Good afternoon, everyone. Welcome to the 43rd Annual JP Morgan Healthcare Conference. My name is Grace Cho, and I'm an associate on the JP Morgan Healthcare Investment Banking team. Our next presenting company is Arcus Biosciences. And speaking on behalf of the company, we're pleased to have Dr. Terry Rosen.
Thank you very much, so I'd also like to thank you. This is actually the first time we've ever presented at JP Morgan, so we're thrilled to be here, and we appreciate you and anyone else who's listening in, and I'll just jump right in. I'm going to start just elevating a bit and talking about where Arcus stands. I know oftentimes they say you should suggest three things that people should keep in mind. Since JP Morgan, and we think maybe it's a little smarter audience, we're going to go for four and figure we could do 33% better, so I'm going to start with the first two, what we would say are near-term value drivers. And one of those is casdatifan, which is a best-in-class HIF-2α inhibitor. And the second is domvanalimab, our Fc-silent anti-TIGIT, which we're combining with our anti-PD-1 zimberelimab.
That's in three late-phase III studies, and we're going to talk about all of these later. The final two points I would emphasize that I think are somewhat differentiated from a lot of biotech companies is that we have a very strong R&D engine. So, we have substantial resources devoted to the internal discovery. In fact, that expertise is primarily in the area of small molecules, and we're focused on oncology and I&I. And finally, another differentiating factor is that we're well-capitalized with over $1 billion in cash. And everything we're going to talk about today, all of those plans were funded into 2027. So, building on that a bit, we've had pretty incredible partnerships on all respects. And one thing I would emphasize just on the various things that those partnerships bring, to date, our partner-related funding that's flowed into Arcus is over $2 billion.
I think a lot of companies, when they do a collaboration, they struggle to come up with $2 billion in bio bucks, but we actually have a steady stream of fuel supporting our programs. That's why we can have a deep, broad portfolio and, like, what are pretty competitive, some of the biggest markets in oncology, and do it in a very efficient way. Beyond that capital, these are great partnerships. We get a lot of execution. Human resources, for example, both Gilead and AstraZeneca are executing two of our phase III trials. This slide is a bit of a 2024 accomplishments, and I'm not going to say much about any of these individually here because we're going to get into a little depth of data on every one of them. In 2024, we actually had five presentations at medical conferences on four different molecules.
So, what I would also emphasize about those presentations is the data we generated certainly contributed to proof of concept, but all of these programs, I would sort of express that they were also graduating, that we were not getting to some nodal point with proof of concept and waiting for how are we going to advance these. But in parallel, they've been moving along into later phase studies. So, to just go through those really quickly, in October of last year, we presented data that we believe clearly illustrated that casdatifan, our HIF-2α inhibitor, has an improved profile relative to that of belzutifan, the only other HIF-2α inhibitor, which is Merck's. We presented two new data sets in the context of anti-TIGIT, one in lung ARC-10, one in upper GI cancers, EDGE-Gastric, that made three proof of concept studies in the last 18 months.
And then finally, at the bottom, ARC-9 and ARC-8 were two studies with our adenosine modulating molecules. Both of them showed unprecedented overall survival in one case in the context of colorectal cancer and the other pancreatic cancer. Great data. And in fact, for quemliclustat, we've just recently started and dosed our first patient in the phase III registrational study that's looking at quemliclustat CD73 inhibitor on top of gem-Abraxane versus gem-Abraxane. I think one of the important aspects about all of our programs as you think about them is that in all cases, what we're looking at is something that we've generated a good quantity of data that shows efficacy, but on top of a standard of care. And that's actually very important for a number of reasons. The first reason is we're not looking to displace the standard of care.
Second thing, from an execution standpoint, from if you want to think about value proposition to a physician or a patient, is basically you're bringing on something with a relatively benign safety profile. The patient's either going to get the standard of care or they're going to get standard of care with something that looks like it may bring them added benefit. This gets at a summary. I'm going to come back to this slide a few times that looks at these late-stage programs. I'm going to start off with casdatifan, our HIF2 inhibitor, and say a little bit more about that. These data are old news, but in a sense, they also foreshadow what's going to be coming this year because it's going to be a data-rich year. These represent data that we presented at the Triple Meeting in October.
There's a lot of data here, and so I'm going to walk you through some of the key highlights. What these data are looking at are two different cohorts, a 50-mg cohort once a day and a 50-mg twice a day, so 100-mg cohort in clear cell RCC patients. They're each 30-patient data sets. The left-hand side where you see the waterfall plot, a couple of important aspects that you should take away. First off, you can see how the geography of that waterfall, that such a vast majority of the patients are getting some benefit. They're getting tumor reduction.
I think the other thing that's important is if you see under those bars all the forward arrows, despite the fact that this had 11 months of maturity, all those patients were still on study, which gives you a sense of the durability effect. So, now let's go to the right-hand panel, which is even more complicated, but I think we can actually break it down in a fairly simplistic way. So, the first two columns actually get at what we're thinking about as we compare this data set to the historical data from belzutifan and belzutifan's registrational study, which is called LITESPARK- 005. So, the first column shows that in our cohorts, we actually are enrolling a more advanced patient population than that which was in the belzutifan study.
As a matter of fact, between 25% and 30% of our patients wouldn't have even been eligible for the belzutifan trial. The second column has the median follow-up time. We presented relatively immature data, 11 months for the one cohort and the 50 mg cohort once a day, eight months, versus 18 months median follow-up for belzutifan. The reason that's important is for this mechanism, it's been well established that the data continue to get better over time. With respect to our two cohorts that we've shared, you would expect that the eight-month median follow-up or the 50 mg once-a-day cohort has the most probability that the data will evolve with time. The next point I would just make is whether you look at ORR, the rate of primary progression, which is important because it affects everything else.
That's those patients that don't even make it to a first scan or durability, and in this case, measured by disease control rate, we're looking better than belzutifan on all fronts. Median PFS hadn't been reached. So, that gets me to what data will be coming. So, you can see that that primary PD rate is on the order of about half of what you were seeing with belzutifan. And that variable was something that was called out from clinicians when we first got involved in this program is really the Achilles heel of belzutifan. So, what you should recognize, first off, is that belzutifan was a transformational therapy. It's very safe. It's much better tolerated than TKI.
So, physicians love the mechanism, but the one limitation that emerged that affects all the other variables is basically you have almost a third of the patients progressing before they get to that first scan. So, obviously, those patients have no chance to get any benefit from the mechanism. So, as I mentioned, these foreshadow what's coming. So, let me say a little bit about, and I'll talk about when, but we're going to have updated data from this at ASCO GU. So, the titles were just announced. So, we're basically just a month away from a very fulsome data set. And in those data, what we're going to include, you'll have updated data from the two cohorts here. And most importantly for those, now we'll have median PFS. So, you'll get a clear measure comparing back to belzutifan's 5.6 months.
I think the more unanticipated data that we're going to have is that we've fully enrolled another cohort that's looking at the tablet formulation, 100 mg once a day of what our go-forward dose is going to be in our registrational trial that we're looking to get up and going as fast as we can by the middle of this year. So, in addition to these more mature data on these two cohorts, we're going to have the early ORR data set for that 100 mg dose. I think what's important is by the time you get out of that meeting, a lot of people that saw our data say, "Yeah, this looks better than belzutifan.
We want to see more." Not only are you going to see more durability, but you're basically going to have three independent cohorts, so three different experiments that on three different variables, durability, response rate, and primary progression, look better than belzutifan on all fronts. To me, this is the most important casdatifan data. And it hasn't been seen by everybody. There are data that on the left hand where you see the Merck data, Merck published these data in October, and we shared similar data. The reason these data are profoundly important is if you look at these when you think of it coming as a scientist. So, you've got these clinical data. And the question when you have clinical data is always, "Are you sure they're real?
How do you explain them?" And so, what to me always is most compelling is if you can associate some molecular property, some molecular feature that makes sense that explains those data. And you're never going to see two different data sets that more differentiate molecules. So, let me walk you through these a bit. So, HIF-2α is a transcription factor, and it's involved in the regulation of probably hundreds of genes. But one of those is erythropoietin production, so EPO production. And that EPO production is also involved in its on-mechanism side effect, which is anemia. But that erythropoietin production is the gold standard as a biomarker for HIF-2α inhibition in a human. So, anyone who's going to take a HIF-2α inhibitor into a human is going to measure its effect on suppression of that production of erythropoietin.
What you can see is a dramatic difference where with the Merck molecule, this shows the time course, and you can see that somewhere between nine and 13 months, it's basically losing that pharmacokinetic effect, pharmacodynamic effect. What you can see for the Arcus molecule casdatifan is that clearly even at 36 weeks, it's maintaining that effect. If there's anything that you want to see that supports that the clinical data are driven by something, it's this change in pharmacodynamics that you see between the two molecules. Now, let me sort of summarize and finish on casdatifan by thinking where we're going from a development strategy because that's also very different than Merck. Our first phase III study follows that same theme that I talked about. The standard of care in this field is Cabozantinib. What our study is is a very simple study.
It's cabozantinib plus casdatifan versus cabozantinib, so very attractive to clinicians, very attractive to patients. It's a great opportunity, and we're looking to get that up by the middle of this year. The second trial that we're going to be starting is a collaboration that we're doing together with AstraZeneca, and that involves combining casdatifan with their CTLA-4 PD-1 bispecific antibody, volrustomig, which they have reason to believe is best in class, and what that takes us into is a frontline setting, and one of the reasons that's so exciting to the investigator community is it's a TKI sparing regimen, so physicians would love to do as much as they can where they can treat these clear cell RCC patients with a regimen that avoids the pretty nasty effects of TKIs till as late as possible, so just those two settings alone are $5 billion+ market opportunity.
I think a lot of people don't realize RCC is like the sixth largest oncology market. So, it's big. A couple of other things to keep in mind. Every patient in their lifetime that gets this disease is going to get an anti-PD-1. They're going to get a TKI. In fact, the TKI market is pretty fragmented. Even though Kavo sells like $2 billion, there's seven of these TKIs. There's only going to be two HIF-2α inhibitors. It's a two-horse race, us and Merck. And we actually believe that's the strongest mechanism in this field. It's also the most benign from a safety profile. So, from a vision standpoint, we actually think that every patient in their life cycle of treatment should get a HIF-2α inhibitor, and we think that that HIF-2α inhibitor should be casdatifan.
And what you're going to see as the year goes along, beyond these two studies, we'll be adding some additional cohorts to our platform study in this setting that's called ARC-20 that further look to how we'll be expanding that development opportunity. Now, let me turn to our anti-TIGIT domvanalimab that we're looking at in both non-small cell lung cancer as well as upper GI cancers. I think the market opportunity there is so well established. I don't think we really need to say much about it. If these are successful drugs, they're huge. And in fact, in the lung setting, you're really going at the underbelly of Keytruda in terms of the opportunity there. What I think is important is when you think about 2024, if you follow oncology, whether you like it or not, you follow TIGIT.
I think what 2024 really firmly cemented is something that's been talked about for some time, but there were a lot of data. There were data from Genentech. There were data from Merck. There were data from AstraZeneca. There were data from us. What it made very clear is that the two configurations of antibodies, Fc-silent, which we have and AstraZeneca have, versus the others, which are Fc-enabled, you should almost think of them as two different classes of drug. That's well understood because the Fc-enabled anti-TIGITs, in this particular case for that antibody, they target cells that bear TIGIT, and it's been well shown that they target T-regulatory cells. What that targeting does is it leads to immune AEs.
There was no place where this was more evident than in the Merck studies because what Merck was doing was they were using a co-formulation of pembrolizumab plus Vibo, their Fc-enabled anti-TIGIT. So, what that does is it leads to immune AEs that lead to treatment discontinuation, which leads to loss of efficacy. Now, what you saw with the Arcus molecule as well as the AstraZeneca molecule, they have a bispecific where their anti-TIGIT arm is Fc-silent, is positive data from us, positive data from them. And I'll comment on a few of those, but data that looked very similar. So, we think the field has really been divided into those two in that actually you're going to see more continuous data where that Fc-silent anti-TIGIT becomes the dominant player in the field. In fact, Merck is out of it.
The place where I think that's most important is those AEs that we were just talking about are amplified in the context of chemotherapy. We've already shown in our studies that you can add domvanalimab on top of anti-PD-1 and chemo, and you get essentially the same safety profile as just with anti-PD-1 and chemo alone. That's what lets us really feel confident about that biggest market of all, the PD-L1 all-comer frontline non-small cell lung population where you're going to be looking at domvanalimab, Zim, chemo. These are a couple of the data sets that I referred to on the earlier slide that we presented last year. Our registrational trial in upper GI cancers is called STAR-221, and I'll speak to the trial itself on the next slide, but we shared data from the phase II correlate last year.
And what we were looking at in there is exactly the same population with exactly the same regimen. And what you could see is we saw roughly a 12-13 month median PFS in that setting. Now, if you look at the right-hand side, that gives you a sense of where does that stack up. So, CheckMate 649, CM 649, is the registrational study for Nivolumab chemo that was run by BMS. The keynote study next to that, the RATIONALE study next to that, those reflect similar approval data sets for Pembrol chemo as well as tislelizumab chemo. And what you can see is very similar, very consistent PFS on the order of seven months. So, you can see we compare quite favorably with almost double that, and we think that bodes quite well for the registrational study.
What I'll comment is that AstraZeneca at ESMO with their bispecific same study that we ran, very similar PFS within a month or so. So, we feel you have two independent data sets, two different companies that are pointing to the same story. This slide summarizes the design of that registrational study that I just talked about. The important thing to take away from this slide, there's two. So, the first thing is it was really well powered. So, it was fully enrolled as of June of last year with over 1,000 patients, 1,046. The second thing is that it has dual primary endpoints, the ITT, the intent to treat population, as well as the high PDL1 patient population. So, in fact, there's two ways to win if you win on either of those endpoints.
This brings me to a data set that we reported at SITC last year that gets to the lung cancer component of this, and that's the ARC10 data set. This is really probably one of the best data sets, randomized and overall survival with greater than 24 months of follow-up in the anti-TIGIT field. And what you can see is a number of things looking at the curves on the right, the Kaplan-Meier curve. The first thing that you can see is that the hazard ratio, and this you're looking at dom, zimberelimab, the anti-PD-1, anti-TIGIT versus zimberelimab, the anti-PD-1, the hazard ratio is 0.64. So, quite a difference there. The second thing is in an absolute sense, the overall survival for zimberelimab alone was over 24 months. So, very similar, perhaps slightly better than Pembrol in Keynote-042.
Any differences between Zim or Pembrol that people might have thought about or talked about before clearly put the rest here. Probably the most important component of this data set is looking at that upper line in that curve, which is domZim, is looking at the tail. The biology of anti-TIGIT tells you that what anti-TIGIT does is turn anti-PD-1 into super anti-PD-1. And that's exactly what you're seeing. You're seeing that amplification of the tail, which is what immunotherapy brings. These data look very consistent with the biology. The second thing that's worth noting is that in the past, we presented a phase II randomized data set, ARC-7, similar situation. In this case, talking about PFS, PFS was the primary endpoint there. Again, we're seeing very similar data with a hazard ratio for PFS on the order of 0.65, 0.67.
Two data sets that firmly point to that proof of concept that give us very confidence in our registrational trial, STAR-121, that's in the PD-L1 all-comer non-small cell lung cancer setting. This slide wraps up. I started with the slide that showed what did we disclose in 2024. This is the data flow for 2025. And there's a lot. The first thing is, as I mentioned, next month, February 15th, we'll have those updated data from casdatifan. I think what you're going to see are three different cohorts that have blinking lights on them that show all three of them collectively better than belzutifan. Mid 2025, I mentioned our first registrational trial is going to be a combination study with Kavo, where we already have over 25 patients enrolled on the combination. It's primarily for safety purposes. We'll disclose those data in the middle of the year.
Not only will we have safety, we'll have early efficacy data, but what we can already say now is that we're not seeing anything surprising when you think about these orthogonal mechanisms from a safety standpoint. So, it looks like they combine quite well as would be expected. The third data set, second half of this year, I mentioned EDGE-Gastric, the PFS data. As I said, we showed 13 months PFS. 13 months is the OS, roughly, that those other molecules were approved upon. So, we're going to actually have OS data later this year. And what I can tell you is that we have said publicly at 18 months of median follow-up, we had well over 50% of the patients still on study. So, we think this is going to be another strong data set supporting the outcome of that STAR-221. We'll continue to report on casdatifan.
This wasn't sort of a one cohort, one-off study. We're going to be in casdatifan. If you think about the evolution of ARCUS, the centerpiece of our development is going to switch as these anti-TIGIT programs go into the later phases of moving towards data registration, commercialization. Casdatifan is going to become the center of our program. And so, we're going to be sharing data on a pretty continuous basis. And finally, we're guiding to readout from that STAR-221 that I showed you that had the 1,050 patients or so that that'll come in 2026. We're excited about that. We and Gilead are working very closely together, basically preparing for that data readout as well as commercialization. So, let me just finish by circling back to those four, 33% more than three points that we wanted you to remember.
Hopefully, we give a lot more granular points on each of them. Two near-term value drivers, casdatifan with the evolving development program. We think that's just going to be huge in clear cell RCC, even as we contemplate moving into other settings. Domvanalimab, these three late-stage programs getting towards data, getting towards commercialization. That sustainable drug discovery effort, because that's how we built Arcus from scratch. So, it's not one of these companies where we're going to bolt on research afterwards. That's really the secret sauce of the company. As the year goes along, we'll actually start to share more about the I and I component of what we're doing in addition to the oncology. And as I mentioned, we continue to be well funded. So, all of these plans we've talked about today are taken into 2027 with the current capitalization.
So, I'll stop there, and I'm happy to take your questions or any other questions that might come in. Okay, great. As a reminder, please wave your hand if you have a question, and we'll pass the mic around. Okay, I can get us started here. What makes the Arcus investment thesis different from other biotechs, and what do you think investors are missing about the Arcus story? So, I don't think they're missing much. I think there's a lot of differentiation and really flows from what we talked about today. So, first off, you've got the breadth of programs. I think the other component is not only do we have broad, but within each, they're deep. And we're in some of the biggest oncology markets with innovative new drugs. And so, we're competing against Merck, we're competing against AstraZeneca, we're competing against Genentech in some of the biggest markets.
And those readouts are either around the corner or in the case of casdatifan, you basically have a very unusual confluence of circumstances. You have a molecule that's validated the target, so it's close to 100% probability of technical successes you can get. You're going to have a strong group of data that support that you have a better molecule, and there's going to be limited competition because of the difficulty of the target. So, there's going to be a two-horse race. We're going to have a very broad development strategy. And then I think the third component beyond that sustainability, I think these days you don't see many companies that build an R&D engine in a bona fide way, is that we're capitalized in a way and have been capitalized in a way to enable us to execute on our programs.
Can you talk about your portfolio approach and overall strategy? How do you prioritize your programs and evaluate potential partnerships? And are you considering more BD in the future? So, absolutely, we consider more in the future, and it reflects that same strategy. So, from a prioritization standpoint, I think we're always looking to be in something where we can be first and/or best. We tend to lean toward small molecules as differentiation because we have a real strength there. And it's something that's been fading in the industry. You don't see as much of that even at the larger companies. We do look to play in large areas. From a business development strategy, what we've talked about today, I think reflects the way we think mostly about our near term.
It's things that give us an advantage to come up with a best-of-class combination and get assistance and execution. We get the capital and human, and those are not independent variables, efficiency. For example, AstraZeneca. I didn't talk at all about our Stage III lung trial that's well along as a phase III study. AstraZeneca has the standard of care there. It's Durva. Durva sells over $2 billion just in that market alone. We're combining Durva with domvanalimab. AstraZeneca is executing that study under very favorable economics. Who would you rather have anywhere on the planet than the company that owns the Stage III lung market, has the expertise, has the connections, knows what they're doing to execute that trial on your behalf? That's an example.
Second collaboration where we're combining with Volru, very similar, where they have a potential best-in-class, think about it, they're bispecific molecule that hits CTLA-4 and anti-PD-1. It's very much a synergistic concept. Combining that with casdatifan, they can bring something on top of what's probably a third of that clear cell frontline therapy where the deficiency can be that you have that higher rate of primary progression that we can actually bring to the table and address with casdatifan. And again, they're going to be executing that trial. So, we're often looking for complementary mechanisms with real partners that can execute and actually enable us to do something that makes it easier than if we were to just do it alone. And for those of us who aren't familiar, can you help us understand the fundamentals of your relationship with Gilead? Sure.
So, this is, you can see it's been very enabling. So, I'll tell you one thing that, like at the highest level, given what our aspirations were, you can almost think of this as looking at, we went into this company thinking 50% of a lot is better than 100% of nothing. And that's how things are playing out. So, the Gilead collaboration is a 10-year all-in collaboration where they can opt into anything that we work on. Now, with that said, we'll agree on what that opt-in package is to get one bite at the apple. So, we anticipate there will be some things that they do not opt into. Once they take that bite of the apple, either we're partnered together 50/50 or the molecule would come back to us and we'd have 100%.
For those programs they opt into, basically they pay us $150 million upfront, then they cost share for everything going forward. We ultimately co-market, co-commercialize, co-promote in the U.S. So, we have 50% of the U.S. rights. Then we get double-digit royalties to get into the 20% outside the world. So, it's extraordinarily enabling for a company that's looking to go broad and deep. Turn. Oh, okay, go ahead. How do you define differentiation? Sure. No problem. How do you define differentiation for casdatifan relative to established competition? And how do you think about kind of first-line strategy where you're competing against established players in the renal cell carcinoma field using a different strategy? They're also partnered with you in part, and there's quite a bit going on there. Maybe there's two questions there.
One is kind of for near term, what is success and kind of how do we measure it? And two, looking forward, and I understand it's years away, but if HIF-2α becomes a real market, given the different strategies, kind of what will enable you to dominate that space versus your other competitors? See, now the way he asked that question, it was testing what I said at the beginning, whether I can remember four things and not just three things. So, the first part of that, what would give us essentially what are our metrics? Now, the good news is you're a month away from a third data set. So, we think the compelling data are going to be that you're going to see three different cohorts that on all efficacy endpoints look better than those associated with belzutifan today.
Most notably, durability, but also that rate of primary progression because that feeds into everything else. And then you'll be able to layer on top of it that pharmacodynamic over time course differentiation that to me scientifically says the clinical data are driven by something. In terms of the frontline strategy, we actually look at the first thing that we're doing is the first place to go because from a standpoint of what the field wants and what patients want and what's the right thing to win here is going to that TKI strategy. So, that's something that Merck has not embarked on now. The physicians love it. Again, you want to avoid that TKI as long as possible. So, that combination CTLA4, PD1, casdatifan is a very compelling opportunity for the frontline.
In terms of your point about the established regimens, the way we look at it is you've got basically it's dominated by anti-PD-1 and TKI. The TKI market's very fragmented with seven. You got the PD-1. We think that the best mechanism, and I actually what I'll ask people to watch is our data flow. I think you're going to come to the conclusion that casdatifan monotherapy looks better than TKI monotherapy. So, a big part of that strategy where we believe not only will all patients already get an anti-PD-1 and they get a TKI, but they're all going to get a HIF-2 inhibitor. So, by having a better HIF-2 inhibitor and then thinking about how do you move that into various lines of strategy so that it's available throughout the lifecycle of the patient is where we're going.
And so, for example, what you'll see is we'll be starting a study in ARC-20 where we're actually looking at casdatifan monotherapy in a frontline setting in favorable population to start to build that case. So, we definitely are committed to and believe that we should be a big part of what will be a very large, we think it's going to become between a $5 billion and $10 billion market. And that's going to be driven by duration of therapy. Thanks.
And that concludes the presentation.