Olema Pharmaceuticals, Inc. (OLMA) Earnings Call Transcript & Summary

Here for the afternoon session on day 2 of Citi's Back-to-school Biotech Summit. I'm Yigal Nochomovitz, senior biotech analyst at Citi. Our next company for the afternoon session is Olema Oncology. I have with me, of course, Sean Bohen, who is the President and CEO of the company. So we have a lot to discuss a lot of developments in breast cancer over the last year or so.

So maybe, Sean, maybe just give us the -- set the stage in terms of what's in the pipeline and what are the key readouts coming up. There are several things.

Yes. Thank you, Yigal. Thanks to both of you for attending. The -- so obviously, our lead asset is palazestrant. It's a complete estrogen receptor antagonist for the treatment of ER-positive HER2-negative breast cancer. And we're studying it in Phase III in 2 contexts. One is as a monotherapy in the second, third-line settings. These are patients who progressed on a prior CDK4/6 plus an AI, now going on to another therapy. And so the control arm is fulvestrant or exemestane. Experimental arm is single-agent palazestrant. And that trial is -- it's finished enrollment and randomization. It is -- we're awaiting readout, and we forecast that we will have our top line data in Q1. And that -- in that population, as you know, it's very interesting because it's really 2 separate groups. There are those individuals who progressed on their prior therapy with an ESR1 activating mutation. It's about 40% to 50%. The remainder still have estrogen receptor in the wild-type form and is not mutated. And there's been prior success in the mutant population, but no one's been able to do better than fulvestrant or exemestane in the wild type. So we're testing both of those populations, both of those hypotheses in the trial. In total, it's about a $5 billion a year market opportunity. So for us, very significant. The other trial that's ongoing and enrolling very well is in the first-line setting. And in that case, we are combining with the gold standard CDK4/6 inhibitor, which is KISQALI. And that trial is called OPERA-02. So the control arm is KISQALI plus letrozole, an AI. Experimental arm is KISQALI plus palazestrant. That will take -- it's enrolling very well. It will take a couple of years to read out just because of the effectiveness of that treatment. But that's a $10 billion-plus market opportunity should we be able to access it. Both of those trials are based on Phase II data that suggests that we can do better than the existing therapies and have activity in these different settings we're describing.

Okay. So let's start with -- let's go in order, I guess, and start with OPERA-01. So I guess the first question is, so there was a bit of a -- originally, the data was the second half of the year and now it's 1Q '27. This is like the age-old question of some of these event-driven trials, the significance of moving the endpoint or moving the data out a little bit. Anything you want to say there? Or is it just...

Yes. I mean I wouldn't overinterpret it. First of all, the trial obviously is -- it's not a blinded trial, right? It's an open-label trial, but the reading of the endpoint is blinded. It's a blinded independent radiographic review. Progression-free survival is the primary endpoint of both OPERA-01 and OPERA-02 trials. Yes, I mean, we do blinded event rate. And so that's in there to some extent. Mostly, the slight delay had to do with a slowing toward the end of enrollment in the enrollment of the ESR1 mutated subset of patients. And we think -- we're not 100% sure. We think from our investigators that, that might have been related to greater availability of ORSERDU in Europe. Again, it's past us. We are completely enrolled in the trial. We did not compromise the number of patients in either population. So it's fully powered for the statistical plan. And I think the other important part about this is that we -- overall, we had predicted 40% to 50% of patients would be ESR1 mutated. We actually did end up in our predicted range. So I think that part isn't different. It's just that we were in the higher percentage earlier on and it sort of fell a little bit toward the end.

Okay. So well, you mentioned, of course, the 2 populations, the mutant and the wild type. So the mutant, obviously, is the lower bar. But more specifically on the wild type, what -- tell us more about what gives you a confident view that palazestrant can show a difference there versus standard of care? What is the -- what evidence do you have previously that would support that? Because you pointed out that together, I think it's $5 billion, although even with just the mutant, it's probably like $2 billion or something.

Something in that range, yes. Yes. So I'll go into what molecularly we think might be going on, but I think the strongest evidence is our Phase II data, right? The question is, obviously, can you replicate that in the Phase III setting. So in the Phase II setting, post prior CDK4/6, in that case, a little more heavily pretreated patients because a significant number had had prior chemo, that's not allowed in OPERA-01. We saw over 7 months median PFS in the mutant setting, 5.5 in the wild-type setting. And that is better than anyone has been able to see in either of those settings, but certainly in the wild type. The bar in wild type is to extend PFS by about 2 months, right? Lilly got approved with imlunestrant at 1.7, but -- which is probably a little on the edge, but it did lead to approval, but you'd say about 2 months. And so recognizing that the control arm really should be 2 to 3 months, if we can replicate that 5-month range, we should be able to access that population, and that's what's being tested in OPERA-01. Why might that happen when others haven't been able to do that? Well, in addition to being a complete antagonist, we have very high exposure, 14-day half-life and a very high steady-state exposure compared to other drugs. And we think that, that is important in the context of maximizing the benefit you would get.

Okay. Let's also go through just the statistical. You mentioned the statistical plan because you have the 2 populations. So how does it -- remind everyone how it works in terms of the process of analyzing these 2 populations and how -- where you can win and how you -- in the order of which things are analyzed.

Yes. So we haven't disclosed in detail the statistical plan, but I can tell you basically the performance characteristics. And the performance characteristics are the trial can be positive in 1 of 3 ways, right? There's the obvious one, which is it shows a significant benefit over the control arm in both mutant and wild type. Mutant and wild-type subsets are tested separately. So the way the trial is designed, you can actually have 2 other types of positive trial. One is ESR1 mutant only, which shows the significant difference, wild-type does not. You then get a positive trial in that mutant subset. Not trying to explain why there would be a biological rationale, but from a statistical standpoint, you can do the opposite as well.

Although, it would be unlikely.

It doesn't make a whole lot. Yes. If that happened, I would -- we'd all be wringing our hands and wondering what went on. But we could statistically have ESR1 wild-type be positive, ESR1 mutant not be positive and still end up with a positive trial.

Right. Okay. All right. So that makes sense. And then as far as the commercial opportunity, you kind of alluded to it a little bit in terms of the numbers up to $5 billion. Yes. Anything further to add on that in terms of how that works geographically? Is that U.S.? Is that global? What are we talking about there?

Yes, it would be global in that situation. Usually, if you look at markets in oncology, the U.S. -- in revenue terms, not patient number terms, it's usually about 2/3, 70%. So it is the majority United States. Two ways really to differentiate in this space. One is to do better than the 2 months prolongation of PFS in the mutant setting. And again, we saw 7. So instead of 2 to 4 -- 2 to 3 to 4 to 5, we could see 7. That would be significant. The other is to get a benefit in the wild type, which is at this point is unmet, right? So there's nothing that's been successful in that subset. And it's probably, as you said, you kind of alluded, it's probably split up around $2 billion and change per year in the mutant, $3 billion.

Yes. But ORSERDU got -- I mean, they worked in mutant with like 3.9 versus...

3.8 versus 1.9.

Yes, 3.8 versus 1.9. So they worked if the 2-month delta, meaning that's a good argument for potentially while you could work -- I mean, it's a different setting, but in wild type, if you saw 2 months, you would be working.

You would be -- yes, you would -- I think that's the basis for approval, would be the basis for use. So that's the question. Can we replicate this Phase II data? And can we show that delta? Obviously, the market dynamics are very different in these 2 places because wild type, there's no endocrine agent competition really, whereas there are sort of 2 molecules certainly launched, maybe 3 coming in the mutant subset.

Yes. Yes. And then I think earlier you mentioned the Phase II data as anchoring your conviction. But I think in that data, I believe the -- some of the patient characteristics were less favorable than in OPERA-01, right? So can you speak to that because that's sort of like a headwind on your 5.5 number. So how does that figure into your math?

Right. We think it is. The most -- the biggest difference in that respect was that in the Phase II experience, we allowed prior chemotherapy. And we know from a variety -- it's been known for a while, but I think the EMERALD data's retrospective analysis really showed that, that's a pretty strong negative prognostic. So we eliminated that from OPERA-01. You couldn't have prior chemotherapy in the metastatic setting. And the other thing that we did is we said, "Look, if you -- whatever your prior endocrine regimen was before going on this trial, you had to be able to be on it for at least 6 months without progression." And that's an effort to avoid primary endocrine resistance. This isn't -- these aren't strong selectors, but they do seem to have some power. So the 5.5 was achieved in that, and obviously, in the Phase II, we didn't make that criteria. So 5.5 was achieved with the chemo, with the enrollment of patients who progressed relatively quickly. And then in OPERA-01, we don't do it. So the hope is that those truly refractory patients, we kind of somewhat select against their enrollment.

Okay. All right. So then data, as you said, 1Q '27, unless there's a further change, but that sounds like where it's headed.

I think that's where we're going to be.

Okay. Where are you with regard to thinking about the commercial build-out? Is this is a tractable market, the second and third-line setting that you would be running the launch yourself? Is that right? Or...

In the United States, yes. So a couple of things, right? What is our -- I'll do our strategy, and then I'll do the commercial. I'm going to reverse your questions a little bit. Our plan is to launch this initial indication, second, third-line monotherapy in the United States, promote it ourselves. And that is a doable. That's probably less than 100 field sales that is needed to do that effectively. We do not -- we are enabled to file outside the United States, so to progress the regulatory packages. But we do not plan to launch and promote. So we will have to seek a collaborator. Obviously, we're 6 months maybe and change from the data. So our assumption is that a collaborator will want to see the data before they enter an agreement. So that's kind of where we are with that part of the strategy. With regard to that U.S. launch, we've already started the commercial build. We've hired people. We've done market research on it. We have a full plan to ramp up. Some of it will continue ahead of the data. Obviously, the data being supportive of launch, there will be an inflection point, and we'll ramp it up quite quickly at that point, probably early next year, right?

Okay. One other question I forgot to ask, but maybe you haven't disclosed this yet. You're counting the PFS events. Is it across both mutant and wild type? Or do you need a certain number of PFS events in mutant and a certain number in wild type? Or how does that work?

Yes, it's interesting. So the way the trial is designed, if you look at the trial from like the standpoint of execution or a patient coming into it, it's one trial. We have one inclusion/exclusion criteria. There's one randomization. It's the same. You're stratified, right? So you get tested, you're stratified, so you make sure it's even between the arms. When you go to the analysis plan, it really kind of looks like 2 trials, actually. It looks like an ESR1 mutant and ESR1 wild type. So there are actually statistical design that are different between the 2. So what happens is you have to achieve a certain number of events in each of the populations. The thing is there's one unblinding. There's one closing of the database. There's one unblinding.

So it's not like...

Whichever one comes later will be the one that triggers that unblinding. So it's not like you can read them out separately.

Right. Even if one meets the threshold on the events.

We just wait. It will probably have more. We'll get a little -- there'll be a little more power in that particular population than we had planned in the statistical design, but that's fine.

Okay. Cool. All right. So that's second, third line. Then you mentioned frontline and OPERA-02. And there's a lot of interesting things that have happened with persevERA, and we have the SERENA-4 obviously coming up soon. Well, tell -- first of all, we learned a lot of things a little bit from persevERA. You learned something about the control arm performance, which maybe helped you in thinking about your frontline trial. Is there an opportunity to revamp the powering now that you have a cleaner sense of the control, the modern control arm performance? Maybe just speak to that first.

Sure. Right. So just to set the context here, one of the things that happens in oncology fairly broadly, not necessarily specific to this, but seems to be applying to this is that a given regimen often performs better over time. And what that probably is it's probably learning curve from the oncologists. They are very good at learning how to manage, particularly the AEs, maintain dose intensity. And so you will see in many different tumor types that the initial approval of a given regimen has a certain PFS benefit. And then as you look at what happens over time as more trials are done with that, it improves. And we suspect that, that might be the case here because what we're using for the design of OPERA-02, which is a 1,000-patient trial now, 500 per arm. It's a 1:1 randomization. And again, that's with KISQALI. Letrozole is the control arm. Palazestrant is the treatment arm. We had always suspected that the control arm might outperform the 24, 25 months that was historical. And persevERA suggests that, that is the case. In the overall population, the median PFS in the control arm, which this again is -- that's not KISQALI, it's IBRANCE. But for PFS, they were similar. It's 28 months. So that's 3 months longer. But actually, remember, they made a mistake. They enrolled endocrine-resistant patients, patients who had progressed within 1 year of completing adjuvant. Those patients did very poorly. So if you exclude those patients, it's actually 33 months. So it's almost 5 months longer than I'm sorry -- 31 months. So it's almost 5 months longer than the historical. And so we may have to revise our statistical assumptions. What can you do about that? So what it does is, obviously, you're doing a hazard rate. The way you design a trial is you have, "Hey, what's my control arm going to do? How much delta do I need to show to be clinically significant?" And you calculate out a hazard ratio and you decide how many events you need and then how many patients you need at risk and what will the timing be? So the only variable we really can control right now is patients, number of patients. And so we may increase the size of the trial. Now what would be great, persevERA is informative. It tells us 2 things. One, maybe the control arm is doing better than it did historically, not a big surprise. It's not a ridiculous amount, but it is significant. Two, don't enroll the endocrine-resistant patients.

And you're not.

We don't. Nobody does. SERENA-4 doesn't either, and AstraZeneca rightly has made this significant point about one of the differences in their trial. OPERA-02 never enrolled them.