Dana Aftab: Sure. Okay. Thanks for the question, Andy. Yes, so in terms of the partitioning, we generated data in rats, and this is really data for preparing for the mass balance studies in humans. That was the first sort of view into differential partitioning into normal tissues that we got. So that was using radio-label drug. So of course, that measures everything metabolites and anything else that’s attached to the radioactive tracer. In terms of the tumors and actually the data that I showed on the slide came from sort of a side-by-side experiment in mice where we were determining the compound concentrations by mass spectrometry. And at doses that generated similar free drug concentrations in the plasma, which again were determined by doing protein binding experiments, et cetera, we saw those free drug concentrations in normal tissues and tumors, and that was just one of several representative normal tissues.
So we’re still generating a lot of data. There’s obviously a lot of different components that go into how drugs distribute within a living animal or person, including things like protein binding, tissue binding, which involves other components other than protein, membranes, lipids and whatnot, transporter effects, pH-dependent effects. There are so many different pieces of the puzzle that go into understanding how this happens. So we’re still gathering data to try to understand the full model that is driving these differences. And what I would just say is stay tuned as we generate more data and publish those data that will hopefully lay out the full mechanism of how this happens. But I must say that it was a surprise to us to see this happen.
We had not anticipated or predicted that this would happen with these drugs a priority.
Michael Morrissey: Great. Thanks, Dana. P.J.?
P.J. Haley: Yes. So, hi, Andy, our Part D — Medicare Part D accounts are approximately 40% of the business. And as you know, with regards to the IRA, that will continue to evolve in 2025. So the out-of-pocket cap for patients will be even lower next year, around $2,000 and also it will be spread out over a monthly basis. So the thinking is that could potentially reduce the burden on patients even further.
Operator: Thank you. Please standby for our next question. Our next question comes from the line of Jay Olson with Oppenheimer. Your line is open.
Jay Olson: Hey, thank you for providing this comprehensive update and for taking our question. For Zanza, can you talk about when we should expect to see some combination data. And Bristol recently mentioned initial clinical proof-of-concept for Opdualag in non-small cell lung cancer. What’s your thinking and interest level in the combination of Zanza with Opdualag and STELLAR-002? Thank you.
Amy Peterson: Sure. Thanks for the question. I’ll take that. This is Amy. So you saw in the slides, we do have a variety of cohorts that we are expanding in both STELLAR-001 and STELLAR-002 and in combination with PD-1 in addition to other IO agents, including CTLA-4 and LAG-3. We will present the data when it is mature. Some of these are early line cohorts. It just takes a while because you want to get ORR, you want to get DOR, you want to get PFS. Some of them actually also have OS, they’re event-driven. And we just have to wait for those events before we can report on that. When it comes to interest with combination partners, I also presented the various combinations that we’re doing, not only IO, IO, IO, but also we have the collaboration with HIF-2 alpha, and we’re looking another combinations.
So I would say that we’re data-driven. And we’ll go where the combinations tell us we should go, but we are and we remain open. I think that what we’re continuing to identify and uncover is that the ability for Zanza to combine with all of these other agents is actually rather straightforward that’s reasonably well tolerated at full doses. And so we don’t think that there’s an issue in terms of Zanza’s ability to combine with any of these agents. It just has to be — the decision to move forward into additional studies just has to be made upon the data that we see as it matures in the 001 and 002 cohorts.
Operator: Thank you. Please standby for our next question. Our next question comes from the line of Akash Tewari with Jefferies. Your line is open.
Unidentified Analyst: Hi. This is Cathy on for Akash. I just wanted to follow up on the Medicare Part D question that was asked earlier. And specifically on how will the restructure of the catastrophic coverage component impact Cabo in the coming years? And also how does Exelixis specifically plan to mitigate these pricing impacts? Thank you.
Michael Morrissey: Thanks for the question. This is Mike. Yes, I certainly wouldn’t want to comment on what’s going to happen in the years ahead. We have a pretty good idea about what to expect relative to ’25 and beyond. So again, I wouldn’t want to opine beyond what’s happening in 2024. And we have a high degree of confidence that we’ve got that really good sense of where that’s going and how to navigate those different changes. So moving full steam ahead and when we get to ’25 and beyond, we’ll talk about those changes then, okay? Thank you.
Operator: Thank you. Please standby for our next question. Our next question comes from the line of Chris Shibutani with Goldman Sachs. Your line is open.
Chris Shibutani: Great. Thank you very much. Perhaps if you could help us understand your prioritization of capital allocation between the share repurchases and the business development activity, I think Joe had tried to ask earlier and recognizing that you aren’t necessarily thinking of sharing specifics. But it sounded as if it was contingent upon the outcome of the MSN IP decision for you to perhaps lean in more intentionally on the BD front. I just wanted to make sure I understood because you also included in your release that you plan on completing the share repurchase allocation that the Board approved for the full year 2024. Thank you.
