Oric Pharmaceuticals, Inc. Common Stock 12th Annual Cantor Fitzgerald Global Healthcare Conference

Sure. I am happy to start.

First time doing this? First time at a fireside chat, sorry.

ORIC stands for Overcoming Resistance in Cancer, which, in a nutshell, is the mission of the company. We are most focused on two programs that are in late-stage clinical development at this point. rinzimetostat, which is our PRC2 inhibitor that is being developed in combination with a couple of different androgen receptor inhibitors in prostate cancer, right now, specifically in CRPC. enosartib, which is our brain-penetrant lung compound, is for two different targeted therapy populations within non-small cell lung cancer, primarily within the EGFR family of mutations, but specifically EGFR exon 20 and EGFR atypical mutations. rinzimetostat, our PRC2 program in prostate, has recently entered its first phase III study, HIMALAYA-1, which I am sure we will discuss. enosartib is about to have a lot of data that is presented at ESMO for atypical EGFR mutations.

If all goes according to plan, we will start the first phase III study for that program next year. A lot going on. Okay.

Yeah, I'm always a little hesitant to comment on other companies' assumptions or to make predictions on what's going to happen, but obviously, this is probably the most common question we've been getting over the last couple of weeks, ever since their Q2 quarterly call. I think by Pfizer narrowing their guidance for when the MEVPRO-1 readout was coming to Q4, I think it probably fed into a lot of folks' event-driven analyses as people are trying to predict when would the events come in that MEVPRO-1 trial. What does that imply about treatment arm versus control arm performance?

I think you put out, obviously, a very thoughtful analysis on that as well, and I think the net conclusion of that for us is pretty much the same conclusion you came to, which is that, in general, a Q4 readout for MEVPRO-1 ought to be a positive signal in terms of how that trial plays out, and in general, the later, the better within Q4 itself. We've done everything internally to stress test all the big assumptions you can on an event-driven analysis around that trial, namely things like control arm performance, composition of the physician's choice control arm. So in other words, what percent of patients get chemotherapy versus get enzalutamide? What is the performance of the chemotherapy subportion of the control arm? What's the performance of the enzalutamide subcomponent of the control arm? Things like dropout rate. When was enrollment completed?

Which I know is a hot topic of debate, and I think the bottom line is you sort of have to lay out a whole bunch of different scenarios under all those different assumptions, and I think you generally see a skew to the positive. So that's probably the conclusion we come to as well. I think maybe just taking a step back from that, Prakhar, where we get comfort is obviously in seeing how our own data have developed in two different populations within CRPC, so in the post-abiraterone CRPC population as well as post-AR inhibitor within the CRPC. You've got a couple different phase I data sets from Pfizer. You've got a randomized data set from Pfizer. You have another data set from another PRC2 inhibitor called igermetostat.

So at this point, I think the preponderance of evidence is that the mechanism of a PRC2 inhibitor in combination with an AR inhibitor is, in fact, synergistic, and I really think now it just comes down to trial stats and whatnot to try to figure out, is it going to be positive or not?

Yeah, look, we've always been pretty simplistic in the way that we think about how those scenarios might play out. At a high level, you can have MEVPRO-1 with a big win, a small win, a bare miss, or a big miss. I think the conclusion of the analysis, the very good analysis you did and that others have done, I think at this point, especially with the Q4 readout, pretty much takes the big miss scenario completely off the table. It's almost statistically impossible at this point for that trial to have a big miss. Now you're left with those other three scenarios, and I would argue that certainly the first two are, in general, better read-throughs for us, which is that they have either a big win or a small win.

But even in the small miss scenario, it doesn't necessarily change our base case plan given what we already understand to be the key differentiation of our compound versus theirs, which really comes down to the drug properties and then how that translates into the safety of the compound. If you think about the ways that they could potentially have a near miss, we've scrutinized that every which way possible. You can look at things like trial design, and in that sense, you would look at things, for example, like do you somehow have an unexpected enrollment of patients in the control arm more heavily weighted towards chemotherapy, for example? That's one of the ways that could pressure the trial stats, so to speak.