Thank you so much. Good afternoon. Welcome to Barclays Global Healthcare conference. We're in Miami and do email us, so hit us on Bloomberg if you have any questions. My name is Peter Lawson. I'm one of the Mid-Cap biotech Analysts at Barclays, focus on Oncology-related names, and really delighted to have with us from management from Relay Therapeutics, Sanjiv Patel, President, CEO, Don Bergstrom, President of R&D, and Peter Rahmer, Chief Corporate Development Officer. I guess first question, just with kind of pretty pertinent kind of looming data in the PI3Kα space, kind of what should we expect to learn from this data update? Is it something investors should be, you know, laser-focused on? Is it something that's gonna kind of help enrollment, or is it more kind of investigative-related data, you think?
Thanks for the invitation, Peter, the opportunity to get out of what was a very cold and windy Boston. We're thrilled to be here.
Anytime.
In terms of the data on PI3Kα Mutant Selective, I think we're excited about sharing it at the AACR Meeting that's upcoming in Orlando. Yes, I think it will be informative. As you know, this is one of the largest unserved Precision Oncology unmet opportunities out there. You know, given the number of Patients that could benefit, I think the Data will hopefully be informative. As you know, this target has been served by the non-selective PI3Kα Inhibitors, and the dose intensity for those therapies is limited by their Off-Target Toxicities.
The goal of this program we set out to work on it in research a few years ago was to try and dial out those Off-Target Toxicities such that we could maintain the Dose Intensity, and that would then translate into a step change in efficacy. This first Data disclosure we've been guiding towards for the last year is a, you know, the first in-human disclosure. The goal is to be able to demonstrate PK, PD, safety, and then early signs of efficacy. Maybe hand it back to Pete and just talk about some of the expectations that investors could expect.
I think it's just as Sanjiv suggested the, you know, the goal of all our programs, generally the through line is that using traditional tools, there's a lot of efficacy being left on the table for some of these targets. By using our unique platform, we tend to be able to gain insights that allow us to drive to greater selectivity and therefore greater tolerability and safety. Because of that, can eventually drive to greater efficacy over time. This initial disclosure, similar to our 4008 Disclosure for our FGFR2 Inhibitor when we first showed data, it starts to answer the first part of the question, which is, have we been able to translate our preclinical findings of having developed a more selected PI3Kα Pan-Mutant Selective Inhibitor into early clinical data?
You can see that because these Off-Target Toxicities, you can measure those and start to see if at clinically relevant doses are those meaningfully differentiated from what we've seen with Alpelisib and Inavolisib. You can tell for a clinically relevant doses because by our PK modeling and Ex Vivo PD Assay and early Antitumor activity, which acts as a Pharmacodynamic Biomarker in these early datasets, we can start to understand if once we are able to choose a dose and in a larger N, will we be able to drive to greater efficacy.
This update, what the key thing here it is to show safety and that you don't get this glucose spike that's essentially killed the PI3K α class for most physicians.
I don't know, Don, if you want to take that.
The elevated glucose is certainly part of the toxicity question. That is the toxicity you see with the non-selective PI3Kα Inhibitors that is most directly related to inhibition of wild-type PI3Kα outside of the tumor. When you look at the overall tolerability profile, it goes beyond just hyperglycemia, and you see AEs such as diarrhea and rash that with hyperglycemia are the three most common toxicities that lead to Discontinuation of Alpelisib. We think that these are AEs that are also due to inhibition of wild-type PI3Kα, but also potentially due to some of the residual activity that drugs like Alpelisib have against PI3Kδ and other family members. As we're looking at the safety profile, certainly looking at glucose is an important marker for us for proving the selectivity hypothesis.
I think for being able to look at the profile of RLY-2608 in light of the future development of the asset, you have to look across the totality of the safety data and really assess whether we're able to generate a safety profile that's meaningfully differentiated across the board.
Gotcha. How do we kind of understand that collection of safety data points? I mean, I guess longer run, it's going to be discontinuation rates we look at. But for this set of data, what's the best way to triangulate, you know, and balance diarrhea, rash, glucose spike?
Yes.
You know, what's good, what's bad, how do we fit into those quadrants?
I think you're looking, you know, first of all, just in terms of acute toxicity, what's the overall rate of grade 3 and grade 4 AEs? Then you're looking specifically at those three key AEs I just mentioned, hyperglycemia, diarrhea, rash. What is the rate that we're seeing with RLY-2608? Then while our data will be early, we can start asking the question of whether you're seeing the ability for patients to stay on drug. What's the rate of dose modification or discontinuation?
Got you. Do you think you've taken the hyperglycemia down to kinda grade 1, grade 2, or do you think it's too early to determine that yet?
I think you gotta look at it in its totality. Obviously, you know, the goal of this program is to try and get a step change in efficacy. Ultimately, the regulatory hurdle is gonna be PFS. I think obviously the goal is to try and maintain as much dose intensity as we can, but I think it's a kinda multi-parameter optimization question in the end. Yes, the goal is to try and reduce it down to as low as it's possible. Obviously, that will then translate into dose intensity, which we hope will then translate into efficacy.
You can't just focus on just hyperglycemia. You can in the context of understanding the translation of our selectivity window, because that is the most translatable toxicity associated with PI3Kα wild type. You know, we have a good analog for what happens if you held all other safety intolerability the same, but just lowered hyperglycemia in the AKT inhibitor from AstraZeneca, Capivasertib. That's exactly what that agent generally did. It has a very similar safety intolerability profile to Alpelisib, except for a lower hyperglycemia and a higher diarrhea rate, and it's resulted in exactly the same efficacy as, of Alpelisib. That is not our goal. Our goal is to have, as Sanjiv has said a couple of times now, a meaningful difference in efficacy for patients with PI3Kα mutations.
That's why it's truly the totality of the safety profile that.
Got you. Yeah. We should really be looking at all three of those safety profiles being nudged down.
Your comparator data set is coming from phase II data sets from Alpelisib and Inavolisib or large phase I-B data sets at a recommended phase II dose. We are obviously gonna have a much smaller end coming from a dose escalation patient data set. I think you have to be able to look at our data set compared to that, proportionately adjusted for the difference in end, and have confidence that once we get to a dose in a larger end, that that will hold up. Like, I don't think we're looking for incrementalism here, and that you know, will probably be the lens in which we try to look at this initial safety intolerability profile.
Gotcha. Okay. just, yeah, if you could remind us the number of patients we see, will we see recommended phase II dose at AACR?
We haven't guided to the specific number of patients that we'll see. It'll come from both the dose escalation, Monotherapy Dose Escalation and Combination Dose Escalation. We've said that the goal is to have a robust enough of an end to be interpretable against all these parameters that we just discussed. In terms of a recommended phase II dose, we That was not a hurdle for making this disclosure. If and when we choose a recommended p hase II dose and move into expansions, we would announce that. By proxy, we haven't and it is not a requirement at this disclosure.
Okay. Very clear. Thank you. That's really helpful. Just I guess when we think about these patients going into the study, are there any that have kind of background level of hyperglycemia that we're kind of You're kind of battling against?
I mean, it's a Western population. As you know, given the demographics, unfortunately, it's just a fact of life that there is a background level of grade 1, grade 2 hyperglycemia in the populations that are being studied in any clinical trial. I don't know if you wanna specifically comment on ours.
Yeah. I think our trial, you know, we are, excluding patients who have uncontrolled diabetes from coming on the study. We will allow patients on study who have a Hemoglobin A1c up to 7%. We, you know, we will allow patients in the study who have borderline glycemic control.
Gotcha. What do you wanna see, whether it's this data set or continuing data sets this year, what... To move the drug forwards?
I mean, I think we've been consistent around this since the start of the trial last year, which is we wanna be able to show that we can sustainably maintain a dose intensity above the IC80 and do that. To do that, obviously, you need to have be able to hit the target. We need to be able to demonstrate that through PD, and that then is in the context of differentiated safety profile. I think if we could, we get confident around those three things, then that would give us confidence that if we could then enroll a larger number of patients in the defined patient populations that we're looking at, and find a recommended go-forward dose, you would start to see the step change in efficacy that patients require.
Gotcha. At AACR, will we see kind of the dose escalation portion that's in combination with fulvestrant as well?
Correct. We will show both the Monotherapy Dose Escalation and the Combination Dose Escalation data. For reference, just to make sure everyone knows, the Monotherapy Dose Escalation started in December of 2021. The combination with fulvestrant started in April of 2022. It was when we started that combination, when we guided to data in the first half of this year, 'cause we were very focused on making sure we had about a year's worth of experience in that combination cohort 'cause obviously, that's where the breadth of the data exists with the precedent inhibitors. That's where you're gonna be able to make the, probably the most robust cross-trial comparisons.
Okay. Yeah, how do we think about the bios in each of those two groups, essentially?
Sure.
The dose escalation, et cetera, et cetera.
The Monotherapy Dose Escalation, that is simply a part of the study that allows us to understand dose and safety and tolerability. There, That is in all comer solid tumors, obviously with PI3Kα mutations, but not enriched for tumor types in which we a priori would suggest or think would be sensitive to single agent PI3Kα mutation inhibition. For example, colorectal cancer, non-small cell lung cancer. In those tumor types, PI3Kα is commonly co-mutated with KRAS G12C, and so a single agent in those settings, we wouldn't presume would be effective by themselves. In the combination, though, we are going into a patient population in a regimen where there's a good amount of efficacy data from the precedent inhibitors. It...
These early data sets at clinically relevant doses will give us a pretty good hint into the profile of RLY-2608 in that context.
Okay.
All you're hearing us caution against is that efficacy data, specifically in this setting, but in really any first human data set a year into the study, is hard to interpret. You really need to get to a recommended phase II dose in a much larger patient population before you can start to really define that.
How many doses have you been through so far?
I haven't disclosed that, suffice to say, you know, we've said that We were gonna be starting the Combination Dose Escalation with fulvestrant once we've reached a biologically active dose in the Monotherapy Dose Escalation. We define that to be crossing over the IC50 mutant inhibition. Fair to say we at least covered that as we started to start the combination, we likely had some dose escalating to do to get to clinically relevant doses.
Gotcha. Will we get durability data as well?
We will disclose what the median duration of exposure is at that time, but inevitably, it's gonna be small. There's not gonna be a lot of follow-up, especially at the clinically relevant doses.
Gotcha. Do you wanna see, I guess, as this data pans out, do you wanna see a step change in efficacy as well as a kind of step down in safety as well?
That's essentially the goal of the program. It is only one goal, which is efficacy, that's exactly our... Now, we think the way you get there is greater dose intensity. How you get to greater dose intensity, you have an agent that's more tolerable, which patients can stay on for longer periods of time. The trade-off will be... If you can provide an opportunity for an agent that is more tolerable, that covers the target for at a higher level for a longer period of time, it should drive to greater efficacy.
Gotcha. Okay. Do you have a sense from physicians, your own internal goals of, like, the percentage of grade 3 events which would kill the drug, or you feel it's acceptable to move the drug forwards?
The existing inhibitors, Alpelisib and Inavolisib, sit somewhere between, you know, depending on the study, 40%-70% grade 3 of adverse events. As Don said in the opening, the hyperglycemia, rash, diarrhea are clear toxicities leading to discontinuations. All these things are contributing to the lack of the ability to maintain dose intensity with these agents, which is leading to a lack, subpar efficacy. I don't think there's one particular AE in which you're gonna say it's at 30% now, 5% grade 3 is okay. It's the totality of the safety and tolerability profile, I think, that we really need to.
Yeah.
meaningfully differentiate on.
Okay. As we think about expansion opportunities, where else is there good rationale here? Not trying to discredit the scale of the breast cancer opportunity. I just... Where else?
As we were designing the first human protocol for the monotherapy cohort specifically, we tried to design cohorts that we felt based on our understanding of the genomics of the tumors, our preclinical data, and the experience with PI3K inhibitors in these patient populations. We tried to identify cohorts where we thought there'd be the greatest likelihood for single agent activity. The four patient populations we identified consist of three patient populations that are sort of conventionally defined, so clear cell ovarian cancer with PI3Kα mutation, squamous head and neck cancer with a PI3Kα mutation, cervical cancer with a PI3Kα mutation.
There's a fourth population that we defined as well, which is a pan-histology population that is defined by having two mutations in PI3Kα. This is a phenomenon that was first described by José Baselga about six years ago when he was still at Memorial, where they identified patients who had two PI3Kα mutations that are actually in the same copy of the PI3Kα gene. That leads to a significantly hyperactivating PI3K α protein that then renders the tumor very sensitive to PI3Kα inhibition. That is estimated to represent about 10% of the overall PI3Kα patient population, and represents the fourth cohort that will enroll in our expansion cohorts in monotherapy. As Pete Rahmer alluded to, we did not, as we're performing Monotherapy Dose Escalation, perform any enrichment for just those patients.
We have other patients we anticipate will be represented in the Monotherapy Dose Escalation as well, not just from those four patient populations.
Gotcha. Thank you. I guess the other question we keep on getting is around Scorpion's molecule in the space. How are you differentiated, and how do you do those kind of cross-preclinical explorations of differentiation?
You wanna take that one, Pete?
Sure. the two main next generation inhibitors, if you will, in the space come from Loxo Oncology and the other one from Scorpion. The Loxo Oncology molecule from our understanding interpretation of their preclinical data is specific to H1047R, so just one of the hotspot mutations makes up anywhere from about 30%-40% of the patient population, depending on what tumor type you're looking at. that one entered the clinic shortly after we did but addresses a minority of the patient population. unclear to us.
You know, we think that as we contemplated what mechanism to bring forward to fully serve this patient population, we kind of had both options at our disposal because we started with full knowledge of the target and having solved the first full-length structures of both wild-type and mutant form of the protein. We are understanding of a pocket that would allow us to get H1047R specificity and an allosteric pocket that we discovered that allows us to get pan-mutant selectivity. As we progressed through our decision-making as to which mechanism to bring forward, we decided to bring the pan-mutant selective forward first. Now we do have an H1047R molecule also in discovery, in addition to multiple pan-mutant selective molecules.
That is because the size and importance of this opportunity is too great and the depth and breadth of our knowledge here is so large that we will continue to prosecute inhibitors for this target until we definitively define the best efficacy for patients clinically. The other molecule from Scorpion looks like to be a pan-mutant selective inhibitor that looks and feels a bit more like our pan-mutant selective inhibitors. It's just 18 plus months behind.
Is there anything to triangulate from their preclinical data? I mean, when you look at their molecule and...
Neither of them, neither Loxo nor Scorpion, nor us, frankly, have published the structures of our molecules. None of us can do head-to-head comparisons in the same assays to really start to give you a more in-depth understanding. It's all just conjecture and interpretation of each other's preclinical data.
Gotcha. I guess the other very exciting story, of course, is FGFR2 inhibitor and kind of data in the second half. What should we expect to see from the, I guess, the non-cholangio expansion cohorts?
Well, I mean, yeah, you're exactly right, which is obviously last year, we showed what we believe to be pretty definitive evidence around the efficacy of our selective FGFR2 inhibitor, in cholangiocarcinoma fusion patients. Obviously, the question there is, what is the breadth and depth of the opportunity outside? I think in the second half of this year, we'll share data that will start to answer that question. Maybe, Pete, you can detail the types of data that we'll share.
Sure. We initiated those expansion cohorts in December of 2021 at 70 milligrams once daily. The target enrollment for those, each of those three cohorts, non-CCA fusions, non-CCA amplifications, and non-CCA mutations, was 30 patients each. In the second half disclosure, we would expect to have those close to fully enrolled, if not fully enrolled, because the goal here is to be signal-seeking to start to define areas of further development for RLY-4008. We do anticipate there's likely an opportunity outside of CCA, this data set will start to tell us where to focus our efforts.
Gotcha. Thank you. I guess maybe the final question just on the kind of the background AI platform.
Yes.
I mean, how much do you rely upon that now as if you've kind of migrated from AI platform company into full development company, and what do you do with that AI platform?
First of all, I mean, the company is built as an experimental plus computational approach. Everything that we do is based around both coming together. You know, we focus on validated targets, and so we're not one of these people that are using computational methods to elucidate novel biology. We're focused on making medicines. Then we're focused on combining experimental approaches to novel kind of approaches to structural biology with both computational approaches that involve physics-based simulations as well as using machine learning and algorithms to help us make the process of making new medicines both more efficient and effective. We break that process down into many, many steps.
Essentially, the computational approaches that we deploy in each of those different steps are all about making the experimental work we do more efficient and helping us answer what is the next question or the next experiment that we need to do. That all remains fully intact, and the fact that we've now put three experimental therapies into the clinic and, you know, we're about to put a fourth one into the clinic starts to validate that. As we build out the development organization, I think all that does is start to test the biology of these molecules that the platform has delivered. The platform gets ever more experienced and then hopefully becomes ever more effective, producing molecules against the hypothesis that we're trying to go against.
I think the development organization is testing the biology, and so I think they are related, but one doesn't, you know, change the other.
Yeah. Perfect. Thank you so much.
Great. Pleasure talking to you.
Thank you so much.
Thank you again for the invitation to get back into the sun.
Yeah. Thank you.