Good afternoon, everybody. My name is Zaki Malvi. I'm an associate on Akash Tawari's team, and I'll have the pleasure today of hosting Enanta Pharmaceuticals. CEO Jay Luly, always a pleasure to have you, Jay. We'll present some slides, and then we'll get into the Q&A. I'll let you take it away, Jay. Thank you very much, and thanks for the opportunity to update you on Enanta today. Before I begin, I want to remind you that I'll be making some forward-looking statements. For a summary of the risks associated with these statements, please see our filings on sec.gov and on our website. For those of you who are less familiar with Enanta, we are a virology and immunology company. We started very early in the hepatitis C days and discovered some protease inhibitors that later became part of the drugs now sold by AbbVie. The leading drug is called Mavyret. It's a two-drug oral eight-week cure for all genotypes and is the only eight-week cure for hepatitis C today. We moved into respiratory virology shortly before the pandemic, getting ready, no doubt, to do good work there. We targeted RSV as a huge unmet need. While today and only more recently there are vaccines that have been approved, the penetration of those vaccines is still fairly low, and the majority of patients are—or the majority of adults are eligible for a therapeutic because they are not vaccinated. We have two programs there. They're both direct-acting antivirals. They're replication inhibitors. One targets the N protein. One targets the L protein. We recently announced data on our high-risk adult study last month. We'll spend a little bit of time talking about that. We have a next-gen molecule behind that called EDP-323, which has demonstrated some of the best challenge study data ever generated by an—I'm sorry, RSV therapeutic. We couldn't not work in the pandemic era on both protease inhibitors and respiratory drugs because we were already working on RSV. We also have a phase two data set on a protease inhibitor called EDP-235. Most recently, we started to expand into the INI space, first with a program we announced early last year in KIT. We have progressed that now to a clinical candidate, EDP-978, which will be targeted for an IND in the first quarter of 2026, moving from KIT, which is a mast cell target, to STAT6. STAT6 is a program we're very excited about because we hope to have an oral molecule that recapitulates the activity shown by Dupixent in the many and broad indications that Dupixent is approved for. We will spend some time talking about that. Just last night, in connection with our earnings, we announced a development candidate for that program, EPS-3903. I will show you a little bit of data showing that it has pre-clinically activity comparable to Dupixent. Okay. Just a couple of slides on the data set that we reported a few weeks ago. This is our high-risk adult population for RSV. These are people in the general population that are 65 and older or who have COPD, asthma, or congestive heart failure. We pre-specified a subpopulation in that study, which is actually 80% of the study, called the HR3 population because we did not want young, mild asthmatics to constitute too much of the trial. We wanted to make sure it was generally targeted for high risk, and we did not want otherwise healthy 65 to 74-year-olds, again, dominating the study. Instead, we pre-specified what we now call the HR3: people who are 75 and older, people who have COPD, people who have congestive heart failure. What you can see on this slide is when you look at complete resolution, the time to complete resolution was actually shortened by about a week in these patients. When you look at all RSV symptoms, there are 13 to choose from there. It is a fairly diverse patient population. We looked at a smaller subset, which was actually our primary endpoint, of lower respiratory tract disease symptoms only. There are four of those. What you can see is that the effect was most broadly manifested when you looked at all 13. Then 29 parameters include 16 other measures of sort of quality of life scores. You can see a very nice effect. This was basically a one-week improvement in terms of time to resolution. We also looked at another patient-reported outcome called the PGIS. It is the Patient Global Impression of Score. It also showed a statistically significant improvement in both the broad population as well as in the HR3 population. Perhaps really importantly, we saw a lower hospitalization rate. The hospitalization rate in placebo was around 5% in this patient population, and that was reduced to about 1% in the treated population. A very important observation there. There was also one death in the study, which was on placebo. It may come as no surprise, we also saw good antiviral activity associated with all this and a good safety profile where we have now been in over 700 patients with Zelicapavir. This data, we believe, supports advancement into a phase three study in this high-risk adult population. Shifting gears to immunology, we have a mast cell target called KIT. We have a clinical candidate called EDP-978. It potently inhibits the target. It has very good selectivity versus KIT family-related kinases and more broadly across a whole population of kinases. Also importantly in this business is good ADME properties. It's well absorbed. You don't see any reactive metabolites which cause problems with some other KIT inhibitors previously. We've looked at SIP analysis and modeled this out extensively. We are very much on track for an IND filing in Q1. Shifting to STAT6, our goal here is to come up with a best-in-class oral STAT6 inhibitor. Again, Dupixent targets the IL-4, IL-13 pathway, which is transduced through a transcription factor called STAT6. If you can intervene at that step, you can effectively inhibit the pathway that is otherwise activated by IL-4 and IL-13. We're working in a small molecule program that is targeting an inhibitor, not a degrader. We look at that as having a lot of advantages of traditional small molecules, well-behaved PK/PD relationships, good predictable metabolism that you can target pre-clinically, and other characteristics. Importantly, we've generated good data now in multiple animal models, two of which I'm going to show you a little bit about, but one is of asthma and one is of atopic dermatitis, one of the biggest markets for Dupixent. We are on track, given the announcement of this candidate last night, to be in filing the IND in the second half of next year. Here is just a quick snapshot of data. This is the human or the house dust mite challenge model. Effectively, you dose animals and provide an intranasal challenge. What you can see is that pathway without drug leads to an increase in phospholipid levels in the lung, bronchial alveolar lavage fluid, eosinophils, BAL TARC, and serum IgE elevations. That can all be knocked down very successfully with EPS-3903 and shown at the rightmost of each one of these graphs as the activity for Dupilumab, or otherwise known as Dupixent. We are seeing very strong inhibition in these targets. Again, this is an asthma model. Here is the same molecule given in a coincidentally named MC903-driven atopic dermatitis mouse model. Once again, you can look at phospholipid levels in various compartments, also serum IgE, and you can see a very good knockdown with EPS- 3903 comparable to Dupilumab. We are seeing very good activity. We know we can see good STAT6 inhibition continuously, even as measured at a 24-hour trough concentration time point. This is a very robust profile for a small molecule inhibitor. With that, I just want to, you know, the IND enabling activities just wrapping up for EPD-978, again, targeting it to be an IND in Q1. A STAT6 development candidate was announced. We plan to announce our third immunology program in the coming weeks. We also reported very positive RSV data in high-risk adults. Again, we're looking at Zelicapavir, and EPD-323 is a very robust combination of assets in this space. Zelicapavir is the most advanced asset in RSV. We have a follow-on next-gen molecule with that. We'll be exploring sort of strategic partnership opportunities in that program as well. With that, I'll turn it over to Q&A. All right. Thanks so much, Jay. I think, you know, let's start with kind of the newer agents that you press released yesterday. I think, you know, we've talked about the STAT6. I think, you know, we're starting to see the space heat up, right? You know, we've seen kind of non-degrading approaches being used. We also have the degrading approach from Chimera, but we've seen non-degrading approaches from Deepcure and Recludix that also have kind of suggested similar data as you in terms of mouse models being able to show DUPI-like efficacy. In terms of actually, like, you know, being able to compete, differentiate with all these approaches, I guess, one, what should we know about the differentiation between a degrading and a non-degrading approach? And then between those, how do you differentiate further among the non-degrading approaches? Sure. I think the—sorry. Thank you. The modality that we're using here that Jay presented is small molecule inhibitor. You know, traditional small molecule, something that we have really good expertise at pre-clinically, both from a medicinal chemistry standpoint as well as pre-clinical development, understanding the drug metabolism, pharmacokinetics. You know, these are all things that we've got decades of knowledge and how it translates ultimately to humans in the clinic. I think the degrader is a newer modality. We'll have to see as more data accumulates how these things work out. Traditionally, they've had some a little bit more unpredictability around those parameters. You know, we don't have any approved one to date, but again, ultimately, we'll see how these things go forward. In terms of within the small molecule inhibitor class, what we've done with EPS-3903 is really the goal was to develop what could be a best-in-class molecule. Optimizing the different parameters pre-clinically around potency, really good nanomolar potency. Selectivity is very important as well. And then all of those ADME properties to generate something that's going to be once-daily dosing with good profile. Got it. Kind of maybe thinking a little bit more theoretically, right? There's been an argument made about, you know, the actual interface between, you know, the STAT6 protein, its interactions. Might be because it's so large, you would think that a degrading approach might actually be easier than, you know, having, you know, a non-degrading, you know, small molecule fit in there and block that interaction. I mean, how do you kind of reconcile, you know, that viewpoint with, you know, your viewpoint of taking the non-degrading approach? One is theoretical and this is actual. That's the main difference. All right. I think you—I ingest. These pathways have been, you know, tricky to work on historically. I see a former Abbott alum in the room. And when I was an Abbott person, you know, we were working on JAK/STAT pathways in the 1990s. And many of them were really, you know, challenging to target the drug, get selectivity. Over time, I think some of the structural biology has helped. Other sorts of just whacking away at it for a few decades has helped. You know, ultimately now, once you start knowing some of the sweet spots in terms of where and how to target the protein, you can find those pockets and successfully intervene with a small molecule drug. I think a priori now there's no reason not to do that or to have to rely on a degrader to do that. I understand the degrader approach and, you know, it can make sense. This is certainly a target that appears to be amenable to it. You know, we're just sort of taking a tried-and-true pathway on oral small molecules that are well-behaved. That can give coverage over a 24-hour time period. Great. Got it. I want to talk a little bit on the oral KIT because you also showed some data, you know, in your updated presentation. You know, we're seeing in vitro selectivity. It looks like you're kind of in the nanomolar range, similar to what we saw with BLU-808. It looks like selectivity on some parameters, at least in terms of the lower bound, you know, could be argued to be a little bit different. I think the real question for the oral KIT, you know, mechanism is how do you get comfortable with, you know, the therapeutic window? Because we've seen, you know, other companies try to go after that mechanism and see on-target, you know, hemoglobin decreases as well as neutrophil decreases. Have you seen anything pre-clinically right now that you think kind of, you know, makes you feel more comfortable about the safety? I think with KIT, you're always going to have to face the fact that it's KIT. There's potential on-target, you know, side effects that could be observed. I think the real challenge will be going in and investigating and understanding, you know, how you might be able to modulate that by dosing paradigms and, you know, to create the best profile ultimately in a patient. You know, how tunable could that be? That was certainly the approach that I think Blueprint was also thinking about, coming up with different dosing paradigms to allow, in this instance, more refined targeting of the mechanism as opposed to longer-acting monoclonal antibodies, where it's a little bit hard to turn it off, right? You know how to turn it on and it can be persistent, but turning it off in the instance where a patient side effect might emerge is harder to do with monoclonal antibodies. We're going to be looking at the tunability of that. We'll have our eyes wide open, you know, for that mechanism. We think it's worth pursuing because, you know, KIT has given sort of the best-in-disease efficacy for CSU. As a mechanism, we know it's powerful. The question is, is, you know, how best to tame the powerful mechanism. Right. And to that point, I feel like PK plays a big role because, you know, like you mentioned, with the antibodies, you can't just stop dosing an antibody and stop seeing, you know, and curb safety issues that way. When it comes to developing an oral, is there an idea in mind of, you know, a target half-life that you want, you know, 20 hours versus 40 hours just to kind of avoid accumulation and be able to reverse some of those on-target AEs? Yeah. Again, not every target needs to be hammered down all day long with full force. I mean, you do in virology, we're used to that. STAT6, you know, you probably want to knock it down pretty good. With KIT, the question is, you know, can you modulate, you know, mast cell numbers as well as mast cell activity with something less than, you know, hitting it with a hammer? In terms of our pre-specified half-life, I think we would like to find something that still allows convenient dosing in the QD range, but that you could also modulate things by dose itself because not everything will carry the same level of drug load throughout the day independent of the half-life. Right. And then the other—sorry. One question from the audience. Jay, just in terms of, okay, Blue got, you know, you saw the Blueprint drug. They said that they were not seeing retic hemoglobin outside of the normal range. I can't help but think there's error bars there and to a certain extent, if it's on target, that seems like an unrealistic expectation. I'd love to get your view. A, when are you going to have 28-day trip-dase reduction data in healthy volunteers? Number two, do you think we could see a press release with the exact same framework that Blueprint laid out, which is, hey, we're not seeing heme parameters outside of the normal range? Yeah. So, I think for that, again, let us get into the clinic. You know, we're, again, we're targeting IND in Q1 and we'll be, you know, generating data from there. Again, you know, the good and the bad is there are people in front of us. The bad is they're in front of us. The good is we've seen what everybody else has generated and can think about trial designs and other parameters with that in mind. You asked a good question, but I can't really— Just to follow up on that, A, are we going to get—because again, it's healthy volunteer tryptase reduction. Is that something that we should get in the back half of the year? Number two, when you talk about trial design differences, I think that the key, and I think Zaki is hitting on this, is you have a half-life, you have a therapeutic window, but then you have a titration scheme where maybe you dose to a certain PD effect and then stop. How do you design a healthy volunteer study that could maybe suss out that difference in a way that maybe Blueprint did not? It's a good question. I mean, you can measure a lot of this stuff in healthy volunteers. The key will be, you know, figuring out what level of target engagement we get with what dose. Then, you know, ultimately figuring out how persistent it is and working from there. Again, you really need to start to get your feet wet with the clinical data in phase one. Akash, I was just going to add, I think, you know, obviously we'll have to do some dose ranging initially just to understand where we're at. We are absolutely thinking about ways that we can be creative around clinical trial design in order to get us a little bit more information and figure out what can be done with these inhibitors. Any backup next year? Again, IND in Q1, you can work from there. We haven't—yeah, go ahead. All right. In our last, you know, two minutes, I just want to hit on RSV for a little bit because we, you know, we upgraded the stock after seeing the RSV data. I think what a lot of people were confused about was that the subgroup that you showed the efficacy in was pre-specified. And when we looked at the data, it seems like excluding asthmatics does kind of have some, you know, mechanistic explanation. Like those patients, it's harder to suss out a response in them. How confident are you that, you know, that will kind of carry over into a phase three and that, you know, that signal is something that's going to be consistent? Yeah. I think we had a broader inclusion criteria for the whole study. And then, as you mentioned, we hone in on this HR3 population or, you know, the patients of greatest risk. For the asthmatics, we did not have any criteria around the severity of their asthma or, you know, whether it was well-controlled. That is why we did not include them in that population because we wanted this initial study to be, you know, focused on the highest risk. I think going forward, it is certainly something that can be studied. I think the primary path we would take as a next step is in this HR3 or higher risk population. You know, given what we saw in the current studies, those results should be translated. I would just add to that that it's not just the symptom data that Jay showed you there using the RIIQ tool, but a whole host of other secondary endpoints that we saw good effects on, including hospitalization, but other PRO tools as well. Got it. And just last question that I want to fit in. In terms of, you know, this is kind of like a large-cap development program, is there any kind of strategic alignment on, you know, how you would specify those subgroups in a phase three and, you know, whether you would use the same LRTD endpoint or RIIQ, any kind of specificity around that? Yeah. I think, you know, given the data from this study, which was very informative for the phase three design, we would use the broader set of symptom data, not just the LRTD. You know, it's more robust when you look at a greater number of symptoms. That's what would likely be the primary endpoint. It's a diverse patient population, right? Right. And to that point, you're doing 500 or 700 patients, right? Your phase three is large enough that I think you would be overpowered to just detect the benefit that you already showed. With that, we're over time, but thank you guys so much.