EP 244: Building the first n-of-1 ASO: The new frontier of rare disease with Timothy Yu of Boston Children’s Hospital

Hello and welcome to the Genetics Podcast. I'm your host, Patrick Short. My background is in population genomics and studying the genetic causes of rare disease. I did my PhD at the Sanger Institute and the University of Cambridge and have been in biotech since 2018, when I started cyanogenetics. Sonogenetics helps academic and industry researchers to run large scale genetic testing programs that speed up their clinical trials, generate data sets for the next big breakthrough, and give participants the best possible experience taking part in research. Each episode of the Genetics Podcast, we bring you insights from the leading minds in genetics and precision medicine, including household names and Nobel prize winners, as well as early career scientists and biotechs working on the next big breakthrough. Whether you are a scientist, entrepreneur, executive, patient advocate, or simply someone curious about how genetics shapes our world, you're in the right place. Thank you for listening and let's get started. Welcome, everyone, to the Genetics Podcast. I'm really excited to be here today with Dr. Timothy Yu from Boston Children's Hospital and Harvard Medical School. This is an episode I've been wanting to do for a really long time. Tim is one of the pioneers in really the most truly personalized form of genetic medicine in what you may have heard of as N of 1 diseases. These are the rarest of the rare. And people who listen to this podcast know that I've had. I've lost a child with a rare disease, and this is a group of people with such a high level of unmet need that traditionally the. Yeah, the. The commercial system has not really had an answer for. Because they're so rare. Tim, I think you probably are. Many people will know you from your role in developing the custom antisense oligonucleotide for Mila, young girl with Batten disease who became, I think, a landmark and an example in the field. But you've taken it orders of magnitude from there and, and I think people look to you as a, you know, as a pioneer of where we could take this in the future. So I'm really glad to have you today. Thanks for joining me. Thank you, Patrick, so much for having me. Really appreciate the kind words and it's been a privilege to work in the space. I'm really glad to talk to you about it. Could we start with the Mila story for people who aren't familiar with it? How did it come about? And you just, like, really take me back to that moment. What were you working on? And why did you decide to, you know, to work with Julia and kick off what I think has Been a revolution in the field. Glad to pat. So, back in 2017, I had just started my laboratory at Boston Children's Hospital. And we had started it built off of a legacy of getting to do, being lucky to be able to do some really exciting work with genome sequencing technologies to discover new causes of neurologic disease. And this is really very well familiar, I know, to you professionally and to many people in the field who are at least of a certain age. And above that, from, like, 2007 to 2017 was a really exciting time where we were just seeing the explosion of genomic technologies allowing us to read out the genome and then assign causes to a lot of diseases that physicians could only describe previously and by way of backwards background. I'm a neurologist by training and a geneticist and a neurobiologist by PhD practice. And this had been always one of those barriers that were frustratingly dividing the clinical world from the scientific world. Right. Being able to name the cause of the condition that you were seeing in the clinic, that just wasn't possible. So with that kind of backdrop, we worked as a field clearly in discovery mode in January of 2017. And a contact reached out to us, to my wife through Facebook, saying, hey, I just saw a post about a family that's looking for access to this newfangled genomic diagnostic technology, whole genome sequencing, because they have a really tragic case that needs expert help to try to solve. And that outreach, which happened on a Friday night that, you know, my wife turned to me and said, hey, look at this. A friend forwarded this to me. This family in Colorado needs help. Introduced me to a young girl named Mila Makovich, who had just been diagnosed in air quotes, diagnosed with a condition called Batten disease, a fatal, neurodegenerative, progressive condition of children. She was six years old at the time, and she had had several years of declining neurologic health, and she'd had a clinical workup, all of which were pointing towards this really esoteric but really terrible condition called batten disease. The reason that they had reached out for additional help, because they had arrived at a clinical diagnosis, was that the clinicians who had expertly figured out what it likely was, couldn't figure out what the genetic cause of it was, what the specific genetic diagnosis was. Standard genetic testing had failed. And so there you had us, as a young small lab working with this genetic diagnostic technology, now being asked to help apply it to a patient to help solve a case where existing testing had failed to find the mutation. And that case led us into places where we just really would have never expected. That's the backdrop. I spent a little bit of time on just to highlight how unexpected this was and let me then complete the story. Completing the story. As many people know now, we were a lab that had been lucky to be one of the very first early adopters of the whole genome sequencing. It was very hard to get back then on a clinical basis, so we were doing it routinely on a research basis. So we said, we can help here. And we had some expertise in using it to solve tricky cases. And we found out the answer, the genetic answer to this particular child's presentation. She had a very tricky mutation that we found on manual inspection to be deep, intronic and hidden away from the usual places where standard clinical testing could interrogate at that time. And a little mini victory dance is about being able to find the missing mutation was then quickly followed by the fact that, well, this is the sobering fact that this is simply completing an academic exercise for the child. She was still going to progress. There were still no treatments for this condition, and there was nothing that, having completed the diagnosis, there was nowhere else for the family to go. What we were lucky to realize was that the specific deep intronic mutation that we found in her actually mapped onto a neurobiological mechanism that we knew could actually lead to a treatment. She had a deep intronic mutation, creating a new splice site that broke the critical gene that causes CLN7 Batten disease. And now switching hats from the genetic detective hat to our neurobiology and our neurology hats. We were in the position to know that drugs called antisense oligonucleotides had just been approved for spinal muscular atrophy, and that the way that they worked was exactly what this child needed. The mechanism of action was exactly what this child needed. And so the bold idea at that point in 2017, because we made the diagnosis in two months, three months, was to take this diagnosis and turn it not from just an answer, but also now a direction to take it in a therapeutic direction and to say, let's try to make an antisense oligonucleotide drug to correct her mutation and hopefully help her. That's kind of how all this started. Yeah, I mean, it's a. It's an amazing story, and I wanted to understand some of the bumps along the way, like, and especially the ones that you weren't expecting or that have led to an additional insight that have helped you scale. Like, what was easy about it was printing the oligo easy but what, yeah. What was the hard part and what were the easy parts relative to your expectations? Yeah. So not to trivialize the complexity of the science and all the work that was done preceding this that we stood upon in order to make this work, but actually designing the drug to actually correct the spicing mutation in her was scientifically, knock on wood, surprisingly easy. We designed a dozen candidates in our first round and found that immediately two of them worked really, really well. And then from those we designed a dozen more. And all of those worked well and only incrementally better than the initial candidates. And before we knew it, in a very short order, we had some promising looking candidates and actually being able to show that you could rescue splicing in her cells, that you could now improve the health of her cells. These were standard laboratory things that we actually that fell in front of our experimental plan. It succumbed to our experimental mental plan very, very quickly. And I should say that doesn't always happen in science. Right. Usually science bench experiments, they fail more often than they work. But we did all that in about two months time. So that was actually surprisingly easy. What was really surprisingly hard? Well, it wasn't surprising to us that making a drug is hard. Making a clinical scale drug is a serious business and I don't want to trivialize it. So we knew that it was going to be difficult, but what we didn't expect was where the difficulties would lie. Right. We knew that going up and actually turning this into a clinical grade drug would require clinical grade manufacturing, clinical grade safety testing, and a whole area of things that we knew that we had never done before. It was surprising, but also heartening that we had a ton of help from folks who were expert in those things, who advised us and got us through it really efficiently. But some of the pieces that were more surprising about actually hang ups and hiccups in the road had to do with really this really painful but understandable question of liability. Yes. Right. That when we manufactured the drug, we had a lot of, we had a hard time convincing folks, well, what standing did we have to be manufacturing this drug for this purpose? What use would we apply it to? Would actually that were we being responsible in doing this and all those are reasonable questions and we had very reasonable answers to them. We had talked to our ethics, medical ethics committees, we Talked to our IRBs, we talked to the FDA, we had gotten all of the buy in. But who were we as an academic laboratory and a physician scientist? Sure, we have, we're from a known hospital. But CROs are not working, used to working with hospitals, so actually getting the manufacturer to release the drug to us, knowing that our intent was to use it to inject a patient, even knowing that we had all the blessings of the irb, the FDA and so forth, that was actually a significant challenge. The folks who were manufacturing it for us extended themselves quite a bit to make it happen. But at some point, like hard questions became really pressing and, you know, maybe a couple days before the delivery date, we might have received word that the project would have to be stopped because the risk to the parent company was too high. Those were successfully negotiated, thankfully, but not with a lot of. A lot of 11th hour phone calls. Sleepless nights. Yeah, sleepless, sleepless. Several successive days where we were not sure whether or not the drug we had painstakingly made and had lined up to start into animal toxicology studies the next, the next Wednesday would actually arrive in time. There were arguments about exactly how one needed to label the product to make sure that it was that its provenance was appropriately disclosed. I think it was initially described to be. The initial proposal was that it be labeled not for clinical use to protect the parties that had made it, which of course made no sense because everyone knew what we were doing with it. So being able to navigate all of these things into effect, find the right label. Right. I mean, these are. This is not science, but it was certainly unexpected, but happily something we found solutions to. Well, and that experience didn't scare you off by any means. You've expanded this, I understand, to more than 80 patients now, working with collaborators around the world. You're also looking at different parts of the toolkit. Can you talk a little bit about that expansion process? But also beyond asos, where are you seeing promise in treating this very long tail of patients in need? Oh, yeah, really, really glad to. First, it has been amazing to see over the last nine years this idea grow. And actually I don't take it at all as a foregone conclusion that that was what was going to happen. Yeah, I mean, I wondered after this, one might reasonably say after running a program like this, the best thing you could do is walk away while you're still ahead. Right. This was very clear to us, something that was appropriate to do ethically, compassionately in this situation. It was something that hadn't been done before and the question was, could it be pulled off? It was not clear whether it would just be a single existence proof, but then proved to be too difficult to scale or whether there would be some way to keep it up. So I actually do not take for granted the fact that we went from that first Anna 1 to to then N of 3 programs at Columbia and UMass, and then expansion quickly to 2050. And right now, I'm guessing there are probably about 100 patients worldwide that have been dosed under this type of mechanism. I do not take credit for running all those programs by any means, but the idea that it's been adopted by others and has worked to get to the point of investigational clinical administration is. That's pretty heroic. And I pat the community on the back for doing that. Not us per se. We've run ourselves four programs treating seven patients to date and have many more coming. But just the ratio between what we've done and the community has done is sort of shows how viral the idea is. I think that as a field, we are to set expectations still at the place of evaluating the success of these therapies. I do want to cap expectations there first is someone's done one, and can you do a couple more to show that it's repeatable and safety being the first consideration? But we all know that, and many of these are. Almost all of these are rolling out for neurologic conditions. And many neurologic conditions take time to read out. The next really critical question is once you can repeat it, then can you validate the efficacy? And I should say that we haven't done that yet at scale. Our first patient, Mila, eventually passed away from her disease, even though we think the drug helped forestall her worst symptoms and improved some of them for a time being. And for all of these amazing expansions that I just cited in the numbers, the jury is still out. The data isn't yet in as to whether or not ultimately they've worked. So I think the next inflection point is going to be over these next year or two, seeing the readouts from those small patient trials to be able to say, hey, is this working? I think it's amazing that these patients have been dosed largely safely today. Let's celebrate that. But then the really interesting thing to come imminently is when some of these programs might be declared sort of a relatively unmitigated success. We think we're getting close. We have one where we think actually we're on that cusp that we're writing up right now. But seeing that across a couple of programs, several programs, to really kind of fortify our belief in it, that's really the important thing. Yeah. And with these small numbers, how do you think about that? Because there's the Hopeful case of you know it when you see it, where it's clearly safe and it clearly has a dramatic effect. But you also have to think about everything in between. Are you bringing in real world data to look at patients like the ones you're treating and that you haven't been able to treat and how do they progress? I'd love to hear a little bit about how you think about the clinical evidence in this kind of really low end regime. Yep, yep. I think that this is something where we are very clearly building the plane as we're flying it. There have been very few of these n of 1 programs where we've been in the position to be treating a patient or a few patients with an N of one drug that isn't a disease, where there are validated biomarkers, where folks have demonstrated exactly that they're sensitive to clinical change and meaningful to patient lives and acceptable to regulators. So that does mean that, and that's almost by definition because if those measures have been developed, it usually means that someone is like a company has invested great resources to actually go and do that. And those are by definition the ones that the N of 1s which are really designed for orphan indications are not encountering very often. We think of this as needing to extract more from less. And you know, one of our cases I'll use as an example, our second ever program was in ataxatelangiectasia, ataxial telangiectasia, which apparently I even after working on it for seven years sometimes have a hard time pronouncing it's a multi system disease. Its primary challenge is neurodegeneration of the cerebellum. But in order to extract signal from individual patients as a field, we think that we have to throw the book at these individuals and track many different measures to try to capture objective change. We are following clinical rating scales, her neurologic symptoms that are her most prominent disabilities promised by the disease. This is a disease that if you're diagnosed with it at birth, you are promised to begin developing in coordination of your walking, your speaking, your swallowing, your ability to protect your airway, your ability to control your eye movements from ages 5 through 10. And each of those can be measured and quantified in clinical scales in a, well, semi quantified by clinical qualitative rating scales. And so we throw that, that's one of the books we throw at it. But that's not enough. That's a clinic visit with a rater a couple of times a year and there are error bars around inter rater reliability. What about more detailed longitudinal measures? What about wearables? Nupam Gupta, one of our collaborators, has hooked up wrist and ankle sensors to measure accelerometry patterns in these patients and that can be worn and to generate data for days at a time to support or refute evidence of clinically meaningful change. We're also looking at some basic things like biomarkers like neurofilament levels or alpha feta protein which track in this disease. Even basic things like your overall height and weight, somatic growth parameters in this condition are really affected. Children tend to be very, very small. We take a full court press and we measure all of these and then we look at their trajectories of our patient compared to natural history. I'll go ahead and give away the punchline that we've talked about it publicly but it's not yet in a peer reviewed manuscript yet but hopefully very soon that in that program I think it may be one of the very first successes, official successes that we'd like to declare. We'll see if our journal editors agree where she's been treated for six years and she's not shown decline. And we can show it using all of these different measures that I just described to convince folks I would love to hear a little bit about the N equals one Collaborative. This whole enterprise strikes me as it's very expensive to do in the sense that you know, you're on the frontier and all the things you described that you're measuring, plus the cost of goods. But it's also expensive in the sense that if you don't share, everybody's relearning the most challenging lessons over and over. And for me the, the central piece of the N equals one collaborative is let's share infrastructure, let's share learnings and, and I'd love to just hear a little bit more about that because I think it's an underappreciated part of what you're doing. Thanks, Patrick. We were really lucky to have folks who helped us launch Milasen. And I'm going to especially call out folks in a society that's called the Oligoclutide Therapeutic Society, a society that's existed for decades to nurture this budding field of oligonucleotide therapeutics. And there are many times over its history when it almost looked like it might not make it, but it sure really has made it in the last several years. And the OTS is the reason why there was a task force that was set up after we went through the Milson experience that we were fortunate to have. Folks from the ots, the then president, Art Krieg, the a past president, Anamika Arts Marousse, Jonathan Watts, Keith Gagnon. They gathered to form a task force to study Milasen and its implications and to bring additional OTS expertise to it. And that task force grew into the N of one collaborative like OTS and the N1C, that's what we call it by shorthand, is an independent, it's a nonprofit. It's meant to interact with physicians, scientists, industry, all alike, patients as well. And the idea is to help support others who may be interested in working in this space. Frankly, you might consider it a little bit of a survival mechanism for our lab because you can imagine the types of inquiries that we would get. There was like way more than we could handle. We knew that this was a space that would require lots of folks to chip into. And this is a group then of folks who would be willing to share their experiences and create more capacity to explore the space. Right. And it's been fascinating to see. I think the original folks that I that I mentioned were largely motivated to help academically and that was appropriate because this type of work had just been done once or a handful of times. You know, a case at Columbia, a case at UMass followed after me, listen. And so we very much were in that exploratory mode. But it's also attracted folks from industry who are leaning in more heavily. One of them is a nonprofit called the Anlorum foundation that was birthed out of Ionis and they've leaned into it in a big way to expand it because as they saw the initial academic led efforts looking like they were promising, then they said, well, let's do more of these. And another soon to be announced partnership. I'll just say for now I'll leave it a little bit obscure. But another large biopharma has also leaned in through this mechanism of the N of 1 collaborative to offer its technologies and expertise to help this community run more of these programs for the benefit of patients and for science and also frankly back with learnings coming back to the partners who are involved in the programs too. So it's been a really, it's been a really great way to amplify and connect the community. Yeah, I saw just a couple of days ago, we were recording this on 12th of June that Servy A is starting to work with and Lorem Foundation. I don't know if that was the one you had in mind or another One but that I just saw that one come across maybe a day or two ago. Survey has been a great champion and supporter in this space. The most recent to join alongside nlorem and there's more and I'll discuss yeah, I want to get your view on RNA versus and yeah maybe we can start with asos. There's a huge amount of progress. There's a huge amount that's known about safety profile, about chemistry of the RNA molecules but there's a lot of limitations. You would know the numbers better than me but probably single digit fraction of patients may be ASO amenable and then you have new things like gene editing that in theory may be access a much broader population but we know a lot less about it. And there's other concerns you might have like off target editing. How do you think about how much resource you put into continuing to, you know, build on what you've done in ASOS versus thinking about gene editing or other tools you may be thinking about. Great question and one of the things that's been really amazing through the N1C is to as as you say the technology has an aperture, right? You have to get through whether or not the ASO can splice modulating ASO can be used or a knockdown ASO can be used sometimes in very clever and intricate and elegant ways but oftentimes only 5 to 20% of the population might be applicable. I would say that having the N1C has allowed us to grow this space initially with ASOS enough to show that this is a viable, at least initially, a viable pilot compassionate activity. It has also shown it to be sufficiently impactful like the numbers of patients that we now know that 5 to 20% is not 100% but it's also not to be sneezed at and it's enough to track capital and further investment and partnerships like from Servia, like from Enlarm and others. And then this last piece that you raised Patrick is really key. Taking the lessons and the regulatory lessons and the ethical arguments and the strategies of patient platform and regulator partnership and extending it to other modalities. That's actually a place where NC was really, really thrilled to host leaders like Kieran and Becca who ran the N1 based editing program for Baby KJ last year. And to see that now as one of the additional modalities where N1C can lean in. We think that there are very complementary tools available in this N of 1 space in the toolbox. On one hand you have ASOS where this all started which have narrow applicability, but they're beautiful for some applications like the eye and the brain and the spinal cord and the liver. They do have an additional superpower of being inexpensive to manufacture, easy to ship around, and stable as heck. They will last for decades. And they're also reversible. So you can get leeway in running these programs knowing that you can run them in a somewhat exploratory dose ranging basis by titrating the dose up if necessary or pausing if necessary if you reach efficacy earlier than expected or toxicity that you didn't want. The new tools that now we've seen are possible to apply light based editing have very complementary strengths and a few complementary weaknesses. They're incredible in organs like the liver. They do offer the prospect of one and done dosing, although that's not nearly as easy to do as it is to say right there's getting the right doses and tuning the right dose is still important. The off targets are a different issue that have to be handled, but they're handled. Their costs of manufacturing are much higher and that's one of the big challenges in that space. But there are many other parts of it that are advantages like the wide applicability that in theory, like, you know, at least half of mutations, often for certain disease indications, should be amenable to a base editor and to a prime editor. It's a very, very large fraction, right? I won't say 100%, but a very, very large fraction. So each of these has different places in the toolbox and they're places where we're actually doing a lot of interesting work. I will make sure to cover at some point that, you know, N1C is involved in. A as one of the supporting nonprofits around a new initiative that I'm pleased to be involved in. It has started out of conversations between folks like David Liu and myself and Kieran Musunaro and Becca Aarons, Nicholas. It started out of conversations with those folks, plus folks like Kat Lutz at the Jackson Labs and the Rare Disease Translational center there, and Madeline Brown. And it's been catalyzed by a mentee of mine, Winston Yan. We're starting a new effort that mixes The N of one work that we've worked in for now almost 10 years with the editing work to create what we're calling a center for Therapeutic genetics. A partnership between these individuals that we're turning into a partnership between a formal institutional partnership that will take these incredible tools that David has invented and that Kiran and Becca have applied and structure their delivery to more N of 1 applications. Liver, brain, kidney. Amazing. Yeah. That is actually a super segue into probably my next question, which was going to be about how it sounded like at the moment we've got across the field as a whole. What I heard you saying earlier was we're not necessarily in a rush to scale because we have a lot of fundamental questions to answer. How safe is it? How does it work? But I think you also mentioned that you may be finding individual cases or pockets where maybe it is time to scale how for the either the future, once we do figure this out, or the present for these pockets of cases. What's the bottleneck now? I suspect it's less the manufacturing side and maybe more regulatory or commercial. I'd love to hear a little bit about that. You're right. I am being cautious about scale. That's not because we're exceedingly patient. We're actually pretty impatient people. But it's just the clinical and scientific reality. Right. We can't let our expectations outrun the data. And so scale is out there to be had if we can successfully navigate the next phases. And that's proving that this works. The really big bottleneck though, to being able to generate the data for that proof is in the regulatory and business model domain. And that's actually one of the things that's been most interesting about this space. I'm completely untrained in any of those issues. Right. All that good medical and PhD basic science training falls short when it thinks about what. But it's been really fascinating to actually explore this issue and offer our perspectives, which I think have really been able to sharpen the question for what's needed. Scaling really, really big. That's in the future. Let's put that aside for a second. Finding a vertical within the space that can be done in a sustainable way. That is the immediate goal to make this grow. So we have to scale and think big. But in order to do that, we have to start by thinking small and make one small sliver of it self sustainable. One of the ways that we can think about that is to think of use cases where you can build the business case around. One of those use cases is illustrated by this amazing example of Baby KJ where you have a monogenic liver disorder that manifests in neonates. You can screen for it, you can catch the patients immediately and you can diagnose them. In principle, the patient is right there in the NICU already available for you to work with if you've got a credible therapeutic strategy. And so finding them early in this synchronized way is actually a unicorn in medicine. Right. Most of the folks that we see in neurology clinic come to us at hugely varied stages of disease. But having them all at the same time with a clear diagnosis and a biochemical biomarker, that's a pretty special situation. That's a vertical that you can actually do a lot with. And Karen and Becca have done the pioneering work of thinking through that vertical really carefully and thinking, well, what would be needed to stand up a trial for patients like that and that disease Indication, describing what the scientific needs are for that indication have allowed them maybe with some encouragement from us, to talk to regulators about what, what would they actually need to accommodate to generate the scientific data package that we're talking about. And that's led to really interesting regulatory new initiatives like the Plausible Mechanisms Framework where they purpose built it to support a vertical like that. ASO is contributed to that framework too. Yeah. Could you tell people who aren't familiar with the framework? It's one of the biggest pieces of regulatory news I think in the last year or so in our space. Yeah. It'd be great if you could talk a little about what you, what the potential is you see there. Yeah. I'll throw out there first, is that in 2021, after several ASO programs had moved forward on an individualized, quote, unquote individualized basis, we got from the FDA a guidance that allowed for continued investigational work with individualized ASOs with individualized medicines. It was a pathway that allowed sponsors, typically it was even in the guidance expected to be academic sponsors, to run these programs on an experimental basis so that we could continue to generate data and the FDA could figure out, could control them, responsibility responsibly, oversee them responsibly, I should say, and the field could learn. The Plausible Mechanisms Framework was released in February 2026, and it was the natural next step from that first investigational guidance. It didn't just the original guidance was just around asos, the new guidance was around ASOS and base editing. And it was a guidance importantly for industry. Right. The subtitle of the Plasma Mechanisms Framework is Guidance for Industry. And that signifies something really important. The FDA is saying now we're beginning to think about not just how to allow these experiments to occur, but how to actually commercialize them. And that once you say that magic word that societally closes the loop where now you can imagine building a sustainable program not funded by just philanthropy or foundations or research grants, but to turn it into something that's Reimbursable they have stipulated that they understand there are now these platform technologies available like base editing, like asos, where you can make a drug that shows benefit for patients by correcting their root cause of disease. The principle is that if you're developing a drug that targets a very well known mechanism, a very plausible mechanism that should benefit patients with that condition, and we would argue that there's no more plausible mechanism than correcting the underlying DNA defects in a genetic disease, then you get certain allowances that you may be allowed to make a family of those drugs that are all closely related to each other, but without having to seek approval for each individual molecule, which is the way that the previous system has always, always worked. How that's actually rolled out. What are the safety data packages that you can use to try to cover a broad swath of, of a family of related conditions like those are all the double in the details, but at a super high level, Patrick. That's what the plasma mechanisms framework is promising to figure out. Last question that I have for you before we wrap up today is I would love to hear how you're thinking about linking the work, or you probably are already doing this linking the work you're doing with the other part of the field that's pushing on rapid genome sequencing and NICUs and PICUs as well as the even further upstream healthy newborn, you know, presumed healthy newborn screening and that Guardian and generation project. I think for many of these cases, the further upstream you get, the better. And you know that. I'd love to just hear about how you're thinking about merging these two worlds together over time. Yeah, that's a really, really good question. So finding these cases early at a time when the intervention is most meaningful, where you can actually learn something, that's the critical thing to making these work. I'll perhaps focus on the cases where we have, where we are applying those newborn sequencing programs to the nicu because those are places where you can actually now do you can stand up some of these verticals that we were describing. We already talked about NICU early identification of patients with liver diseases and feeding them into umbrella style and liver editing programs. I think that's a very, very clear linkage that we all see immediately. Where get further ahead of our skis is for other indications where that are not quite as easy to capture. What do we do with patients who have neurologic findings on a newborn screen, on an acute screen for which the outcome measures aren't as well defined as for the urea cycle disorders for which you might be you still can make a drug quickly, but it might not be quite as off the shelf as making a new guide RNA and really quickly testing it. That is a really important interface. We actually just recently got a grant from the NIH to study this problem to take kids that present in the NICU with the neurologic diseases to build a registry of those individuals to build, to connect them to the community that makes therapeutic for those conditions. That would include my lab, but also in Lorem or other entrants into this, into the field that are always popping up and then to track how they do and to turn this into an implementation study, right, to see what actually happens with this cohort of individuals who are diagnosed, given a diagnosis of something which is potentially correctable. We have to study that. It's not as clean as a umbrella trial that you can well define around a liver disorder, but it is more of a systems medical implementation problem. And it is beginning to look at exploring the boundaries of this that take you in really interesting directions. Look, there are some kids who are born with serious heart defects that make them eligible for a corrective surgery, right? And we have a system that's in place. It's not an investigational drug. It's not, there's no drug for those kids. But there is a system that's in place whereby medical professionals with significant scientists backing and an incredible array of immunosuppressive drugs can come in and operate on these kids to correct an underlying, say, heart defect. And it's a plan that's customized to that kid that doesn't require checking with an oversight body every step of the way. We've developed common protocols for doing these things. Even though it's not cut and dried as C kid and plugin to Intervention Kid A, Intervention A, you match it and you go, you have to customize it as you go. I think a really interesting question is that when you have a kid like that who's born with a serious, not a cardiac defect, but a serious genetic defect, some of them you can slot into a trial like a liver targeted baby KJ trial. But others might require more thought and more preoperative planning and more coordination. That is a practice that we have to begin collecting data on to figure out how well does it work, where does it fail, where does it succeed, how efficient is it? Are there ways of streamlining it and is there a way to gradually capture that type of activity that's right now happening through lots of different parties in the ecosystem and codify it and make it go faster and Smoother and safer every time. What's the right level of oversight over that process? Right now you have clinical care being handled by professional societies and hospital oversight mechanisms. You have the research studies for enrollment into an IRB protocol that then might allow them to investigate, making an investigational drug that is overseen by the fda. Those are all, at some level, necessary pieces. But is there a way to actually integrate it to make it smoother? I think that's a really interesting area where this is going to go in the next five years. Yeah, I think that's a amazing note to end on. It's a really great analogy as well. I mentioned to you before we started recording that I lost my daughter Hazel when she was about 10 days old. And, and she's exactly, actually the conventional path that you described. She had a heart defect. And we had a plan from 20 weeks of pregnancy of exactly what was going to happen. They were gonna, you know, what, how they were gonna operate on her. She passed away before they could operate. But we had the, like, they, they had. There was no science involved. They were, you know, there was a plan. And I, I think it's a really beautiful vision to where we could get to where genetic medicine is a part of, you know, part of that journey, just in the way that something like, you know, neonatal heart surgery would be. So I just. As we wrap up, I appreciate the work that you do, parents like me who've had children in this situation and, and you've worked with countless families. So I know you feel this directly. But yeah, your work really matters. So appreciate everything that you do and taking us today. Thanks so much for having me, Patrick. And as. As a physician and a scientist and a dad, I think all of us are really motivated in this space. So it is something that kind of is common to all of us and that actually what makes us so sticky and these problems so compelling for us too. Thank you. That's right. Well, thanks everybody, as always, for listening to the Genetics podcast and we'll see you next time. Thanks, as always, for tuning into the Genetics podcast. If you enjoyed today's conversation, the best way you can support the show is by sharing it with a friend or or colleague who might find it interesting as well. We'd also really appreciate if you could subscribe, rate and review us on Apple Podcasts, Spotify or wherever you listen to podcasts. This helps other people discover the show when they're searching for content on genetics, precision medicine or biotech. We always want to hear from you as well. If you have feedback or questions or want to be featured on the show, you can email us@podcastsonogenetics.com you can find me on LinkedIn. Patrick Short, you can find us as well Sonogenetics on LinkedIn or reach out on Instagram. Hegenetics Podcast. And finally, a special thank you to the team behind the show who makes this possible. Joy Ismail produces and manages the show. And James Pierce from Selective Frequencies for his expert audio engineering. I'm Patrick Short, your host. Thanks again for listening and we'll see you next time on the Genetics podcast.