Good, everyone. I hope everyone's been hanging in there as I have been. I just looked at my calendar. I've had a breakfast, 15 fireside chats, and I just got one more company dinner today, and then I'm done. Get some sleep.
No lunch.
Yeah. But last but not least, I get the chance to hang out with the Terns management team, Amy and Emil. Thanks so much for joining us. Amy, why don't I hand it over to you for some brief introductory remarks, and then we'll get started.
Sure. Well, we're excited to be here. It's been a great 2024. As you know, I took on the CEO role in February. We read out data on TERN- 601 in September showing that we have a, you know, competitive small molecule GLP-1 agonist. And we just announced at earnings that we are going to be sharing data in early December, for TERN- 701, our BCR-ABL and CML. So, yeah, so we're quite excited.
Understood. You know, why don't we start actually with 601 and, you know, I think, since your data's come out, we've had more data from the space. Obviously, Obesity Week, we had the early cut on the Eccogene data. We had the Roche data, as well, I believe at EASD. Some of those, you know, data sets maybe weren't as well received as yours was initially. Of course, market caps are relative here. But, you know, let's start just more holistically. How much should we be really reading into these 28-day studies, right?
Yeah.
'Cause, you know, you've even heard Lilly talk about it. They're like, "Look, you can get pretty much whatever efficacy you want, in these trials." When you look at your data set and you compare it from what we saw with Eccogene, what we've seen with orforglipron, what we've seen across the space, why are you confident that you have a competitive profile here? And what do you think is most misunderstood about the 601 data set that's come out?
Yeah, so, first of all, I do think it can be difficult to compare numbers necessarily across the studies. They're all a little bit different. They're small sample size, so we actually look at our 601 data set holistically.
Right.
In terms of, you know, what do we see? We see that we tested what we think is the appropriate dose range. We see that we got competitive weight loss. We were not optimizing for tolerability. I think one of the things to answer your last question that people miss is that a lot of different companies talk about fast titration. We titrated every three days, which I don't think anybody titrated that fast, and we really were optimizing what we could learn versus trying to present everyone with an ideal 28-day data set that would demonstrate competitive differentiation. What we saw is we think, you know, competitive weight loss, we see that we have a GLP-1; it's acting like a GLP-1 should. We also see that we were able to titrate quickly and still get, you know, no dose interruptions or treatment-related discontinuations.
So we saw what we see as an excellent tolerability profile. Some of the GIAEs we expected to see. But we also expect when you look at our low-dose group that as we slow down the titration, that we could see a much better tolerability profile. And we also see that our molecule is very differentiated versus others. It really doesn't look like any of the others out there. In terms of, you know, we really see the high dose as a feature, and something we think that will translate to a competitive profile that not only produces good weight loss but also good tolerability because of our unique properties that we've talked about.
Understood. And maybe to that point, you know, your molecule is, you know, seemingly you're trying to decouple plasma PK with gut PK.
Mm-hmm.
You know, if you put your money where your mouth is, it seems like you wouldn't have to go with, you know, the 750 dose, you know, a very high dose. You know, when I talk to investors, I wouldn't be surprised if your go-forward dose ends up being kind of in that 300-500 mg range. Is that the right way to kind of think about this? What are you guys expecting about your go-forward dose?
No, I think the unique properties that Amy alluded to is what I think is one of the key differentiators. But I would argue just to take it to the question you asked earlier, I think the main differentiator, even in the 28-day data set, despite similarity of these data sets on the weight loss front, I mean, we achieved what every other molecule does on the low end and the high end, close to 6%, 5.5% weight loss at 28 days. But I would argue that our 28-day study has the best tolerability profile of any 28 days, not based on the incidence of the GIAEs, but no study has titrated this fast and gotten to a profile of zero interruptions, reductions, or discontinuations with more than 95% of AEs being mild.
I think that's a key thing that people miss is that the titration speed was on purpose 'cause the purpose of the 28 days is to see what your bracket dose range is.
Right.
Where you get to the range of efficacy that you'd expect in 28 days, which we hit, but also where you get to the point where you, you know, I think the limit of the dose in this indication is defined as making sure all your AEs are well below moderate and making sure that in a 28-day setting, people don't interrupt or discontinue or dose reduce. And the fact that the dose is in the 750 or 500, to your point around the PK, I think, you know, the hypothesis around the relative role of the gut versus the plasma was more of a reverse engineering because, again, our goal was to get sufficient plasma exposures to get 24-hour coverage over target. And I think we saw that happening in a unique way compared to other drugs where they were just trying to solve half-life.
You know, we were able to show 24-hour coverage over the EC50 despite a half-life of four to six hours. And we saw that that was because the absorption phase was prolonging as we went higher and higher in dose. And so that's where we started thinking, well, when you look at the total plasma exposures at even the 500 and 750 doses and compare across the board to drugs like danuglipron, we're on the lower end of total. And then when you factor in the fact that we're more protein-bound than several of the other drugs, when you look at a free drug-to-free drug comparison, you know, we're achieving the same weight loss or better as the other drugs with lower plasma levels. So why is that?
When we looked into the biology and we looked into the pharmacology of the molecule, we did see preclinically that the gut concentrations, free drug concentrations, are higher, and mechanistically, we think that's because the prolonged absorption leads to the solubilization of this compound throughout the length of the GI tract, but it's also highly gut-permeable.
Right.
So when it dissolves, when, as it's being absorbed, you're getting these local high gut concentrations that are, we know, activating GLP-1 receptors there, which are in the epithelial cells but also in the vagal nerve terminals, that we know endogenous GLP works that way. They activate vagal afferents, which goes to your brainstem, says you're full, and you stop eating. Endogenous GLP-1 has a half-life of less than 30 seconds. So endogenous GLP-1 is not an endocrine mechanism that tells you the satiety. So that's sort of the reverse engineering hypothesis that we came to based on what we know about the properties of the molecule's distribution. Is there a direct way to measure GI PK? Probably not, especially in people.
But I think the argument around why we're seeing competitive weight loss with the tolerability profile we're seeing given the low free fraction is, you know, there's another mechanism outside of the plasma that's probably playing a role there. And we have some preclinical data to support that, and we plan to generate more.
Understood.
Akash, going back to your question about the dose.
Right.
In terms of the dose range, you know, we've done quite a bit of work with KOLs. And, you know, we agree we are testing sort of a full dose range from 250 to 750 in this next trial. We'll talk more specifics early next year about the trial design. But we could end up at a dose in more of the 250 to 500 range for sure.
Understood. Kind of an esoteric point, but, you know, one of the things if I do think orforglipron probably has a best-in-class profile right now. I think that's not necessarily a hot take. You have 44-hour half-life at the 36-mg dose. But I think what we've seen, with Structure, Eccogene, you're seeing this with the Roche compound, is some of these drugs that maybe have less than ideal plasma PK are actually taking higher doses later on. And I think when you look at orforglipron, a potential weakness, at least my team and I think about, is that the bioavailability starts to flatten out between the 36- and 45-mg dose, right? Like, the exposure's effectively the same at those doses.
I feel like what some of the fast followers in the GLP-1 space are doing is they are basically starting at a lower dose, but they think that they have more dose response as they continue to titrate up, unlike what we've seen with orforglipron. So, Ergo, you might have initially worse efficacy, but as you continue to titrate, you might be able to catch up over time. When you think about a compound like yours, which, you know, again, very high plasma protein binding and your gut permeability.
Yeah.
Is that potentially an angle that you could pursue as well where you actually have a more protracted dose titration?
Yeah.
In your phase II design?
Absolutely. I mean, protracted is relative to what you did in phase I, right?
Sure.
So, I mean, relative to what we did in phase I being every three days, even a weekly titration is protracted. But I think the key advantage that we have is that in the phase I, we didn't start the 28-day titration at the lowest dose in SAD. And we on purpose put an intermediate portion of the study to be able to start the titration at 28 days at a higher starting dose that we knew was pharmacodynamically active, which we had a measure for, which is, I mean, glycemic control, which is a very rapid, you know, measure that you can use, and tolerability. So I think that gave us a unique advantage in that now we have narrowed the entire dose range that we have to titrate through, and we know that we're starting at an active dose, at least in the pharmacodynamic side.
So what that does for phase II, therefore, even in a 12-week study, you know, if you had six dose levels to get through to get to your max dose, you'd have to speed up titration to at least weekly. Now that we only have four.
Right.
I think we can take our time, and that taking the time improves your tolerability even further. We know that from longer-term studies without sacrificing the amount of time you spend at the higher doses in each cohort. And so I think that's a unique advantage for us in terms of still maintaining that slope of weight loss, you know, pretty linearly as you get to 12 weeks and 24 weeks, but having the luxury of even slowing the titration more than others have been able to do because of the narrower dose range that we were able to identify.
Where do you think titration ultimately heads at? I wouldn't be surprised if orforglipron for their phase III ends up being monthly titration. They showed kind of one and two-week titration in their New England Journal of Medicine paper. For a compound like yours, what's the appropriate titration kind of schedule?
We've gotten a lot of feedback from KOLs as well as, you know, clinicians within both the specialty and the GP world that monthly titrations would be very attractive, that you know, from a just a simple prescribing standpoint, it's very easy for them to write a 30-day prescription, especially if you have, you know, the other thing we've heard is simpler titration is also attractive. Where you don't have to go through five or six steps to get to target. You can go through three or four or two to three. And I think we're probably arguably the best position to get there given, again, we only did four steps. You know, we could do a four-step going into two, and we could even narrow it down to a three-step or two-step if our target dose is 500.
And then a monthly titration could be a goal that we could pursue. But again, I think knowing where we are after phase I, I think we're much better positioned to get there without having to do a lot of interrogation in the phase II setting.
What's the bar? And, you know, when I think about orforglipron and the data that they showed, I think you can project it out to 52 weeks. I wouldn't have been surprised if that 36- and 45-mg dose would have shown maybe 16%-18% weight loss. But again, you have vomiting that's 25%. You're gonna have to slow that down, get it more to like a Wegovy 10% range to be really commercially viable.
Yeah.
First of all, I'm curious if you would agree with that assertion, 10% vomiting is what you really need to hit. But then number two, when we go to your drug, would you agree that with slower titration and the dose range you're looking at, you're aiming for not, you know, high single-digit, low double-digit weight loss? You're also aiming for, let's say, 13%-15% weight loss, which is probably where orforglipron's gonna.
Yeah.
End up being with monthly titration?
No, absolutely. And I think the pretest probability of that, based on what we've seen, I mean, you've seen that the drugs that have identified the dose range that gives you approximately that 3%-5% to 6% in the 28 days, provided you can maintain that same dose range with the tolerability profile that somewhat approaches what you just described, going out to a 52-week with, again, the probability there being high, knowing the tolerability profile we saw with the three-day titration. And so I think that would be the target. We wouldn't aim any less, you know, in terms of the target weight loss at a 52-week point.
Understood. Then on vomiting, just say absolute vomiting. Some people say there's grades of vomiting. I feel like if you're vomiting, you're vomiting. What's the range that you think would be, you know, clinically what you're targeting in a phase III profile?
You know, I think when you get to a phase III, 52-week, yeah, the lower, the better for sure. But I also think it's more complicated than just putting it on one number because, again.
Sure.
You know, there's different patient segments we're talking about here, though. So there's like, you know, the overweight to sort of the moderate obesity category and that BMI of less than 33. You know, these patients don't need to lose a ton of weight over, you know, X period of time. And so for those patients, more of a slower approach, you know, weight maintenance approach where you can do sort of slower titration to a slower target could give you zero vomiting. We saw that in our 250-milligram dose, no vomiting, no nausea.
And so if you just imagine that being translated out to a longer-term time point where, for example, if your goal is, you know, you're in the mid-30 to 30-35 BMI range and you don't need to get to that 20% weight loss over 52 weeks, you can imagine a slow titration to 500 where you get zero nausea, vomiting. That would be our goal. With the 750, I think it's possible to get there at the higher doses. Again, it's, there's a good amount that's dependent on the titration speed. And so, you know, in the context of a 52-week study, if we only have two or three steps or maximum four steps to get to your target dose, that's a lot of time that you can play with, with the slow titration schedule that gets you under that 10% number you just described.
So again, going into the longer-term studies, I think we're in a good position.
So it sounds like you don't think about 10% vomiting as some type of unachievable.
No, absolutely not.
Understood. GIPR antagonists. You guys have them. Pfizer just announced theirs, and they it's almost bizarre. They described, you know, they said it's a muscle-preserving target that everyone knows, and I didn't expect it to be a GIPR antagonist. But I think the question a lot of people have is, A, the data that we've seen from Lilly so far, it doesn't necessarily seem like GIPR has a meaningful improvement on efficacy beyond that kind of like 3.5%, 3% placebo-adjusted delta that you see. It doesn't continue to deepen, right? You see that initial benefit is probably on food intake, but it doesn't continue to deepen. So and then number two.
You said from Lilly. Do you mean?
From Lilly. Lilly's release long-acting GIP agonist data.
Oh, agonist, sorry.
Not antagonist, and then two, there's you know data at ADA. There is data where I think it's kind of emerging that GIP antagonism and agonism are actually not two sides of the same coin. GIP antagonism is actually more like GLP agonism, but you may not actually get the antiemetic effect. You know, but that was also a scientist that had done a lot of work with Lilly, so I wouldn't be shocked if they said that. What's the Terns in-house opinion, right? So why go GIP antagonist? Number two, do you think you're gonna have an antiemetic effect? And then number three, do you think we should think about this as a standalone mechanism of action, or is it more about co-formulation with semaglutide?
You want to go first one?
Right.
Okay. So I think, you know, the Terns philosophy has always been, can we improve on validated, clinically validated mechanisms of action, right? And I think the biology risk and the clinical risk we've designed by design to be on the low end, which largely explains our portfolio. And, you know, knowing that we have a very strong discovery engine in-house on the metabolic side that's produced a lot of good compounds, you know, the team, and biology expertise as well, you know, we were looking at both agonism and antagonism, and we geared towards agonism and antagonism because I think, again, from a biology standpoint, it's much simpler, right? Like you shut the switch off versus agonism, it's like, how much do you turn the switch on? Is it, you know, 30%, 50%, 90%? There's.
Right.
There's that question, and, and there's that variability in that piece. And so antagonism is generally much easier. It's more binary to measure. And then, you know, in terms of the validation piece, we've seen our own preclinical data. I mean, we haven't disclosed it, but we've obviously done the work on the biology side to validate that antagonism meaningfully adds to a GLP-1. And we've seen that from other companies as well in terms of the.
Right.
Preclinical data showing that actually can cause, you know, meaningful weight loss and potentially even a synergistic effect. And so that's our philosophy that you know antagonism is clearly effective on the weight loss front. With regard to the antiemetic properties, I think the data are too immature to say. I think it is probably true that GIPR agonism does potentially have this antiemetic effect. I think we're seeing that kind of play out as we get more clinical data on the mechanism. But that biologically, I don't think that necessarily means the corollary is true that therefore antagonism should be pro-emetogenic. I don't think that's the way the biology necessarily works.
You know, I think we just need to see more data on that front as we go into, you know, data sets coming from Amgen and others who are pursuing the antagonist approach, and so I do think that, you know, from a validation standpoint, preclinically, it's certainly validated on the weight loss front. I think we'll need more data on the clinical side on the safety tolerability, but I think we remain optimistic about what the antagonist can show.
Understood. Actually, just maybe lastly on this, I feel like, you know, I wouldn't be surprised with amylin combos that you actually need a very low dose of amylin when you combine it onto GIP/GLP. And I feel like where we're headed in the space is you really wanna lower the amount of GLP-1.
Yeah.
That you're dosing here. So I feel like maybe I'm mistakenly thinking, okay, you're gonna take that 500-mg dose and then add it to your GIPR, and you're gonna get tolerability issues. How do you think about the benefits of just changing the, whether it's energy expenditure tolerability?
Yeah.
Can you get a meaningfully lower dose of GLP when you're adding a GIPR antagonist? And is that the right way to think about this?
Yes. Absolutely. I think we would think about it the same way, and I think.
What would be the benefit of lowering your dose of GIP, of GLP and then having GIP maybe make up the difference on efficacy?
I could think of two right off the bat. Your GI profile, your tolerability profile drastically improves. Especially if the GIPR piece doesn't add anything to that. And two, you don't have to deal with these complex titrations on the GLP.
Interesting. Okay. On 701, and you know, I will openly admit a lot of times when companies do these events, I will fall asleep within 30 minutes, but I actually listened to that event. I thought it was really, really well done.
Oh, good.
I thought you did a great job. No, but I think it's really important to put, I think we've all forgotten how to look at CML data 'cause, you know, Ariad got taken out a while ago. We don't understand the nuance of, you know, MMR benefit, you know, where you are in terms of log reduction depending on.
Yeah.
What types of TKIs you're on. Here, I'll ask a blunt question. When I look at what you did with 601, I think what I was impressed with was, A, you had a different angle, but then B, you did a great job sandbagging expectations, right? Are you sandbagging expectations with CML, or are you really just warning us that, like, look, it's three months, six months' worth of data.
Yeah.
We're not gonna be able to have a real clinical response? Like, how should we think about why you hosted that event and really what why you're framing expectations as conservatively as you are?
So Akash, I think that, you know, we're not the only company now talking about CML.
Sure.
And I think we did that event in August to really share our perspective on an early CML data set and how it should be interpreted. And we purposely did it in August and not now or not in concert with the data to sort of set that expectation and, you know, frankly, it with a study like this, not to you know sort of decide how it should be interpreted after we've seen the data. So, you know, I wouldn't say that we're sandbagging. I would say that we're really appropriately laying out what you can expect with something this early.
Yeah. I mean, I would just add that, you know, the purpose of that was to say that when you're in the middle of a dose escalation study in anything in oncology, you can't make definitive conclusions on our response rate is X compared to.
Right.
Another drug that's been through a phase III study. That's just you can't do that. Right? But what you can do is say on the, on the axes that you can compare apples to apples, you know, for example, safety is DLTs, right? What are the DLTs that you see? That's one axis. On the efficacy front, it depends on what tumor type you're talking about. And CML being a chronic disease where historically the benchmarks have always been what is your response rate, whether that be CCyR or MMR, that's the sort of two standard benchmarks that have always been used historically. The minimum time to that risk, that landmark endpoint is six months and then 12 months, right? And so when you look at what are the historical benchmarks that you have available to do a side-by-side, there's not three-month data there, right?
Does that mean that if I were to show an interim dose escalation or interim phase I data set with a median duration that's small and a total end that's also small, can I say nothing about efficacy? Absolutely not. What you wanna say is what are the clear signs and evidence that this drug is clearly active in some of the hardest-to-treat patients, which are the ones you get? That was the intent of that, right? But, you know, what you can say is in the totality of data, looking at it aggregate, the trends that you see in efficacy and the trends that you see in safety can signal you to whether this drug has potential to be the best in class. And we, you know, we think that we're potentially there.
All right. I'm gonna push back.
All right. Push back.
and in a bullish way.
Yeah.
A lesson from your GLP-1, you had, you know, healthy volunteer study. You understood what the exposure was. And so.
Yeah.
When you took your dose, like, I think if you told the street your starting dose was 240 mg, everyone would've freaked out.
Yeah.
But you took a much higher starting dose.
Yeah.
In terms of your dose titration. I'm still trying to find the Hansoh protocol. We are gonna find that eventually. But my suspicion is you have data from China and Hansoh that you've been able to see under CDA that shows you exactly what your target exposures are. And you've explicitly said on transcripts, we've been able to take a higher starting dose.
Yeah.
Put that into clinical trials. When I look at Scemblix's data, and especially in a late, more refractory line setting, I do see evidence of patients who are on second-gen TKIs that within three months, they actually are getting into MMR responses.
Yeah.
When normally you wouldn't see that.
Yeah.
Why should I walk me down that hill?
Yeah.
You know, why isn't that the right way to think about this? And any color, let's put it this way. Can you give us color on your target, your starting dose in your dose escalation?
Yeah.
What is that IC90 coverage that you're starting with and you're then getting to in your dose escalation?
There are two questions there. There is the dose question, and then there is sort of the why cannot you see MMR within three months? I will get the first one. The first one is that, you know, you want the traditional sort of target efficacious concentration that has been applied for asciminib and several others is the IC90 value in a native BCR-ABL cell line, such as KCL-22. That is exactly what Novartis used. They can use either the in vitro IC90 or an in vivo, you know, pharmacodynamic marker like phospho-CRKL. The reason people do that is sort of that is sort of a native BCR-ABL line where you can kind of say, okay, if you are above that for, you know, your full dosing interval, the argument is that you are achieving pharmacodynamically active exposures throughout.
Right.
So, you know, the reason that we picked the 160 milligram dose and, you know, the Hansoh design, they started at much lower. They started at 40. And so were we even, were we just looking at when the IC90 hit that line for whatever dose? No. The key advantage or the most important property of allosterics is their therapeutic index, right?
Mm-hmm.
Now, here's a mechanism that's, you could say, hyper-selective to the fusion protein because of the uniqueness of that myristoyl-binding pocket to the fusion protein. So if you have a molecule with a really wide therapeutic index, the argument is, you know, the safety should be maintained throughout the dosing interval. And the more coverage over that threshold you get, it doesn't have to be one-to-one.
Yeah.
It could be two-to-one or three-to-one. Pick that dose because that will address the maximum heterogeneity in the clinic that you're gonna get, especially in the relapse refractory setting, and that's why we picked 160 because is 160 the dose at which the line hits? No, it's well above that because, again, the safety would allow it.
It's meaningfully higher than Scemblix's, I would say.
We think that that's the goal.
Yeah.
Yeah. We think that the goal here is to get to a dose where your effective target coverage over that line, but also the other if you were to draw a data line for K562, which is a less sensitive line, or if you were to draw a line for T315I or several other mutations, we want that average exposure or trough exposure to be as high as we can because the safety of this mechanism allows you to do that. So that brings me to the next question. Can you see MMR at three months? You absolutely can. It depends on where the patient started. So if you have a patient who's six or seven line post-3G TKI, post-2G TKI with a baseline transcript that's 80%, that patient's not gonna get to MMR by three months no matter what you throw at them.
They're gonna take, and we know that from asciminib.
Right.
On the other hand, if you have a patient who is 0.121 and just lost MMR, that patient can get to DMR within three months if you want.
Wouldn't that be fair to say that was a lot of the Enliven patients?
I can't comment on that, but I think, you know, yeah, the starting point matters. Yeah.
Yeah.
I mean, you want so ideally, if you see meaningful shifts at the early time point, I think the most informative data is look at those high patients. If you're seeing, you know, 0.3, 0.5 logs or even more than one log reductions in those north of 10% patients, that's very informative that your drug is clearly active and that you're gonna hit that MMR or exceed that MMR target at six months. And so, you know, I think we would be very impressive if you can take one of those 10% or higher patients and get them to MMR in three months. I think that's a clear indication that the drug is differentiated.
Right.
I think this goes back to your first question.
Yeah.
Right? About, like, the expectations we set. It's really about looking at it on a patient-by-patient basis on a small set versus comparing across and saying this is an X% response rate. It's really like taking individual patients, seeing where transcripts are going, and seeing what kind of impact the drug has.
It almost seems, and I know, I know we're out of time, but I feel like this is the last one, so I'm gonna do it. It almost seems like you're saying it's the baseline, and then there's a net reduction that you're able to get. And whatever that baseline is, is really what's gonna determine whether you get into MMR or not.
The baseline is a key component. The other component is what types of therapies have they seen? Do they have a resistance mutation? There's at least three axes on which you can predict and probableize what is the chance that I'm seeing this patient in front of me getting to an MMR or a CCyR in X amount of time. And so that's what we're trying to convey is that clinicians have a lot, a higher threshold or to keep a patient on therapy if they're in that very difficult-to-treat category and they're seeing downtrending BCR-ABL, that's a great sign in a patient like that. Whereas if I have a patient who's 0.1%-1% coming in and they're mostly intolerant to their prior therapies, yeah, I wanna get them to MMR and better. In three or six months.
So that's sort of the flavor you gotta apply before you just say, okay, my MMR rate is X at three months with, I don't know, 15-20 patients with.
Yeah.
Less than three months at the follow-up.
Got me all bowled out. The end. Thanks so much, everyone, for joining us and Terns. Thanks so much to the Terns team.