Okay, let's go ahead and get started. Thank you for making the trip down to Miami to be with us. And before we delve into Q&A, we'd just love to kind of give you the chance of introductory comments, give an overview of the business. We can look forward to going forward.
Yeah, perfect. Yeah, thank you very much for inviting us. It's always nice to come to Miami. We were in New York first. That was really cold. Now here it's really nice. The overall interesting fact about the company is that we're trying to do something that biotech should be doing. We're trying to improve healthcare for diabetics, primarily diabetics. That's how we started. We're now seeing there's positive attributes of our drug also in obesity. But when you think of diabetes as a disease, you'd say, okay, you get diabetes, and then what are your options? Your options are to be on drugs for the rest of your life with a chronic agent. And these agents fail over time, and they stack them, and then you get the next one, and the next one, and the next one.
Your outlook is, at some point, I potentially will become insulin dependent, and then I run the risk of death and all these other sort of complications that come with the disease. And if you look at statistics, diabetes, if you get identified with diabetes in the age of 40, you lose potentially up to 16 years of life. Think about that, right? For us, when we looked at the disease and we saw what Mother Nature is doing to prevent diabetes in two scenarios. One, pregnancy. Mother Nature found a way to avoid diabetes by upregulating the insulin production. How does the mother do that? She does it by downregulating a protein that is sort of a scaffold protein controlling the pancreas called Menin. Now, Menin has also implications in cancers, and people are addressing Menin for cancer and for the proliferation of cancer cells.
That's a different area, and they do it by inhibiting a contact point to Menin when Menin is being used for something. In this case, Menin has the control function, and if you take Menin and inhibit it, the pancreas actually allows for the production of beta cells. And that aspect, you can see papers in literature that indicate people have CRISPR-bound Menin, and they can control diabetes that way. So when we saw the papers and we looked at the target, we said, wow, if we could potentially "cure," and it's difficult to make that statement, but that's the goal of the company. We would like to cure diabetes. And so we're now in the pathway of achieving a cure signal. We've had those patients for 12 weeks. We pre-specified them.
They're insulin deficient, and these patients now show a year later still the reduction of their A1C, which is a matter of glucose toxicity. That's phenomenal. They were nine months off drug. And so the company overall started with a target Menin. We addressed it with a covalent binding molecule. That is a very elegant way of addressing the target, and we now have early clinical data that indicates we're on the right track. We're now coming out with two phase II studies that go after specific patient populations where we saw greatest response. And we have, in the meantime, because we're developers, we came up with an oral GLP-1 because at the time the space needed an oral solution for obesity, so we came up with a drug that addresses obesity.
Excellent. Excellent, and I'm getting ahead of myself, but I was looking at some of your preclinical data. Even Menin, or indeed inhibition of Menin, also kind of boosts GLP-1 too to some extent, right?
That is an aspect we haven't really known much about, but now preclinical data indicates not only are we upregulating by inhibiting, and that makes sense for the pregnant woman, right? She needs more GLP-1 around. So when you inhibit menin, GLP-1 is upregulated, and the expression, the receptors on the beta cells that are now waiting for GLP-1 to come around, those receptors are more expressed. So two aspects that we found in preclinical studies, and so that is beautiful, right? The whole story fits wonderfully together. We now have to translate that to patient benefit, which we have seen, and that patient benefit we hope is lasting.
Got it. That's very interesting. But just to kind of drill down, take this step by step, just to review the COVALENT-111 data. When you look across the 52-week data in the SID subpopulation, just these patients were dosed for 12 weeks, followed until 52 weeks, but after 12 weeks, their A1C continued to improve, I think to the tune of maybe 1.5% A1C. So how would you describe the variability you see within this SID group and the GLP responder groups?
Yeah. Okay. So when we started by addressing the target, we had to ask the question, who is coming in the door and who has a benefit? So if you look at diabetes, there's a wide phenotype difference between diabetic patients. You have some patients that are insulin resistant. They're more on the obese side. And then you have some that are just lean with a BMI of 25 and have diabetes. Their diabetes is quite different. And in the case of the insulin resistant person, that has a high insulin response that is now wearing out, and now they're hit with diabetes. But their insulin levels are pretty high. If I add more insulin productivity to this person, you will not see a response because we're measuring A1C, which is the reduction of the effect of insulin, meaning the reduction of glucose, which comes to insulin.
So we found that we subtyped these patients, that the ones that are defined as Severe Insulin Deficient, those are the ones that respond best. So you see in those the response starting in the 12 weeks during dosing, and then they keep on going down. And if you look at the trend in the trajectory, it stays on. I mean, the trend was continuously going down. So the other subtype that we tested, which was more of a post-hoc analysis, were patients, because of what you said earlier, the GLP-1 is upregulated, could we have an impact on those patients that are on a GLP-1? They are typically resistant. So we tested those. We had 11 patients in our study, and those patients as well showed the exact same trend, whereas other obese patients that were not on a GLP-1 didn't have that trend.
So now we're specifying those two subgroups to the FDA, and we're in protocol discussions so that by what we said publicly in Q1, we will have our first patients enrolled in either of those two, in actually both of those two studies. We will have an FPI in Q1.
Excellent. Excellent. And for folks less familiar with the story, just in general, including myself until I really started to delve deep into it by this data, you just think of diabetes as kind of just pretty much one type two diabetes and type one. But here you're kind of subsegmenting the type two into subpopulations. Maybe just give folks a sense as to the market prevalence of these subpopulations and how you go about identifying them.
Yeah, and it's not me basically who's doing this. We had to learn all this. We thought similar to you, oh, diabetes is diabetes. The subpopulations are defined more or less by first an academia, then the practitioner, the endocrinologist, then the practitioner, and so when you ask an endocrinologist, hey, how would you recognize the various types? He says, typically by BMI because BMI is your measure of resistance. If you have a high A1C and you have a high BMI, you are one category. If you are low BMI, meaning 30 and below, you're a different category, so it's fairly simple to identify them, but we needed to find a mechanism that is not based on our own interpretation, but on something that is standardized.
So we used an algorithm that was developed by a group in Sweden, and they came up with that in 2017 because also practitioners need to know, what do I do with whom? Do I give a GLP-1 to this guy or to this guy? And what's the treatment modality? And we used that algorithm when we pre-specified these. They have four subgroups, and we used their identifying markers to come up with our four subtypes. But that's very complex, and we needed something to show to the FDA. This is not an ad hoc approach by us, but in the future, it's more or less A1C, BMI, and how long have you had diabetes.
Got it. So clearly the SID subgroup is the clearest responder group, but as you think about the future soon to be initiated COVALENT-211 trials, how are you approaching, I guess, the challenge of helping sites distinguish these patients upfront? I mean, is it what you just said?
Just that, and the one piece I didn't say when you asked for prevalence, it's about a half-half resistance deficient, and within deficiency, you'll find another half being severe, and this is very broad, but you can find in the Asian population up to 40% that are severe insulin deficient, and in the more Caucasian, you find up to 20%. So if you assume that our target is about a quarter of diabetes, diabetes is 38 million in America, 80 million U.S. and Europe, you're at a quarter.
Just to be clear for folks, when people hear insulin deficient, they think type one. This is type two you're talking about.
Exactly. All type two. Type one is, and for those who don't know, type one is basically severely insulin deficient, yet you have an autoimmune response that destroys the cells that you need in order to make insulin. The interesting thing about type one is that you still have, when you do a test, when you do what is called a mixed meal tolerance test, and you give a type one patient a meal, and then you see, is there a spike of insulin coming after that? Most of these patients still have a spike. Where is that coming from if your immune system is attacking those cells? Well, there must be cells around that haven't been attacked or flagged for attack and the theory now for us is, and we are exploring that with Harvard. They have a type one division that is phenomenal.
They do a lot of cell work, and when they saw our data, they became excited, and they're looking at it from the viewpoint of those cells can be replicated. We want you to try it in type one. That was the initial because in type one, the help is more needed than in type two. And we're now starting up that effort again post this first wave of early results.
Got it. That makes sense. Makes sense. Just to focus on safety for a bit. I mean, with a 200 to 400 milligram dosage, you previously saw liver enzyme elevation. So what kind of gives you confidence in the long-term safety at 100 milligrams?
Yeah, because the data. I mean, 200 and 400 is a starting dose. You will find most of the diabetes drugs are titrated, and so you go from one dose until the body is comfortable with the dose, and you step it up. And what we've found that when you step up to 200 with a starting dose of 100, you don't see those elevations only if you hit the body initially with 200 or 400. And that was probably our mistake to not go at ease with the titration schedule just to, because we wanted to see what is the response like. We should have gone with the titration. That would have avoided the spikes, and it would have avoided all the concerns. Now we were cleared. We showed the FDA every individual narrative on every patient, and they said, okay, with 100, you're fine.
We don't see it either. I mean, look at our results. They're really, really good on the safety. And if you want to go to 200, just titrate. And so that's what we would be doing.
Got it. Also, your data shows that exposure seemed to clearly drive efficacy. So how confident are you that covalent menin could achieve consistent exposure every day?
Yeah. I mean, first of all, I'm really happy that exposure drives response. That means the target we're affecting is a relevant target. It's always the difficulty of getting to the target, and then first you need to know the target makes sense. We feel very confident the target makes sense based on not only our work, but everybody else's work. Now the question is, how do I get variability out of the results? And we have seen variability. You see variability with everything, but you're trying to optimize it so that you or I or somebody, when we take the drug, we have a similarity of response. And so the way we are approaching it is with another food effect study where we test if you take the drug an hour, half an hour with different types of food, does the exposure change? And it does.
So, you will see us come out with new dosing instructions in the first quarter before we launch the first patient dose that give clarity to what have we learned. And we're in the middle of this, and we have to wait a little bit until we come out with that.
Got it. Just thinking about the food effect study and just the effect of food on optimizing exposure, how do you see that previous data kind of shaping up the dosing rationale and design for?
In the future?
For studies 211 and 212?
I think what you will see us do is within X, so take the drug within one hour post-dosing as an example. And because the further you get away from food, the more you have trouble absorbing or the lesser absorption occurs, and people do not, that's one of the problems. The other problem is when people like to take their medicine after lunch because it's easy to remember. You don't want to set your time. So we need to explore, can I even give you that? Because I want to give you clear instructions so it's easy for you to follow. And a clear instruction would be within one hour. And we're testing how much variability do I get within that hour and what types of foods. And if these results come out fairly homogeneous, then that'll be the dosing that we will ask for.
Got it. Just kind of want to pivot now in the last maybe five minutes we have left to your oral GLP-1. I know it's very early. It's currently in phase I. Any insight into how it may be differentiated versus the other orals in development at this point?
Let me pivot to Steve. Steve is our head of development, so I think the lay of the land is when we started about three years ago, you saw some efforts in trying to get away from injections, and Orforglipron is in the lead, but what did we do, Steve?
Sure. Thanks very much, Ramses. So first of all, Orforglipron, Lilly's oral GLP-1 receptor agonist, is an excellent drug. The problem with Orpho is it's probably too potent for its own good. And the reason I say that is that that high degree of potency makes the compound in many patients poorly tolerable. For example, a significant percentage of patients have to come off drug. There's a ramping up period when the clinician initiates Orpho with the patient. Many patients cannot execute the full ramping up to the desired therapeutic dose. So given those liabilities of Orpho, Biomea designed a BMF-650. This is built on the Orpho scaffold, but it has molecular attributes that we believe will yield better tolerability. For example, again, by design, it's less potent than Orpho. It has a smaller peak to trough ratio than Orpho.
Both of those attributes should yield better tolerability for patients. So as was mentioned, we are early in the clinic now dosing patients. This study should go quite rapidly, however. We anticipate results in Q2 of 2026. We are enrolling obese, otherwise healthy individuals, examining, of course, safety and tolerability as well as weight loss.
How long was the study? How long was the phase I study?
It will enroll approximately 60 patients. As I mentioned, we will have data in Q2 of 2026. It's quite a short study. We anticipate it will go rapidly, quick enrollment, quick results.
We'll show you 28-day weight reduction.
28 days. Okay. That's what I'm getting.
That's kind of the comparator for everybody. So you titrate up to 28 days, right? Then you're at your dose, and you show those results for a week, and then you follow up with another two weeks later on. So we will have six weeks at the end, but the first data point is four weeks to make it comparable to structure, to the other orals.
This will include titration, the phase I.
Yeah.
Okay. Just more, I guess, on the chemical properties. Steve, have you commented on to what extent it influences beta-arrestin versus not?
We have preclinical data indicating it does not significantly affect Beta-arrestin. Yes.
Okay. Okay. Excellent. So any thoughts? I know the COVALENT-212 is a combination study with GLP-1s, correct?
With any GLP-1.
Any GLP-1s.
That's not quite correct. The drug we believe has an additive value if a diabetic patient is on a GLP-1, and your A1C is rising, what do you do? Your next step is insulin. In this case, we're offering an alternative with adding Covalmenib, and that's where we have seen the benefits. With Lilly's or Novo Nordisk's compound, we are designing the study 212 with semaglutide because it's very broadly used, and it's easier to see the differences. And that's the study design for 212. But it should work with all the GLP-1s.
Great. In the final maybe 30 seconds, with the recent reads that you've done, you guided to a runway into the second half of 2027.
Actually, it's into 2027.
Into 2027. Okay. So as you plan studies 211, 212, and advance the oral GLP-1, what are your goals in terms of what do you want to achieve by the end of that runway? And where partnering discussions fit in?
Yeah.
The GLP-1 itself is a massive undertaking, right? I mean, to do a phase II and to look at what Metsera did and to see how much money was needed, is that going to be our outlook? Very likely not. It's not that I don't want to do it or that we don't have the capability. So we're a shop of 40 people. We're research-focused. We invent things. Do we develop them? Yeah, we develop them, but how far can I do it or would another do it better, cheaper? And if that's the case, and we will explore those alternatives with BD partners, then we would do that. The idea was, give me a drug that has Orforglipron-like efficacy, but better tolerability, better safety.
When Steve says it's not as potent, well, it's not as potent per unit, but we give you enough units to be potent enough, right? So it's an adjustment to the space because Orforglipron is the leader. We have experience at Pharmacyclics. People were right on our tail with a BTK inhibitor that was more specific. And this is kind of what we're doing here. We're trying to give better drugs to people. And if Big Pharma does it, Big Pharma is really good at development. So I would not try to compete with them necessarily.
Excellent. Unfortunately, we're out of time, but gentlemen, this has been extremely interesting. Looking forward to following the story more. And thank you so much for being with us.
Thanks for the invitation.
Thank you.