All right, great. Thanks everyone. Good afternoon. Happy to be here moderating a chat with the Lexeo Therapeutics team. Super topical time for the company after coming off solidifying their plans for their phase III program and FACM, we'll talk a lot about that, then we'll talk a little bit about probably PKP2 later. Maybe, I think we're going to get in the weeds fairly quickly on the regulatory stuff and the design of the pivotal and the Lexeo team's thoughts. I thought it'd be helpful, Nolan, if maybe you could just start off with some just brief opening remarks on where things are at with Lexeo, and maybe also level set and just talk about the data you've generated to date in FACM, and include some of the nuances we've talked about that I think will help inform your thinking on the pivotal and the patient selection for phase III. Yeah. Then we can do follow-ups. Thanks again for joining. Appreciate it. Great. Well, thanks for having us, Paul, and we appreciate it. As many know, Lexeo is a company focused on cardiac genetic medicines. Our most advanced program is treating Friedreich's ataxia, where we're having both an improvement in the cardiovascular component of the disease and the neurologic component of the disease coming out of data from our phase I/II study. We've undertaken an effort over the last several months to complete the protocol for our registrational study focused on an accelerated approval. This study is going to evaluate patients that have left ventricular mass index disease burden at two standard deviations or greater at a six-month time point initially for accelerated approval. We'll talk a little bit more about the data that we demonstrated in the phase I/II study because I think this is an important aspect of how we designed the pivotal both around effect size, endpoint profile, patient profile, and so on. Maybe Nani, I'll just pass it to you to speak to the data we've generated to date across the patients, in particular with abnormal LVMI. Thanks, Nolan. Happy to discuss that. The data that we've generated to date have really shown clinically meaningful and durable improvements in cardiac structure, this is particularly in patients with an elevated LVMI at baseline, this is the population that's most relevant to our pivotal study. If you look at the patients with the elevated LVMI, we saw an 18% reduction in LVMI at six months, 23% at 12 months, with even greater reductions of 28% and 33% respectively in the high-dose cohort at six and 12 months. These are the effects that we've been seeing, they are really durable because many of these patients have normalized their LVMI, some are maintaining this benefit out to three years. Really a durable effect on disease modification. We're also seeing a strong indication on the biomarkers. 16 out of 17 patients showed either stabilization or reduced troponin in the study. This is a pretty favorable impact when you think about the troponin representing a sign of cardiac injury. Alongside, we've shown and demonstrated a good safety and well-tolerated safety profile for LX2006. As we think about this, I think there's one patient that really stands out in the phase I, phase II data. This is a patient who had quite advanced cardiomyopathy. Their ejection fraction was 35%, following LX2006 treatment, substantial improvement was noticed in this patient on multiple measures. An 83% reduction in troponin, a 48% reduction in LVMI, an increase, I think most importantly, from ejection fraction of 35%-74% at 18 months. This is a single patient, but it really illustrates the potential LX2006 has to meaningfully improve patients who may be even at a later stage of their FA cardiomyopathy disease. Beyond the heart, we've also seen a benefit on the mFARS scores in the LX2006 treated participants in the phase I/II studies. If you think of this and look at the patients that we've published now in a propensity-matched analysis from the UNIFAI registry, we're showing a difference analyzed progression difference of 2.3 points per year. This is very encouraging to see this data and support the potential broader use for LX2006 and hopefully even a more comprehensive label down the road. Awesome. Great. Thank you so much. Yeah, maybe to that point, level set too, and talk about the recent regulatory update. I think it also would be helpful to maybe also just talk about when you started engaging with CBER and how that dialogue evolved also as the leadership has changed. We started discussions about the accelerated approval path in late 2024. This is when we determined that left ventricular mass index was an appropriate surrogate endpoint for this disease. We had subsequent meetings in early 2025, and then in late 2025, really beginning to narrow on study design, patient population, structure of the approach. We had another meeting with the FDA in late 2025, and ultimately submitted a protocol out of that meeting to the FDA in Q1 of 2026. It probably took a bit longer from a response perspective than what we originally anticipated, but we ultimately did have quite a bit of back and forth with the FDA over the last few months, and we're able to finalize the protocol. We've been able to enroll the first patient in this registrational study within this month. They were enrolled last week. We've made quite a bit of progress despite, let's say, some delay in response from the FDA. We're still able to meet our guidance on having the first patient enrolled in the study by the end of the second quarter. Awesome. Okay, great. Maybe let's talk a little bit about just the threshold for clinical meaningfulness and statistical meaningfulness. Maybe to start, you guys have historically talked about a 10% reduction in LVMI as clinically meaningful. Maybe one, to clarify, where does that come from? Is that Lexeo's work? Is that something that you've presented to the FDA that they've agreed upon? What was involved in the decision to power the study at a 15% effect size? Was this driven by FDA feedback? Or again, what's the thought? Yeah, maybe I'll say a few words about the 10 versus 15, and then I'll pass it to Nani to talk about the study design and the statistical picture. The 10% effect size was the focus of several conversations and document exchanges with the FDA. There is a publication, and really one of the seminal publications for mortality in FA, demonstrating that a 10% increase in left ventricular mass index is linked to a 20% increase in the likelihood of mortality from FACM. This was really the basis of the conversation on the 10% effect size with the FDA. There's never been a different number discussed with them. This 10% remains the target number from a treatment effect perspective. That's really the clinically meaningful threshold in FA, and nothing has changed with respect to that. Now, with regards to how we design the study, I will pass it to Nani, our CMO, to speak to the 15% and how we thought about that. I would note, obviously he just spoke through, we're at a 28% improvement on LVMI at six months. From our perspective, a 15% number really looks like a slam dunk study. There's a few factors that go into this that we can talk through, some nuances, but I would argue that the 28% could even be an underestimate of the effect size at six months given some of the dynamics we'll talk about on an individual patient basis. Maybe, Nani, you can just talk to some of the stats and effect size parts of this. Yeah, I think you're on mute, Nani. It's all good. I do that once a call. The rationale Nolan kind of started the conversation that if you look at just our phase I/II data, and you look at on average, patients with an abnormal baseline LVMI, and I think that's one of the key things here, achieved an 18% reduction in LVMI at six months. The higher dose cohorts, if you look at the dose 2 and 3 cohorts, we saw even a greater reduction of 28% at six months. That's the dose that we're taking into our pivotal study and again, making sure that these patients are greater than 2 standard deviations above the mean when it comes to the enrollment criteria. Even though we've seen some deepening later on, it's very minimal and really the six-month endpoint remains a tangible endpoint. I think there's been also some discussion about responder analysis. I think it's important to understand that this is the mean population, a continuous variable as a mean change of the population from baseline, compared to the comparator group. I think it's important to recognize those. When we think about how we looked at the phase I, phase II data, I think there is a missed fact of this patient, one of the patients, patient number 11, where the data was missing for six months because the patient missed their appointment for their imaging because of a hurricane. As a result, we assumed the three-month endpoint, which was just about 10%, as their carry forward. If you look at what they then did at nine months, and you start from baseline to three months to nine months, it's pretty much a straight line going down. If you re-estimate that patient on that line to suggest that, "Hey, what would that look like?" That would be much closer to 20, 25%. At that point, that's where we get the 28% from for the six-month overarching reduction. When you take that into account, then after that, we looked at all the different variability that we've seen in not just our study, but also in published data. One of the data sets that Nolan just mentioned, actually, and some of the other studies that have documented LVMI distributions. When we take a look at all that variability, we then ran a number of Monte Carlo simulations, actually about 10,000 Monte Carlo simulations. Nolan, if you want, Lou, if you want to go to that slide, you can. If you look at it, basically if we take that threshold of 15%, assuming that 28% reduction that I talked about, 99% of the time you land pretty much at hitting the 15% LVMI reduction in the threshold. We feel that given those simulations, the variability that we have seen in our data, in other published data, there's a consistency to the assumptions that we've made that we feel very confident after running these simulations that we can match and math and get the distribution we need to get to that 15% threshold. We've also seen initially the patients coming into Clarity and where they stand when it comes to their overall baseline LVMI. Again inducing confidence in us that we can bring that distribution to life, which will get us to that 15% LVMI reduction. Yeah. Okay. Go ahead. If I can just punctuate another point. Look, we're at almost double the effect size that we need to achieve in the trial, and that's with an imputed, therefore underestimated value in one of the patients. We'd be at more than double the needed effect size. I think from our point of view, the trade-off of designing a study around 15%, relative to the size of the study that we're going to be running. Again, this looks to us like a slam dunk study here. Again, we're at 28% with a underestimated value in one of the patients. It really looks like an effect size here that we can be very confident in. The other factor I would note is, as we come into this study, we have patients that will be crossing over from CLARITY-FA, which is our natural history study. We also have an understanding of the existing LVMI disease burden that's likely to find its way into the treatment study. We know that those patients do have meaningful LVMI burden. We know they have enough disease burden to improve by more than 15%. I think the combination of the effect size that we're observing, combined with an understanding of the baseline characteristics of the patients that are likely to enroll in this clinical trial, the two together, I think give us a lot of confidence that this is a slam dunk study for us at 6 months. Yep. Okay. Makes sense, Nolan. Thank you. When you guys are powering at 15%, what are the key assumptions in that? What are you assuming for the severity of the population that you end up with in the pivotal versus the phase I/II, and do you feel like you have enough information here, given the kind of small Ns and subsets to sort of make a good assumption around variance or other key variables? Yeah. I think if you look at the assumptions that we just talked about, it's really the distribution at the end of the day, Paul. That's what you would have to strike to get that similar effect size that we have seen in the phase I, II trials, and also in these simulations and the assumptions we've made in the simulations. Certainly, given what we are enrolling into CLARITY, because remember that we have patients that were coming into CLARITY that were then going to feed into SUNRISE-FA, and they had the same inclusion criteria as the pivotal study. As we look at the initial data set that's in CLARITY currently, and those patients, when we look at those distributions, we're pretty comfortable and confident that those patients that are coming in are already starting to represent these LVMIs that we have seen in our phase I, phase II, and at least similar, or in some cases actually even worse. That's important because these are the patients who are going to have the room to give benefits, so to speak, on the therapy. We know that the greater LVMI and the greater the starting point, the greater the chance that you will have that benefit down the road. We're already starting to see that population coming in. That's actually the driver of the confidence that we can meet this 15% endpoint. Yeah. Okay. Makes a lot of sense, guys. Thank you. On the assumptions for the control arm, maybe before we even get into the just sort of what we know about LVMI test retest variability, if there should be any change in control, do you want to just give a little bit of context around the FDA dialogue here, and how you went from a pure single arm study to a study now with two arms with this concurrent untreated control? What's the rationale there? Yeah. Yeah. I think there are some concepts that evolved a bit during our conversation with the FDA. From our point of view, there wasn't a wholesale or fundamental change in their position. There was a single arm study we discussed, but it was always relative to a natural history control. In fact, CLARITY-FA, the study that we're describing that's now, in effect, a feeder study, was launched originally as a natural history control to the single-arm study. As the conversation advanced with the FDA, they wanted to find ways to reduce sources of bias. Having an untreated arm of the study that had the same approach to assessments, the same assessor practices, and so on, at the same sites would reduce sources of bias and how the patients were being evaluated. The other difference is, obviously with the separate studies, that the PI could choose which patient goes into the treatment study, which patient goes into the natural history. With this approach that we have in this trial, we have a random allocation, it removes the PI choice of which patient goes into which aspect of the study. Ideally, reducing bias in that regard, but also potentially resulting in a balance of patients across the untreated and the treated arms, so we can have the most confidence, and everyone can have the most confidence in the effect across the disease. That there, for example, aren't sicker patients in the treatment arm than in the natural history arm. Right. I think those are a few of the factors that went into this. From our point of view, that was a design change that we were comfortable with. Functionally, the external natural history relative to the untreated arm is not materially different, did not result in a materially larger or more complex study. We still have patients that do not have a sham procedure or placebo or anything of that type in the trial, which was very important to the patient community. I think we landed in a good place with regards to bridging the gap between the FDA's comments on needing to reduce sources of bias, but also not having a placebo or a sham procedure included in the trial. Yeah. Okay. Going back to the powering discussion, what do you assume from that Sham group, and what evidence can you point to people that sort of shows that the test-retest for LVMI measurements in this population should have little noise or I don't know. It seems silly because this should be objective, right? Is there any chance that someone could scan with a very high number and then kind of randomly go down 10% the next time? What data can we look at to Narinder, do you want to say a few words about that? There's certainly natural history observational data, Will, that suggests that there is no change, especially in a six-month period. When you do see some change, and it never really reaches to that 10% threshold, even actually in some of the published data, when you see it even change to some degree, it's because either imaging technology is different, you've gone from MRI to echo, or there are different MRIs being done, different inter-observer variability plays into it. All of that, but it's never a significant quote-unquote morphologic change that's actually occurring in the LVMI. In our study, we're making sure that we avoid such a thing because we have a core lab that's reading our MR, and they're all on MRI, by the way, so it's not echo or MRI. It's all MRI. It's a core lab that uses very advanced technology to make sure that there's consistency in measurements across the various measurements of the same patient and across all the different patients. It also then controls for inter-observer variability. Okay. Great. Makes sense. Okay. Very good. Just to clarify one more thing on the primary analysis. Does the responder rate no longer matter? Obviously, you want as many patients as possible, if not all to respond, but from a regulatory perspective. Yeah. That was a misunderstanding of some kind. There was a discussion of a responder rate for a prior frataxin expression endpoint, and it was binary. Either you had more- Right frataxin post-treatment, or you had less. That was discussed as a responder rate. The LVMI was always a continuous variable. I see towards an average, that has never changed. The design of this study with respect to LVMI and the approach to evaluate it numerically has been consistent throughout our discussion, both with the agency and with Wall Street. Yeah. Okay. Thank you, Nolan. Appreciate it. Yeah, maybe you've already sort of alluded to this, do you want to talk a little bit more about enrollment in Clarity? I guess, what have you seen so far, and what is your confidence that you can find enough of these very high LVMI patients and meet your guidance on data timelines? Yeah. Okay. Look, we have a meaningful double-digit number of patients enrolled in CLARITY-FA. I think we have to go through the process of those patients having their neutralizing antibody tests, and then consent them into the registrational trial. I think you can see just from the timing at which we announced our regulatory update and the trial design to which within, I think it's a week or two, we have the first patient enrolled. You can see that we have made a lot of progress on the enrollment front with the sites that are ultimately in our treatment study. I think we're progressing well there and have a lot of confidence. What that also means is we have, because it's a natural history study, we have visibility into the baseline characteristics of the patients in that natural history study. As we agreed on this approach, as we work towards the 15%, we had an understanding of the underlying disease burden from an LVMI perspective. Right. The understanding the patients have enough LVMI disease burden to improve by more than 15%. I think we can confidently say, let's say on average, the patient profiles in LVMI that are reflected in our, at least in CLARITY-FA, appear to be even further along from an LVMI perspective than in our phase I/II study from a disease burden point of view. I think from an ability to improve substantially, we have a good understanding of that picture as it sits today, and we'll be working to move as many of those patients over to the treatment study that we can in the near term. We're working across 19 sites in various countries. These are some of the top FA treatment centers globally. Many of these centers, especially outside of the U.S., they've not had clinical trials there yet. There's a substantial interest for a lot of those patients, both in the U.S. but also outside of the U.S., to access a treatment like this, and we're seeing that in terms of our enrollment progress and speed as well. Yeah. Okay. Great. Good stuff. Do you want to briefly just talk about the competitive landscape in FA? There's other players talking about disease modification, like- Yeah Larimar had an update today, design, and just what's your thought there, and how does that sort of shape where- Yeah Lexeo fits in over time? Yeah. Look, I think obviously, one of the challenges in Friedreich's ataxia as a disease has always been that the different components of the disease have different levels of technical complexity associated with addressing them. From our point of view, the cause of death in the disease is the cardiac disease. We want to first focus there, prevent patients from progressing into later stages of heart failure, that the patients live long enough to benefit from future cerebellum-focused treatments, which we knew would take a lot longer to advance because of the technical complexity. I think that that's the picture that's playing out now. We have the most advanced therapy, treating the cardiac disease at a very meaningful effect size. Whether you look at LVMI, you look at, for example, ejection fraction troponin, you look across these endpoints, we think we're having a very meaningful impact on this disease. I think ultimately you'll see, obviously with the abnormal patients all returning into the normal range, you're seeing an ability to correct the cardiac disease from a biomarker perspective. I hope over time we also see this improvement in mortality and so on. Our therapy was designed with a ubiquitous promoter where we're expressing frataxin not only in the heart but in skeletal muscle, likely in dorsal root ganglia as well, and it was designed that way purposefully so that we could have a broader impact on other aspects of the disease than just the heart. As a result- Yeah we're seeing about a 2.5 point improvement in mFARS, which is a neurologic scale, which is roughly equivalent to the commercially approved treatment today. I think we're impacting both the cardiac and aspects of the neurologic disease. I would say that admittedly, it's not a cerebellum-targeted treatment option today. We have started to look at other approaches. Notably, we presented data at ASGCT this year showing that sequential dosing of a gene therapy is possible. What I mean by that is a systemically administered vector followed by a brain-targeted vector, and we evaluated both intracisternal administration and we evaluated intraparenchymal administration. In both cases, the gene therapy reached its target of transducing the cerebellum. The point I'm making is that the introduction of LX2006 can be complemented with other CNS-focused approaches in the future. I would argue that we're advancing the best-in-class cardiac treatment, and this would need to potentially in the future, to the extent this is de-risked in the right way, can be paired with a best-in-class neurologic option, whether it's one of the gene therapy solutions or one of the non-gene therapy solutions. It's not necessarily my understanding that every therapeutic option out there that's treating FA is a direct competitor to one another. There's nothing to prevent a patient that's been treated with the gene therapy from receiving one of the other modalities. Even as I described, a patient treated with LX2006 may still be able to benefit from a dentate nucleus approach as a standalone thereafter. I think there's still a lot to play out here in the competitive landscape. To my knowledge, we have a handful of patients that have been dosed with any other gene therapy. I think from an efficacy signal perspective, I think there's still more to look for here with some of the other treatments. I think we're just going to be waiting to see how the competitive landscape plays out. I think it's always great to have more options for patients, particularly where they're complementary to one another, and they can address different components of the disease in combination. Yeah. Okay, great. One last question on FA that I missed, then we can briefly talk about PKP2, but just as it relates to the pivotal study, I think you've talked about two dynamics I wanted to just kind of get into. One was that there's this opportunity for a blinded interim sample size re-estimation if needed. Maybe talk about just when that happens and the mechanics and scenarios around that. Second, I think you're allowing patients to cross over from the untreated arm to drug at six months. Yeah, maybe not connected, but comment on that as well. Does that influence your ability to look at the 12-month data as a backup option if the six-month data was less robust than expected? Realize there's two questions in there. Yeah Just to round out this discussion. Do you want to take the first one, and maybe I'll try to take the second? Yeah, sure. If you look at the question you asked about sample size re-estimation of blinded fashion, that would occur when half the population has reached six months, their six-month endpoint. Basically we would have looked at half the population of blinded weight to understand what kind of blinded change we're seeing, and that's where the DMC will assess the data and make a recommendation regarding a sample size re-estimation. What I'll say is that given where we are right now and given the standard deviations that we have thus far assumed in our simulations and what we have seen in our trial, if those assumptions hold up and those standard deviation across the measurements hold up, the chance that we will require a sample size re-estimation to occur is extremely small. That's, I think, the punchline there, that if everything holds up that we have talked about, it is an incredibly small probability that we will need to re-estimate or change the sample size in any way. That's the big thing there. What I'd say on the question that you're asking is the patients that are crossing over, I think one, from an ethics perspective, to have patients stay in an untreated sort of set up for a meaningful amount of time. There are some questions there. More importantly is this. The untreated arm is designed to show that LVMI does not spontaneously change. We're going to be pulling data in support of that, both from our own study, those untreated patients. There are untreated patients in CLARITY-FA, some of which have been in the study for quite a long time. We have data, therefore, in CLARITY-FA supporting the idea that LVMI does not spontaneously improve. Obviously, there are other outside natural history databases. We have access to natural history data from Cornell. We have access to a study in Australia. We have access to a natural history registry at CHOP, so on. There's quite a bit of data out there with cardiac MRI that we can utilize to support the case that it does not spontaneously improve. I've just mentioned. Right Up to five data sources. To the extent we have patients that have crossed over and we're able to look at the longer time points, we have several different sources to utilize to support the case that even without those patients still on control at 12 months, that LVMI should not spontaneously improve so that the effect size that we see across all 26 patients is credible relative to that. It's not an efforts-based endpoint. Right. It's one that's very objective in its measurement approach. Yep. Okay. All great. Makes sense. Thank you guys for all the added detail. Yeah, maybe we can briefly just talk about PKP2 and you had some preliminary data this year on JP Morgan. How much additional data are we going to get next? What's your expectation for how that data might mature? Is this the type of disease where you think the effect could sort of expand over time, or is just durability sort of good enough to remain excited? Yeah. Maybe I'll say a few words and I'll ask Narinder to add. We showed at the JP Morgan conference this year, I believe, roughly 14% improvement in premature ventricular contractions versus a pre-treatment baseline. We showed about a 22% improvement in non-sustained ventricular tachycardia at the same time point. This is with most of the patients at six months of treatment follow-up at the highest dose, which is the earliest time point where we can evaluate efficacy. We also have a natural history study running alongside that trial. We saw about a 20% worsening in non-sustained ventricular tachycardia across that same time point. If you look at the delta between the 22% improvement and the 20% worsening, we're at about a 42% effect size on non-sustained ventricular tachycardia, which there's a discussion we're having about whether this is a surrogate or if this is even just a real clinical endpoint that we're evaluating that's very central to this disease. We're having about a 40% improvement in an endpoint that's highly clinically meaningful. We think that that's an interesting early signal. What we saw for the patients that were at longer follow-ups, so they're patients at nine months of treatment follow-up in that high-dose cohort, we saw about a 65% reduction in non-sustained ventricular tachycardia, which is a very meaningful effect size there. I think we are seeing that deepening over time. I think we're at a pretty meaningful effect size already. What we should have later this year is all of the patients at least 12 months of treatment follow-up. Maybe one will be short of that, but we'll have the vast majority of the dataset at 12 months or greater of treatment follow-up. I think we'll really get a sense of where the effect size is trending. I think to expect that all of the processes in respect to biology have all concluded themselves at six months would, and especially in a disease like this, would be very optimistic. I think we can continue to expect a deepening effect. I think the other thing we're looking for is consistency of effect across the patients, that we see improvement across the majority of patients in the disease. I think we're looking at data of all 10 patients. All of them should be at 12 months. We also have two patients that we've treated since the last data readout. There has not been six-month data seen for those patients yet either, and those last two patients are in our commercial manufacturing process. It's our highest potency process that those patients were dosed with as well. I think we're in good shape on the safety front as well. Obviously, no new safety updates either. Yeah. That's great, Nolan. What additional work needs to be done on endpoints and effect size on something like NSVT to get the FDA comfortable with the measure and comfortable with what constitutes a clinically meaningful benefit? I don't know, Nani, do you want to say a few words about that? Yeah, sure. The NSVT reduction we've seen so far, as Nolan said, is very compelling, and I think that's a more important endpoint if we think about it relative to PVCs. PVCs are incredibly variable. There's much more to PVCs than just maybe even a drug effect. There's a lot of patient variability. There's a lot of other things that can induce PVCs, just exercising, walking up the stairs, drinking a couple of cups of coffee, et cetera. There's a lot of variability that can occur. NSVT reduction really remains the main endpoint, and we think that's the compelling endpoint that we have to go after. As Nolan said, it's not just that maybe it's a surrogate, but even thinking about it as the formal confirmatory endpoint for a trial like this. From an efficacy and what we think is a compelling efficacy, 20% is a good bar. We've shown that bar currently in our data set. If you think about where the current standards of care are, they're kind of around that 20% or lower than that. Those are drugs like amiodarone, which are usually given at a high dose in these patients. They're not without their side effect issues, and it makes it very difficult for patients to stay on these types of drugs for long-term. We think that given to where the standard is currently, we can beat that and improve on that if we shoot for that 20% type of therapy with just one injection and hopefully, getting beyond what the patients will need from the current standard of care. Yeah. Okay, great. Is the plan to engage the FDA soon after this next data cut? Well, we have guided to a regulatory update this year. We expect to have one. We've not guided to the timing of that update yet. Obviously, we're describing a meaningful body of work to first validate the endpoint, the clinical meaningfulness of the endpoint. I have this question, is it a surrogate or is it just a clinical endpoint, so we're actually working towards full approval instead of accelerated approval? Topics like that. Yeah will take some time, but we can commit, reconfirm our guidance that we will have a regulatory update this year, and we will have the data update this year. It's an important year for PKP2 for us, obviously, with the 12-month data. We're already seeing an effect size that's similar to the standard of care, and this is without even the later time points yet. We're really looking forward to progressing this discussion with the FDA and working towards this data readout later in the year. Okay, great. Well, thank you. This was all super interesting, helpful, and clarifying, to me and others listening in here. Maybe just to wrap things up, do you want to talk a little bit about your cash runway, your comfort that you can get through the PKP2 readout, and obviously the FACM readout, more importantly, and then just any other sort of closing remarks you'd like to make, Nolan or the team, would be- From a cash perspective, our last disclosed cash balance at the end of Q1 was $227 million. We're in very good shape. We anticipate to burn in the range of $25 million-$30 million per quarter, and we're very carefully managing that to make sure we get at least through the completion of the BLA filing. No immediate needs for a cash raise, and we're well-funded to ensure that we get through the BLA. Yeah. I mean, closing remarks, we're seeing a regulator in CBER that is beginning to shift itself back to a more moderate position. The fact that they're reopening the discussion with companies like uniQure and REGENXBIO and Replimune and others, is a good sign. We're seeing some just overall de-risking on the regulatory front that's positive. We have a study design that we can execute given the size of the study, given the number of patients we already have in our natural history study. I think this 28% effect size that's even underestimated given that imputed time point from that patient, we're at a dramatic effect size of the therapy relative to the 15% that we need to achieve, and that's even with patient baselines that are patients that are less severe from an LVMI perspective than the ones that we can see are coming into the trial. From our perspective, this looks like a slam dunk picture here, both from the type of patients we will ultimately have in the trial, the effect size of the drug, the executability of the trial, and then we have a regulator in CBER that's becoming obviously more flexible or let's say more open to rare disease gene therapies, as we're seeing with these couple of examples that are advancing here. I think in general, this picture from our perspective is shaping up very positively. We think there's a lot of great tailwinds behind us from a regulatory point of view and other factors, and we look forward to working towards this top-line readout and reporting the results next year. Yep. Okay. Awesome. Thank you guys very much. Really appreciate the time and all the detail. Yeah, thanks everyone for joining the call today. If you have any follow-ups, feel free to shoot me a note. Thanks, Paul. Appreciate it. Okay. Thanks, guys. Thank you. Thank you, Paul.