Good morning, everyone, again. I'm Ami Fadia, Biotech Analyst here at Needham. Welcome to the next session with Wave Life Sciences. It's my pleasure to be hosting Paul Bolno, who's the CEO of the company. Paul, thank you so much for taking the time to join us today. I wanted to just give a quick reminder to our listeners: if you'd want me to ask any question on your behalf, feel free to send it over to me through the dashboard. With that, Paul, I'll turn it over to you. Thanks so much, and thanks for letting us present this morning. Before I begin, obviously we're making forward-looking statements during this call, so please refer to our SEC filings for updates. But exciting on our path to building a leading RNA medicine company, what's driving us up front are our 4 clinical-stage RNA medicine programs, and that's the first allele-specific silencing drug for Huntington's, our DMD program for exon 53 amenable boys that's demonstrated best-in-class exon skipping, followed by our leading RNA editing platform with ADAR, where we'll be bringing the first RNA editing data for Alpha-1 antitrypsin forward this year. And lastly, the first new genetically defined target for obesity, which will be accelerated this year, potential CTA as early as the end of this year, and beginning clinical studies in the Q1. All of these programs are uniquely grounded on our ability to develop a multimodal drug discovery development platform that can sustainably bring new medicines forward based on clinical genetics. We continue to support this through our own internal R&D efforts, as well as substantial strategic collaborations, particularly the one with GSK that we'll explain, and ultimately grounded that we can bring these medicines forward rapidly with in-house GMP manufacturing. I think this is sometimes one of the underappreciated aspects of oligonucleotide medicines. But the ability to have a GMP manufacturing capability in-house is what's enabled us to accelerate programs like our Inhibin E program for obesity, all based on strong and broad IP, and capitalize to deliver on these clinical inflection points. As we think forward over the last now nearly over a decade, we've really invested fundamentally in building a best-in-class chemistry capability. I think too often in the oligonucleotide field we hear time and time again from others that, you know, you can plug and play off of existing chemistries. We do think chemistry innovations are critically important in driving the potential for this class to bring new insights and new innovations to oligonucleotide medicines and unlock new possibilities. When we talk about the ability to drive chemistry to unlock new biology, there's really two fundamental areas of biology that we seek to unlock. One is accessing new endogenous modalities or mechanisms inside the cell. So these are enzymes that cut, great example of this is what we've done in RNA editing with ADAR, so unlocking a new endogenous base editing enzyme inside the cell. But in addition to that biology, which I call the intercellular biology, are the target biology and opening up new classes of medicines. As we think about these insights of moving beyond the mechanistic piece, one now puts us in a unique position where we have multiple tools now to evaluate clinical genetics. When you look at the clinical genetic insights, and particularly what we've seen from UK Biobank, in addition from some of our collaborative work with GSK, and you know, they were sharing some of this at our past R&D Day, when you look at the vast majority of genetic targets, in biology, they're not things where nature makes more of something bad that you need to get rid of, that you need to take away. Actually, the vast majority of these mutations actually create a deficiency, whether it's the absence of the production of a protein or the dysfunctional protein. And so having the right tool to do the right job, whether that's antisense or siRNA, whether that's editing or splicing an upregulation, really lets us think about approaching the right tool in the right way. I think the other evolution that we're seeing in biology is really a shift from clinical genetics being focused on monogenic and rare diseases to more common and prevalent diseases, and really being able to think about building a leading genetic medicines company that can really flex and think through right tool, right job, but also new diseases and indications. A great example of this out of the UK Biobank is our target for Inhibin E, which is a protective loss of function variant, that we'll talk about later in the field of obesity. So what this has done is bringing new chemistries, new genetic insights has enabled us to build a substantial portfolio, led by our groundbreaking work in RNA editing, and led with the clinical program, the first RNA editing clinical program for Alpha-1 Antitrypsin Deficiency, our WVE-006 program. This is grounded not just in what we're doing for Alpha-1 Antitrypsin, but we continue to build off of that in our other multiple correction programs and upregulation programs. Continuing on this theme and building on our work on GalNAc conjugated oligonucleotides is our work in siRNA led by Inhibin E. But we also continue to have our work that's been progressing on the field of exon skipping and splice correction with WVE-N531. We'll have data from the FORWARD-53 study in Q3, and our silencing unique ability to silence just the mutant protein in the SELECT-HD study. We'll have our multidose data readout in HD in Q2. As we think about the pipeline emerging, those are our own pipeline programs that we're building. But we have a deep strategic collaboration with GSK that's really focused on developing transformative RNA medicines. While this collaboration came with a substantial upfront payment, we really think about this collaboration as having 3, 3 specific aspects to it. The first is thinking about, obviously, our partnership in Alpha-1 Antitrypsin Deficiency. And this is important because we see GSK as a substantial, having substantial capability, particularly commercially in the field of respiratory medicines. And as we think about maximizing the opportunity for Alpha-1 Antitrypsin Deficiency, which is both treating lung and liver, we see GSK as a strong partner for us with this program. We have substantial milestone payments under this program, so another $505 million in milestone payments in this program received $20 million in Q4, related to the initiation of the study. And so, as we think about this collaboration and maximizing the potential for 06, again, not just for Alpha-1 antitrypsin deficiency, but actually unlocking our wholly owned ADAR portfolio, we see that as a valuable contribution. Second is a substantial research program. And so we know that GSK has invested substantially in building out capabilities in clinical genetics. In this collaboration, we can work on up-to-date programs with them, and these focus on unlocking that potential within these novel genetic targets that GSK has identified. And I say that, and it's very important, a notion that GSK has identified. So if there's work that we're doing on a target that is a Wave program, if another potential partner is working on a program that is a Wave and partner program. So these are unique insights that GSK is bringing to the table that we're unlocking across the field of siRNA editing. And it comes with another up to $2.8 billion in additional milestone payments related to those programs. So substantial opportunities over the course of 2024 and beyond to bring in additional cash to support our discovery enterprise. The last feature of this collaboration, and I think it was probably one of the most underappreciated aspects, and not surprisingly, because it didn't have a definition of what is that, was when we said, when we signed this collaboration, that actually Wave will get to bring 3 wholly owned collaboration programs onto our pipeline. The value in this is, if we're going to do research together to unlock the broad potential of oligonucleotides, it was important for us to continue to sustain and build our genetic medicine portfolio. We announced last year the first program that would be wholly owned for Wave out of this would be the Inhibin E program, again, taking unique genetic insights from the UK Biobank in this case, and bringing that into Wave as our first emerging program out of that collaboration. I will remind people, this is a wholly owned program that is Wave's with no forward rights to GSK to the asset. As we think about that collaboration and alpha-1 antitrypsin, I think we'll spend a little bit of time on the alpha-1 antitrypsin biology. Why do we think that RNA editing is the right approach for this disease? I think there's several ways for those unfamiliar with this program. I think when one thinks about Alpha-1 Antitrypsin Deficiency, you need to think about it in the context that you have these 200,000 ZZ patients in the US and Europe. They're ZZ because they make 2 copies of a misfolded protein. That misfolded protein can't leave the liver because it's proaggregating. So it builds up in the liver. It aggregates. It causes liver damage. And the absence of having that functional protein in circulation means you're not protecting the lung from injury. And that's really the function of this protein: to protect lung from injury, protect lung from injury. So what's important for us, as we continue to bring this program forward, was that if we could correct, and this is based on human patients, so what are called MZ patients, so these are heterozygous patients. They have a good copy of the M protein, so the normal protein, and then they have the Z protein. But that M protein is sufficient enough, that one allele, to be able to produce a functional protein that enables them not just to protect the lung, but also to prevent liver damage. And so the thesis behind RNA editing was, if you could achieve 50% editing within the liver, you could actually correct these ZZ homozygous patients back to a heterozygous phenotype. That thesis was explored by saying that if you could also do that, you'd prevent that protein from aggregating in the liver, and therefore you could fix both the liver and the lung pathologies of AATD. I say this because it's really important that sometimes we'll hear people say, "Well, this is a liver patient with AATD," or "a lung patient with AATD." It's a continuum. You have Alpha-1 antitrypsin deficiency, and you are both in the ZZ population. You're on a lung and liver. There's not a definitive population. Both target organs are opportunity sets. The current field really has 2 therapies that are both on the commercial side, which is protein replacement therapy. This is IV protein replacement infusion. And the design behind that IV protein replacement and infusion was, if you have patients who are ZZ, and you could get them to what was the lower limit of the MZ population that was 11 micromolar, the theme was that you'd be able to restore those patients back to MZ. I think a little bit of the challenge, as we hear discussions on the protein infusion space of saying, "Well, is 11 the right number? Should it be more?" is a different discussion than the RNA editing field and the editing field in general, which was, if you can correct patients back to the heterozygous phenotype, then they would be similar to that lower level of the 11 micromolar, which is that patient population that sits there, because those patients still have a functional net now, because they're edited and corrected, have a functional M copy of the allele to be able to make a healthy protein, and therefore are more analogous to that patient population. So we'll talk a little bit more about that in the context of the therapy. As we built our program, we built that off of the SERPINA1 ZZ model. We think this is a PiZ model, is a great way to identify and be able to correct the mutation. As I walk through our data, I think it is really important, as all of us know, when you develop medicines and you think about model systems for developing drugs, model systems are purely that. They're models to be able to look at, identify, and exploring the disease. So when I often say we increase the serum AAT of up to and above 30 micromolar in the model, that implies that we correct the model back above a human, normal human level of protein, which is the lower limit of normal for a human is 20 micromolar. I think what often happens now is people become fixated on the micromolar number. And I think when we get back to the utility of the model, one has to remember in the model how the model is run. And so it was really important when you recognize how we run this model to be able to discern the most information for what a model is good for, which is designing your human clinical study of which we're in the clinic. The goal is really to say, does your model establish a nadir? Are you below, well below 11 micromolar? Since the model is representing the pathology of disease. If you don't wait for the model to get below, and we know there are preclinical companies that have started treating above 11 micromolar before the model has actually established itself as a disease model. What we establish in this model is that we could do what we anticipate doing in humans, which is take the disease while it's fully entrenched or below 11 micromolar. This model, when we're treating it, actually has liver pathology, because the liver is damaged and not just not producing protein, but actually producing aggregates of liver damage. We could show that we could bring that model back above to where a normal human level is with over 50% editing. We could see that we characterize that protein. We're getting substantial amounts of M protein, meaning it's doing what it's supposed to be doing. We actually, and importantly, could test the functional level so that we could see in the elastase inhibition assay that that protein we're generating is functional, and very importantly, show that we could improve the liver phenotype, meaning not just generate levels of protein sufficient to restore normal levels of protein, but actually be able to show reduction in liver globules. And importantly, to actually look at hepatocyte turnover and see that we can improve liver health. So if we think about the portfolio what we built before we started the clinic, the goal was really to define the core biology that one wanted to replicate in humans. I think equally important is the delivery mechanism that we used. The disease is in hepatocytes in humans. We see these patients who have liver injury from sustained damage. And the goal with us in a program, ideally, as we know in the oligonucleotide field, is to use GalNAc as a delivery vehicle that substantially delivers your drug to the hepatocyte, which is the target cell type. The challenge we've seen, and we've seen this with a number of current programs in the clinic, is LNPs have their own challenges with them. They can cause and induce liver injury, which in patients who already have liver injury are difficult. They require IV administration. Importantly, in the preclinical models, one of the challenges you would have in discerning your doses with LNPs is that the transgene in this model is expressed not just in hepatocytes, but also in other cells in the liver. And so, therefore, the benefit of translating our findings in these preclinical models to humans is that our drug only goes to the hepatocyte. And so, therefore, what we can discern from our preclinical studies, as we think about translating that to humans, where the pathology is only in the hepatocyte, I think it gives us our best approach to modeling for that target therapeutic indication. So where are we today? RestorAATion was initiated. We're in the healthy volunteer dose escalation. The purpose of this was because we don't permanently edit DNA. We could go into healthy volunteers to rapidly push dose escalation so that we could begin our RestorAATion-2 in AATD patients at the dose that we would anticipate being a therapeutic dose and engaging target. We're on track for doing that. We gave an update in our last earnings that the pharmacology is behaving as predicted, and we will expect to give an update on the initiation of the RestorAATion-2 in the not too distant future. The benefit is that we'll have a low dose, a middle dose, and a high dose. And this will really let us establish the therapeutic range for what we can see in editing. The initial data set that we'll provide would be a proof of mechanism, which means, can we see and replicate that ability to engage target, produce protein in patients who don't produce that? And we'll have multiple assessments of that over time, and that will help us then predict across the ranges where we anticipate maximum editing and dosing frequency to be. We anticipate this data also in 2024. Beyond this, and what AATD unlocks is it literally lets us think more broadly about the editing universe. And as we shared at our R&D day last year, we have a robust data science system up and running, leveraging what we've done in machine learning to be able to really deconvolute those targets that are amenable to upregulation. We see about 50% of the transcriptome is eligible for our AIMer technology. This includes not just correction, but also upregulation, and have built a system in place to not only identify targets, but actually maximally predict how we would rationally design those programs to actually impact therapeutics. I say upregulation because a lot of times we spend time talking about ADAR in the form of correction. But it's important to give some context to what we mean by upregulating the expression of protein. So if you think about what happens to transcripts inside a cell, you've got this transcript. The transcript can become degraded, and when it gets degraded, you don't produce a protein. What we've been able to do with editing is actually prevent that mRNA degradation, and therefore within the cell. So as opposed to if you think about exogenous mRNA therapies, you have to put mRNA into an LNP and deliver that into the cell with all the challenges that come with that. The advantage we see in this approach to editing is that we can endogenously in the cell prevent that degradation of the transcript. And so, therefore, what you end up doing is increasing copy numbers of protein inside the cell and that, or sorry, transcript inside the cell, which ultimately translates to protein. We've done this. We have multiple programs now that leverage both upregulation and correction using GalNAc. So these can immediately leverage the benefit of pharmacology translation that we've seen before in other modalities of going GalNAc from mouse to non-human primates to humans, but also the ability that we've seen across our platform for extrahepatic delivery. And so we have programs in both kidney and lung that leverage our ability to do editing without GalNAc and outside the liver. Just as an example, I think lots of times we see a capability sets where we're like, one could do this, but we are doing this, and we've shared these data before. This is an example of a target that we've identified within the network. In vivo, we showed that again, we could edit, see substantial editing inside the cell. We could translate that editing to a greater than twofold improvement in the mRNA transcript inside the cell, and then, importantly, see that translate to the relevant aspect of it, which is increased protein. So these are in vivo examples of being able to do that. And then, importantly, these were functional. So not only could we edit and see that increase in protein, but we could actually see that that functional protein translated meaningfully to, in this case, significant weight loss and improvement in insulin sensitivity. So we see this as a really valuable platform building off of alpha-1 antitrypsin deficiency to really think about how we could leverage the RNA editing platform more broadly. Beyond editing and leveraging GalNAc in our work and our collaboration with GSK, we have built what we believe to be a best-in-class siRNA platform. And I say that because, you know, with data and a publication from NAR last year, we actually showed, compared to state-of-the-art chemistry and siRNA, much better AGO2 loading. We see about a 30-fold improvement in AGO2 loading, translating to sustained durability and potency. This is important as we think about unlocking this field across targets where it would be important to leverage this capability. And so, rather than taking that modality and applying it to existing targets and saying, well, maybe we can, you know, I think a lot of times investing class one says, well, let's take something we already know and see if we can make it better. I think we took the approach of, well, what's new and really genetically meaningful? And could we apply this new technology, this capability, these enhancements to this new target and establish a footprint out in the front? And so this was that target I mentioned before that we developed with, out of the GSK collaboration for Inhibin E. Importantly, Inhibin E came out of this analysis of the UK Biobank, where it's a protective loss of function mutation. We find these very rare in genetics. The beauty is the genetic outcome studies have essentially been done in the population. This is a protective variant. If you have a loss of function in this variant, you see low hip to weight ratio, low visceral fat, low triglycerides, and LDL, high HDL. These patients also have, as I said, low visceral fat. They also have, because the outcome studies have been run, a reduced rate of cardiovascular disease, as well as a reduced incidence of type 2 diabetes. In a lot of ways, the prospective studies have been done for Inhibin E. I think what's always important when we think about clinical genetics is actually, can you induce it? Meaning, do you need to be born with that loss of function to see the benefits from it, or is it inducible? But when we think about this, these patients have strong lean muscle and low fat and improved lipid profile, which made it, in our minds, an ideal target for our siRNA platform. We also recognize that, in addition to the improvements we see with the Inhibin E, these actually really complement some of the challenges that have been posed with GLP-1. So, you know, one, a GalNAc-conjugated siRNA. And we'll share, you know, some of the updates on the program. But right now we anticipate, based on our candidate that we've identified, that it will be no more than twice a year, potentially once a year, subcutaneous dosing. So we see the benefit of infrequent administration. We see fat loss, equating to weight loss, without the expense of muscle loss. And we've shown that before. We see the tolerability profile of a GalNAc siRNA that's only delivered to hepatocytes and non-centrally acting as being important. So we think this, by not working in the central nervous system, as where you're thinking theoretically about GLP-1s and other classes that are really focused on appetite suppression. So in, you know, suppressing the general reward system, and therefore, in some ways, inducing starvation weight loss. This mechanism is purely metabolic and involved in adipocyte survival, and therefore you're causing lipolysis and improvement in metabolic disease. We have translated these data. We showed the first data, in an in vivo model last year, where we show that it is inducible, that we can see induction of all of what was seen in the human clinical genetics in the DIO mouse. As we brought forward our candidate, we see best-in-class potential for this. We're already at an ED50 that's improved over existing siRNAs, including inclisiran. So we think the profile of potency and durability looks outstanding for this. Again, thinking that we've seen durable silencing after one low single-digit dose supporting again every 6-month annual dosing. We have demonstrated consistently that weight loss, and we've seen weight loss similar to semaglutide without muscle mass loss. And so we think it really has, in addition to just fat mass, we've actually been able to discern, similar to the genetics, that it really is coming at the expense of visceral fat. And as we know, visceral fat has ultimately been tied to the public health challenges of cardiovascular disease. So we think profile-wise it sets itself up in a genetically stratified way, uniquely from existing obesity programs. We expect to initiate the clinical trial for the Inhibin E candidate in the Q1 of 2025. As we said, we expect to see TA as early as the end of this year. I think, as we move past obesity and AATD, which are really the drivers of where we've taken the company directionally, we have built a best-in-class exon skipping franchise, leveraging our chemistry in DMD. We're focused on, right now, initially proof of concept within the, exon 53 amenable boys. We see that the goal of improving functional dystrophin protein, and that's what we've seen consistently as we built the program for the very beginning, is critical and ultimately driving a beneficial outcome for these boys. As we'll show you later in our preclinical data, as we thought about the core drivers of what one needs to treat DMD, meaning functional dystrophin protein, meaning you can get to the right tissues. So beyond skeletal muscle to heart and diaphragm. And we can do this in a dosing format that we believe monthly. We think we've got a profile for a best-in-class franchise in DMD led by 53, but we've already seen as good, if not better, skipping across the other exons in our other formats. What drove this and why we came back to DMD after our initial experience with suvodirsen, where we saw no exon skipping in a large clinical study, was that we could go back to a different model. And we see the double knockout mouse as a core driver for us in decision making in DMD. I think mdx gets used a lot, but mdx has a knock-in of utrophin, and therefore no phenotype. What's important around the double knockout mouse is there is no protective protein that's added to the model. So the model. These mice die because of cardiorespiratory failure secondary to the lack of dystrophin. So any improvement is seen is seen by the generation of dystrophin protein. And what we've seen compared to our first generation backbone in light blue over placebo and orange is that in across a dose range, including doses lower than we are in the clinic, we see that we have 100% survival in the double knockout mouse. This translated functionally to restoration of respiratory volume back to wild-type levels. While it is, and I will always say, the caveat is, this is a mouse model at the concentrations we see. We saw double-digit dystrophin here, at again the ranges that we are in the clinic. So all of these supported our transition to the clinic with the realization that ultimately this study has to be shown in DMD boys to ultimately demonstrate protein production. We've seen substantial generation of protein in the patient-derived myoblasts as the best and only way to study in DMD boys the benefit of producing protein. And we see substantial protein at muscle concentrations that we've achieved in the clinic. And additionally, within the non-human primate, we see the consistency we saw with our mouse model, which is substantially higher levels of drug concentration in the heart and diaphragm over skeletal muscle, meaning the data you can get with biopsies in the skeletal muscle is underrepresenting what one sees in the heart and diaphragm. And we think that's a really important balance to thinking about this program. So where were we? So we've shown data versus suvodirsen, the first generation program, where again we saw low muscle concentration, short half-life, and no skipping or protein. Where we are today is, as of December of 2022, we shared the first insight into the first DMD boys. So this is clinical data from our DMD boys. We saw 42,000 nanograms per gram. And I think that's really important, because when one talks about DMD, oftentimes we hear the first discussion point is muscle delivery. When we see 42,000 nanograms per gram, the existing conjugate programs have shown muscle concentrations around 650. And so we see thousandfolds improvement of drug concentration in the muscle without the requirement for a conjugate. Additionally, this is functional distribution into muscle because it's getting into the nucleus, and it's skipping. We see 53% skip transcript, which is the highest level of exon skipping that's been seen to date across studies. One has to remember, this was only after 3 doses at 6 weeks, so 3 doses 2 weeks apart. Very short timeframe, very small amounts of dosing regimen. But the principle of this study was really designed to answer a difficult question, which was, does this support the expansion of the study? We'll talk about where we are with the Part B study. Half-life of the program is 25 days, again supporting the ability to do monthly dosing. Also important as we think about the pathology of the disease and the opportunity to expand, you know, where we think the treatment paradigm could go is we do get uptake in the satellite cells. So the regenerative cells in the muscle actually get exposure to drug. This is unique across the various exon skipping therapies, not just in exon skipping, but also in gene therapy, that we get this broad distribution beyond just the myoblasts themselves. Where we are today is dosing has been well underway in FORWARD-53. This is the potentially registrational phase 2 study in exon 53 amenable boys, and we'll have our two biopsy time points in this, so of the 24-week time point and the 48-week time point in Q3. We'll have the data from the 24-week time point, which will enable us to assess dystrophin levels at an equivalent time point to NS Pharma's Viltepso. So this will give us a benchmark comparison against the existing commercial product at 24 weeks, as we know golodirsen's at 48 weeks. So we'll have time points under both to be with which we can compare to existing standard of care, and we look forward to that update in Q3. In addition to DMD, we've been doing a lot of work in HD from the early days, and we're really always now with that data in Q2 coming, to see the results from this study. We went into HD in a very specific way, driven by biology. And what we realize in HD, and I think we've seen this play out in pan-silencing programs, is HD is both a toxic gain of function disease and a loss of function disease, meaning you're balancing within this paradox, a mutant protein that aggregates inside neurons and is responsible for killing neurons. And at the same point you have and were born and as an HD patient with a 50% decrease in your wild type protein. And this is involved in stress protection. It's involved in BDNF trafficking. And I think the understanding more and more of wild type protein is coming into play. There was a paper, even as early as this year, looking at replicating data of wild type silencing causing thalamic calcifications and neuro injury. And so I think the work that's really being done to understand wild type protein is important. This is an important disease, because if we can treat the way we're planning to with our program, which is taking out just the mutant protein, but preserving and leaving functional wild-type protein alone, not only does this enable us to treat patients who are symptomatic in terms of HD, but importantly, have a therapy, since one can be diagnosed at birth with Huntington's disease, to being able to start treating patients before they become symptomatic, or what's called pre-manifest HD. And so the ability to really change the paradigm for the treatment of HD patients. We have data from this study from September, where we had our single dose data. Importantly, in models, one has seen that a 30% reduction of mutant protein is clinically relevant. What we saw in this study was that we saw a 35% reduction versus placebo, and we showed that we could preserve wild type protein. So these were the first human data ever to show allele-specific silencing in humans. But again, it's a single dose. So we've continued this study, and we'll have data in the Q2, where we look at this 30 milligram multi-dose data, and we'll be able to assess protein levels of mutant protein, wild type protein, and assess the next steps for this program. I think when we think about HD, we tend to think about the existing clinical paradigm, too, for what a late-stage study looks like. And I think what's changed pretty dramatically in the last several months has been that we went from a theme where, and this anybody who attended CHDI would have heard this theme. That, I don't think the field clinicians, patients want to see another generation HD study with 800 patients being taken out of the the clinical trial realm and being really subjected to long-term follow-up. I think what supported the ability to do smaller studies and really think about alternative endpoints and open up the potential for accelerated approval has been some remarkable work. Sarah Tabrizi's group at IXICO, along with CHDI, who has tracked HD and other longitudinal natural history studies. The work on imaging that was pretty substantial and was presented at CHDI showed that within 12-18 months you could see changes in caudate nucleus putamen and total brain volume on imaging, and those changes correlated statistically with changes in total motor score and UHDRS. Meaning, for the first time in the field, we now have a correlation between imaging and clinical outcome measurements that could be tied to biomarker measurements on that approach. And when you put that constellation of findings together, you can start thinking now about accelerated endpoints, including accelerated approval potential, to being able to run a study where you now can correlate to a clinical outcome measurement. That's important for us, because what we don't do is we don't damage the brain by injection. We don't damage the caudate nucleus. So if you don't disturb or disrupt the inside of the physiology and anatomy of the brain, then you can use those anatomical structures going forward. And so we do look forward to these data sets that we're going to be presenting, really defining the biomarker engagement strategy. I think another aspect to imaging we'll be able to see in this study is the absence, as we will look for, of changes to ventricular volume. What we've seen in the two discontinued studies in pan-silencing, so branaplam and tominersen, was that you saw ventricular expansion, including hydrocephalus. And so that change did correlate with the discontinuation and, say, improvement of, but actually it was the induction of safety signals in those patients. And so when we think about that, you know, one of the important characteristics we want to see in this study is improvement in directional movement of the biomarkers that are clinically relevant, but the absence of brain findings that would be detrimental. And if we think we can put those two pieces together, you know, that will obviously support our submission of our package, our data package to Takeda. But I think most importantly for this program and for patients is that we actually, I think, have a path to a meaningful therapy in Huntington's disease, and we'll let that data in Q2 drive that. So we're continue, as we said at the beginning, poised for sustained growth. We're building off of our exon 53 program, and if positive can expand to the additional exons in HD. SNP 3 will drive the potential for expansion and our collaboration to multiple additional SNPs for the field of Huntington's disease, a substantial market opportunity, one that actually is substantially larger than DMD. We've got our Alpha-1 antitrypsin program that we can continue to grow for that treatment. But importantly, as we shared, expansion to the additional RNA editing programs, and then obviously the work that we've been shifting into the cardiometabolic space led by genetics and our work in Inhibin E, and we'll begin to initiate that study in the Q1 of next year. So continuing to address a massive, total addressable market of patients of over 50 million patients in the U.S. and Europe, across 4 clinical programs. We can remain on track to delivering these data sets. So we will deliver our Alpha-1 antitrypsin data this year. We have already delivered 2 quarters ahead of time our candidate nomination for Inhibin E and look forward to bringing that into the clinic. Our DMD data is on track, as we said, at 24 weeks in Q3 to deliver dystrophin data to unlock that potential, and we'll have HD data in Q2. So that, in addition to the cash on hand, in addition to the cash inflows that are not calculated in our runway from our collaboration partners at both GSK and Takeda, we're excited about the potential that we will deliver over 2024 and beyond. And with that, I thank you for your time. Hey, Paul, thank you for that presentation. Just wanted to remind listeners quickly, if you've got any questions for me to ask, feel free to send it over to the dashboard. I've got one here for you, Paul. The proof of concept data for WVE-006 is expected in this year. What is the serum AAT level that you might need to demonstrate for clinical efficacy? Do you think the 30 micromolar that you saw preclinically is achievable in humans? Yeah, I think when we talk about proof of mechanism, and I separate, we're going to have multiple data reads. So initially, and one knows that we have a collaboration which comes with various milestones. So we think about proof of mechanism. I think the first step is nobody's ever demonstrated that you can do human RNA editing and generate a protein. So I think there's a piece that's mechanistic about a threshold level that demonstrates where one could get to. So I want to separate the concept from what I would call proof of mechanism from proof of concept. Proof of concept we use to mean, okay, is this clinically translatable from our preclinical models? Interestingly, a question. So, I, you know, we're not gonna guide to the target threshold of proof of mechanism that could come at any point in time, because these patients have 0 protein, and we can even engage that at an early time point with a single dose. So I want to separate kind of mechanistic from concept. Proof of concept. I mean, as you pointed out, we've already achieved correcting the PiZ mouse back to normal human levels of Alpha-1 antitrypsin protein. So I think with multiple dose thresholds, inclusive of 2, thinking about dosing paradigms, I think we'll get to substantial levels of protein. I think one has to really approach this again. And I think this is where the field has spent a lot of time, and I know investors in particular with Inhibrx have spent a lot of time on the protein replacement discussion. I think the protein replacement discussion is very different than the protein correction discussion. So if you're in protein replacement, that bar was set at 11 micromolar because people looked and said, okay, well, an MZ patient said 11, we should be able to do 11. But they were treating patients who never had or made a healthy protein. So the concept of protein replacement was, I think about it like a bucket with holes in the bottom. You're kind of pouring protein into the body. That's kind of a race to the bottom, right? You're eventually breaking down that protein and needing to put more in, because the patient's never able to intervene and start producing protein. The difference on correction, and why we really need to focus on why, what's important about what? What does 11 micromolar mean beyond the number? What does it mean? 11 micromolar was a number that was set by an MZ patient that has a phenotype. And actually, in those patients, they do have that M allele that can make normal protein. That's the goal of editing of 50% or more in a patient, which is you're actually restoring that patient truly to a heterozygous patient phenotype, where they have a healthy allele that can compensate and actually produce protein. And therefore, 11 micromolar may be that number. 20 micromolar is a threshold of a normal human. So if we think about just what is the normal threshold level where we don't talk about Alpha-1 antitrypsin deficiency, that's about a 20 micromolar level. So I think when we say, you know, 30, and I think it's important again, when we say 30, that's a 7-fold improvement from baseline in a model system that was dysfunctional. So I think one has to remember, because we do know preclinical companies out there kind of post numbers. We've heard even numbers of some saying, well, it's 50 micromolar. I said, well, look, if you go back to the model, the model was never a SERPINA1 model. It wasn't. A patient never got below 11 micromolar to actually be dysfunctional and have pathology that you were rescuing. It's kind of like a cancer model before a tumor engrafts, and you treat it, and you say, there's no tumor, and you're like, but the tumor never engrafted. And so I think about, you know, the fold improvement over that baseline and that nadir as being rescuing and restoring what one anticipates to see in humans. So as I think about the target levels, I think 11 micromolar could be a very good target level for restoration of a heterozygous phenotype. But not saying, you know, as soon as you say that, people are going to, well, do you not believe you can go higher? We've demonstrated, as we said, that we can restore an animal model back to normal levels of protein in humans. So I think the opportunity that we really have in front of us, which I think is exciting for the field of editing. I think it's exciting for patients who have AATD or are looking for a therapy where you don't knock out the protein. You don't have to do replacement. You actually do true correction, and in a way that's not going to permanently edit their DNA and run all the risks that come with that and hepatic injury, as we've seen with some of the other DNA editors with lipid nanoparticles, and not have bystander edits. You know, I think one of the other things that we've seen very cleanly is no bystander edits, and we're only producing the M protein, which is important, because we do know that bystander edits create isoforms that have various degrees of functionality, including putting indels in that prevent the production of Alpha-1 antitrypsin protein. I think by bringing editing and showing that we can actually restore a corrective phenotype back to that heterozygous phenotype, I think we're actually doing what the promise of RNA editing is, which is correcting those patients back to a normal state of physiology. Okay. Paul, unfortunately, that's all we have time for. So I'll have to close the session here. Thank you so much for joining us today and taking us through the story, and thanks to all our listeners as well. Thank you for your time, and we appreciate everybody tuning in. Thank you. Thanks. Have a good day. Take care.