Okay, great. We can get started. Good afternoon. I'm Eric Joseph, Senior Biotech Analyst with J.P. Morgan, and our next presenting company is Biomea Fusion, and presenting on behalf of the company is CEO Tom Butler. There'll be a Q&A session after the presentation. Just raise your hand. We'll bring a mic over to you, and for folks tuning in via the webcast, feel free to submit questions via the portal. With that, Tom, thanks for joining us.
Great. Thank you very much, Eric. And thank you guys all for attendance. It's an honor to be here again for the 43rd Annual J.P. Morgan Healthcare Conference. So without further ado, just real quick, so I'll be making forward-looking statements during this presentation, so please take note. As we announced Monday morning, Biomea Fusion is a diabetes and obesity medicines company. And as you can see on our pipeline, we have a very robust program set. It starts with icovamenib, or BMF-219, as a potential first-in-class menin inhibitor for Type 2 diabetes, as well as Type 1 diabetes. It starts with COVALENT-111 and 112 for our two key studies. Anticipated milestones for 2025 are getting week 52 data in the second half for Type 2. And then for Type 1, it's generating open-label data in the second half as well.
I'll walk you through during this presentation and speak a lot about two key patient populations for further late-stage development with icovamenib in the severe insulin-deficient diabetes patient population, as well as patients who are about to initiate a GLP-1 or uncontrolled on a GLP-1. And then lastly, I'll cover BMF-650. That's our small molecule oral GLP-1 receptor agonist that's currently undergoing IND-enabling studies. And we're pursuing obesity as well as diabetes. We expect IND cleared in the second half of this year and FPI. So here's our executive team. We have a long history of developing very successful medicines for patients. And we've had a lot of success working together. So we have Ramses Ertman, President and CEO, who I co-founded the company with back in 2017. We have Dr.
Juan Pablo Frias, CMO, Naomi Cretcher, Chief of People, Heow Tan, who covers CMC and is our Chief Technical and Quality Officer, as well as Franco Valle, our CFO, so icovamenib and BMF-650 are to become the cornerstone of this metabolic franchise, and we're prioritizing the development of icovamenib in the metabolic space to address critical unmet medical needs, which I'll cover. We previously announced the top-line data back in December from COVALENT-111, the Phase IIa, as well as we covered in vivo preclinical data supporting the future of GLP-1 combination and the support, really the focus. Really, the data culminating together in December crystallized to a point that made it very clear this is the path for icovamenib and the path for the company.
Icovamenib development in Type 2 diabetes to focus on those two key patient populations, the severe insulin-deficient group, the SIDs, as well as the GLP-1 therapy agonist. So the key benefits of icovamenib are first-in-class therapy with a novel mechanism of action, a unique treatment effect, durable treatment impact on beta cell function, as well as incretin effect. It's oral, once daily, 12-week treatment, simple. It has enhanced endogenous insulin production. It results in improved beta cell function. It also promotes body weight loss and has shown increased proportion of lean mass and preserved lean mass in our preclinical work. And really, the development rationale is people with the lowest insulin production demonstrate the highest all-cause mortality and the highest treatment failure rate among all phenotypes. icovamenib has demonstrated superior treatment efficacy in this patient population.
We've promoted weight loss and increased muscle percent when combined with the GLP-1 therapy in our preclinical work. We've also seen acceleration of weight loss in the clinic. This supports the combination work, both as maintenance and in combination with monotherapy. Also supports novel combination with an oral small molecule GLP-1 receptor like BMF-650. So we all know that diabetes is a huge unmet medical need, really, across the globe, especially in the United States. One in three Americans will develop diabetes during their lifetime. And it actually results in the loss of life of about 12-14 years, which is really unbelievable. And most importantly, 800 million adults globally are living with diabetes. It remains poorly controlled in half of the patients as they cycle through multiple therapies, which I'll cover.
So the challenges with current standard of care, and I think we're just not quite yet appreciated, but we do hear this from those who are in this space, is that the top three mechanisms of action, the GLP-1s, the SGLT2s, and the DPP-4s, both exhibit high discontinuation rates over time. Patients don't want to stay on medicine for the rest of their life. And there's a number of reasons why they come off therapy, such as side effects, not reaching glycemic targets, just aversion to the route of administration, and the cost of unaffordability. So what's going to happen for those patients in this kind of gray space on the right-hand side of this slide? Where's the maintenance? Where's the long-term glycemic benefit? That's the unmet need that we hope to provide.
We also know that as soon as you discontinue, there's a rebound both in the glucose level control that these agents exhibit. There's also a rebound in weight, and it happens very quickly. The treatment paradigm shows you that as the pool of beta cells continue to deplete at diagnosis. Keep in mind that when you get diagnosed with Type 2 diabetes, you've already lost 50% of your pool. That pool will continue to decline 4%-5% per year, whether or not you start an anti-diabetic medication, and once you get to about 10%, the Type 2 subject mimics a Type 1 individual, where they're completely insulin-dependent, and so the current strategy is to try to just medication stack to try to capture this depleting pool and try to get as much glycemic control as you can with the current mechanisms of action that are available.
With a combination of medication stacking and high discontinuation rates, what you see are adults with Type 2 diabetes really cycle through many therapies to tackle their disease. When you think about the average age of diagnosis being 45, right, the time that you spend actually controlled is very low. We all know Type 2 diabetes is very heterogeneous. There are multiple phenotypes. Here we're highlighting the fact that there are four key phenotypes. They're really broken down into two key segments. This analysis was done with two independent 4,000-patient studies, the ADOPT and RECORD. What they found is that if you look at the two segments, insulin-deficient diabetes and insulin-resistant diabetes, you can really understand what drives these phenotypes. What's driving it is their ability to produce C-peptide, their ability to produce insulin, their baseline A1C, and their BMI.
Those who are deficient have relatively low BMI, relatively very poor beta cell function. They don't have a lot of C-peptide activity. The insulin-resistant have actually an elevated HOMA-b eta compared to the deficient. So they have much higher HOMA-b eta function. And they have a much higher BMI, which really suggests that it's insulin resistance or the inability to be sensitive to insulin that's kind of the core driver of their hyperglycemic state. And then specifically, what is a SID patient? SID patients have the lowest insulin production out of all adults with Type 2 diabetes. They represent the highest unmet medical need, as they display the highest all-cause mortality. They have the worst cardiovascular outcomes. And they have the highest treatment failure rate among all adults with Type 2 diabetes. And they represent about 18% of the Type 2 diabetes patient population in the Western world.
That's about 14 million in the U.S. and E.U.. And a significantly higher proportion are in Asia, over 50 million. They typically, again, present with a BMI of less than 32 and a baseline A1C of at least 8.5. To walk you through the mechanism of action of icovamenib, because it is a very unique mechanism of action as a first-in-class product candidate for the treatment of diabetes, it's a selective and partial menin inhibitor. Its mode of action, its PD effect, is not to disrupt protein-protein interactions. It's to actually form a covalent bond with the target menin and send it for degradation. It actually has global disruption. Menin has multiple protein partners. Disrupting MLL or another protein partner alone is not sufficient to drive this strong efficacy that we see.
This dual effect of driving down menin protein gets you beta cell quantity and function impact, so increasing beta cell mass and function, as well as increasing insulin synthesis and secretion. It also impacts, most importantly, GLP-1 expression. So we presented at World Congress in December that icovamenib in human islets increases GLP-1 receptor expression and protein counts and enhances the incretin effect. We also see an enhancement of body weight loss, but quality body weight loss. We see the preservation and actually increase in muscle mass, which is also menin-dependent. So COVALENT-111 is our Phase IIa double-blind randomized placebo-controlled study in Type 2 diabetes that had top-line data this past December, just a few weeks ago. This is an ongoing dose-finding study evaluating the addition of icovamenib in Type 2 patients who are uncontrolled glycemia while on standard of care.
So these patients have stable weight, stable A1C, and now we're, and they're still uncontrolled, so above 7%. And now we're adding icovamenib on top. And so patients receive icovamenib for a fixed treatment period. This is how unique this mechanism of action is. And the reason why we're able to just have a fixed treatment period, again, is because we're increasing beta cell mass, increasing beta cell function. Beta cells have a very long half-life on the order of decades. So the treatment period is up to 12 weeks. And so if you see Arm A is dosed for eight weeks of icovamenib, Arm B is eight weeks at 100 mg once daily, followed by additional four weeks of 100 mg once daily for a total of 12 weeks. And then Arm C is eight weeks of 100 mg once daily, escalated to 200 mg or 100 BID
for the final four weeks. The durability of the treatment effect is then measured at week 26, which is the primary endpoint, and then the key secondary at week 52. This is a double-blind placebo-controlled study, and there's a three-to-one randomization, so there's three active patients for every placebo. The placebo is pooled together to do the analysis. For our statistical analysis plan, it was very important for us to first execute a trial that was very real-world, so we wanted to have the ability to analyze how icovamenib impacts the four key phenotypes that I walked us through earlier, so that's the SID, the MARD, the deficient patient segments, as well as the MOD and the SIRD. The subgroup analysis is based on an algorithm established per Ahlqvist, so these patients are then categorized and labeled as these phenotypes as part of the statistical analysis plan.
And this is done prior to unblinding of the study. And then we really look at Arm A, B, and C as a primary analysis and A1C reduction. So icovamenib met the primary endpoint, showing statistically significant in a key patient population. So we exhibited a clear dose response when you compare eight weeks versus 12. 12 clearly outperformed, giving you an extra 55% additional reduction in A1C compared to eight weeks. And then on the right-hand side, really a clear mechanism of action validation. You can see the MOD and the SIRD patients, patients who have robust beta cell function but high insulin resistance, did not show statistically significant effect. However, those who are beta cell deficient or insulin production deficient showed a very robust response of an additional 560% reduction or sixfold.
Now, when I dig in further to this severe insulin-deficient diabetes patient, which is going to be one of the key focuses for icovamenib in Type 2, you can see that Arm B performed very well. Arm B had the highest end and the most patients who finished the full 12 weeks. And you can see as we move from all subtypes of a 0.5% reduction at week 26, we see that when we move to the insulin-deficient subgroups, MARD and SID, the response doubles. And then we move to SID patient population, it increases another 50%. So nice to see that as you move down in C-peptide capacity, insulin production, we're getting further and further impact in the response. And again, the SID patient population is quite large at 14 million in the Western world. Here's the breakdown of the table.
And again, looking at Arms B and C we did during the top line as well as Arm B. Keep in mind that Arm B, six of the seven patients that were classified as SID, completed the full 12 weeks. In Arm C, only two of the four patients completed the full 12 weeks. The other two were in the range of eight to nine weeks. So they really behaved more like Arm A patients. And then when we compare how we're performing in this SID group, 1.5% reduction at week 26, we compare very well to the really robust effects of tirzepatide as well as semaglutide, Ozempic, and Mounjaro. And of course, comparing to the oral agents, SGLT2 inhibitor Jardiance, as well as Januvia, the DPP-4 inhibitor. What's also very important to know is that the responses are continuing over time.
So as we see this trajectory, the effect has not plateaued. We see that these patients are doing quite well and that week 26 represents the lowest point in the course of treatment as well as during the off-treatment period. So this robust effect that we're showing you in these patients is now 14 weeks off treatment. As I showed you before, if you discontinue any of the current mechanisms of action, the A1C comes right back up towards baseline. So this is the unique drug effect. And this is what we're really aiming for is long-term glycemic benefit so that patients don't have to stay on therapy for the rest of their lives. And this is what gets us so excited. And so we're really excited to see what week 52 shows, but the trajectory looks strong.
And then again, for Arm B, obviously going from week 12 to week 26, we did see a doubling effect. So the last day of dose was week 12. Week 26, 14 weeks after last dose, we see a doubling effect in the A1C reduction. So when we wanted to look at the Ahlqvist algorithm identifying SID patient populations, we wanted to see how can we move forward into late-stage development. How would you move forward in commerciality? What are kind of the key characteristics that really describe what a SID patient is? It's actually very simple to do. And what we did is we looked at baseline A1C and we looked at BMI. And in the literature, it suggests that a BMI of less than 32 and an A1C baseline of 8.5 or higher should be sufficient to categorize these patients.
When we did the analysis for COVALENT-111 at week 26, we compared the SID per Ahlqvist algorithm to just using two of the key characteristics, baseline A1C and BMI, and we got it. That's very encouraging for us to know that as we move forward, we just can use two simple criteria to enrich for the SID patient population and move forward in this group. Now the second important development projection for icovamenib in diabetes is the combination with GLP-1 therapies. Just quickly, what we're trying to share with you is that when you properly inhibit menin function, again, MLL is not involved here. It's really PRMT5. You can really increase GLP-1 receptor expression. We shared this data in October just to quickly remind you. When you add icovamenib on top of tirzepatide, you can get a doubling or tripling of insulin secretion in human islets.
You can also get a similar effect when you use semaglutide, so a doubling or tripling of insulin secretion. We also see it with the oral small molecules, ORFO, and of course, our BMF-650. And then just last week, we shared that we'll be presenting our first in vivo experiment where we look at Zucker diabetic fatty rats, a model of insulin resistance and mimics Type 2 diabetes. We used semaglutide as the GLP-1, and we compared semaglutide monotherapy to combination with icovamenib. And what was so exciting to see is seeing the fasting blood glucose improvements, as you would expect, and obviously increasing GLP-1 expression. You're really sensitizing the animal to a GLP-1. We're seeing functional improvements in the beta cell pool with OGTT here. We're also improving HOMA-IR, as we'd anticipate. The animal is much more sensitive to insulin as it's losing weight.
It's increasing C-peptide production per unit of glucose, shown here. We also see an acceleration of body weight loss, an increase in lean mass composition, which means the body weight reduction we're getting is really pure fat. So again, really highlighting the quality of the body weight loss that we're getting when you combine icovamenib and a GLP-1 at the same time. And this is the clinical data that we announced in December when we take patients who are uncontrolled on a GLP-1 and now adding icovamenib on top for 12 weeks. And what was great to see is that all arms performed very well. Arm C performed the best, showing us a 1% reduction at week 26. And so again, let's see how these responses over time, but we're very excited to be able to get to that 1% mark.
And then most importantly, we're also seeing weight loss occurring and acceleration of body weight reduction. We're observing up to 14% of additional weight loss and really highlighting that it's a doubling or tripling effect of the weight impact when adding icovamenib on top of an existing GLP-1. To overview the adverse events through 26 weeks, so really balanced across the three arms and comparing to placebo, of course, patients with at least one treatment-emergent AE. There were no SAEs in the study in any arm. There were no treatment discontinuations due to AE, no study discontinuation due to AE, and no deaths. The safety and tolerability was very encouraging as well. As you can see, nausea, diarrhea, hyperglycemia occurring in about 4% of patients. Headache was observed in about 2% of patients.
These are all grade 1 and grade 2 in one hyperglycemic case and in one nausea case. And then importantly, ALT increase and AST increase was observed in 2% of patients, mostly grade 1, with three of them in one event of grade 2. And remember, back in the summer of last year, we were under a clinical hold. And that clinical hold was really because of the dose escalation study where patients were starting at 200 mg or 400 mg in the first 30 days. When we submitted to the FDA the safety and tolerability of this study, the study was about 50% completed. The clinical hold was lifted in about 30 days. So very encouraging. And now that we have the 100% of patients completed here, it's very encouraging to see that these results have held and show a very strong safety and tolerability.
Now that the FDA does not have an issue with this dosing scheme and study design, we're very excited to be able to move forward. Late-stage clinical development in Type 2 diabetes for icovamenib, just to summarize, we focus on two key patient segments: the severe insulin-deficient patients, the SIDs, then all patients in combination with GLP-1. Keep in mind when we're doing the combination work with icovamenib and a GLP, that is independent of the phenotype, all phenotypes. For the SID patients, we aimed to really improve glycemic control in the patient population with the highest unmet medical need in Type 2 diabetes. For the GLP-1 patient population, we really aimed to maximize the incretin effect while preserving lean mass and increasing body weight loss in two subjects. Subjects who are initiating a GLP-1-based therapy and subjects already on a GLP-1 and uncontrolled.
Again, here's the pipeline. We have a lot of anticipated milestones. We really wanted to highlight that there are going to be several high-impact milestones in 2025. So that's obviously sharing more week 26 data at ATTD Asia or sorry, ATTD in Europe, as well as ADA. We'll have week 52 data from COVALENT-111, as well as open-label data from our Type 1 study. We're going to meet with the FDA in the first half of this year to discuss an adaptive design for the SID patient population and advance to late stage, as well as discuss the design and the sizing of the GLP-1 combination study. And then, as I mentioned before, BMF-650 is on track. IND enabling studies are going well. We expect to file the IND in the second half and prepare for FPI.
Advancing a first-in-class precision-based treatment for diabetes gets the team extremely excited. It's an oral, once daily, simple 12-week treatment for diabetes. We displayed comparable efficacy to GLPs, chronic therapy, and the patient population at week 26 with just 12 weeks of treatment. Icovamenib displayed in the pre-specified SID patients placebo-adjusted mean reduction of 1.5%. SID patient population, again, represents the highest unmet medical need and about 18% of the total population. Icovamenib was well tolerated with no study drug discontinuations due to treatment emergent AEs. Icovamenib added on top of an existing GLP-1 demonstrated a clinically meaningful 1% reduction in A1C in study participants with uncontrolled diabetes. And then BMF-650, a next-generation oral small molecule GLP-1 receptor agonist to treat diabetes and obesity, is on track, advancing towards the clinic in the second half. Company financials, we ended Q3 with about $88 million.
And so this funds us well late into 2025. And thank you very much.
Okay, great. We have some time for a few questions. So first question for me, and if there are questions from the room, just raise your hand and we'll bring a mic around. But the delineation of the various of the Type 2 diabetic patient population by insulin sensitivity is sort of not the, I guess, an aspect not well not as much discussed among programs that are pursuing this population. I guess how well how routinely are Type 2 patients typified for insulin sensitivity in practice? And I guess how robust are these parameters that define the various populations, SID, MARD, and so on and so forth?
Yeah, great question. I think using an algorithm is certainly not practical, and so for us, the good news is we've been able to really verify based on our own data, as well as have literature support, that you can just use two simple criteria, which is something that all healthcare practitioners can use, which is BMI, as well as baseline A1C, and that gets you up to over 90th percentile in enriching for that key patient population for us, which is, again, SID, and that would be BMI less than 32 and a baseline A1C of 8.5.
Do you have a sense of how SID patients respond to existing approved therapies across classes, DPP-4s, SGLT2s?
Yeah, so I would say that the MOAs of a GLP-1 and an SGLT2 or DPP-4s, their efficacy is not really dependent on the phenotypes. It's pretty evenly balanced. But what I can say is, particularly for the SID patient class, that they have the highest and quickest treatment failure rate among the current MOAs. So they're the first ones to kind of relapse or "start to rebound and discontinue therapy" due to uncontrolled glycemia.
You know that the different distinct patient populations was a pre-specified segmentation in the Phase IIa trial. What's the significance of that, considering this was in a registrational study?
Of the significance of having a prescribed?
Having pre-specified the various patient populations.
Yeah, I think it's just a great question. I think it just makes the data just a little bit more robust, is that you've already pre-classified and pre-identified them prior to the unblinding. So then we just let the data speak for itself. We don't have to go and look to see where do we see responses or don't see responses. We just start looking at the phenotypes and looking at it all. And I would say, because the mechanism of action is focused on the beta cell, right, it's great to see that the patients responding the strongest are those who had the least amount of beta cell activity. So it's really validating for us and confirming that the MOA is working. 12 weeks was clearly better than eight. And so now we have this kind of clear path of development in Type 2.
I would say just to, having a biomarker approach just increases the probability of success of a clinical trial. I think we've all seen that, right, that if you can pre-identify your responder, the probability of success is just that much higher. We have a question over here.
No.
[audio distortion] .
You've frequently referenced beta cell mass and function. Now, are you seeing a multiplication or mitosis of beta cells, or are you seeing a growth in the existing cellular base?
Yeah, great question. So when we talk about the mass or the number of beta cells and the function, in our preclinical work where we look at human islets, we see actually replication of existing beta cells. So it's multiplication, replication of these cells that's leading to this increased output of insulin secretion. And so we've documented that very well and have presented that at EASD and ADA. We've also done it in our animal preclinical work where we're doing staining of islets. We see an increase in the size of the islet, as well as an increase in the number of islets. Great question.
Your type of diabetic patient, basically, you would be competing with insulin. This would be the same patient population that would be just on the verge of going on insulin. So this would probably be a prevention of insulin therapy, number one, which I think is interesting. Number two, do you have absolute C-peptide levels and preservation of C-peptide levels in this patient population with your drug? I think that would be helpful for the case.
Yeah, so the team is preparing all that data. Our team is going through that now. We haven't seen it yet, but we will get HOMA-beta, C-peptide, OGTT data for ATTD and ADA. So we can see that dichotomy of insulin-resistant and beta-cell-deficient. But we're very excited to see it because I agree it's very validating to have.
Yes, I concur with that as well. And so picking up on just having you kind of frame expectations for when those data will be presented, and you kind of gave us not on C-peptide, but just a little bit of a glimpse on the post-treatment follow-up, which seemed new on slide 22. This is looking at, I guess, A1C decline for all treated patients, all SID patients on 12 weeks. Can you talk a little bit about just patient study continuity or patient retention in the post-treatment phase and sort of the kind of full the numbers of patients for which you would have also C-peptide and HOMA-beta analyses for when presented?
Yeah, great question. So retention in the study has been very strong. So that's been very good just from a robustness and data readout perspective. So we expect to have a very robust data set going to week 52 to that point. And then again, as this is a very large study and that's 200 patients, even though when you break it down into the different categories, it shrinks, we will have plenty of data from each subcategory to look at the HOMA-beta and C-peptide scores.
Okay.
Yep. And here again, I mean, for looking at the SID patient population with arm B, six of the seven finished the 12 weeks, and all seven 100% response rate. So the error bars on these patients is very tight. All patients are experiencing a reduction and coming down over time. So when we look at the all patient A1C reduction, you look at the MARD and the SID, as well as the MARD and the SIRD, we anticipate for these reductions to continue over time.
So just on this, sticking on this slide, this is across all treatment arms?
Yeah, that's A, B, and C.
So how many patients are kind of comprised? And does it shift over time here at all? And maybe if you were to sort of disaggregate by dose, what would it look like?
Yeah, so this is just over 20 patients. So it's about 22 in A, B, and C. And so the numbers are consistent from each time point. So there's no drop-off at different time points.
Okay, great. All right.
Yep. Super.
All right, well, any other questions? I think if not, we'll leave it there for time. So thanks very much for tuning into the session. Thanks, Tom, for the presentation.
Absolutely. Thank you so much.