Welcome, everyone, to 2025 Jefferies Global Healthcare Conference. My name is Roger Song, one of the senior coverage mid-cap biotech at Jefferies. It's my pleasure to have the fireside chat with our next presenting company from Wave Life Sciences and then CEO Paul. Thank you, Roger. We're excited to be here. We have a lot to talk about going into the second half. Yeah, we have a few minutes to cover your pipeline, but we'll try to do our best to do that. We're going to learn a lot more in the second half and then from all of your pipeline. Maybe just a right start, and then you have a couple of pipelines, different modalities, but all related to the RNA space. Maybe we'll start with the AATD because that's one of the lead programs you have. You just guided, I believe you update the guidance and say, "Okay, you will have the 200 mg data in subcu, and then you have a 400 mg later in the four." Tell us what you try to show us, what you expect to see from those two different cohorts: multi-dose, single dose, higher dose, and then we can drill down a little bit. Yeah, I think this is a continuation of the work that we have been doing and really establishing fundamentally a new category of medicines, namely RNA editing and bringing the first RNA editing medicines forward, utilizing our unique chemistry and really being able to show that that indeed can translate to this. Last year, and this is building on these data sets that we'll have in Q3, really build on the data sets that we had in 2024. We hit what we called proof of mechanism, meaning we demonstrated the first two patients that crossed forward into that cohort, delivered therapeutic levels of alpha-1 antitrypsin protein. We saw nearly 11 micromolar of total protein. We saw about 7 micromolar of M protein, which is the edited protein. That's just to be clear, in alpha-1 antitrypsin patients, it's zero at baseline. It's a great way, M protein, and a wonderful way to follow the ability to actually edit cells because the only way you get that production is by driving that efficiency. We saw that out to day 57, which suggests the potential for monthly dosing. A very exciting proof of mechanism that this could translate. The reason the data coming forward is going to be important and I think highly informative is now we not only have the full cohort of the single dose, but importantly, the multi-dose data set. I think what's always been important about multi-dose data sets where we've looked at our PN chemistry is usually we see higher cellular uptake and retention, so not just drug in, but delaying drug out, which translates uniformly we've seen to better exposure uptake durability. The opportunity we'll have with this cohort is it's a substantial amount of drug. We're going to have 200 mg with biweekly dosing and seven doses with a GalNAc conjugate. That's a substantial amount of activity. We're going to have a good sense of both in protein production, assessing durability and modeling. Behind that in the fall, we'll also have the 400 mg cohort. That'll give us another opportunity to look at a dose response of 400 versus 200, which will continue to give us ways of assessing the frequency. I'm excited about the upcoming data set. Yeah, absolutely. I think the first data set already proved the concept, as you said. The M protein, the production is coming literally from your drug, which is very important and gets to the level of the heterozygous patient population. You may still keep asking me the question I am going to ask you. You probably get the question all the time. Do you expect you will get to a higher level of the production? Do you need to get to a higher level? Just put it down to the record so I can give a downside. It's the more is more. It's like arms race to more protein. I kind of step back and say, what's the biological rationale around the mechanism? I think to date, the challenge on this kind of do you need more is really stemming from a period of time that the community, investment community, physician community has spent in IV protein replacement. If we think about IV protein replacement, that's been a weekly IV therapy. Patients get infused. They have to come in every week. That was all predicated on this kind of heterozygous level of 11 micromolar. That was all predicated there. There was this belief that if you can sustain that level of protein and come in, then you're at this therapeutic threshold. When the inhibitor X data was coming, and so now we were talking about a different form of the protein, that's where there was this discussion of, well, now that this protein might be different, do you need more of it in order to have therapeutic activity? That's where kind of in the field there was this discussion of, is it 11 micromolar? Is it 20 micromolar? Stepping away from IV protein replacement and really focusing on editing and correction, the value in editing and correction is twofold. One, by getting that transcript back to a normal level, you can produce a normal functional protein and therefore reach a steady state of protein that walking around a heterozygous patient would have. That's where we talk about M protein. If you can achieve, if we think about kind of being able to get there, 11 micromolar, and particularly if you can achieve 11 micromolar of all M protein, now you have this baseline of normal protein that's sitting there to protect individuals at a baseline level. Importantly, with editing, when you correct the underlying transcript, what you're now able to do is say, actually, if you're exposed to an insult, not verbal, you can suddenly start producing more protein, right? Now the endogenous machinery that's normally doing its function is there. That is why this is very different than IV protein replacement. The benefit in once you can do both of those things means now you can fix the lung, you protect the lung, but actually by taking on the burden of aggregating protein, you fix the liver. There are really two aspects of this that distinguish it from IV protein replacement. To look at that in the context of, okay, with that as the background, how do you set up the therapeutic profile that you need to achieve? Coming into this data set, if you had asked, and you did, what is the target product profile that you want to see at the end of the study? We would say, look, if we can achieve 11 micromolar or more and 50% of that was M protein, you now have the heterozygous phenotype, and we hit that. I think going into multi-dose, the key is going to be where are we on that range between not just heterozygous, but can you get to normal levels? That is in that 11-20 range. I think of those as kind of the bookmarks. Really where the focus is, is not on needing more, it's how do we push out dosing intervals and play that out. The one other feature that I'd say is when we talk about M protein, and it's really critical because we've seen with other programs bystander edits, particularly in the DNA editing field. When you install bystander edits, and actually the vast majority of protein produced through DNA editing is actually bystander edited protein, there have been demonstrations that those isoforms have different degrees of productivity in terms of protection. I think if we're really going to do comparable work to say, what is that therapeutic comparator, we really need to not look at the bystander edited total, but really look at apples and apples. What's the M protein produced? How is that similar? How can that ultimately drive therapeutic effect? I think we're well poised to look at that at 200 and then really think about how infrequently do we need to give this to sustain that. Yeah, got it. In terms of the data readout, particularly for the multi-dose, is it possible you can start to give us some functional data into the lung and the liver part? We always look and measure. I think with these patients in this study, the degree of the health is very, too short a study, and patients are not sick enough to look at changes on functional outcome at this point in time. Really the driver in this is the biomarker and threshold levels of protein, and then we can continue to follow that out and in subsequent studies be able to evaluate. Sure. Okay. All right. Understanding this is a partnership with GSK. So what's the next step for 06 for this program? Key for 06 is we're not done yet. We have that 400 mg cohort. There are two things to think about: alpha-1 antitrypsin and its critical importance to Wave. One is obviously it's important to the patients who we are developing this for and the relationship with GSK as a collaborator and partner, which does bring in milestones that are related to that, over $520 million in milestones still on the table for this plus IT royalties. Most importantly, the whole value driver between that and the rest of the GSK collaboration, which has about another $2.3 billion in milestones, is to advance the rest of our RNA editing pipeline and the work that is being done to have that pipeline translate to CTAs next year, moving clinical programs forward in a way where we can now, not dissimilar to how when siRNAs were accelerated with GalNAc, you could take advantage of clinical pharmacology from the translation of si from animals to humans and then rapidly expand that. Our goal is to be able to take the human clinical data with GalNAc from alpha-1 antitrypsin and rapidly de-risk the pipeline beyond that. These data are really important. We will have the 400, we will have the third cohort. After that third cohort, this is not an option agreement, it is a license. It's set up to streamline the transition where they pick up the next piece of the development and regulatory filings and 100% of the cost. We continue to obviously have milestones in relationship, but those data continue to inform our ADAR RNA editing platform. Yeah. Yeah. We don't have too much time to talk about the other gene editing program in the early. Another data. Yeah, that's absolutely the power of the platform and even more milestones associated with GSK. Okay. Let's move on from the gene editing for AATD to obesity, right? That's always the hot topic. Inhibit-E, you are, I think you say you will give us data later this year. How much data should we expect from that program? Yeah. I mean, as we gave an update on last earnings with now having fully dosed the first two cohorts in the study, we'll give updates on subsequent cohorts. We are poised to have the obesity data this year. The two cohorts, the best way to think of that, since it's a phase one healthy overweight volunteer study, is first cohort is by nature subtherapeutic, but it's very easy to assess that the cohort above that was modeled to be a therapeutic cohort. With those two cohorts moving, we are poised to have the data that we need to be able to assess the mechanism and weight loss with Inhibit-E. The study does allow up to five cohorts. We have room for continued expansion and dose escalation as well as looking at dosing intervals. I think what's intriguing about the single dose study is based on preclinical data, it looks to be once to twice a year dosing. The way the protocol has been designed is each cohort. When you think about where we'll be following patients out to, it goes out to six months, and then we have an option to extend a cohort if we want out to 12. We don't have to keep the study rolling on every cohort out to 12 months, but that optionality is built into it. This is important because between those two cohorts, it can enable us to have various dose response. We can look at safety tolerability, which, as we know in the obesity landscape, tolerability is important. We'll be able to look at that in this assessment. For those unfamiliar with Inhibit-E, what's critical is the mechanism. If we step back to think about how do each of these features in the trial de-risk the mechanism of action, Inhibit-E generated out of the U.K. Biobank data set as a protective loss of function. Patients who have a 50%, so heterozygous patients have a really favorable metabolic profile. They have low waist to hip ratio, so low visceral fat. They have improved lipid profiles, so low triglycerides, high HDL. They have beneficial cardiovascular outcome benefits. They have decreased risk of cardiovascular events and type 2 diabetes. On the longitudinal study of kind of running the human experiment, the human experiment both on safety and efficacy and outcomes has been run. It is really now about recapitulating that data. As we demonstrated in preclinical models, we can see weight loss, single agent similar to semaglutide. We can double the weight loss on GLP-1s in combination because it's completely orthogonal in mechanism. I should say that weight loss comes with complete muscle sparing because the mechanism of action is a secreted ligand from the liver that binds to fat cells, so alpha-7 receptor on the adipocyte and drives lipolysis. There's no implication of it's not chemical starvation, so you're not getting catabolic events of muscle, so you're not consuming muscle for energy. Its whole mechanistic pathway is around fat loss. Getting back to the clinical trial design, what's nice is we can assess all of those same features we looked at in the various DIO mouse models, including the one where we stopped GLP-1s on stable mice, gave Inhibit-E, and then showed that all mice returned to hedonic eating except those treated with Inhibit-E while they consumed calories, stable on weight loss. We will be able to look at safety, tolerability, target engagement, and because activin E is a secreted serum biomarker, you can measure it, we can look at target engagement and impact of activin E reduction tied to what will be the next milestone measurement in the study, which will be percent body weight reduction. We will be able to look at that. I think what's important there is a reminder that if we think about the GLP-1 category and weight loss, 40% of that weight loss is muscle loss. When we talk about percent body weight reduction, we're really focused on that 60% of body weight reduction, which is true fat loss and how do we drive fat reduction and fat loss. We also have to all remember that when we cite percent body weight reduction, everybody jumps to the end of GLP-1 studies after a year plus on therapy. Stepping back, thinking about the one, three, six-month time point where you see about one and a half versus placebo, about 4% and about 6% on the six-month. That ability to look at those kinetics, be able to look at that correlation between target engagement, activin E, and body weight reduction is really what we're set up to do. We'll have both essentially a subtherapeutic dose and a therapeutic dose with the ability to assess target engagement and activity. Yeah. I definitely can see a lot of the possibility for the profile using the induction or combination, maybe the long-term maintenance given the dosing frequency and then the muscle sparing aspects. Yeah. As we step back and think about this, and our data is very different from what other siRNA companies. I think it's critical because when we tend to think about some of these modalities, some of what we love to talk about with them is as if they're all the same, right? As if siRNAs are a commodity now and it's really just about target selection. While that could be true, there are certain targets where you can see differential activity. We go back to a paper that we published about two years ago where in NAR we showed we had 30-fold the AGO2 loading over best of state of the art of siRNA formats. We compare that to targets like HSD and saw better knockdown and better durability. I think at the time that publication came out, there was a lot of the so what? SIs are good. You're going to make a longer acting TTR. How are you going to use this in the field of siRNA? I think the opportunity we really had was the convergence of an interesting metabolic-driven genetic target with a siRNA format that gives us uniquely and proprietary better knockdown and better suppression of that target. Where actually Inhibit-E is the ideal place to actually differentiate the siRNA format and unlock it on a really high-value target. I think the rationale on that is this is a target that evolutionarily nature is designed to put pressure on to store fat. When you suppress it, there's a natural inclination to get that target back and expressed. What we've seen, we've looked at other development programs in this space, is the need to do weekly siRNA delivery to get a separation of preventing weight gain. When you look at normal siRNAs, you're not dosing them weekly to see effect. What was unique is we could see single dose activity that was highly durable, highly suppressive of the target itself, activin E, but importantly also then translated meaningfully to weight loss. I think when we think about that development cascade, it's let us think kind of fundamentally differently about how do we think about that marketplace. When we think about Inhibit-E, it's interesting to hear you say, okay, there's like three aspects. I don't disagree. Orthogonal combinations are interesting. You can see double the weight loss and how do you use that in a setting. I do think in the field of obesity, this push to talking about double therapies, triplets, and I think there's a certain threshold where the sustainability of that. When we think about the opportunity to have single agent activity on the front end with body weight loss and reduction where you're really obviating the need for GLP-1s and the risks associated with that when you can go on a once or twice a year subcutaneous therapy, see fat loss that's healthy and sustainable and muscle preservation. Being able to not just think about the U.S. market, I mean, if we think about an siRNA format that's once or twice a year, the global billion patients worldwide suffering from obesity become amenable because you can think about ways of distributing that care. I think the other second opportunity we see is not building on that combination strategy, although it's completely viable, is maintenance. The idea that taking the data we've already demonstrated that you can dose stable mice on GLP-1s and see that you don't return back to rebound weight gain and weight cycling also becomes a highly interesting aspect of already going into an existing market. We see those both as high-value opportunities in advancing the program that all begin with the data from the second half of this year. Excellent. Okay. Yeah. I do want to use the rest of the time to talk about you have two more, right? Clinical program that you have a lot. For DMD, right? You reported 48-week data, seems you are having conversation with the FDA to potentially file for approval. Maybe the question is what you need to show us or show FDA to be able to file for accelerated approval and then what's the confirmatory study discussion right now because with all the going on within FDA? I know everybody talks about all that's going on there. We can say that nothing's changed in interactions with FDA on any of our programs to date. We did have the conversation already, and I think that's important that the filing discussion occurred on the six-month data on Dystrophin. There was what we see is very consistent in the exon skipping world. There was not a change that Dystropin is still a surrogate endpoint in DMD. I think the conversation that we're having, which impacts the design of a confirmatory study, is bringing the 48-week data to the agency where we have the clinical data in addition. It's not just about Dystropin expression. It's about return of muscle health, decrease in fibrosis, and the TTR data that we have and clinical activity. That data is important because thinking about endpoints of confirmatory study designs and using TTR lets us think about powering and running a study differently with onset of activity, what we need to see, and how we need to run that study to deliver that. That discussion that we'll be having is really about the existing data on the clinical endpoints and utilizing those clinical endpoints as part of the future studies. Just one follow-up for the DMD. How's the Basque trial in terms of other exons? The conversation with the FDA, is that still possible to do that? Yeah. So I mean, to be really clear, that was something that we had already had when we were developing Suvodirsen in the past and actually had published on that study design with the FDA on using a common placebo cohort, doing matching. So you take natural history matching and use essentially virtual placebo patients to minimize placebo patients on the study. I mean, that was something that we had actually done in partnership with the FDA back with the Suvodirsen trial. Our view is we'll bring that forward as part of this study and really have that conversation in the context of the subsequent programs that advance. Okay. Nothing changed there either, right? Okay. Good. Last minute, talk about the Huntington, right? This is also related to the regulatory. It seems you are getting the feedback from the FDA. You will file an IND for the potential pivotal. Tell us what's the current thinking and then what's the plan and status of that? Yeah. The current thinking of the design remains unchanged at the agency. I mean, I think we, again, this is a conversation we had last year utilizing natural history data on Track and Predict-HD where we showed caudate atrophy stays consistent across stages of the disease and actually gives a very clean way of following progression of patients that you can really measure meaningfully changing patients off of that course. That piece of the pivotal trial design remains unchanged. I think it's highly encouraging given other companies' recent conversations with the agency and the agency reflecting on the use of natural history in HD stays very much consistent with what we're hearing. I think our view remains on how do we power that appropriately. As we've said before, how we think about collaborations as a mechanism to helping us fund that study as well without having to share the cost of that study, without having to allocate capital away from some of the other programs so that we can advance this really important medicine. I'd add that the landscape from a regulatory environment in HD is interesting as we hear other companies are pursuing a discussion with the agency on accelerated registration utilizing mutant huntingtin with clinical data as a potential endpoint. I think while that would be surprising, we don't see that as where the agency has gone in the past. We are positioned that if the agency changes its opportunity of thinking about mutant huntingtin as a clinical surrogate endpoint, then we would be poised to use our phase one to existing data, which is a robust placebo-controlled study where we did see more mutant huntingtin knockdown than any of the other formats. We are well prepared should the regulatory landscape change in HD. Yeah. One way or the other, you will be able to do that registration trial. Okay. Good. I think the time is short when we have a good conversation. So thank you for being with us this afternoon. Thank you, everyone, for listening.