Well, late addition, Mick Hitchcock, interim CEO. Ramses Erdtmann, Founder, Chief Operating Officer, and President. Finally, Steve Morris, who is the Chief Development Officer. I'm just gonna make a couple of opening remarks, then we'll kick off the discussion. Let me just start by saying that we really like the Biomea story for a variety of reasons. In addition to the management team that's got a documented track record of value creation via the de novo development of a novel agent for the treatment of a condition, and in this particular case, CLL, chronic lymphocytic leukemia, that had seen little in the way of innovation prior to the advent of ibrutinib, which, as you all remember, was the first of the BTK inhibitors. The company's, Biomea, that is, their lead program, icovamenib, is the first in the category of menin inhibitors directed to the treatment of both Type 1 and Type 2 diabetes that holds the potential to preserve and potentially increase the function of pancreatic beta cells, and therefore could redefine how the world looks at the treatment of diabetes. With a relatively minuscule market cap but with a tremendous market opportunity in front of it, we believe the stock is poised for significant upside. Welcome, gentlemen. We're pleased you could join us today for this discussion. I just want to remind everybody, if you do have questions for the team, you may email me directly at mking@rodm.com, and I will ask your question anonymously. Please do not put it in the chat box. With that, let's get started. As we discussed prior to this call, really wanna focus on, you know, the mechanism of action of icovamenib with respect to menin inhibition in the context, disease context of diabetes and in the context of elevated glucose. I feel like folks are very familiar with the menin inhibitors from both Kura and Syndax, which have been marvelous drugs for genetically altered acute myeloid leukemia. I think there may be this intellectual disconnect, if I may put it that way, with regard to how could a drug that treats hematologic cancers be a useful drug for diabetes. Maybe we could step all the way back and look at the Stanford, you know, the initial Stanford University publication and talk more about this and how menin plays a role in the life cycle of the beta cell. Ooh. Yeah, I'm gonna hand that to Ramses. Okay, I'm gonna pitch it to Steve in a second. Okay. Mike, great intro. Thank you. Thanks for hosting us. So w hen we started and there is a, if your want me to show slide, i can show it to you. When we started the work on menin, we actually were, just like the other two companies, focused on- I recall. ... oncology. However, the preclinical information showed in a 2005 paper in a PNAS paper from Karnik, the same gentleman you just quoted for the Stanford study, menin regulates pancreatic islet growth by promoting, etc. But he had isolated menin as a target in the pancreas. When we saw the work that was done on menin, we thought, "Wow, wouldn't it be cool if we're safe enough in oncology to move and sort of migrate over to the diabetes space?" As we learned over time, we were safe in oncology. We've dosed quite a few patients over a year, so we knew what menin does, and how our drug has an impact on menin. We can go into all of that in part of this discussion here. Just to answer your question, menin is a scaffold protein that is being used either way, and in the pancreas, menin has the function of control. If the control is no longer there, a restoration effect can occur that we see in obesity and we see in pregnancy, and that's the paper you just quoted. We saw that as well, and it was an aspiration at the time in 2017, if we end up developing a drug that is safe enough, which we now have and have evidence for, and if these effects can be replicated in animals, in cells, then we may potentially go into humans. We've done all the animal work, we've done the cell work, and now we are in humans, and the effect that these papers describe is exactly what we see. We see that by down-regulating menin, the restoration of the pancreas or the beta islet cells occurs, beta cell mass expands, insulin is increased, and you have the residual down effect into the glucose in the bloodstream than in the human. The islet work is phenomenal when you look at it. It's all in our deck. We're, like, at the forefront of something new. Nobody has done it before. They've only CRISPRed out menin and then looked at the Right. Well, maybe you can, I mean, that's a good segue. We talk about those. Yeah knockout experiments and what Oh, it's cool. I mean, let me show it to you because it's Yeah, go ahead. Yeah, I can share. Yeah, I think so. Yes, you can I can. Look at this right here. This is the paper you just mentioned, which is the original paper on the right-hand side from 2007. This is in our deck. If you, in this slide here, what we're showing here is something that, Ramses, can you just slide it over a little bit? 'Cause we're only seeing about three quarters on the slide. Oh, okay. okay. Let me show it. Is it better? No. Yeah, there you go. Much better. Okay. Yeah, you can see here, this is the work that I had quoted earlier. This was done, I believe, in 2010. Here they excised menin in diabetic animals, and they basically said, "Let's look at a knockout model. If you don't have menin, what happens?" You can see the control group under conditions of hyperglycemia. The glucose cannot be absorbed, but in the menin-excised animals, the glucose is absorbed. Something is occurring. That was sort of the first giveaway. When you look at that, we then looked at it, we asked, "Well, what if a drug could do this effect safely versus you know, CRISPRing out the- Right ... the menin? We ended up doing this exact experiment, and I can show it to you. What we've found is this. I mean, this is our work. The red line is our drug, and this is 2022 when we published that. From there, we went to cells. From there, we went into the early human data, did an all-comer study, and now we know where exactly the effects are most pronounced. Right. I'm just surprised that it didn't get picked up sooner, but, you know, and you would've thought that this, Yeah Paper would've had replicate studies and a flurry of drug development. You know, kudos to you guys for picking up on that. Yeah. I don't know if you wanted to show any animal data, rat, you know, rodent data, primate, but I mean, I think it's pretty clear. No, no, this is the only slide I have sort of in the deck. Okay That summarizes everything, yeah. Okay. Maybe you can talk. You mentioned the, you know, pregnancy prolactin, maybe. That's another thing. You have a nice chart in your deck, or one of the decks that I've reviewed that shows how the, you know, you get this prolactin bump in pregnancy, and I know that there's been a, you know, that was, again, where the insights into the biology first came from in pregnancy. Maybe we should explore that a little bit more. Steve, do you wanna go into that? Because it's more of a physician's viewpoint. Happy to do that, Ramses. Mike, it's been known for at least 50 years that women avoid pregnancy-associated diabetes by actually increasing their beta cell numbers and the insulin secretion. The mechanism by which that occurs has been unknown until this Stanford paper that was published in Science in 2007, as shown on this slide. What these Stanford investigators showed that in pregnant mice, as pregnancy proceeds and prolactin levels normally increase, prolactin actually down regulates the expression and function of menin. Now, normally, menin serves as a brake, and when prolactin decreases menin function, it takes the foot off the brake and allows the beta cells to increase in number. Oh, I think we lost Mick. No, Steve. Stanford work showed. Oh, there we go. that this compensatory is. Yeah, I'm not sure when I lost you, but what I was saying is that. You lost, we lost you for about 10 seconds before, when you were talking about the increase in beta cells. Why don't you pick up from there? My apologies. That's okay. Yeah. What I was saying is that the Stanford study showed that prolactin down regulates menin. Menin, because it normally inhibits beta cell proliferation, once it's inhibited, it allows the beta cells to increase in number and avoid pregnancy-associated diabetes. It's also interesting that epidemiologic studies have followed women and segregated women who had live births, those who did or did not breastfeed, so whose prolactin levels remain. Those women are followed for a prolonged period of time, up to 30 years after giving birth. The incidence of Type 2 diabetes is reduced by 50% in women- Right who had live births and breastfed, so it's quite remarkable. Hey Steve, if I may ask you, it might be better, 'cause we keep losing you, why don't you turn off your video and just stay on audio, please, if you don't mind? I apologize for that, but I think it's gonna be a lot smoother if we go that way. Maybe, I don't know if Ramses or Steve wanna take this question, but also talk about that glucose-dependent beta cell proliferation, because I think that's important from a clinical standpoint. You guys have shown that, but maybe we can talk, explore that topic a little further. Yeah. I have to show you that graph for that. This is this slide here. Can you see it? Yes. Yeah. What the experiment we've done here is we've used human pancreatic islets, which are from a person that is about to die. They're live. They are resembling the pancreas most closely. You can see on the left-hand side the amount of menin protein through the use of icovamenib has been downregulated by about 50%, depending on the donor. On the right-hand side, you can see as icovamenib is increased. On the bottom you can see we use higher levels of icovamenib, meaning more menin inhibition. Under standard glucose conditioning, it doesn't have an effect. However, with high glucose, when there is a need for the beta cells to respond, then you can see that the more menin inhibition leads to a higher replication of those beta cells. That was profound, right? It's Yep It's controlling itself. You need glucose as a stimulus, but once you have the glucose, we have a dose-dependent effect. More menin inhibition, more proliferation. Right. Okay. Great. Obviously, there's maybe I don't wanna jump to conclusions, but there it is, the correlation between menin expression and beta cell function a sort of one-to-one relationship, or does it, you know, plateau out at some point? Yeah. You mean the more we reduce, the more we get? Right it just keeps going? Right. We haven't done all the work yet. I mean, this is very early work, so what we found at first is we studied four weeks of dosing versus eight weeks versus 12 weeks, and we saw that. 12-week inhibition gives enough beta cell restoration that over the course of 52 weeks of observation you can see up to 1.5% A1C reduction, which is order of magnitude. This is a very functional diabetes care, like Ozempic, right? It's in the upper 75 percentile of reduction in glucose if you just use 12 weeks of dosing. We feel that's completely sufficient, and the trend is still going down. From our perspective, if we were to dose longer, could we achieve more or dose harder or higher? Maybe, but we didn't really see much more improvement when we went to 400. It caused safety concerns versus it's, it actually has a beneficial effect. So t hat's why we don't need to. Right. Mike, I think on e of the things is it's self-limiting, right? Once you get the glucose under control and the glucose level falls, then you've got nothing to facilitate the response to icovamenib. You, for example, we don't see any cases of hypoglycemia- Right in our trials. Yep. I do wanna, you know, talk about the clinical results that Ramses j ust referred to, in terms of durability of effect. Was that anticipated based on the preclinical work? Because you would think that once, let's say, prolactin, let's say in a pregnant woman, or in the animals when you take when you take the, you know, the inhibitor away Yeah You would think that would return to, you know, sort of the normal relationship once again. Yeah. What's the hypothesis behind why this produces such a sustained effect? This is the hypothesis behind it, and it's us creating an understanding of this mechanism. This is something obviously which will be explored further. Companies who've done stem cell transplant have seen this, that the maturity of these beta cells, these newly created cells, take time until they're fully functioning. We see an effect. For instance, what I'm showing you here is the beta cell mass decreases. You use icovamenib right before you become insulin dependent. That's the spot where we think we're best utilized. You enhance the mass, you build the pool, and now the beta cell pool matures, meaning cells come online and become active. You can, what does this translate to? If you see here in these particular insulin-deficient patients, you can see during the dosing period that is- Right Included in green, we have an effect, but the continuation of the effect is because we believe these beta cells are maturing and coming online. You can see it even more if you look at just C-peptide, which is the output of these cells. Right. You can see that the C-peptide improves, and it even improves further as you are off drug. Right. Do you think you create sort of a beneficial do loop, so to speak? Are you know, kicking off a positive domino effect where, you know, then you restore beta cell health and function, and now, you know, you got a healthier pool, and even if there's, you know, glucotoxicity still hovering around, you've got a healthier population of beta cells that can, you know, deal with it? Yeah. Unfortunately, you can't look inside, right? But what we- I know. In these experiments, we do know. The animals can't speak, so We do know that this pool that we are sort of restoring at first is not fully functioning, meaning it needs time to mature and become a fully functioning beta cell. The other interesting fact is we don't know how long this effect lasts. We've seen, if you see here in this slide, 52 weeks, but the trend is still going down. Yeah. There is still toxicity to be worked through in this, in these patients that we have dosed. We're exploring it, but so far very exciting. Okay. Yes, indeed. Yeah. I share your enthusiasm. Yeah. Let's talk a bit more now about the clinical development. Yeah aspect of the story. One thing you say in your slides that icovamenib is synergistic with GLP-1 based therapies. Where's the proof for that? What kind of data can you point to to show us what that means? Yeah. Here's the proof. This is work we've done, and it kind of goes along with all the ideas around pregnancy and obesity, that these pathways need to be, if menin has a control function, then if menin is no longer there should be sensitivity to these pathways. You can see here that the GLP-1 receptors are more expressed. They sit on the surface of the beta cells, and when the hormone GLP-1 receptor agonist, the GLP-1, comes along to ask of the beta cell to produce insulin, that this whole aspect should be improved in a pregnant woman or in obese individual. You can see that we saw the same thing in our own pilot studies. We see receptors more expressed, insulin heightened. Now the combination of semaglutide, which you, we've tested it, at higher levels of semaglutide, we see more impact through icovamenib, and at higher levels of icovamenib, we see more impact of semaglutide. The pathway of having a GLP-1 receptor agonist on board is sensitized to the use of menin. That's why we see in patients, and this is. I mean, think about it. Patients are enrolled. They are on semaglutide. A1C is rising. The GLP-1 is not working. They're diabetic. Okay, what do we do with them? Their next option would be insulin, and what we're saying to this patient, "Try icovamenib," and this is what we did, and you can see it here. These patients here, there were 11 in our study, and this is a post-hoc analysis. The graph I showed you earlier was pre-specified. Here, we asked the question very generally, "Of all patients enrolled, who was on a GLP-1?" Literally, that's the question we asked. There were 12 patients on icovamenib. We pooled them, and we saw this pathway that we had explored pre-clinically earlier does have a profound impact on these patients. We enroll them as the A1C goes up. They have this benefit, again, the same benefit as we described earlier, and over time, the effect is even more pronounced here from 0.3- 1.2 in absolute reduction in A1C. That's strong. While you are on background GLP-1 that didn't work for you earlier, because you have more GLP-1 natively expressed and you have more receptors. You're having more GLP-1 expressed, more GLP-1 receptors, healthier beta cells, and possibly more beta cells as well. Yeah, exactly. Right. It's a additive or synergistic effect. Now, think about two aspects that are important to note. One, how easy it is to identify this patient. Well, you're overweight or obese, you're on a GLP-1. That's it. Yeah. Your GLP-1 is not working. I mean, we wanna find a patient where the FDA and we and the patient, we see a need for a drug. Once you're not working on a GLP-1 and you are unfortunately in the position of being overweight or obese, there is not much more you can do. You will then become insulin dependent. What we are proposing, you don't need to become insulin dependent. Look at the amount of HbA1c reduction you can achieve with icovamenib. This is if these cells keep on working for you, we may push it out over years. If we can push it out over years or redose over time, what benefit can this do for you, the patient? Not being on insulin. Right. Exactly. So that, you know, you anticipated one of the next questions I had, which was, you know, novel mechanism, does it matter? Does it need to possess best-in-class benefits like A1C, cholesterol, inflammation markers, weight loss? What's a win? Just from a regular term, we'll get into this, the specific- Okay Covalent studies in a minute. Just in general, what's a win for icovamenib as far as a novel mechanism of action in a disease state that's got 50, 60 different options that patients can be on? Including GLP-1s, either oral or injectable? Yeah. You can see here there's a little line that we drew in there, 0.5 threshold for clinical significance, CMS, clinical endpoints review, blah blah. This is us looking at when did the FDA consider an agent, and by the way, all chronic. We're not a chronic agent. This is a chronic agent that has obviously, through the chronic use of a drug, you have more side effects just by the nature of being chronic. The they were approved at 0.5 improvement in A1C. That's our hallmark of a win. If I can achieve and surpass- As a single agent. Yeah. Of a single agent, in addition, that is given for a 12-week period, we believe that's enough for the FDA. All right. Well, that's enough for the FDA, but what about from a commercial standpoint? You know. I show it to you. This is kind of important because we've looked at where we fit in. Yeah. On the left-hand side, you can see all these agents. You're gonna adjust your lifestyle. You're gonna take metformin. You're gonna use all these drugs, but at some point, they fail. One in three patients move over to the right, and we would be in between that. That's the benefit we give to the healthcare system. Once you're over on the right, the way your body responds to exogenous insulin is heartbreaking. Meaning you're gonna be uncontrolled because the exogenous insulin does not. It works in to a degree, but it does not control your HbA1c either up or down, as we know. So you get these side effects, quote-unquote, that are comorbidities. Now you're gonna die potentially of coronary artery disease, chronic kidney disease, et cetera, et cetera. You don't wanna be insulin dependent. That's on the right-hand side, and we will prevent you from getting there by using icovamenib. That's the Yeah. Well, two questions. Number one is, do you think the GLP-1 will shift the curve? I would imagine they'd have to, but that's just intuition. There's no proof yet of that. The GLP-1s are in there, meaning they're on the left-hand side. Right. I mean, they're relatively new agents and, you know, they're doing an amazing job at reducing weight. There's more to come. So I would imagine that, you know, the- They didn't shift the curve. Okay. Over the last 20 years, look at this curve. Well, that's the kind of answer I was looking for. What it may do, Mike, it may actually Go ahead, Mick. Can we go back, please, Ramses? Yeah, sure. Yeah. What it may do is slightly reduce the number of patients who are going into that middle bucket. Our expectation is that, you know, this is where we get our foot in the door, and this is where we start the process. We are gonna sit between all the other agents. When they fail, we will be the opportunity that you take rather than going on injectable insulin. We will be three months of oral for who knows how long, a value. So we think that's a good place to start, and we have evidence that that's, you know, already shown by the studies that we have to date, and we just have to, you know, sort of redo those to make them more credible. We think eventually that, you know, icovamenib, based on its mechanism, it should probably be the first thing you think about using, and so we can move further back up the line there. You know, you've seen this with a lot of other drugs where you start at the back end of therapy and you move up the line. Yeah, of course. As long as you're safe enough, you can go down that pathway. Well, again, just to, you know, I guess to—It's a 35,000-foot question I'm trying to get your answer to and hear your thoughts on is, you know, that is what you're saying is true, and I agree with it, but the question is, in a clinical community, in order to do that, will you know, eventually need things like outcome studies or, you know, impacts on other metrics of d iabetes beyond just 0.5. Even a 0.5 reduction in A1C is not a bad thing, but again, in the crowded marketplace, lots of options, higher demands from payers, et cetera. Will you have to show some of the outcomes on these ailments that we see here on the chart? Or do you think it will be taken as a given, based on, you know, based on prior studies of antidiabetic agents? Yeah. I think none of us will know firmly until the FDA votes on it. At the end of the day, if you enroll patients that otherwise would have gone on insulin, everybody agrees on the need. Insurers, everybody. If I can make that part of the enrollment criteria and get closer to that statement, right now it's inclusion/exclusion criteria, and you could potentially argue, but from what we're seeing in our studies, most of these patients would end up on insulin if they wouldn't be on our drug. If we can firm up that thought, that argument further, I think that would be sufficient in my mind. Yeah. It sort of reminds me a little bit. I hate to make the analogy back to cancer, but if you can, in the early stages of cancers like breast and prostate where, you know, progression takes a long time, if you can have. Yeah A therapy in the early stages that prevents someone from going on chemo or going on something more aggressive or deleterious, then you can get a regulatory approval on that, on that endpoint, but that is, you know, we haven't tested that yet. All right. Why don't we talk about some of the studies that have been conducted already. You've done COVALENT-111 in type 2 diabetes. You did COVALENT-112 in type 1. The COVALENT-211 and COVALENT-212 are enrolling now, correct? Yep, correct. Okay. Let's talk about a couple of things. First of all, I'm curious to know, and I was looking at the demographics of your previous study, it doesn't seem to influence it, but given women's, you know, the prolactin and such, do women have different baseline levels of menin and their response to inhibition? Do they respond to menin inhibition differently than men do? Do you have to account for that as you- I didn't. I checked the statistics on all the various parameters of the biomarkers that go in. I didn't see that. I did not. Okay. Do we know if there are any different levels of menin where based on adiposity or BMI or anything like that, or is it more uniform? Do you feel it's more uniform? I don't know if it's more menin, but BMI is a huge criterion for success or not. I mean, for defining a patient population that is insulin deficient. When we look at severe insulin deficiency or insulin deficiency overall, the higher your BMI, the more you potentially become insulin resistant. The reduction of weight versus your production of insulin, just by reducing the weight, you could create a benefit for a patient, and that benefit could be enough to control your sugar. We see, as we go in our study and we look at our patients, that BMI is a driver, that if you're above a certain level of BMI, the drug doesn't work as well for you unless you're on a GLP-1. Interesting. I mean, have you tried to play with the dose based on, you know, whatever body mass index of 35 or above or trying to- We've tried that, yeah. Yeah. That would be interesting, but I think it's too complicated. Right now we know any less obesity is better for patients who are just on icovamenib. Okay the background they're on. Yeah. Got it. All right. I want to ask a couple of specific questions about this was from. I think this is from COVALENT-111. You had A1C at the 8.0. So A1C at 8.0. Sorry, 8 weeks at 100. A modest reduction. Arm B, 12 weeks at 100. Yeah. Very nice reduction. Arm C, where you had eight weeks at 100 and four weeks at 200, sort of in the middle. Yeah. Can you know, address that? Why do you think that A1C was less impressive in that third arm C regimen? Do you wanna do that, Mick, or? Yeah, sure. You know, I think we're we've got limited number of patients here, and I think it's small numbers that are probably having the major impact in terms of why we don't see a dose response. You know, when you think about a dose response and you know, you can think about you know, what do you look at generally to find a dose response with any drug, you've got to do at least a twofold or sometimes a fourfold increase in a drug to actually see a difference. You know, I feel here that, you know, where, you know, if you take the 100 mg as being a dose of one, then the lower dose is sort of 67%, and the higher dose is, I think, 150%, so it's only a little bit more. I think the doses are somewhat close. I think it's the time that's probably the difference in terms of eight weeks versus 12 weeks, and that's why we've concentrated on the 12 weeks for our future studies. Maybe one more. One more aspect, Mike. Go ahead. Yeah ahead. Yeah Just to add to it. This is the number one thing we learned from this all-comer study. We had to run an all-comer studies. We didn't know the difference in dose concentration that is needed. We found that out, 100 mg works. We didn't know the dose duration, whether eight weeks or 12 weeks. 12 weeks is better than eight. We found that out in this study. We also, and this is a key component, we didn't know the diversity of Type 2 diabetes patients. What you see here in this graph is they're all together, and we just organized them by one got eight weeks, the other got 12, one got 200, one got 100. That already is confusing by itself. If you think through what we learned from this study is. Yeah These criteria are not the drivers. The drivers are BMI. The drivers are the subtypes primarily. That's why our inclusion/exclusion criteria in 211 is 12 weeks is what you need, 100 mg, we learned that from this study, but underneath what you see here are subtypes that are grouped together. They actually need to be not grouped together, and that's why we say BMI in the obesity range, you should be in a different segment. Right. Right. You know. You're doing that in COVALENT-212, right? Exactly. Yeah. In 211, lower BMI, they work, and there we saw overall these arms perfect results. Okay. I wanna do a little bit more exploration of 111 j ust because I wanna, you know, I wanna set it up to help us understand what we might expect from 211 and COVALENT-212. On slide. Let's see. Oh, the one question before I do that. The one question I wanted to ask about this. Was this was ARM-C impacted at all with adverse events or tolerability issues? And I know you hit a COVID problem as well. I don't know if these A1C numbers were, you know, thrown off by that. No. We did not have that as an issue. Think of the 100 mg. It's not really 200. It was 100 mg twice. Was it? This is BID, right? Yeah. Yes. The final four weeks. BID on the last four weeks. On the, yeah, four weeks. Right. Yep. You know, you do it here and you do it there, right? You do it twice daily, but one in the morning, one in the evening. Are you really generating 200 mg of drug or are you just putting it in twice when the drug is no longer there? You can run a lot more experiments trying to figure this out. We don't think it's necessary. We think 100 mg does beautiful. Okay. On slide 22, you had 12 weeks of dosing of arms B and C, but the numbers are quite a bit smaller. They're 10 and 12. Yeah, right here. 10 of icovamenib and 12 pooled placebo. Why is there such a big reduction in the numbers analyzed here? Yeah. I can show you the. Well, it's not in this deck, but at the end of the day, the definition of what is an insulin or severe insulin deficient diabetes patients, we left that up to. We took all 160-plus patients, and there's an algorithm online that you put in five inputs and it says, "This is now segmented as a subtype." We did all that together with the FDA. We showed them the algorithm, the inputs, and how we're subtyping. So it's predefined, meaning before the readout, these are the four groups. This group in particular, and we were very keen on looking at this group, because we knew the less amount of insulin production you have. Right the greater the potential effect could be. These are the severe insulin deficient patients. Dosed at eight weeks, they're not quite as good. The 1.2 is roughly. Since we're dosing for 12 weeks, w e wanted to look at what would that look like if we replicated these patients. You can see here, 1.2 is what these patients that are insulin characterized as severe insulin deficient from arms B and C, because arm A was an eight weeks arm, what the results were. This is 10 patients because that's all we enrolled. These are not selected. Okay By any other criteria. Okay. All right. Just, yeah, just don't want anybody accusing you of cherry picking. I know. I know. And, and it's a lot of information. I agree. Yeah. The, the- The next study will go after. The thing about it though, Mike. Go ahead, Mick. We had to look at the patients who'd got 80% of dosing, because if they got less than that. Sure. Yeah That didn't really make sense to include them in the efficacy analysis. Right. Okay. One more quick question. Sorry to be, you know, so nitpicky, but on slide 28 you show that you've got short treatment of the icovamenib delivered A1C reductions comparable to chronic injectables and orals, but are we comparing like to like here, or are we comparing- Yeah Better to worse, or maybe talk a little bit about this. No, no. We, wherever we could, and you can go to the study SUSTAIN 8, SURPASS-1, blah, blah, blah. This is not handpicked. What we're trying to find is where did Ozempic show 52-week data. Sometimes they go with 48, sometimes they go with longer. Here we took, we tried to get as close to our readout as we could find. You can see 1.5 Ozempic, 1.9-2.1 depending on what study, is Mounjaro at 40 weeks, so that's pretty good. But I'm not even trying to compete at this is a chronic agent with side effects, et cetera, et cetera, given, you know, every day, and in this case, an injectable. I'm comparing myself as an oral dosed for 90 days only, and we're looking at 52-week data readouts. It's an unfair comparison. We're doing it anyway just to show. Right order of magnitude. That's it. We're also Are the patients as healthy? Worse off? Your patients healthier? Worse off? That's a good question. We, in this case, these are all failing, these drugs, right? Right. You could argue they're one row behind, but we didn't even look for that. We only have failing patients on our study. Okay, good. All right, the next two studies that are going on right now, COVALENT-211, COVALENT-212, you're still using 100 mg. Do you think the food effect is gonna influence compliance at all, or do you think people are pretty adherent to having, let's say, breakfast and then taking their drug at- No, I think. You know, 30 minutes after? What we're actually asking is the major meal. Okay. That's kinda what we want because we've w e really needed to figure this out. We now figured it out. We actually spent quite a bit of time understanding what is the impact of food on the drug before, after, without food, fasted, and these are the instructions we come up with that we feel consistently give us less variability. You can't predict everything, but this is fairly we think we're gonna increase exposure with that. We should have better exposure in our next study because of it, and it just allows making it all the same versus some guy in the morning without food, the next guy after a heavy meal. That is different exposure, and we needed to learn this, and now we know. Right. Okay. Typically the FDA likes to see, you know, multiple dose exploration. You know, any thought to? I mean, I guess. We've done that. Yeah. We've done higher, we've done lower, and we can show that this is, we think, with a safety profile that we didn't wanna jeopardize a very, very good dose, and when we go lower, we can't achieve the results. The GI tolerability is good enough that you can get right to the I mean, we get the results. therapeutic dose. Yes because of our safety profile. Yeah. If I wouldn't show you the upper combined arms, and if you look at combined arms like a minute, in the brackets is the percent. Well, we're like equal, except liver grade 1, primarily grade 1. These are because you have a drug, the liver says, hey, something's something Yeah, sure. First pass. First pass. And so we have 3% and 2% grade 1 liver. That's it. The important thing on the liver is that these effects disappear while we're continuing to dose, and so they go back to baseline, and so we don't believe it's a serious issue. It's more of an adaptation than a toxicity. Right. Okay. Let's see. All right, let's talk about the patient enrollment criteria. I think it's worth spending about a bit of time because we've used this two terms a number of times in our discussions here. One is inadequate response to insulin. How do you quantify that? Also tell us how you define severe insulin deficiency, and what's the difference between, and there's a nifty slide in your deck that talks about patients who are insulin deficient versus insulin resistant, and you're going into the insulin deficient population. So maybe talk about the choice that you made there. So you want to discuss the enrollment criteria. So to create a new category for a body that is governing all of us is really difficult. The FDA, I understand that completely. We needed to find a standardization that we could use that people could reference that we not willy-nilly come up ourselves with, so that's why we used criteria that academia had agreed on. There are four different types of diabetes, and if you read the literature, you can see in general people agree with that. The algorithm we used was the most quoted algorithm on how to identify those patients. That is not the way the FDA wants us to run more regulatory-oriented studies. They want standard inclusion. Inclusion criteria, as you can read them here. Now, they bring us very close to those patients. It's not a perfect landing, but good enough that we feel this is a path forward. If you have a BMI that is not in the obesity range, less than 32, if you have HbA1c that is elevated, 7.5-10.5, and you are failing your current therapies, which puts you further into the disease progression. We don't want you early disease. And failing means what? Increase in hemoglobin A1c, reduction in CRP? What do we measure? [crosstalk] Is it the constellation? Typically, your A1c is above seven. Okay. And it can't be controlled. Okay. And you know, our criteria are a 7.5 and above, so anybody who's 7.5 and above is by definition [crosstalk] Poorly controlled. Yeah. But we want you to have failed a prior agent where the physician says, look, this agent had an effect, no longer has an effect, I've got to find another one. That's where we define ourselves, and you can go up to three failing agents. And sometimes they get stacked on top of each other. And so that's 211. This is characterized as a sufficient deficiency of patients. You could argue, are there other criteria? Yeah, you could look at other criteria, but in the bulk of the definition of where we saw the response was statistical analysis. This explains +70% of the responders in a very predictable way, easier predictable than other criteria that are too specific and you can't find the patient. This enlarges the pool quite a bit and it makes things, it smooths out the curves, at least from our perspective. If you look at 212, the criteria is fairly simple. You are either overweight or obese, okay, that's defined by BMI, and 25-40, and you have high HbA1c, above 7.5. And that's kind of where, that's the patient that we saw in study 211 and that we're now enrolling in 212. Pretty simple. Right. And it's interesting to me that 212, you know, the body weights are, you know, are relatively low for the population. Yes, that's true. Very true. Yeah. And I thought the same thing when I looked at all the data sets, and I thought, interesting, it's the driver, the GLP-1 is the driver that allows, together with a menin inhibition, to create this response, even in somebody who is not necessarily obese just already. Yes, that's true. Very true. Yeah. And I thought the same thing when I looked at all the data sets, and I thought, interesting, it's the driver, the GLP-1 is the driver that allows, together with a menin inhibition, to create this response, even in somebody who is not necessarily obese just already. Right. Right. Yeah. Okay. It just said, as far as 212 is concerned, that you have a much wider range of BMIs, and to your point about the greater the obesity, the lesser the response, do you, you know, are you concerned that you may not see the same kind of impact on clinical outcomes within, you know, with the heavier population than you would in 211? Well, you see that 212 has, I mean, I don't think it matters much. We could have gone to 10.5. I don't think it would be necessarily much different, to tell you the truth, but the higher you go, the more placebo will be failing. And if it's failing, then you can't use them because then they're on rescue. If they're on rescue, the patient is gone for you in the database past that point. You wanna have patients that you can follow down a year. If a patient doesn't wanna come back because he's on placebo and he's failing and he's on rescue, one, you lose him on rescue, and two, can you get him back? It's a dance, 10.5, 9.5. I tell you, personally, it's an opinion of mine, I don't think it matters much. Okay Either of those two studies. Okay. Just timelines, when are we expecting readouts for 211? Yeah COVALENT-212? We said publicly, one, we initiated the studies. That means you have to get the sites identified, you gotta sign contracts, you gotta negotiate all of this. We're in the middle of this, and we are starting enrollment very, very soon. You should see press releases coming out soon. Okay. That means upon clinical trials, there's a heavy push then on enrollment, which will last very likely for the next three months when we hope to have 60 patients in both trials enrolled. Why is that important? Because our goal is to finish the 26 weeks' data readout of the last patient enrolled before year-end. Okay. So that we have the data in before year-end. That's Okay ... where our- It could be either or both. No, both. Yeah. That's both. Both. Okay. Yeah. I mean, I tell you the goal. I mean. That's the goal. We're all humans, but that's the goal. Yeah, yeah. Okay. Yeah. Wonderful. Would you know, I had always thought that icovamenib was also, you know, a really interesting drug for Type 1 diabetics, and that's, you know, there's a real unmet need there. Not a lot of novelty. You know, we've got teplizumab, we've got the SAB-142 to preserve beta cell function. We've got the transplant from Sana, from Vertex. Where is your attitude? Where is your head at on Type 1? Is it gonna wait for the data to read out in the second quarter? No. We're gonna have data readout in the second quarter of this year, meaning- Yeah the next couple of months. It's the 52-week. The data, right? Yeah. We've done a proof of concept study in patients that were three years from a disease identification and patients that were three to 15 years from disease identification. Now, if you look at every one of them you just quoted, except maybe the stem cell transplants- Yeah If you look at all, everybody is trying to get patients within 90 days of the disease identification because there are still enough beta cells there. We asked a different question. We asked a question of even if there are no beta cells there, or very few sporadic patches, can we have an effect there? What would that look like? It's a proof of concept study at two dose levels with 20 patients over two big cohorts, 0-3, 3-15, and in different dose ranges. So very little data. But it'll be directional hopefully. The direction that we hope to see is can I, and this is kind of what everybody's trying to do, C-peptide is the hallmark of your beta cell health. As C-peptide goes down with the attack of the immune system on your beta cell. Right How quickly does it go down? The literature, if you read up on it says about 47% per year, and it goes down that 47% every year. By, you know, year three or year four, you are- Yeah. It's so low. Yeah It's mostly gone. That's why everybody is shifting up front here. Yeah. We said three years for a reason, because we think within that timeframe, we can still have an impact on that depleted pool of beta cells. That'll be, for me, the most important update in the zero-three category. Does those 100 or 200 have an effect on these patients? That's what we're gonna show in the second quarter. Very exciting. The companies you just mentioned, SAB-142 is the one who just came out last week with four patients, and they saw at, two times dosing, right? Yeah. It's the AUC that they looked at this patient over here, which had been identified four years ago. Very interesting data, very interesting pathways. That's one that is making a headway. Other than that, there is nothing really in Type 1 diabetes. Yeah teplizumab is stage 2. They're not stage 3, which means- They aren't. They have the disease. Right. When you have the disease, you have insulin as your only agent. There, I believe from our planning perspective, the FDA and we are both, or the whole community is in need of an agent. We hope that we can show efficacy there and collaborate with everybody on getting something. Yeah. 'Cause it would seem to me if you're expanding a pool of beta cells or even keeping them in stasis while you still have an immune attack, you're gonna need, you know, both components of it. Yeah Anyway, that's down the road. We're gonna- That's down the road. We're running short of time, and I know we started a little late, so I'll run a couple minutes over, but not much. Wanna shift real quick to BMF-650 in phase I, initial readout in Q2 2026. Give us your thoughts where you think it fits in. Yeah, I don't know that there's another crowded space like GLP-1 agonist. Is its sole purpose to be an adjunct to icovamenib, or you think it has its chops to stand on its own? Well, yeah. Yeah. I think that's gonna be a great deal dependent upon what data we find from this trial. Now, the molecule was designed and we have at least preclinical evidence to suggest that it has better pharmacokinetics. It may be a bit less potent, but it seems to work very well in the monkeys, and I think you've seen that data before. We think from this particular trial we'll be looking for a couple of things. Number one, I think to be in the game, we gonna obviously need to have a similar type of weight loss. It doesn't probably need to be any better because I think, you know, all the things that you're looking at out there now that are potentially oral have a similar type of weight loss, you know, 3%-5% after four weeks. We'll see what comes out of that. Our main thing in terms of where we think we might go forward is if we've got a better safety profile and if we can titrate up in a more patient-friendly way. Some of the drugs that are out there at the moment, they take a long time to titrate up to the dose where you actually are getting the weight loss. Mick, speaking of that, do you wanna show your titration? 'Cause I know that's something. Yeah that you put in your deck. Show your titrate. There you go. Yeah. What we're doing there on the right-hand side, at the bottom there is the uptitration. You can see we're uptitrating to 100, 200, 300, 400. Those are the four doses in the multiple ascending dose group, and those data are the data that will be available at the end of the second quarter this year. The important thing will be, as I said, the side effect profile. We think that we can probably uptitrate a little faster, and that if these are well-tolerated, they could be a very useful way of getting to a weight loss dose very quickly. Then longer term, we think that, you know, within this space, everybody has sort of tried to go after massive weight loss. People lose weight, and they go off drug, and the weight comes back on again. We think with an oral drug, a better strategy would be to drop the weight and then back titrate so that you've maintained the weight and, you know, basically sort of kept up whatever weight you were trying to get down to. Our expectation is that that will be something that will be more, more feasible with this type of drug. Right. Can you also talk about, I know. In theory, I think there's the opportunity to combine 650 with icovamenib. Have you done anything further to try to elaborate on that? Are you waiting for the results to come out to see, you know, where you stand? We wanna see what goes on here. I mean, again, while there is always the possibility of combinations, especially with two orals, you know, the reality is there's a lot of GLP-1s out there at the moment. What we've done with icovamenib is looked at the combination data with semaglutide. We'll be including that obviously in our COVALENT-212 trial. In animal studies, we've been looking at it not only in terms of the anti-diabetic effect, but also weight loss. Okay. Just a quick question before we wrap up on IP. How do you feel about your IP position? We saw that, you know, Roche paid $100 million to Structure Therapeutics to get access to their IP. Do you have any thoughts about whether your 650 reads on their IP or not, or anyone else's for that matter? We feel very confident that we have a selective patent and that we'll be able to keep others out of the space. Okay, great. Anything I've missed that you wanna mention in closing? I don't see any questions pending in my email. If there's nothing, any concluding remarks you guys wanna make before we close it? If you ask that invitation, Mike, you're gonna get a long answer, but. Okay. Well, then Make it a short answer and- What I'll say, first of all, is it looks like you've got, like, some nice milestones coming up. You got the second quarter where you have. You know, the Type 1 diabetes full 52-week readout. You'll have your initial data from 650. Then by the fourth quarter, let's see, you know, knock wood, we got 211 and COVALENT-212. So you certainly have a list of, Maybe two sentences. Sorry. One sentence is there is a great need. Just remember that. There's a great need in diabetes. We have a lot of agents, but they're not serving the need properly. Because of the depleted pool of beta cells, we're trying to go with the symptoms, but the symptoms management fails at some point. You need insulin. There's a great need, one. Two, we have identified the biologics through others. There, menin has a role in the pancreatic sort of functioning. Menin controls. We have isolated in animal experiments that is actually, if you, if you take out menin or you inhibit menin's function, you have a beneficial effect. We went to the human islets, and we identified it there as well. Now we're in the humans, and we see, gee, there as well, in particular in patients that are insulin deficient, we have a very beneficial effect, and then also in patients that are failing the GLP-1 therapy. That's very clear from us as developers. I got my breadcrumbs, I've figured it all out, now I'm in the clinical, and now I go to phase II to validate those early signals in a larger study. Yeah. If that study reads out by year-end, we feel very confident that we can replicate the results we've seen. This is what I'd like you to think forward with, when I have my end of phase II meeting and I can show the benefit that we create with no or limited risks, if I can move this into a phase III, do I need Big Brother or Big Pharma to help me? No. Yeah. It's not a 5,000 patient study. Right. Meaning we as developers can do. We've done many phase IIIs. We can do a phase III of 300-400 people, no problem. If I can then move the value creation into the phase III, and we have this conversation in a year or two years from now, and I'm ahead of becoming a pre-commercial asset, then you should do the modeling and ask the question, what value does icovamenib have to the industry? I can be thrown into any drug. I can be thrown at any point of the journey in diabetes because I don't add toxicity. I'm not a chronic agent. I'm for- Right Et cetera, et cetera. That's the future story that we're. Okay We're trying to. All right. Well, we will certainly stay tuned. Build upon this. We urge investors to take advantage of the modest valuation that shares present right now because Okay That's not gonna stick around forever. Anyway, guys. Thanks, Mike. Thank you so much for taking the time. No, thank you. I appreciate, you know, the willingness to go deep on the science. Great. Thank you, Mike. All right. Take care. Appreciate it. Thank you. Bye-bye. Bye-bye. Bye.