Good afternoon, everyone. My name is Lisa Bayko. I'm one of the analysts here at Evercore ISI, and this is HealthCONx. Thank you for joining us, and I'm really excited to be introducing Paul Bolno, who's President and CEO of Wave, and I've been tracking Wave from afar. It's not a company I cover, but I've been always really impressed with their AAT program, and now they've got some other cool stuff, like obesity and other things going on, which we'll touch upon as well, so welcome, and thanks for joining us.
Lisa, thanks for having us.
So let's just start off with a kind of high-level company overview, your platform, technology, and that kind of stuff, and then we can get into some specifics.
Yeah, no, I think it's important because, as you pointed out, as you've been following us thinking about AATD and editing, I think it's a step back and realize how we got to editing, how we've been delivering on RNAi for obesity, how we've been delivering allele specificity in HD, all really stems at the very beginning and at the core for Wave as an oligonucleotide chemistry company. So if we think about the investment over the last now over a decade, it's really been in the optimization of building differentiated proprietary chemistry, starting with stereochemistry and realizing that once you have a single molecule, you can now bring rational drug design to the field of oligonucleotides. The evolution of building on that with our PN modifications of the phosphoryl guanidine and its variants have opened up accessibility to cell types, tissue exposure, pharmacology.
And so all of that has really built over time. So when I think about kind of Wave from a platform perspective, we've built best-in-class oligonucleotide chemistry that spans modalities, and then have really now been poised with the progress that's been made on clinical genetics to find that intersection between strong chemistry, strong genetics to open up a portfolio. And so we've seen that with, again, the first allele-specific therapy targeting HD, RNA editing with alpha-1 antitrypsin, the ability to expand beyond that with the other next three programs that we introduced at R&D Day, LDLR, PNPLA3, and ApoB. And then really, I think being at the precipice for obesity and hitting the underlying genetics with Inhibin E, where we find a target that in human population studies shows reduction of abdominal visceral fat, so low waist-to-hip ratio, improved lipid profiles, and cardiovascular benefit.
I think it's been really fun to watch the evolution of chemistry now translating into therapeutics and where that's going to take us.
Great. You just hosted an R&D Day, so thank you for that. Maybe you can give us some of the highlights.
Yeah, I mean, I think if we kind of build on that introduction on the company, I think first and foremost, we started with an introduction to PN chemistry because I think for a long time, as we generated three positive clinical data sets in 2024, HD, DMD, and the alpha-1 antitrypsin data that you were referring to, one of the common features across all of those, despite the differences in modalities, beyond just the stereocontrol backbone, is the phosphoroguanidine modification. And so we shared data from R&D Day. Just the basis was PN chemistry unlocking distribution. So endosomal escape, so improved uptake of drugs into cells. We saw getting out of the endosomes to the right compartment within the cell, and that's drug in. What we also saw was the ability to sustain and retain drug, meaning once drug's in, the other side of that quotient, drug out.
Retain drug, driving better durability, better pharmacologic effects over time. What we're able to do at R&D Day, building on the back of our chemistry engine, was really walk through how we're applying that to the current clinical program. We gave the update following the positive alpha-1 antitrypsin data for the first RNA editing program, where we essentially achieved therapeutic levels of editing, meaning 60% of the protein was M protein at 6.9 micromolar of M protein out of a total of 11 micromolar. We saw M protein out to day 57, so durability. But what was really important was not just talking about AATD, but really building the editing franchise itself. We gave the update on the next three targets that are going to be using our chemistry along with RNA editing. First in those targets was PNPLA3. Here's a target.
We like targets that have genetic drivers behind them, but also where, in the case of editing, where editing is the core modality and you wouldn't want to use other modalities. PNPLA3, where silencing has been shown to increase hepatic steatosis. But actually thinking about this target, not from the disease working back to a targeting of PNPLA3, but rather thinking about the nine million homozygous PNPLA3 patients who are at risk of liver disease, if you can edit PNPLA3, so improve the protein, just like we're doing with alpha-1 antitrypsin, you can take those patients who are at risk of liver disease as homozygous and bring them back to a heterozygous phenotype. Again, the parallels with AATD are extraordinary. In those patients, they have lower risk of liver disease. You can measure that both by plasma biomarkers as well as tissue.
We can take a lot of, again, of the learnings going now into multi-dose data in 2025 for AATD that continues to de-risk that program as we think forward, and that's a target about nine million patients, again, with the homozygous mutation.
What's the next step there for that program?
We'll have a candidate in 2025. That'll, as we think about AATD at 2025, multi-dose de-risking platform, being able to unlock the next program, that program will be then set up for candidate to then move towards the clinic. Then subsequent to that, LDLR, another great holy grail within lipid biology and saying, actually, if you think about patients who are currently treated with high-dose statins and PCSK9, only still 50% of patients are at treatment goal. Actually, the holy grail for treatment of familial hypercholesterolemia and, frankly, cholesterol treatment more broadly has always been if you could upregulate the expression of LDLR receptors, so the receptor for LDL on the hepatocyte, then you could reduce LDL levels. That's been a challenging challenge with other modalities.
With editing, we could show that if you modeled to a two-fold upregulation, it would bring 90% of patients into treatment goal. We were sharing preclinical data that we're now at two and a half-fold upregulation of that. We see synergies with statins to where you see about a four-fold upregulation in combination. Really a fundamental shift in the treatment for not just familial hypercholesterolemia, where you can get about a million patients, but ultimately where you could expand that into just the treatment of statin intolerant patients, which is 20 to 30 million patients. What's interesting and why ApoB was brought up as another target is this is one that if you knock out and silence the mutation of the ApoB protein, you actually end up with building up liver fat, right? You can get hepatic steatosis, triglyceride buildup in the liver, liver injury.
If you could fix the mutation, you actually bring that lipid LDL particle into the cell. It gets processed, so if you were looking at LDL as a study, if you were running the LDLR study, you would screen about 10% of those patients out who had this mutation, and therefore, by fixing the mutation, you can now treat, so we could run one study looking at both LDLR, ApoB, and now treat 100% of the patients in that study, so that's kind of the editing component of R&D Day. We then gave an update on the work we've been doing in obesity, and that was the work where we showed knockdown that had weight loss similar to semaglutide, but for obvious reasons that Inhibin E doesn't work centrally, so you don't get the CNS side effects.
You don't get gastroparesis, so you don't get nausea, vomiting, and you don't get loss of lean muscle mass. So we showed kind of single-dose data that was really important and compelling. But then we also showed mechanistic independence. So we showed a synergy study with GLP-1. So you could double the weight loss of the GLP-1s by adding a single dose of Inhibin E. So that's important as we think about the treatment of obesity, where physicians are tapped out and maxed out on how much GLP-1s they can push patients on. And so for patients who have real BMI challenges, you can add this and get mechanistic synergy. But where we think the real opportunity near term is, and commercially for Inhibin E, is getting patients off of GLP-1. We see it as the GLP-1 off-ramp.
So we did the study that showed if you have two arms of mice, DIO mice, both treated with GLP-1s, and then you withdraw GLP-1s, but in one arm you dose them with Inhibin E, you see that the ones non-treated with Inhibin E have just what you would expect. They have weight recycling. They actually exceed the threshold where they were prior to treatment with GLP-1s in terms of rebound weight gain. And those treated with Inhibin E have no weight gain. So I think.
You're not trading one treatment for another treatment. People.
You are. I think the difference in how we think about these different treatments for a real public health problem of obesity is that we're looking at a once to, at worst, twice a year subcutaneous therapy that doesn't work centrally, so you don't have that suppression of joy. There's not a loss of joy by knocking that out centrally, which is why you see that lack of eating and that intake leads to a starvation catabolism of muscle. When you treat with Inhibin E, the ligand for Inhibin E is produced in the hepatocyte, and its receptors on the muscle cell. I mean, sorry, the adipocyte, the fat cell. So if you knock out the Inhibin E protein, you see adipolysis, lipolysis. You see shrinkage of the adipocytes. And that's one of the things we showed at R&D Day was actually that in play.
We saw a reduction of the fat cells, and we see it translate to about a 53% reduction of visceral white fat, so it's mechanistically distinct, non-centrally acting, and you don't have a lot of the other side effects.
So you're going hardcore into cardiometabolic, it seems like, as your next wave, so to speak.
I think we're going particularly hardcore on genetically validated clinical genetic targets that we can tractably measure and have good drivers to drive ourselves there. I mean, I think when we look at various targets, I think near-term metabolic happens to be identified by thinking about genetic obesity. What we didn't say going and thinking about obesity was we need to be in obesity. Let's see if we can find a target that by happenstance drives us there. I think what we were really impressed in the clinical genetics for obesity, these patients who are walking around with a 50% protective loss of function essentially have that treatment at play. Being able to recapitulate that biology is really important.
This all started with my interest in AATD. Let's go back to that.
Yeah.
Tell us more about the program and kind of your studies ongoing there.
So at its core, I think we approached RNA editing with our best-in-class chemistry, so bringing all that we could to now tackling a new enzyme, in this case, ADAR. So designing a short chemically modified oligonucleotide stabilized through the PN backbone. So not only would it be able to engage efficiently with ADAR, we have new modifications we've used specifically for ADAR editing with the N3 uridine, which we saw improving that editing efficiency. So if you take kind of the best-in-class chemistry that could be applied to ADAR, we saw preclinically that translate to high editing efficiencies, durability, and translating ultimately to protein production. So kind of all of the features in the SERPINA1 model, if you think about being able to drive forward, where we could see that therapeutic benefit take hold.
I think what's important, because this was all compatible with GalNAc, means we could think about a sub-Q approach to delivering that, which meant being able to have highly efficient low doses that could go to the right cell type. What's interesting about the model as we thought forward to getting to that data was in the SERPINA1 model, because it's a transgene and you have the production of that protein coming from all cells in the liver, and I agree the hepatocytes are the vast majority of cells in the liver, means that our efficiency probably was still underpredicting what could be translating in humans, where the only target of interest are hepatocytes. So it was a good model to start with because we could say, okay, at best, the model would essentially underpredict what our efficiencies could be.
We saw editing efficiencies in excess of 50%, so well above the threshold for the heterozygous phenotype of 50%. Protein productions at upwards around 30 micromolar or more from a baseline nadir of below 11 micromolar, which is different than others had seen before. We could rescue. That's a normal healthy level of protein. We had all the building blocks on the protein production side, the editing efficiency side, but also saw that with that degree of editing, we could clear Z protein out of the liver. We could actually measure that both on looking at liver aggregates, liver globules, and Z protein coming out into serum. Kind of all of the building blocks preclinically to move into our human clinical experiment. We've moved RestorAATion-1 forward, so that's the healthy volunteer study. We have completed that study.
Single and multi-dose have ample range. That top dose from that healthy volunteer study is well in excess of where we need to be from a therapeutic study. But I think what was most surprising to us was that the first two patients to come through that study at a low single dose, and that's a dose lower than in GalNAc, 200 milligrams, would have that degree of editing efficiency, meaning 11 micromolar of total protein, 6.9 micromolar of M protein that comprised greater than 60% of plasma protein, meaning high degree of editing efficiency at a single dose and the lowest dose in the cohort. So as we think forward, hugely optimistic as we think about moving now into the multi-dose sections of the study where patients are getting repeat exposures at that dose.
How often were you dosing?
That study was always designed to recapitulate the SERPINA1 model since it's the first human experiment of ADAR. That was biweekly, so every other week dosing. When we think about this multi-dose data coming in 2025, we're going to have a high degree of exposure with which to be able to think about not just where we need to go to from a dosing standpoint, but from a durability standpoint. We saw M protein out at day 57 after those single doses. I think what we're going to be able to do with repeat dose is really think about what does that frequency need to look like. Is it monthly? Is it quarterly? Ultimately, the way the study is designed is we don't have to wait to the completion of the multi-dose to move to the next cohort.
So we can look at the next highest dose and the single dose. That'll give us an amplitude or exposure phenomena. So we'll have a lot of data as we think forward, both about the durability and exposures with the multi-dose, but also what the next level of dose cohort's getting us to be able to optimize both the dose and dose frequency.
Then as you think about sort of what you need for registration, how do you design a study for that? What kind of endpoints do you look at?
Yeah, I mean, also work with our partner, GSK, to define how they and we are thinking about the subsequent development. But I think if we think about where the regulatory threshold has been in protein replacement, and this is actually fixing the underlying transcript and therefore generating that healthy, I mean, the level of protein looks like the heterozygous patient, that means that 11 micromolar has been the consistent, that was the driver for IV protein replacement. There's been debates as in Inhibrx and others have developed other proteins of debating whether or not that needs to be 11 micromolar or 20, and not going to enter the debate of protein replacement. But the rationale behind the 11 micromolar originally in IV protein replacement was always predicated upon the heterozygous phenotype having at its lower limit 11 micromolar of protein.
So if you're truly recapitulating that patient, which has a, they don't have respiratory and liver complications, then 11 micromolar of protein is sufficient to drive that. The fact that we're seeing that the lowest single dose as we think forward means we could start thinking about whether or not you start working towards healthy levels of protein. And the fact that we're editing at the promoter site means that patients can make their own protein. So while we're looking at snapshots of where these patients are over time at a baseline level, it still, by fixing the transcript, still gives patients the ability to make more protein when they need it because it is a reactive protein. So I think the advantages of editing over protein replacement really are restoring a normal physiologic balance to the treatment of alpha-1 antitrypsin deficiency.
Great. Now, we don't have a ton of time, but I do want to touch upon your Huntington's program. There may be a little bit of DMD as well. So your Huntington program looks kind of interesting as well. Maybe talk us through what you're doing there.
It's very interesting. I mean, when we thought about the treatment of Huntington's, it's both a toxic gain of function and a loss of function disease. And so driving the biology for the treatment of HD has always been, could we see a reduction of mutant protein and retention of wild type? So you restore that healthy protein. In our clinical study, 30 milligrams repeat dose, we saw a 46% reduction of mutant protein, no change in wild type protein. And so a profile that looked extraordinary for HD, with the other point being that this was the first time in a clinical study anybody's shown the reduction of mutant protein correlating with slowing of caudate atrophy. So actually looking at the physiologic benefit of an anatomical benefit of slowing the key region of the brain responsible for symptoms.
So that was important as we looked forward at some of the natural history studies being run. There's been a lot of conversation in the HD community recently, including regulatory interactions around looking at caudate atrophy as a clinical surrogate endpoint for HD, with the recognition that in all the natural history studies, there's a steady slow reduction in caudate atrophy that's sustained from the early stage one all the way throughout the course of the disease. So it's highly correlated. And it was statistically correlated with total functional capacity, total motor score, and CHD-RS, which are the clinical regulatory endpoints. So it lent itself ideally as a clinical surrogate endpoint.
And so by de-risking in the clinic that we saw not just target engagement, so hitting the mutant protein and preserving wild type, but seeing that correlation with slowing of caudate atrophy, it lent itself nicely to what's the next step for the program, which is submission of a potentially registrational study that uses caudate atrophy as a primary endpoint.
Great. So when should we be, what's the next steps there?
So the next steps where we gave guidance in last earnings on the regulatory interactions and the planning for that IND submission, and that IND is planned for second half of 2025.
Okay. Well, I don't think we're going to have time too much to talk about your DMD. It's funny, several years ago, you were a DMD company. Now that's like the last thing we're talking about.
I think we remain an RNA medicine company. DMD, we showed high levels of dystrophin and consistent across patients. That was key in our last data readout at six months. I think what was also important in that data set, beyond safety looking like standard of care, is that we saw CK reductions, muscle structure was improved, and we also saw getting to muscle stem cells. So I think if we think about that first data set, there was a lot of de-risking that happened at the six-month time point. I think as we think forward in DMD, and we'll have our 48-week data in the Q1, not only do we want to see the consistency of the protein expression and the like, but we'll have clinical endpoints on 95% stride velocity, time to rise.
I think it is important in this space to start seeing trends on those clinical endpoints, and 48 weeks would be the time where we'd look to see that.
Okay. So in the next one second, if you could just tell us, give us just a view on 2025 sort of key catalysts and goals for Wave?
Yeah. So I mean, 2025, our goal is to consistently deliver like we did in 2024. 2025 being important that Inhibin E CTA will be submitted this quarter, so Q4, starting dosing Q1 of next year for obesity, so getting that study up and running so that we can deliver data like other obesity studies at that three, six-month time point in that range. Being able to think about the multi-dose data for alpha-1 antitrypsin and also in 2025, the 48-week data for DMD Q1 of 2025, and then the progress across de-risking of the other RNA editing programs beyond alpha-1 antitrypsin moving into candidate in 2025 as well. So if we stay on task, 2025 is poised to be another exciting year.
Great. Thanks so much, Paul.
Thank you.