Generate Biomedicines, Inc. (GENB) September 2026 Conference Transcript

Hello everyone. Welcome to the third day of the HC Wainwright conference here in New York. My name is Mitchell Kapoor. I'm a senior biotech analyst here at the firm. Today I have the pleasure of welcoming Generate Biomedicines for a fireside chat. From the company I have Jason Silver as the CFO. Jason, thank you so much for joining us. So I like to start off the discussion for those who may not be familiar with the company or up to speed in the last couple of months. Maybe, Jason, you could start off with an overview of Generate and then talk about, you know, the lead programs, but also kind of the broader platform context and the technology and the future of the company, how that could shape and evolve over time.

Sure. So Generate, I mentioned JetGPT and AlphaFold and some of those. other technologies and really what we were found to do is use generative machine learning technology to ultimately discover innovative differentiated novel protein therapeutics for patients and really trying to discover things that traditional drug discovery is unable to do just given the ability of technologies to explore a much broader landscape of potential opportunities for proteins um what we did very early on at the company is started to understand what the technology could do and one of the big concerns that or these ideas that we could have been concerning is are these novel therapeutics that are generated by ai or machine learning are they immunogenic and how would they actually be in the handled in the body relative because they're not you know, formulated using the traditional technology or traditional techniques. And so we started very early with looking at low biology risk products, which is why T-slip, our lead asset, was even just talked about and we initiated on low biology risk, known pathways, safe molecule, but had some deficiencies in it that could be improved upon that could improve patients' experience with a medicine that was very highly effective and safe. And so tezapelumab was kind of the first or anti-TSLP molecule was kind of the first lens that we took as a company and what we did with that molecule is effectively used half-life extension technology which a number of other companies are certainly using but use our technology to change the molecule to get a much better binding affinity to the cytokine so while we hit the same epitope as tezapelumab we have tighter binding affinity by 20 folds frankly 100 femtomolar level of binding affinity We think the critical nature of that molecule is not just the long half-life, which is a 98-day half-life, but also you need that tight binding affinity on the cytokine to ultimately get six-month dosing and not have waning efficacy over time. And so that's why we started with TSLP. Ultimately, we've done multiple partnerships with Amgen and Novartis as examples, who we would view as some of the greatest protein engineering companies out there. And they obviously have been extraordinarily successful at using traditional techniques and coming up with molecules and what they did in our partnerships amgem we partnered with five years ago novartis we partnered with two years ago is they're bespoke around individual targets where ultimately they gave us some of their most challenging uh or most difficult challenges with protein engineering to come up with molecules or test biology and so these are target specific partnerships but what it taught us in addition to great partners that we have it taught us where the struggles that traditional techniques have in protein drug design and so i'll get into some of that because it really gets the platform in the next wave of products that we have and so ultimately we've learned from that and so some of the new wave of things that we're working on are those innovative technologies now one of the core things that differentiates us and i'll come back to the platform is we're not just a machine learning ai company that uses you know models and ultimately believes we're going to come up with the next wave of therapeutics based on the quality of our model. We think models are ultimately going to commoditize or already commoditizing. And so frankly, just having a better model, and even though we think we were first and probably have one of the best models out there, that's not enough. Biology is just such an unknown science, an unknown space. If you think about large language models and using the internet, if you ask ChatGPT to write you a paper, it can do an incredibly great job at writing you as long a paper as you want on almost any topic. Biology is just not known, so it doesn't have the breadth of knowledge. It's probably only 5% or 10%, maybe 15% known, and so it's not like you can use LLMs to come up with billions of hypotheses and know which one is actually going to be the right hypothesis. You need something to be able to test, an experimental wet lab capability to be able to test at scale these molecules, so one of the core differentiators for Generate is while we've invested heavily on the models, we've invested as much, if not more, on the experimental side. So while we can get billions of hypotheses, we actually, in the order of days or weeks, can test every single one of those hypotheses in bespoke assays to determine which are the ones that are going to be most promising for protein therapeutics. And so happy to get more into that. The last point I'll just mention, because there's a lot more, we've translated five molecules from our model into the clinic. We've shown they're not immunogenic. There's no more ADA formation, actually very low ADA formation. They're highly efficacious molecules. We have lead assets are in phase three, which is the anti-TSLP. We have a couple oncology assets that are in phase one, which I'm happy to talk about as well. And that next generation of molecules and where we're focused now are on the things that China can't necessarily brute force their way into today or traditional techniques really struggle to do. These are things like pH dependent binding. So can you get a thousand fold difference in a binder, a protein binder at a pH of 7.4 versus a pH of six internalization. We're working a lot with ADCs or other molecules where you have great targets, but very poor internalizers to be able to kill cancer cells as an example. And we've developed techniques that can get, you know, logarithmic fold improvement on internalization of these antibodies or other protein, um, crossing barriers, blood brain barrier, cellular barriers, gut barrier, as another example. And so using these types of techniques, we have a number of programs that are on the come, other than just the ones that are clinical, in clinical development, where we think we're more highly differentiated.

Excellent. So, you know, that's a great overview. And I think it leads into a couple of questions here. One, you know, can you talk about T-slip as a target and what it does in asthma? And what you know generates design allows for two injections a year what in that design is allowing for that but also kind of what can we take you know from what we expect will be positive data and if that is the case you know how do we know that the platform is working and that this can be extrapolated into the next elections and maybe even the rest of the pipeline even oncology we say, hey, even though this is INI, we know that generates, you know, techniques to get there should be accretive to the rest of the pipeline versus just this readout. Sure.

So T-slip is a known mechanism in asthma. The test buyer has been on the market for five years. It's a biologic. Biologics in respiratory and asthma particularly are very low penetrated. So it's about 20% penetration in asthma. But the great thing about the T-slip molecule, has been shown through Tespire is it's in all comers of EOS population in the asthma population. And so what you saw with the Tespire data is a 70% reduction in exacerbations in the high EOS population above 300 EOS and about a 40% reduction in the low EOS population below 300. And so overall the population, you saw a reduction of 56%. It's a monthly dose medication in asthma. And so the benefit for our drug over that is it's a six-monthly dose drug. Now, we hit the same epitope as I mentioned before. We've chosen our dose and moved from phase one to phase three, which I'll talk about and why we think we're very confident with that. And 300 milligrams, we're seeing 99.9% saturation of the target, which is the cytokine in this case, which is about the same as the approved dose in tezopelumab, the 210 milligram cell, so it has 99% saturation. So there's no reason to believe there'll be better efficacy in the clinical trial. Now, we did show preclinically a five times better potency. But again, if you're 99% saturating a target that you're hitting the same target, the likelihood of seeing better efficacy is probably small. In the real world, however, what has been shown, and some data were presented at ERS last year, is that only about 20%, or it's suggested that only about 20% of patients on biologics in respiratory are adhering to their medicines. And so if that's true, it's leading to a very significant cost to the system, but also a cost to these patients. And having an every six-monthly dose drug has a benefit, especially for asthmatics and, frankly, more so for COPD, which is the other indication that we're contemplating, of being commensurate with when patients are going to their physicians. And so if patients are more adherent to a six-monthly dose more convenient drug, you might ultimately see better efficacy over time and a much better cost to the system. As far as the jump from phase one to phase three, which is a question we get a lot, this is not an unproven path. So Depomocumab moved from phase one to phase three with a single dose and was approved by the FDA and EMA without any phase two or dose finding data. Glaxo, with their Aeolus molecule, has just announced they're going into six phase three trials with the T-slip molecule they bought from Aeolus. And one of the indications is COPD, which we have not seen any data in COPD from that molecule and moving directly to phase three. So it's a proven pathway, let's say. Again, I've mentioned multiple times we get the same epitope. Number three is we're seeing biomarker suppression out to, frankly, a year in the asthma data we just presented data at ERS last week. And so we're seeing for EOS, Pheno, IL-5, and IL-13, deep suppression sustained out to a year in patients on a single injection. And there's no difference between the 300 milligram or statistically significant difference between 300 milligrams, 600 and above. And so even the data we showed on our COPD trial also showed complete overlap between 300 and 600 milligrams. And so those data, plus the fact that if anyone studied the tezapelumab data in phase two, where they studied an eight-fold difference in dose, 70 milligrams every four weeks, 210 milligrams every four weeks, and 280 milligrams every two weeks, that eight-fold difference showed zero statistical significant difference in exacerbation reduction and they chose 210 and so you put all the totality of that together the likelihood that we believe the probability that our drug will work at 300 milligrams we believe is extraordinarily high and so that's what we've done we've moved directly to phase three as far as the competitive landscape which you touched on a little bit we are the first long-acting molecule in phase three we started the trial back in december and so we believe we'll have full enrollment on the trial it's about a two-year enrollment so by the end of next year. It's a 52-week follow-up, and so data we think will be by the late 28, early 20, 29. And then, as I mentioned, we did study it in COPD, and we presented those data recently. Very similar to 98-day half-life. We're seeing deep suppression out to six months in our COPD patient population and overlap between the 300 and 600 milligrams. So right now, we're contemplating what we do with that and whether we move directly into phase three as well. The other question you answered, sorry. I'm trying to answer all your questions without boring everybody here because um you know hearing me talk is is a lot the um so how do you validate the platform so number one is it is a white it's a 98 day half-life so on a yte half-life extension typically you expect something in the 70 to 90 days so this is a longer half-life does that potentially have some impact from the fact that we're binding tighter the cytokine potentially we've seen some other examples of long half-life extended molecules that don't have binding affinity improvement have waning efficacy out in the at the tail end of that our binding affinity which again is the 106 femtomolar binding affinity level it has such a tight binding to the cytokine that we believe it's not being released out at that six month period and so therefore we think the efficacy will last for that six month period that was designed by the platform right i mean to actually take a femtomolar to a picomolar level molecule and make it a femtomolar level binding affinity is not something that others have shown able to do using traditional techniques. Our second set of molecules which are in the clinic on the oncology front also we think will validate in part our technology. So the second asset which is in phase one is an oncology asset. It's an MMA neutralizing antibody. So for those familiar with an antibody drug conjugate, many of the all the Seattle genetic antibody drug conjugates, PADCEV is one example, have MMA based payloads. One of the big issues with those is when the payload, the MMA gets cleaved and freely circulates, it causes significant toxicities, peripheral neuropathy, skin toxicities, neutropenia, which in the clinical trial for PADSEV showed a two thirds of patients ended up getting peripheral neuropathy. 20% of those patients end up off drug or reducing dose or having dose holidays. And so it's a significant liability to the drug, even though it's an amazing drug for urothelial cancer patients, given the response rates you're seeing. And so we designed through the platform, an antibody that binds only to the region on the free MMAE, which is a small molecule, the MMAE, that's only exposed when it is off the linker. And so that takes technology to do that. So it's not simply using techniques where you immunize a mouse, a llama, a human to try to come up with a range of antibodies. You're actually designing this specific for a region so that you don't impact the intact ADC so it can go to the tumor and kill the tumor cells. But you can limit, bind, and clear the free payload that's causing the toxicities. So that is in phase one right now. We'll have proof of concept data at the end of the year. Happy to talk about what the trial design is. I want to give you a chance to ask more questions.

I'm just piling the questions up because this is great.

Those are the types of things that will continue to show the technology. And again, what I mentioned up front, the new wave of things. So we're looking at extracellular target protein degradation. Using our platform, we've shown that we can do great things with selectivity and specificity. We've now shown our ability to do pH-dependent binding differences up to, frankly, a thousand-fold difference in binding at pH of 7.4 versus 6. And we've shown internalization. So for extracellular target protein degradation, you need to bind the target extracellularly, bring it to a cell, get it endocytosed into an endosome where the pH is lower, and then recycle your drug so that you can go and do the same for additional targets. And so those are the types of things that you're going to start to see emerge because we've now directed our technology to the more innovative side of things and really where traditional techniques. And again, Chinese companies have not shown their ability yet to go after these more novel areas.

Very interesting. Maybe I start with, so the MMAE, whenever it's cleaved and it's free, I'm curious, how do you make sure your drug doesn't get into the tumor and then whenever the payload is cleaved, MMAE payload is cleaved, it's kind of a counter effect on the ADC that's supposed to be treating the tumor?

It's very interesting. No, so the bystander effect we think is really important. So you can't clear 100% of the free MMAE, otherwise we do think you'll impact tumor And so in our preclinical studies where we studied mice and non-human primates, we actually showed if you get up to 80% clearance of free MMAE, you don't impact the tumor killing, but you do get a significant reduction in skin toxicities and neutropenia in mice and non-human primates. Again, in humans, we're going to be studying peripheral neuropathy. But when you get to 85% reduction, you actually do start to impact the tumor killing. And so the design of our phase one trial, which we're in right now, the first portion of it is a dose escalation portion where we're looking for what is the dose of our antibody that will reduce free MMA by 50%. So the FDA gave us fast track designation for this product. We're in first line treatment for urethelial cancer patients. They've told us that we can go up to 80% reduction, but we want to be careful getting too close to that impact on tumor killing. And we know at a 50% reduction of free MME, you're getting a substantial benefit for patients in terms of reducing these toxicities. So we've already dosed the first cohort of patients in that trial. And we believe by early 2027, we'll have the dose of our drug that reduces the free MME by 50%. Then we'll do an expansion cohort in the phase one in 2027, where we'll look at patients who have already developed peripheral neuropathy, urethral cancer patients. They're on PAD-7 Keytruda. And now can we give in each cycle our drug with PAD-7 Keytruda for those patients and stop, slow, or reverse the progression from grade one to grade two neuropathy? If you can do that, you've shown your proof of concept. And then our discussions with the FDA to date have been we potentially could do a registrational trial with safety endpoint. Obviously, we have to have that discussion in more detail once we have the phase one data. And ultimately, you know, we would think we'll need to do either non-inferior study or something that shows you're not impacting the tumor killing. But in reality, there are three huge benefits for this. Number one, you're obviously dealing with patient side effects and treating significant toxicities. It's a huge benefit for patients. Number two, at ASCO, what was recently shown is the longer patients are on PADSEV, the more complete responses you get. So if you can improve, increase either the dose or the longevity in which patients are taking PADSEV, which our drug we believe can do, you might actually have a better impact on tumor killing and complete responses. And number three, one of the challenges in the community where you're only seeing about 50% of urethelial cancer patients get PADSEV is physicians, many of which have challenges dealing with the side effects. So if this drug is successful, then you could see a huge uptake in the community where the drug is not getting to patients at the level which it should.

Very interesting. Okay. And so the design of the phase one, is it patients who are exhibiting peripheral neuropathy and you're now trying to show a reversal in that? Or is it patients who are all patients and they're prone to peripheral neuropathy and you're just trying to see if you can prevent it?

Well, so the first part again is dose finding. So it's all patients who have urethelial cancer, first-line therapy, getting PAD-7-contruta. They'll get their first cycle without our drug. So you can actually get a baseline MMAE, free MMAE level. Then at the second cycle and beyond will give our drugs so then you can measure the impact of the reduction of free MMA. So that's number one. The second portion of that will be patients, urethelial cancer patients, who already have developed peripheral neuropathy. So if you can imagine, we were a little bit surprised at how quickly the first cohort enrolled because imagine being a urethelial cancer patient and you don't know if the drug you're getting with a great drug of PAD-7 in Keytruda is ultimately going to impact your tumor. And yet it rolled incredibly fast. Now you think about that expansion cohort, these are patients who already have grade one peripheral neuropathy and have the promise of a drug that can be dosed to prevent the progression. And so we'll really be looking at, you know, if 50 plus percent of patients are progressing from grade one to grade two peripheral neuropathy in the literature, if our drug can reduce that by 25%, and 20%, 50%, whatever the right number is, that would have a huge impact on these patients. And that's what we'll be looking for in this expansion cohort.

Yeah, absolutely, interesting. How do you see like that being used? You know, let's say the ideal situation, is it where patients are taking this in anticipation of developing it or would you see it more as kind of a situation where they develop a peripheral neuropathy and then they're?

I think you'd want, so two-thirds of the patients in the clinical trial of PADCEP develop peripheral neuropathy. And once it becomes irreversible, or grade two, it's irreversible. And so we'd envision that all patients would get this drug.

Very interesting.

Starting at cycle one. Now, peripheral neuropathy is an accumulated side effect, so typically around cycle three or four, and ultimately it accumulates over time and gets worse for patients. But if you started at the beginning, as long as you're not impacting the tumor, you know, we believe that you can maybe prevent even the progression to grade one neuropathy and certainly to irreversible neuropathy.

Great. OK. And then one other thing you mentioned earlier that was quite interesting is, you know, the the target coverage you're seeing with your T-slip is high enough that you don't expect the efficacy to be better. But the durability is obviously the value driver here. When you look at expansion of your platform and potentially going after other targets, is there a situation where a drug might not have as high target coverage, like 99% like Tespire does, that you could potentially improve upon and show not only a durability benefit, but maybe kind of like a efficacy benefit as well?

Yeah, absolutely. I mean, so one great example, we did an IL-13 study, a phase one study, with an incredible molecule, probably, I would say, one of the best, if not the best, profiles out there. I mean, what we showed, even relative to the Apigee molecule, is we had twice the bioavailability with our molecule, so over 100-day half-life. But bioavailability that showed at an equivalent dose, we had twice the bioavailability. So, you know, their 600 milligram dose is our 300 milligram dose in terms of PK profile. And so we actually believe that our technology can show better efficacy on various, you know, drugs out there that have liabilities. Again, where we focus the technology, and right now the biggest issue is our platform has capability to do a lot more than we could possibly afford, right? It's very productive. And so where we focus the platform now are on some of the more challenging, maybe more. They don't have to be biologically high risk. We could still choose biologically low risk targets, but ones that traditional techniques have been struggled to actually either hit or address.

And finally, I think, you know, I like to close discussions by just giving a preview. We talked about a lot of different areas of generate, but just give us a preview of the next 12 to 18 months, the key catalyst to watch. And specifically for, you know, your lead program, what should we expect in terms of what we could see at the data and set up kind of the inflection point for us?

Yeah, so I guess the first thing is we're well underway enrolling the T-slip molecule in asthma. We're in 30, we have regulatory approval in 39 of 42 countries. We're across six continents. And so that's well underway. we'll have that enrolled we believe over the next you know 12 to 15 months by the end of 2027. Number two is the other indications so COPD we just revealed data in the last couple weeks on that we think it's very strong there may be a path to move that also into registrational trials and that market opportunity that's probably one percent penetrated in biologics and has a huge market opportunity we didn't have time to talk about tozo and what the implications for tslp but we think even based on the tozo data there's a huge opportunity for the tslp asset and particularly one that's six months long so that's a decision we'll make in the near term the oncology assets will play out over the next course of the year and i think both in our car t which we didn't talk about as well as the mma neutralizer we'll have proof of concept data over the course of the next 12 months or so by the end of 2027 and both of those. And I think, you know, we have done some great partnerships to date. Now that we're getting to the end of those partnerships, we have a lot more capacity to do more partnerships. So you will see us do additional partnerships, similar to ones we've done in the past and potentially licensing other interesting innovative technologies as they emerge. So that we think you'll see. And then I think, as I mentioned, now that we've directed our platform and technology to some of these novel differentiated areas, I think over the course of the next 12, 18 months, you will see some of these new proprietary products emerge, many of which we will keep ourselves and some of which we might either spin out as new companies or license out.

Excellent. Thank you so much, Jason, and thank you to the Generate team. I'd like to thank everybody in the audience as well for joining us for this fireside chat.

Thank you.