic rates and then the consequences of those for care. So some things we've already figured out and are ready to go. Others we haven't. So one is that we now have methods that can give us genome sequences, and that's from consent through return of result in a timely manner, even for acutely ill infants. Second of all, we have instruments now that are population scalable. I would point out that we have a huge problem here, which is that you can either have cost-effectiveness or speed. Today we don't have both. So we need to work on that. But there's lots of bits that we haven't figured out, and that's really what I want to focus in on. So first one is timely patient ascertainment. As I told you, in the studies that we've looked at today, it took about two weeks to three weeks to ascertain a patient and enroll them for genome sequencing. One of the problems is that no phenotypic feature seems to enrich for diagnosis. And so clinicians struggle to understand where you deploy this. They're not ready yet maybe to think about giving it to all babies of, say, greater than 36 weeks gestation. And so one innovation that I think I'm keen to see us work on is the idea of a surveillance system that would trigger alerts for clinicians that a baby might benefit from a genome or an exome sequence. In order to do this, we don't need very much. We need a data model. That exists. Then we need an algorithm that exists. And then we just need to parameterize that with enough cases so that we can look at the area under the receiver operating characteristic curve and understand the sensitivity and specificity of that. This exists for sepsis. If you're a CERNR hospital in the United States, you can opt into this. And this will run dynamically on all patients under care and will send two levels of alert, the first one to a nurse, the second one to a clinician to say Mr. Jones in bed six to get checked out for sepsis. So something like this for genomic medicine, I think could be quite feasible. Second major problem we have is that we've been very successful in discovering genetic diseases. The list now is over 8,000 long. The problem being that no human being can contain that information. And his presentations, inheritance patterns, treatments, and so on prognosis and complications. Furthermore, we only have 23 genetic, 2300 genetic counselors. And so we have a gap here. I don't have the numbers for medical geneticists. I imagine it's somewhat similar. We do have these tools, which are first generation tools that can bridge that gap. These are algorithms, software tools that will take a set of clinical features and marry those to the entire OMEM database and thereby give something of a rank ordered differential diagnosis. However, one major problem with all of these is that they're not really modeled on empiric data. They're modeled on simulated data. And so two things that we really need are data driven models of genetic disease topologies in terms of the range of presentations and their temporal evolution, especially in infants and automated dynamic clinical feature extraction, very much akin to what happens with the sepsis alert. Third gap where I think it would make sense to focus some effort made by a famous by Elaine Mardis is the fact that analysis and interpretation is a bottleneck. Very fortunately, the ACMG and CAP, or maybe it's AMP, came up with computerizable guidelines for giving variant pathogenicity. Unfortunately, to my knowledge, nobody has yet automated these. It seems that most of this could be pre-computed. And if it was automated, we would be married with some of these types of tools that do a pretty good job of semi-automated, pardon my spelling there, auto-moleted, variant filtering. We could have something that could greatly accelerate the bandwidth of lab directors and other analysts. Gap 4, obviously one that we all cry much about in our tea leaves is the fact that we don't get paid for our work. But frankly, historically, what's been necessary is to have high quality evidence, which typically has meant randomized controlled studies. And I know that that's a radical idea for the diagnostics world. But we live in radical times in terms of the constraints of payors. And the other thing I think we haven't done very well is to get strong MD support from powerful MD lobbies. Much as we love geneticists, we don't have the clout of, say, cardiologists or neonatologists. And so we need to educate and garner support from our colleagues. And I don't foresee that there will be a problem with reimbursement, sort of carve outs. Once we've established that this is clinic has clinical utility and in certain settings, cost effectiveness. So to summarize some challenges and some solutions, timely patient ascertainment could be solved by an alert system, genome cost versus timeliness. Some what we just have to wait, both for Moore's law and for market forces, we need to pray for a competitive landscape, comprehensive differential diagnosis, a huge bottleneck. And as I've tried to show you, I think that we could largely automate this, certainly at first pass. And bear in mind that, you know, if we look at genomic medicine and we're talking about democratizing this, we're not talking about a few quaternary referral centers across the United States. We're looking at putting this in the hands of many, many, many physicians in hospitals who may not have medical geneticists. And so this may seem absurd to you, but I think it's going to be incredibly necessary if we're really to reach all of the needy kids. We have too few staff, expert staff, and we need targeted education of generalists, both nurse practitioners, certainly in an intensive care unit setting and an outpatient setting. And we very much need electronic clinical decision support. What I mean by that is you don't hand them a typical genetic test report, which for many MDs is largely unintelligible. What we need is clinical decision support that explains and walks them through the management plan, the counseling plan, et cetera. The last one I've mentioned. So just to get back to where I started, at four in the morning, this cartoon made a lot of sense. For the life of me, I can't understand why. So adoption of genomic medicine will require investments in implementation science. I think this is a new world. I think we've gone from basic research to translational research. I think implementation science is even further downstream. These are the components as I see it. We've got these researchers down in the left-hand corner. Many of their efforts will relate to computation. So both building software, but much more modeling large data sets to build predictive tools. We need teams and process engineering and versioning to implement at scale. That's pretty obvious. I've just mentioned this education and engagement. A lot of engagement, clinical decision support tools, and then very much, I believe, randomized controlled trials where we measure success and failure. Thank you very much. Okay. And just like for the last panel, we'll take a few minutes of questions if there are any immediate questions for Steven before we move on to the next speaker. Yes. So I have one question. So for rare disorders, when we're looking at therapies, enzyme replacement, we've used natural history data and then how you modify it. So is there a way, without doing a randomized clinical trial, you can look back at outcomes, collect that data, and then use with the new technique, rather than having to do a randomized clinical trial? Yes, there definitely is the ability to use historical information. It has caveats. It's not the gold standard, but I think it's going to be necessary, I think, to quote my colleague, John Lantos, we have extreme fragility of equipoise. And what I mean by that is that some of our neonatology colleagues are not willing to randomize to the control arm for diagnostic tests. I do think we need to differentiate between what I would call precision medicine and genomic diagnosis. And I think today is a ripe opportunity to think about implementation at scale of genomic diagnosis. I do think implementation of protocols that deliver precision medicine is a longer term need and requires a lot of thought and planning. For example, a precision palliative care plan might make a lot of sense, but that's not something I think we can just do today. It will take quite a while to get our heads around what those are and then how to implement them. So you mentioned, Stephen, that it would be relatively straightforward if laborious tasks to develop an algorithm based on real data versus speculative or simulated data. Do you have a feel for how many patients, how many centers, et cetera, would be needed in order to develop really robust algorithms that could be used throughout the country? I think provided we look at homogeneous groups and provided we ask targeted questions, the numbers are not outlandish. And so in particular, obviously my focus is on the infant at birth and within the first three months of life. So that's a very focused group. And there, I think maybe 20,000 individuals could give us a really nice, a really nice group. Having said that, you know, the historic point is a good one where we can use historic data largely to model that people have been receiving genetic diagnoses for decades. And so that could be a retrospective study. So just in follow-up, I wasn't clear if that focused target group you were looking at was all neonates or neonates and ICUs, where I see the latter as being a much more compelling argument than perhaps all neonates. Yes. Right now I think we can make compelling arguments for neonates, newborns, infants in general, in intensive care units, both PICUs and level three and level four NICUs. I'm not so sure about level two NICUs. Is there one more before we move on? Okay. I wanted to know, in your presentation, you suggested that the NICU-PICU population are mostly affected by single mutations. And I was wondering what's the evidence that that's the case, as opposed to, you know, maybe more complex genetic models of disease? Well, the evidence to date is really the two studies that I've shown you. I know that other groups have reported large series of exome cases, but they have generally involved patients in many age groups, but certainly in the two published studies that are reviewed, those were the overwhelming groups that were tractable today for genomic medicine. That's not to say that there are many, many other things that genomic information can help in that setting. Let's say nutritional status or organ maturation or early detection of onset of sepsis. You know, omic data can certainly do that. But here now today, if we're to say, what could we flip the switch on and what might the benefits be? This is a very clear cut case where I think we can make a good argument that this is ready for prime time. Okay. Thank you very much.