Biomea Fusion, Inc. ($BMEA)

Okay. All right. So then we can begin. Sorry about all the confusion everybody. We're going to kick it off right away in the interest of time. So we're pleased to be joined by the management from Biomea, including a welcome late addition Mick Hitchcock, Interim CEO; Ramses Erdtmann, Founder, Chief Operating Officer and President; and finally, Steve Morris, who is the Chief Development Officer. So I'm just going to make a couple of opening remarks, and we'll kick off the discussion. But let me just start by saying that we really like to buy me a story for a variety of reasons. In addition to the management team that's got a documented track record of value creation by 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 novel agent -- sorry, 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 the 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. So 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 e-mail me directly at [email protected], and I will ask your question anonymously, please do not put it in the chat box. So with that, let's get started. And as we discussed prior to this call, I really want to focus on the mechanism of action of icovamenib in respect to menin inhibition in the contact disease context of diabetes in the context of elevated glucose. So I feel like folks are very familiar with the menin inhibitors from both Kura and Syndax, which have been marvelous drugs for our genetically altered acute myeloid leukemia, but 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 usual drug for diabetes. So maybe we can step all the way back and look at the Stanford -- the initial Stanford University publication and talk more about this and how menin plays a role in the life cycle of the beta cell.

I'm going to hand that to Ramses.

Okay. And I'm going to pitch it to Steve in a second. So Mike, great intro. Thank you. Thanks for hosting us. So when we started, and there is -- if you want me to show slides, I can show them to you, when we started to work on menin and we actually were just like the other 2 companies for oncology. However, the preclinical information showed in a first 2005 paper in PNAS paper from chronic, the same gentleman you just quoted for the Stanford study, menin regulates pancreatic islet growth by promoting, et cetera. But he had isolated menin as a target in the pancreas. And 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. And 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 and we can go into all of that in part of this discussion here, but 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. And 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 described 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. And the islet work is phenomenal when you look at -- it's all in our deck, but we're like at the forefront of something new. Nobody has done it before. They've only crispered out menin and then...

Right, well, maybe you can -- I mean that's a good segue. I mean talk about those knockout experiments and what...

No, it's cool. I mean, let me show it to you because -- let me see if I can -- yes, I can share. Look at this right here. So this is the paper you just mentioned, which is the original paper on the right-hand side from 2007. And this is in our deck. But if you -- in this slide here, what we're showing here is something that...

Ramses, can you just slide it over a little bit because we're only seeing about 3 quarters on the slide?

Yes, is it better?

Yes. There you go, much better.

Okay. Yes. You can see here, this is the work that I had quoted earlier. This was done, I believe, in 2010. Here, they excised in diabetic animals. They excised menin. And they basically said, let's look at a knockout model. If you don't have menin what happens. And 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. So something is occurring. That was sort of the first giveaway. And when you look at that, we then look at it, we asked, well, what if a drug could do this effect safely versus crispering out the menin. And so we ended up doing this exact experiment, I can show it to you what we found is this. I mean this is our work. The red line is our drug and this is 2022 when we publish 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 would have thought that this paper would have had replicate studies and a flurry of drug development, but kudos to you guys for picking up on that. I don't know, if you wanted to show any animal data, rodent data primate, but I mean, I think it's pretty clear.

No. No. This is the only slide I've sort of in the deck summarized everything.

Okay. Maybe you can talk -- you mentioned pregnancy, prolactin, that's another thing. You have a nice chart in your deck, one of the decks that I've reviewed that shows how you get this prolactin bump in pregnancy. And I know that there's been -- that was, again, where the insights is at the biology first came from in pregnancy. Maybe we should explore that a little bit more.

Steve, do you want to go into that because it's more of a physician's viewpoint.

Happy to do that, Ramses. So 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. But 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. And what the standard investigators show that in pregnant mice, as pregnancy proceeds and prolactin levels normally increase, prolactin actually downregulates the expression and function of menin. Now normally menin serves as a break. And when prolactin decreases menin function, it takes the foot off the brake and allows the beta cells to increase the number. So -- to avoid diabetes is -- yes, I'm not sure when I lost you but what I was saying is...

We lost you for about 10 seconds before when you're talking about the increase in beta cells. Why don't you pick up from there?

My apologies. What I was saying is that the Stanford study showed that prolactin downregulates 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 breast feed. So -- prolactin levels if 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 when you had live births and breast fed. So it's quite remarkable.

Steve, if I may ask you, it might be better because we keep losing you. Why don't you turn off your video and just stay on audio, please, if you don't mind. Apologies for that, but I think it's going to be a lot smoother if we go that way. Maybe I don't know if Ramses or Steve want to 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.

Yes. I have to show you that graph for that. This is this slide here. Can you see it?

Yes.

Yes. And so the experiment we've done here is we've used human -- pancreatic human islets, which are from a person that is about to die. And so they're live, they are resembling the pancreas most closely. And you can see on the left-hand side, the amount of menin protein through the use of icovamenib has been down regulated 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, understanding glucose condition 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 there are more menin inhibition leads to a higher replication of those beta cells. That was profound, right? 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. And obviously, there's -- maybe I don't want to jump to conclusion, but the correlation between menin expression and beta cell function is sort of one-to-one relationship? Or does it plateau out at some point?

I have -- yes. You mean the more we reduce, the more we get and it just keeps going. We don't -- we haven't done all the work yet. We -- I mean, this is very early work. So what we found at first is we studied 4 weeks of dosing versus 8 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. So 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 cause safety concerns versus it actually has a beneficial effect. So that's why we don't need to.

So Mike, I think one of the things is it's self-limiting, right? So once you get the glucose under control and the glucose level falls, then you've got nothing to facilitate the response to icovamenib and so you -- for example, we don't see any cases of hypoglycemia in our trials.

Yes. I do want to talk about the clinical results that Ramses just referred to in terms of durability of effect. But is there -- was that anticipated based on the preclinical work because you would think that once, let's say, prolactin, let's say, in the pregnant women or in the animals when you take the inhibitor away, you would think that would return to sort of the normal relationship once again. So what have you -- 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, but companies who've done stem cell transplant have seen this that when you -- that the maturity of these beta cells, these newly created cells take time until they're fully functioning. So 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 a 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 particularly insulin-deficient patients, you can see during the dosing period that is indicated 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. You can see that the C-peptide improves and it even improves further as you are off drug.

Right. So do you -- you think you create sort of a beneficial do loop, so to speak? Are you kicking off a positive domino effect where you restore beta cell health and function and now you've got a healthier pool. And even if there's gluco-toxicity, still hovering around, you've got a healthier population of beta cells that can deal with it.

Unfortunately, you can't look inside, right?

I know. And the animals can't speak.

But we do know is 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. So we've seen -- if you see here in this slide, 52 weeks, but the trend is still going down. There is still toxicity to be worked through in these patients that we have dosed. So we're exploring it. But so far, very exciting.

Okay. Yes, indeed. I share your enthusiasm. Let's talk a bit more now about the clinical development aspect of the story. One thing you say in your slides that icovamenib is synergistic with GLP-1-based therapies. Where is the proof for that? What kind of data can you point to, to show us what that means?

Yes. This is -- 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, there should be sensitivity to these pathways. And 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 women or in obese individual. And you can see that we saw the same thing in our own pilot studies, we see receptors more expressed, insulin heightened and 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. So 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. So what do we do with them? Their next option would be insulin. And what we're saying to this patient, try icovamenib and that's what we do, and you can see it here. these patients here, there were 11 in our study, and this is a post-hoc analysis. This graph I showed you earlier was prespecified. Here, we asked the question very generally of all patients enrolled who was on a GLP-1. Literally, that's a question we asked. And there were 12 patients on icovamenib. We pooled them and we saw this pathway that we had explored preclinically 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 to 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.

So you're having -- yes, so you're having more GLP-1 express, more GLP-1 receptors, healthier beta cells and possibly more data cells as well. So it's an additive or synergistic effect.

Think about 2 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. and GLP-1 is not working. I mean we want to 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's not much more you can do. You will then become insulin-dependent. And what we are proposing, you don't need to become insulin dependent. Look at the amount of HbA1c reduction, I can -- you can achieve with icovamenib. This is if I -- if these cells keep on working for you, you may not -- we may push it out over years. And if we can push it out over years or redose over time, what benefit can this do for you, a patient, not in one insulin.

Right. Exactly. So that -- you anticipated one of the next questions I had, which was 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 and just from a regulatory, we'll get into the specific COVALENT studies in a minute. But 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?

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. 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.

Yes, as a single agent in addition that is given for a 12-weeks 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?

This is kind of important because we've looked at where do we fit in. On the left-hand side, you can see all these agents, you're going to adjust your lifestyle, you're going to take metformin. You're going to use all these drugs, but at some point, they fail. 1 in 3 patients move over to the right. And we would be in between that. That's the benefit we give to the health care system. Once you're over on the right, the way your body responds to exogenous insulin is heartbreaking, meaning you're going to have -- you've got to be uncontrolled because the exogenous insulin does not -- it works to a degree, but it does not control your HbA1c either up or down as we know. So you get these "side effects" that are core mobilities, now you're going to die potentially of coronary artery disease, chronic kidney disease, et cetera, et cetera. This is -- you don't want to be insulin independent. That's on the right-hand side, and we will prevent you from getting there by using icovamenib. That's the best.

Yes. Now -- well, 2 questions. Number one is, do you think GLP-1 will shift the curve? I would imagine they have to, but that's just intuition. There's no proof yet on that.

GLP-1s are in there, meaning they are on the left-hand side.

Right. But I mean, they're relatively new agents, and they're doing an amazing job at reducing weight. There's more to come. So I would imagine that...

Menin shift the curve over the last 20 years. Look at...

Well, that's the kind of answer, I was looking for.

What it may do, Mike -- can we go back, please, Ramses.

Yes. Sure.

What it may do is slightly reduce the number of patients who are going into that middle bucket. But our expectation is that this is where we get our foot in the door, and this is where we start the process. we are going to sit between all the other agents when they fail, we will be the opportunity that you take rather than go on injectable insulin. We will be 3 months of oral who knows how long value. And so we think that's a good place to start, and we have evidence that, that's already shown by the studies that we have to date, and we just have to sort of redo those to make them more credible. But we think eventually that 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. And 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 as long as you're safe enough, you can go down that pathway.

Well, again, just I guess 35,000-foot question, I'm trying to get your answer to and hear your thoughts on is that what you're saying is true, and I agree with it, but the question is in the clinical community in order to do that, will you eventually need things like outcome studies or impacts on other metrics of diabetes beyond just the 0.5, even not that 0.5 reduction, A1c is a bad thing. But again, in the crowded marketplace, lots of options, higher demand from payers, et cetera. Will you have to show some of the outcomes on these elements that we see here on the chart? Or will you think it will be taken as a given, based on prior studies of anti-diabetic agents?

Yes. I think none of us will know firmly until the FDA votes on it. But at the end of the day, if you can -- if you enroll patients that otherwise would have gone on insulin. Everybody agrees on the need, ensure everybody. And so 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, these are -- most of these patients will end up on insulins if they wouldn't be on our drug. So if you can firm up that thought, that argument further, I think that would be sufficient in my mind.

Yes. 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 progression takes a long time. If you can have a therapy in the early stages that prevent someone from going on chemo or going on something more aggressive or deleterious, then you can get a regulatory approval on that end point, but that is -- 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 the type 2 diabetes, you did COVALENT 112 in type 1, the 211 and 212 are enrolling now, correct?

Yes. Correct.

Okay. And so let's talk about a couple of things. First of all, I'm curious to know when you -- and I was looking from the demographics of your previous study, it doesn't seem to influence it. But given women's prolactin and such, do women have different baseline levels of menin they respond 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. And do you -- do we know if any different levels of menin based on adiposity or BMI or anything like that? Or is it more -- do you feel it's more uniform?

I don't know if it's more menin, but BMI is a huge criteria for success or -- 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. So 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. That we see as we go in our study and we look at our patients, we do see 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 -- but have you tried to play with a dose based on whatever body mass index of 35 or above or...

That would be interesting, but I think it's too complicated. Right now we know anything less obesity is better for patients who are just on icovamenib and back on their own.

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 800 -- so A1C at 800 -- sorry, 8 weeks at 100, a modest reduction, Arm B, 12 weeks at 100, very nice reduction. Arm C, where you had 8 weeks at 100 and 4 weeks at 200 sort of in the middle. And can you address that? Why do you think that A1c was less impressive in that thirdly Arm C regimen?

Do you want to do that, Mick?

Yes, sure. I think -- we're -- we've got a 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. But when you think about a dose response and you can think about what do you look at generally to find a dose response with any drug, you've got to do at least twofold or sometimes a fourfold increase in the drug to actually see a difference. And so I feel here that where, if you take the 100 milligrams as being a dose of 1, then the lower dose is sort of 67% and the higher dose is, I think, 150%. So it's only a little bit more. So I think the doses are somewhat close, I think it's the time that's probably the difference in terms of 8 weeks versus 12 weeks, and so that's why we've concentrated on the 12 weeks for our future studies.

And one more aspect, Mike, 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-milligram works. We didn't know the dose duration, whether 8 weeks or 12 weeks, 12 weeks is better than 8. We found that out in this study. And 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 8 weeks, the other got 12, one got 200, one got 100. That already is confusing by itself. But if you think through what we learned from the study is, 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 milligrams, 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 when you're...

Right. And you're doing that in 212, right?

Exactly. And 211, lower BMI, they work. And there, we saw over all these arms perfect results.

Okay. I want to do a little bit more exploration of 111 just because I want to set it up to help us understand what we might expect from 211 and 212. But on slide -- let's see, 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 thrown off by that.

We did not have that as an issue. And think of the 100 milligrams, it's not really 200. It was 100 milligrams twice. This is PID, right?

On the last 4 weeks.

Yes, 4 weeks, right.

So we do it here and you do it there, right? Do you do it twice daily, but one in the morning, one in the evening, are you really generating 200 milligrams 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 milligrams does beautiful.

Okay. And then 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, 10 of icovamenib, 12 pooled placebo, why is there such a big reduction in the numbers analyzed here?

I can show you the -- well, it's not a mistake. 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 5 inputs, and it says, this is now segmented as a subtype, and 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 4 groups, and 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, the greater potential effect could be. So these are the severe insulin deficient patients. But dosed at 8 weeks, they're not quite as good. The 1.2 is 1 roughly. So since we're dosing for 12 weeks, we wanted to look at what would that look like if we replicated these patients. And 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 at 8 weeks arm, what they were -- what the results were. This is 10 patients because that's all we enrolled. These are not selected by any other criteria.

Okay. All right. Just -- yes, just don't want anybody accusing you of...

I know, I know. And it's a lot of information. I agree.

We had to look at the patients who've got 80% of dosing because if they got less of that, it didn't really make sense to include them in the efficacy analysis.

Right. Okay. And then one more quick question. Sorry to be so nitpicky, but on Slide 28, you show that you've got short treatment of icovamenib delivered A1c reductions comparable to chronic injectable and orals. But can we -- are we comparing like-to-like here? Or are we comparing better to worse? Or maybe talk a little bit about this.

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. And sometimes they go with 48, sometimes they go with longer and here, we took -- we tried to get as close to our readout as we could find. And you can see 1.5 Ozempic, 1.9 to 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 every day and in this case, an injectable. And I'm comparing myself as an oral dose 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 order of magnitude. That's it. We're also...

I'm just -- but are the patients as healthy, worst off, your patients healthier, worst off?

That's a good question. In this case, these are all failing these drugs, you could argue they are one row behind, and we didn't even look for that. They are all -- we only have failing patients on our study.

Okay. Good. All right. So the next 2 studies that are going on right now, COVALENT 211, 212. You're still using 100 milligrams. Do you think the food effect is going to influence compliance at all? Or do you think people are pretty adherent to having, let's say, having breakfast and then taking their drug at 30 minutes after.

What we're actually asking is the major meal. That's kind of what we wanted because we really needed to figure this out, and 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 going to 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. And then typically, the FDA likes to see multiple dose exploration. Any thought to -- I mean...

We've done that. 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 want to jeopardize a very, very good dose. And when we go lower, we can achieve the results.

And the GI tolerability is good enough that you can get one for the therapeutic dose.

I mean the dose is our safety profile. I want to show you the upper combined arms. And if you look at combined arms icovamenib, in the bracket is the percent, we're like equal, except liver Grade 1, primarily Grade 1, these are -- because you have a drug, the liver says, hey, something go off...

Yes, 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 a bit of time because we've used this 2 terms a number of times in our discussions here. One is an inadequate response to insulin. How do you quantify that? Also tell us how you define severe insulin deficiency. And what's the difference between -- there's a nifty slide in your deck that talked 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 use criteria and academia had agreed on, there are 4 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/exclusion 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 to 10.5 and you have been -- you have -- you're failing your current therapies, which puts you further into the disease progression. We don't want you early...

And failing -- and Ramses, failing, it means what? Increase in hemoglobin A1c, reduction in CRP. What are we measuring, is it the constellation?

It's typically your A1C is above 7 and it can't be controlled.

Criteria of 7.5 and above. So anybody who's 7.5 and above is by definition poorly controlled.

We want you to have failed a prior agent where the physician says, look, this agent had an effect, no longer has an effect. They got to find another one. that's where we define ourselves. And you can go up to 3 failing agents. And sometimes they get stacked on top of each other. And so that's 211. This is characterized as a severe insulin deficient patient. You could argue, are there other criteria? Yes, you could look at other criterias. But in the bulk of the definition of where we saw the response was statistical analysis. This explains 70-plus percent of the responders in a very a 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 smoothens 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 to 40, and you have high HbA1c above 7.5. And that's kind of where -- that's the patient that we saw in the study 211 -- 111 and that we're now enrolling in 212, pretty simple.

Right. And it's interesting to me, 212, the body weights are relatively low for that population.

Yes, that's true. Very true. 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 overweight.

Right, yes. Okay. And just as far as 212 is concerned, you have a much wider range of BMIs. And to your point about the greater the obesity, the lesser the response, do you -- are you concerned that you may not see the same kind of impact on clinical outcomes with a 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 at 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 placebo is failing, then you can't use them because then they're on rescue and if they're on rescue the patient has gone for you in the database past that point. But you want to have patients that you can follow down a year, if a patient doesn't want to come back because he's on placebo and he's failing and he's on rescue, you -- one, you lose them on rescue and two, can you get them back? And it's a dance 10.5, 9.5. I tell you, I don't -- personally, it's an opinion of mine. I don't think it matters much, either of those 2 studies.

Okay. And just time lines, when are we expecting readouts for 211 and 212.

So we are -- we said publicly, we -- one, we initiated the studies, that means you have to get the sites identified, you've got to sign contracts, you've got to 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. And that means up on clinical trials, there is a heavy push then on enrollment, which will last very likely for the next 3 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, so that could be data in before year end. And that's...

Okay. It could be easier or both.

No, both. I mean, I tell you the goal.

That's the goal.

I mean, we're all humans, but that's the goal.

Yes, yes. Okay. Wonderful. Can you -- I had always thought that icovamenib was also a really interesting drug for type 1 diabetics, and that's -- there's a real unmet need there, not a lot of novelty. We've got Teplizumab, We've got the SAB-142 to preserve beta cell function. We've got the transplant from Sana, from Vertex. But what -- where is your attitude? Where is your head at on Type 1? Is it going to wait for the data to read out in the second quarter?

No. So we're going to have data readout in the second quarter of this year, meaning the next couple of months.

It's a 52-week data, right?

Yes. So we've done a proof-of-concept study in patients that were 3 years from disease identification and patients that were 3 to 15 years from disease identification. Now if you look at every one of them, you just quoted, except maybe the stem cell transplant. If you look at all, everybody is trying to get a patient within 90 days of the disease identification because there is still enough beta cells there. We asked a different question. We asked a question of even if there are no beta cells there are very few sporadic patches, can we have an effect there? What would that look like? So it's a proof-of-concept study at 2 dose levels with 20 patients over 2 big cohorts, 0 to 3, 3 to 15 and in different dose ranges. So very little data, but it will be directional hopefully. And the direction that we hope to see is, can I -- and this is kind of what everybody is trying to do. C-peptide is the hallmark of your betas cell health. And as C-peptide goes down with the attack of the immune system on your beta cell, how quickly does it go down? And the literature, if you read up on it, it says about 47% per year, and it goes down that 47% every year. And by year 3 or year 4, you are so low, then it's mostly gone. That's why everybody is shifting up front here. We said 0 to 3 years for a reason because we think within that time frame, we can still have an impact on that depleted pool of beta cells. That will be, for me, the most important update in the 0 to 3 category and thus those 100 or 200 have an effect on these patients. That's what we're going to show in the second quarter, very exciting. And the companies you just mentioned, SAB-142 is the one who just came out last week with 4 patients, and they saw at 2x dosing, right? And -- but it's the AUC that they looked at this patient over here, which had been on drug for -- had been identified 4 years ago. very interesting data, very interesting pathway. So that's one that is making a headway. But other than that, there is nothing really in type 1 diabetes. So Teplizumab is stage 2. They're not Stage 3, which means you have the disease. When you have the disease, you have insulin as your only agent. So there, I believe, from our planning perspective, the FDA and we are both -- or the whole community is in need of an agent. And so we hope that we can show efficacy there and collaborate with everybody on getting something.

Yes, because 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 going to need both components of it. So anyway, that's down the road, but we're going to -- we're running short of time and I know we started a little late, so I'll run a couple of minutes over, but not much. I want to shift real quick to BMF 650 in Phase 1 initial readout in second quarter of '26. Give us your thoughts where you think it fits in? And I don't know that there's another crowded space like GLP-1 agonist. And is it sole purpose to be an adjunct to icovamenib or do you think it has its -- the chops to stand on its own?

Yes. I think that's going to 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. And so 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're going to obviously need to have a similar type of weight loss. It doesn't probably need to be any better because I think all the things that you're looking at out there now that are potentially oral have a similar type of weight loss, 3% to 5% after 4 weeks. So we'll see what comes out of that. But 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...

Mick, you -- speaking of that, do you want to show your titration because I know that's something that you put in your deck. Show your titrate -- there you go.

Yes. So what we're doing there on the right-hand side at the bottom there is the uptitration. And you can see we're uptitrating to 100, uptitrating to 200, 300, 400, those are the 4 doses in the multiple ascending dose group. On those data are the data that will be available at the end of the second quarter this year. And 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. And then longer term, we think that within this space, everybody has sort of tried to go after massive weight loss. And people lose weight and they go off drug and the weight comes back on again. And we think with an oral drug, a better strategy would be to drop the weight and then back titrate so that you maintain the weight and basically sort of kept at whatever way you were trying to get down to. And so our expectation is that, that will be something that will be 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 but have you done anything further to try to elaborate on that? Or are you waiting for the results to come out to see...

We want to see what goes on here. But I mean, again, while there is always the possibility of combinations, especially with 2 orals. The reality is there's a lot of GLP-1s out there at the moment. And so what we've done with icovamenib is looked at the combination data with semaglutide. And we'll be including that obviously in our 212 trial. But in animal studies, we've been looking at it not only in terms of the antidiabetic effect, but also weight loss.

Okay. And just a quick question before we wrap up on IP. How do you feel about your IP position? We saw that 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 will be able to keep others out of the space.

Okay. Great. Anything I've missed that you want to mention in closing, I don't see any questions pending in my e-mail. So if there's nothing, any concluding remarks you guys want to make before we close it?

If you ask that invitation, Mike, you're going to get a long answer, but...

What I'll say, first of all, it looks like you've got like some nice milestones coming up. You got the second quarter where you have the type 1 diabetes full 52-week readout, you have your initial data from 650. Then by the fourth quarter, let's see, knock wood, we got 211 and 212, so you certainly have a list of maybe identifiable...

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 failed at some point, you need insulin. So there's a great need, one. And two, we have identified the biologics through others, there menin has a role in the pancreatic sort of functioning, menin controls. We have then isolated in animal experiments that, that is actually, if you take out menin or you inhibit menin function, you have a beneficial effect. We then went to the human islets, and we identified it there as well. And now we're in the humans then 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. Now that's very, very clear from us as developers. I got my bread crumbs, I 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. So that study reads out by year-end. We feel very confident that we can replicate the results we've seen. And then -- and 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, then if I can move this into a Phase III, do I need big brother or big pharma to help me? No, it's not a 5,000-patient study, 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 2 years from now, and I'm ahead of becoming a 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, et cetera, et cetera. That's the future story that we're trying to sort of accomplish.

All right. Well, we will certainly stay tuned and we urge investors to take advantage of the modest valuation that shares present right now because that's not going to -- yes, it's not going to stick around forever. Anyway, guys thank you so much for taking the time. I appreciate the willingness to go deep on the science.

Thank you, Mike.

Bye-bye.