Wave Life Sciences, Inc. (WVE) October 20, 2026 Conference Transcript

Thank you, I want to welcome you to this session, RNA Medicines, Next Generation, RNA Therapeutics. My name is Kane Akai, I'm the Director of Research and one of the Senior Biotech Analysts at Chardon. And I want to welcome our speaker here for this section, Dr. Paul Bolno, the President and CEO of Wave Life Sciences. So Paul, welcome, thank you so much for joining us. Maybe to start, I think most people are familiar with Way, but maybe summarize some of your key highlights you've accomplished so far this year.

Yeah, well, first, Keith, thanks for having us. And I think that the topic is very timely and appropriate to what we've been doing and delivering, not just this year, but really are poised to deliver over the next couple of years. So I think coming into this year, we had a couple of key objectives. first was delivering on inhibiny the first novel target that's grounded in human genetics to really have an impact not just in healthy weight loss in the field of obesity but really via an improvement in body composition meaning reduction of fat preservation of lean muscle mass and that's the data we had I mean we went into the beginning of the year saying if we could deliver in phase one healthy volunteer patients a reduction in fat preservation of lean muscle be able to do that in a potential once-a-year treatment and have the safety and tolerability that will go forward that would be the objective of the phase one study that was the data that was delivered I recognize that people were were and are hoping for a path to where 5% comes and we're very much and we'll spend more time talking about that on that directionally as we think about the phase 2A monotherapy data in obese patients, which has started, as well as a combination study. But that data is important really in twofold. One was obviously for the genetic target in obesity, but the other, and why I think it's very apropos to the topic today, is really unlocking the next generation of siRNA technologies. It's easy, I think, for people to view siRNAs as feeling very commoditized, that they're plug and play, and I think there's a lot to understanding that in the context of the enzyme. I think AGO2 is now very well characterized and very well understood. What's unique about chemistry, and we're big fans of differentiation in chemistry, is that how we can now exploit AGO2 for deeper, more durable suppression, meaning the ability to take a target that's been very hard for others to drug. If you think about preclinical data, for us we had single-dose data preclinically that could demonstrate weight loss in the diet-induced obesity mouse models. and that's an obese mouse model, we could see double the weight loss with combination therapy, and we could actually sustain the weight loss that was seen as a maintenance therapy. And if you look at all of the other siRNA constructs that have demonstrated preclinical data, they were all multi-dose data sets that slowed weight gain versus placebo. So already preclinically, our data was differentiated based on our construct. Same thing we saw in our human clinical data. We didn't just see a strong reduction in visceral fat. We saw a strong reduction in subcutaneous fat, which is what ultimately drives weight loss. And we saw a waist circumference change of 3.3% in this healthy population, and it translated to a 1% change in weight loss, things that weren't seen with the other inhibiting programs. So again, differentiation starts with chemistry. The other key deliverable for this year was an alpha-1 antitrypsin. So the first RNA editing medicine to move into the clinic, we saw strong editing uniformly across patients, so highly consistent across patients where we show patient-level data, and it's very consistent seeing that Z change to M. We saw the percentage of M in circulation was equivalent to what we saw when we validated our assays on the MZ population, so all suggesting that editing is doing exactly what it should do in a reducible, infrequent way and safe and well tolerated. And that's particularly important looking at liver toxicities in these patients because alpha-1 patients are not just lung patients, they're lung and liver patients. So really having the core profile to treat these patients from both a lung and liver phenotype. The most recent update we gave this year is alignment on the agency on a really innovative trial design that the team came up with to contract the total approval time. So looking We can get a two-year trial for clinical potential registration where we could do an interim analysis at a year for potential accelerated approval. So that program's continuing to drive forward. And then PMPLA3, the next generation of RNA editing coming behind it for the nine million homozygous patients with PMPLA3 liver-related diseases, where we can translate what we've seen now with alpha-1 to this population again in an infrequent-dosed manner. And, you know, I think we'll have our research day coming up in November. And, you know, that's always an opportunity for us to highlight kind of next generation on chemistry where, you know, as we shared last year, the progress that we're making on bifunctional oligonucleotides, meaning the ability to look at targeting multiple ligands, whether we're targeting two SIRNAs that are silencing, upregulation, and editing with silencing, and really the ability to think about multifunctional oligonucleotides, which is an exciting opportunity.

Well, great. Yeah, I think WAVE is highly respected for the advancements in oligochemistry that you've developed. I think your platform is serving you quite well as the leader in ADAR and with your first siRNA coming out of the gate with a very strong drug. And I think let's start with 007, which I think is your most underappreciated asset. As you mentioned, you've reported data. I think that maybe what got lost, in my view, is, you know, the really impressive reduction in visceral fat. I think people are maybe too focused on the total weight loss. But talk about that patient population and the, you know, starting BMI and maybe some of the other observations of, as you mentioned, body composition and, you know, some of the key takeaways, in my view, that maybe are underappreciated or just being overlooked?

Yeah, it's a wonderful definition, because I do think the data was underappreciated, overlooked, and I think a lot of that was driven on the first data set that was really exciting. I mean, we saw really compelling data in a phase one healthy volunteer population, so I think the enthusiasm started early, and as we reminded people, this is still a phase one healthy volunteer study, and to your point, when you run those studies, because you have to run those studies in obesity they don't tend to occupy the attention space as our data did but I think it's really critical to remember we often talk about BMI you can have an elevated BMI in a healthy volunteer study where those patients are not allowed to have any comorbidities right because the whole premise of a healthy volunteer study is being able to make sure that you assess the safety liabilities of the molecule and you don't want to confound that with patients So if you take a typical patient population that has high BMI with comorbidities, which is your classic obesity patient population, that elevation in those comorbidities is driven from high levels of fat, visceral fat and subcutaneous fat. We have to remember you can have elevated BMI and be a bodybuilder in a healthy volunteer study where you're going to have low amounts of or lower amounts of visceral fat, subcutaneous fat. And so I think that understanding of the patient population, and most importantly, not just BMI, but the absence of comorbidities, is kind of the core driver in a phase one study, which is, again, why these data were in our minds so impressive, which means, as you point out, I mean, we saw nearly the same amount of visceral fat reduction as GLP-1s, as phase two A companies that have developed in inhibiting data sets that have been seen, and yet that's in our phase one population. So if we compare to the other inhibiting e-silencer in that 2A population, we had about a liter of visceral fat total because those patients had no comorbidity. The comparator had five liters of visceral fat. So just to kind of put that in context of the differences of starting disposition in fat, both visceral fat and subcutaneous fat, and after a single dose, we're still seeing substantial reductions to that point of nearly 15% reduction in visceral fat, substantial reduction in sub Q fat reduction in waist circumference and a 1% change in body weight again in this population purely on fat and so I think with a safe tolerable profile at once a year so to your point I think that data continues to give us the conviction as every other two-way study there's other medicines that cause lean mass stabilization to increases to some of the myostat and medicines that have been developed like the magra map and if you think about that with higher lean mass and less fat loss over a one-year time point they lose over 5% total body weight so it's why you know when we think about the patient disposition in our 2a study which has been dosing for a while now that study those patients have elevated BMI so that's in the range of you know 35 to 50 they have comorbidities so they can be diabetic and have other comorbidities what does that allow that that we believe like every other diet obesity study will lead to, and there's a graph that we did when we plotted the BELIEVE study with the magromab and semaglutide, which was really important because if you look at the starting baseline characteristics of those patients, they look very typical to most obesity studies. They have elevated levels of visceral fat. They've elevated levels of subcutaneous fat. And if you plot on that chart where our baseline characteristics are for a healthy volunteer study, those patients start at where all of those other patients ended after a year on therapy. So very much the same would be said as we plan and model going forward that in our study patients have high levels of visceral fat, high levels of subcutaneous fat, and it's really the subcutaneous fat that ultimately drives the weight loss as measured by pounds on a scale. I think the other evolution that's happening simultaneously with our work is there's a large effort by the patient community and even we're seeing this now with the agency to really identify body composition is an important feature the realization that loss and muscle mass is not just a structural phenomenon it's important in terms of you know preserving the muscle but insulin sensitivity from muscle as an endocrine organ is really important in terms of perpetuating fat reduction so as we think about the ability to preserve lean mass C reduction and visceral fat and subcutaneous fat. I think we're in a really good position with the direction of where regulators are going, the ability to deliver on the regulatory thresholds for obesity, but with a very differentiated profile. And I think in this environment, particularly commercially, a once a year sub-q therapy, I think, competes very well in this environment.

And before we get into more detail about the phase 2a patient populations, I don't want to just bypass your siRNA, because it It is your first one, but you come out of the gate with a really strong candidate. And so maybe talk about, you know, how your platform has allowed you to come out with something that's differentiated. Maybe I know you touched a little bit, but maybe with the focus on how it engages with the risk complex.

No, and I appreciate, Kay, you're mentioning, you know, at the core, WAVE is a chemistry engine. And I think what we and we published this paper, it's probably going on three and a half years ago in NAR. this breakthrough paper on what we could do with AGO2 loading using stereochemistry and modifications and our phosphoroid guanidine and the other base modifications. And so when we think about those, they were giving us nearly 15-fold improvement in AGO2 loading. That translates to once you're on that mechanism, not just deep potent knockdown. And we did this comparison in to the best-in-class TTRs, and we saw better knockdown and more durable, which really lent itself to a potential once-a-year therapy. And I think, you know, as we were looking years ago, kind of saying, well, you know, this is interesting. You could do them less frequently. Maybe they'd be more potent. You know, what targets are going to be interesting for us to pursue really led us down a path to, you know, this target was emerging out of the UK Biobank as a very compelling target. It's very specific. Our view was, you know, the receptor, and there's a lot of discussions more recently about ALK7, which is a receptor on adipocytes that has multiple different ligands. Recently, a company who's deep in that space that has ALK7 and inhibony showed that if you knock both down, you don't get synergy. So it really does speak to that fat adipocyte shrinkage is due to the active in E pathway and that you're not gaining additional things other than potential liabilities since it's not just on an adipocyte. So our view was target a single receptor, be able to deeply, durably reduce that receptor and see the benefits that could come with essentially what was a longitudinal study run in humans, which is the UK Biobank study on inhibiting that shows cardiovascular outcomes benefits, type 2 diabetes outcome benefits, and reduction in fat. And so when we looked at that, that was a compelling target. Well, there was another company that was deep, probably viewed as probably the expert in siRNAs at the time, and we were slightly behind them. And I think the discussions were always like, how are you going to catch up? How are you going to catch up? And I think the translation of our chemistry engine actually had us with a candidate now three years ahead of that technology. So the ability really to deploy this in a way that's unique, being able to harness ACO2 in a very unique way, has given us the ability not just to do hepatic siRNAs. We shared last year, We'll share more data on the extra hepatic silencing, but really being able to open up that space substantially to think about ways of targeting through silencing and siRNA, again, both liver targets and beyond. And I think it's an exciting platform. It's nice to have an application in these deep suppression targets like inhibiting where we can get clinical validation of the siRNA platform and a really important target.

Okay, great. So, you know, 007 now in 2A studies. Let's start with InLight. As you mentioned, first, monotherapy. Two, higher BMI starting level, can be diabetics or not. Once you get to reporting data, from your perspective, what would be a good outcome to report?

Yeah, I mean, I think, as you pointed out, this study is a meaningful study. And I say that because, as you point out, it's not just high BMI and comorbidities. There's actually four arms in the study, so we're looking at two dose groups to be able to establish what the dose and frequency, you know, we think ultimately should be for this medicine. And it's also broken into two different cohorts, a diabetic cohort and a non-diabetic cohort specifically. And we'll talk a little bit about that to your point on outcomes. because I think, one, this is the opportunity for us in an obesity study to generate meaningful fat loss, body composition improvement, and weight loss, so the ability to see those endpoints achieved in that study. I think the other piece that's important in this study is there's a whole host of indications for inhibiting. So if we think about inhibiting as a cardiometabolic target of which obesity is an indication, we built into this trial, because we often get asked the question of, you know, have you guys thought about MASH? Have you guys thought about diabetes? Everything is designed. We've designed this study with intentionality that we don't need to run multiple studies to do that. So case in point, patients who are diabetic with high BMI in the study will have high levels of visceral fat. So we'll be able to assess monotherapy reduction in liver fat with MRI PDFF that's embedded in the study. We'll be able to look on MRI at total body composition and scale weight. but we'll also be able to look at insulin sensitivity lipid profiles so as we think about the totality of the study the important thing is it's going to unlock the cardiometabolic range of indications that can be done without us having to start again and run additional studies so this is a very well characterized well-powered study to be able to assess that I think we're also gonna have the opportunity as we said recently in initiating the combination study that these studies are all kind of running in tandem so now through combination we'll be able to look at the trisepatide combination with inhibiting and the advantage there is this notion of thinking about real-world applications of how these are going to be used right there's a monotherapy population that's probably about 30 million patients who are sarcopenic obesity patients in the US so these are patients who you don't want to run the risk of losing muscle mass in exchange for losing weight and so thinking about a very defined patient population besides those who may want to go on a medicine that causes fat loss without muscle loss but this is a tight patient population you know there's a whole group of people who are gonna be thinking about how do you titrate medicines and so what's nice about a once-a-year therapy is you can get your once-a-year shot with inhibiting and then be able to titrate and give physicians the opportunity to titrate how they want to use incretins whether it's down titration because you don't need as much you don't have to up titrate and have the safety liability that tolerability liabilities that come with that and frankly the reduction of lean mass in exchange for that weight reduction or combine it because you need more fat reduction and weight reduction and think about these together. I think the third application which will start this quarter is probably one of the most interesting applications for Nibini and that's the maintenance therapy and that's really thinking about the application where you can take the universe of patients and say you know do patients want to stay on a weekly and you can say well orals are coming and I I think the real-world evidence as we look at statins and utilization and adherence there will play into the adherence rates as we look long-term in the obesity space. The idea that you could go in for a once-a-year shot, and this is actually probably where the best data exists. If you think about the human data inhibiting experiment as a heterozygous is a long-term maintenance study. We've done our own maintenance work of predosing and removal of incretins and show that because you take the break off lipolysis, you don't rebound weight gain. and so you don't reaccumulate fat, and so you don't go through that weight cycling. The idea that maintenance therapy becomes the long-term solution ultimately for obesity care becomes an interesting therapy at a once-a-year dosing. And so again, we'll have these three different use cases. They'll all be generating data. So as we move through 27, the opportunity to be generating data across multiple different patient populations and multiple scenarios, I think will really open up the opportunity set for inhibiting in cardiometabolic disease.

Well, great. Yeah, I think all of this data will provide an answer and inform the key question that we've been asking for companies that are focused on inhibiting is, you know, what's your lane going to be? So I think once we'll have this data, we'll know what the best applications are. I guess maybe the final question on this is, I know any time you report data, you want it to be meaningful.

So what's your latest thinking of timing and how far you get down the road with either these two studies before you report data yeah I think I think we always realize that meaningful to us doesn't doesn't always translate and you know I think we're acutely aware of that right I mean I think meaningful to us is it's remarkable in a phase one population to see substantial changes in body composition the medicine doing what it's supposed to be doing I think we recognize that the focus and attention on regulatory endpoints and thinking about that is also there and so that's factoring into a lot of where we would decide ultimately to bifurcate and cut the data. I think what is important for people to know is, this is not data sets that we are constantly monitoring. So this is not like constant unblinding. So we'll make a definitive decision and provide an update of where we would decide to unblind the data. And it's very possible that we decide to do that at the six month versus the three month time point. So we know and we've seen that. If we think about around this time last year when the data came out and everybody's excited, the biggest overhang that would pressure point for us that we kept hearing was, is muscle gonna keep growing forever? How are you ever gonna show this if muscle keeps building? And we said, look, everything that we've seen shows that muscle stabilizes at three months. And that's exactly what we saw, the three-month time point, lean mass stabilizes, fat continues to decline. So I think as we think about that, the opportunity for that shift from a powerful body composition time point, which I think three months will show a powerful body composition improvement, whether or not we wait to the six-month time point, because that's where you would expect to see with lean mass stabilization and further fat decrease, that's where you'd see a shift in body weight. So that's our opportunity set, and we'll continue to evaluate it. I think it's also important for people to realize because there will be more inhibiting data emerging. We hear a lot this, you know, is inhibiting a mass drug versus an obesity drug or a cardiometabolic drug, to your point on trying to understand lanes. I think we do need to really reflect that with the progress made in siRNA, there are differences. And I say it again, we saw differences pre-clinically where we saw single dose weight loss in the obese mouse model, and we saw subcutaneous fat reduction, waist circumference changes, and body weight reductions that others haven't seen with their inhibiting. We've done that all with single dose. Even our comparators that people make in the clinic are multi-dose studies in a advanced like phase 2A obese diabetic patient population. And so I think that's really critical as we see data emerge in this class that we do remember that, you know, this is an opportunity for chemistry to matter. Our data has been differentiated, and, you know, we're excited to continue to lead the data for inhibiting for the space and characterize it.

Okay, great. Well, let's talk about your ADAR pipeline. Again, you're the leader there, so much so that, you know, you've been able to meet with the FDA and sort of reach agreement on the path forward to get approval, a two-year registrational trial with possibly a one-year interim analysis that could support accelerated approval. So maybe just further fill in the gaps here and tell us where you're going here.

Yeah, I mean, I think stepping back, much the same way we just described what we did with siRNA and why chemistry matters, we see that playing out in the field of ADAR as an enzyme. And I think, you know, the common thread across all these different technologies, because people sometimes are like, well, they seem so different. There's a lot of similarities, and the similarities are understanding pharmacology and how chemistry impacts pharmacology and treating these enzymes structurally plays a major role. So the ability of making stereo-pure medicines, you know, we get the question of, like, are you still making stereo-pure medicines? And we absolutely are. Because when you can make a single construct, we can now say, what's different about this construct than that construct, right? We can define these as two distinct pharmacophores, right, and then therefore make modifications. So for editing, N3-uridine and other chemistries that we have invented have given us better site-specific editing, better potency on target. And so I say that to remind everybody that, you know, when we talk about these, there's a lot that goes into it when we talk about alpha-1 antitrypsin that really gets to what distinctly makes that medicine unique from others working in that space. That enables us to drive different pharmacology, so durability, potency, specificity. And I think that opportunity that we had in generating these data, I think, gave us a high degree of conviction. I think one of the things that we've seen, and again, I think it was one of the most important data sets for us, is the high consistent patient responses. So this wasn't an anomaly. We often see data reported as averages, and I think it was important for us to say as the first modality to give the transparency of here's a patient-by-patient reduction of what's happening so we can see the dynamics of it because it is important to see onset and what's driving it. I think what was also the most compelling and it was interesting it was an area that even those in the agency were like oh that's that's compelling is this acute phase response and I think as we think about alpha-1 antitrypsin therapies I think we really need to remind ourselves in stepping back of what's the treatment paradigm for ATD and a lot of people will hear or more and think about more is better and a very what I call kind of the augmentation mindset this idea that you need to pour more water into a bucket with holes in it because it's constantly depleted and the notion that alpha-1 antitrypsin deficiency is a chronic disease of acute exacerbation so you've got these inflammatory spikes that injure lung they also produce protein that builds up in the liver during those events and this notion that the whole system for the body was all designed not to have a steady state all the time to be at that max level to protect the acute phase response because it's a depleted protein so actually you know the real question is nobody really knows how much of that protein that you've infused is actually there during the event cycle because it's consumed during it and leaving patients open to injury for lung the whole notion of editing is how do you get those transcripts ready so that when you have those acute phase responses patients can respond naturally produce that protein into the event and I think that was one of the reflections that you know we could share back from the agency is like that's the dynamic that ultimately looks like it's potentially protecting disease yeah you had that one patient and so well actually it was more than one we had a couple that we we said but you know the first one that i think everybody reacted to which is the first time it had ever been seen in a clinical trial for alpha one yeah you could get over 20 micromolar protein produced in the event we saw several others in the next cut and then we actually did the analysis which was important on the correlation that we It could actually correlate those because there's always these background levels of inflammation. I mean, when you talk to these patients, you know, they'll tell you that even walking outside creates potential injury. And so even in the small excursions, you could see that the native protein was getting made during those. So I think we've got a really compelling data set that aligns with that whole acute phase response. And I think it's going to be important for the field as we think about treating these patients.

Do you have clarity about the thresholds that you might want to see achieve for total AAT or percent M-AAT?

Yeah, I think as we've said a number of times, we're not going to competitively disadvantage ourselves by kind of sharing those conversations. You know, we know there's a number of peers that are actively in discussions with the agency around trying to align on either assays and validation of assays or endpoints or, frankly, clinical trial endpoints. So we have what we need to know to move forward. And I think to that sense, I think what we can say is, you know, we went into it saying that MZ-like phenotype is the protection, right? That's the whole goal of editing. And if we could leave with MZ-like protection, that would be an important component of that improvement.

Well, we've reached the end of our time here. I'd love to talk more about PNPLA, which is your next one. Yeah, that's an example. I guess we'll have to wait for your R&D day to maybe get more info on that.

Yeah, please tune in.

Thank you so much for joining us.

No, thanks, Ken.