ORIC Pharmaceuticals, Inc.ORICNASDAQ
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Operator: Good day, and thank you for standing by. Welcome to the ORIC Pharmaceuticals Fourth Quarter and Full Year 2021 Financial Results and Operational Update Call. At this time, all participants are in a listen-only mode. After the speaker presentation, there will be a question-and-answer session. [Operator Instructions] Please be advised that today’s conference is being recorded. [Operator Instructions] I would now like to hand the conference over to your speaker today, Dominic Piscitelli, Chief Financial Officer. Please go ahead.
Dominic Piscitelli: Good afternoon, and welcome to the ORIC Pharmaceuticals fourth quarter and full year 2021 financial results and operational update call. Following the market close today, we filed our Form 10-K and issued a press release with our financial results for the fourth quarter and full year ended December 31, 2021. You may find these documents posted on the Investor page of oricpharma.com. We have pre-recorded a portion of our prepared remarks, after which we will host a live Q&A session. So please bear with us if we have any technical difficulties. Before we begin, starting on Slide 2. During this conference call, we will be making forward-looking statements. ORIC’s actual results may differ materially from those expressed in or indicated by such forward-looking statements. For a description of risk factors associated with investing in ORIC, please refer to our recent filing with the Securities and Exchange Commission. ORIC specifically disclaims any obligation to update any forward-looking statements except as required by law. Now turning to Slide 3, I’ll briefly walk you through the – our agenda and introduce our speakers. During today’s call, we’re primarily focused on an update on ORIC-101, after which, we’ll provide a pipeline update and summary followed by Q&A. Joining me on the call today, we have Jacob Chacko, CEO; and Pratik Multani, CMO. Now let me turn over the call to Jacob.
Jacob Chacko: Thank you, Dominic. Turning to Slide 4. As you know, over the past two-plus years, we have conducted dose escalation and dose expansion studies testing two separate therapeutic hypotheses for GR inhibition as a means of overcoming resistance to chemotherapy in various solid tumors and to AR modulators in prostate cancer. We recently completed interim analyses from both combination studies. And we believe that further development of ORIC-101 should be discontinued due to a lack of sufficient efficacy signals to meet our benchmarks, which Pratik will tell you more about shortly. In both studies, we took on a difficult challenge, namely in later line patients who had already progressed on a prior cancer therapeutic, we were attempting to add a GR antagonist in order to resensitize them to that prior therapeutic. Well, that was a high bar. It was an important clinical question to evaluate because of the limited treatment options available to those patients today. The challenges of assessing efficacy signal in a single arm study of a combination regimen are obvious. So our team put in place two well-designed clinical trials that were complemented by a robust translational effort. We’re confident that we’ve explored the GR hypothesis appropriately and also confident in making this decision. While we’re obviously disappointed that ORIC-101 is not continuing, we’re proud of the scientific rigor and thoughtful clinical design that allowed us to make an efficient, but thorough decision. Despite the discontinuation of ORIC-101, we believe we have one of the most robust and differentiated pipelines and small cap biotech. We’ve been intentional about assembling a broader pipeline of both novel and validated targets that are attempting to address areas of high unmet need with either first-in-class or potentially best-in-class approaches. Last year, we filed three INDs or equivalents for single agent trials being initiated this year for ORIC-533 in multiple myeloma, ORIC-114 in EGFR/HER2 cancers, and ORIC-944 in prostate cancer, with initial data expected from the three programs expected in the first half of 2023. Each of these programs has a unique angle or angles that we believe will help differentiate them in the clinic. Beyond these three clinical stage programs, our discovery research team last year advanced two programs in the lead optimization, one of which we recently introduced as our PLK4 program, which we believe is a first-in-class synthetic lethality approach for breast cancer. Finally, we’ve been thoughtful about bolstering our balance sheet and managing our resources efficiently. So we believe we’re well capitalized to weather a sustained market downturn. With the discontinuation of ORIC-101, our cash runway has now been extended from the first half of 2024 to the second half of 2024, and that guidance assumes advancement of all our pipeline programs. With that said, let me now turn the call over to Pratik to walk you through the summary highlights of the ORIC-101 studies.
Pratik Multani: Thank you, Jacob. Turning to Slide 6, we have been conducting two clinical trials of ORIC-101, each examining a distinct mechanism of action of GR inhibition as a means to reverse cancer resistance. The first study is a combination of ORIC-101 with enzalutamide in patients with metastatic prostate cancer. Given that ORIC-101 was not expected to have single agent activity, we chose this patient population specifically, so that we could identify a clinical signal in a single arm setting as efficiently as possible, namely, patients with metastatic prostate cancer who are progressing on enzalutamide. By adding ORIC-101 at the time of enzalutamide progression, our objective was to test the hypothesis of reversal of enzalutamide resistance to the simultaneous inhibition of GR as a potential bypass pathway, a novel paradigm for treatment post enzalutamide or any androgen receptor modulator, since most second-line approaches involve switching to entirely different mechanisms of action. Here, we were trying to extend the efficacy of enzalutamide itself. This multicenter open label study was performed in two parts. We previously reported on part one, which was the dose escalation portion of the trial, through which we identified the recommended Phase 2 dose or RP2D of ORIC-101 to be 240 milligrams once daily, in combination with standard dose enzalutamide. The determination of ORIC-101 dose relied heavily on extensive translational work that was an integral component of the trial. This effort included baseline and on-study tumor biopsies, and serial blood sampling for pharmacokinetics, pharmacodynamics of GR signaling and tumor genomic profiling at baseline and longitudinally on study. Pharmacokinetic sampling demonstrated that at the RP2D, we were achieving exposures of ORIC-101 that were sufficient to inhibit the target. And through our pharmacodynamic studies, we were also able to confirm that we were achieving targets shutdown through the measurement of downstream GR target genes. After establishing the RP2D, we enrolled patients into the dose expansion portion of the trial with a plan to interim analysis after 28 patients. The primary endpoint of part two was disease control rate at 12 weeks, with progression free survival as an important secondary endpoint. Another important consideration was that through the profiling of patient tumors at baseline, we were able to identify a target patient population for ORIC-101 in which we would expect GR to be a potentially active mechanism of resistance. This population excludes patients whose tumors harbor one of the well described alternate mechanisms of resistance, namely primary resistance variants of the androgen receptor, such as splice variants, or point mutations that inhibit enzalutamide binding and markers of lineage plasticity, implying that the cancer had become AR-independent. In addition, we would also focus on the patients whose tumors were high expresses of the glucocorticoid receptor, which is the target of ORIC-101. After enrolling 10 patients to identify the RP2D in part one per protocol, we enrolled 28 patients into the dose expansion and followed them for at least 12 weeks in order to perform the primary efficacy analysis of disease control rate. Whereas previously with small numbers, we had focused on time on treatment as an outcome measure now with the additional patients and follow up, we shifted to our secondary endpoint of progression free survival, which was – which has ample regulatory precedent. And although this was a single arm study, we referenced as benchmarks of efficacy, the progression free survival for such agents as cabazitaxel and docetaxel, which are used in the post enzalutamide setting, as well as the new agents and combinations that are in development, such as cabozantinib plus atezolizumab. Turning to Slide 7, let me summarize the results of this analysis. First, in terms of safety, the combination regimen was generally well tolerated at the recommended Phase 2 dose. Next with respect to drug exposure and target engagement, extensive PK/PD work demonstrated that we were achieving ORIC-101 levels sufficient for GR target coverage, which we were able to confirm by measuring the down regulation of GR target genes. Finally, based upon tumor biopsies at baseline, we identified that the majority of patient tumors expressed moderate to high levels of Gr. Nevertheless, despite achieving ORIC-101 exposures consistent with biological activity, we were not able to demonstrate evidence of sufficient clinical benefit on any of the efficacy endpoints. In particular, the primary endpoint of disease control rate at 12 weeks in the target patient population of patients with moderate to high GR expression, and no evidence of alternate resistance through AR alterations or lineage plasticity was 33.3%. And the median PFS in the same patient population was 3.7 months. Of note, these values were not meaningfully different from the DCR and PFS recorded in the unselected patient population. In the context of the efficacy of approved therapies for patients after progression on an AR modulator, as well as the efficacy data with new therapies and regimens currently in development, the outcome seen in our study of ORIC-101 with enzalutamide were insufficient to support continued development. Turning to Slide 9, the second trial studied ORIC-101 in combination with nab-paclitaxel, in patients with advanced solid tumors. This multicenter open label study was also performed in two parts. We previously reported on part one, which was the dose escalation portion of the trial, through which we identified the RP2D of ORIC-101 in combination with nab-paclitaxel to be $160 milligrams of ORIC-101 with 75 milligrams per meter squared of nab-paclitaxel weekly for three weeks on a four-week cycle. In this study, as with the enzalutamide study, we had an extensive translational component, including pharmacokinetic sampling and pharmacodynamic testing of GR target genes, which demonstrated that at the RP2D, we were achieving exposures of ORIC-101 sufficient to inhibit the target and that we were achieving target shutdown. And the nab-paclitaxel dose, although lower than the labeled dose for frontline therapy, resulted in rates of neutropenia without growth factor support that indicated that we had a sufficient dose for these late line patients. After establishing the RP2D, we enrolled patients in the multi cohort dose expansion portion of the trial with three cohorts of interest, pancreatic ductal adenocarcinoma, ovarian cancer, and triple negative breast cancer. And the fourth cohort opened to patients with other tumor types. The primary endpoint of part two was objective response rate, with progression free survival as an important secondary endpoint. The eligible patient population was defined to again put us in the best position to identify clinical signal in a single arm setting as efficiently as possible. Specifically, we required patients in the dose expansion to have previously been treated with and progressed on a taxane-based therapy. While this is a higher bar, we felt that only in this way could we distinguish an ORIC-101 effect from pure taxane-driven clinical activity. While there is a taxane, retreatment effect in ovarian cancer and TNBC, this effect is generally modest. And so we set a benchmark for PFS in our study of six months for ovarian cancer. On the other hand in relapsed PDAC, there is no measurable taxane retreatment effect reported in the literature. And so we were looking to achieve a PFS of three months or longer with ORIC-101 and nab-paclitaxel in this cohort. After enrolling 21 patients to identify the RP2D in part one, we enrolled a total of 61 patients across the four dose expansion cohorts and follow them for at least 12 weeks in order to perform the primary efficacy analysis. Turning to Slide 10, the safety profile of this combination regimen was generally well tolerated at the recommended Phase 2 dose. And as I stated, PK data showed good target coverage and PD data demonstrated evidence of target engagement. In addition, baseline biopsy of patient tumors showed high levels of GR expression across most tumor types, but particularly in two of the tumor types of interest, PDAC and ovarian cancer, expression was so high across most patients tested in these two tumor types that pre selection by GR status was not necessary to identify a subset target patient population. Although we demonstrated evidence of biological activity and high levels of the target glucocorticoid receptor, we saw only one confirmed partial response in the ovarian cancer cohort, and no objective responses in the PDAC cohort. Furthermore, the median progression free survivals were 1.9 months at PDAC and 2.2 months in ovarian cancer in these. In these patients who are taxane pretreated, we did not see sufficient evidence that the addition of ORIC-101 to nab-paclitaxel reverse resistance and resensitize these patients tumors to retreatment with taxane chemotherapy. Therefore, we conclude from these data in these expansion cohorts that there was insufficient activity to support continued clinical development of this regimen. Now, turning to Slide 11, I’d like to review what we’ve learned from these two clinical trials and consider how that might help us interpret the clinical data presented here today, and offer our opinion on why we may not have seen sufficient clinical benefit. First, we learned that a glucocorticoid receptor inhibitor could be safely combined with both cytotoxic chemotherapy, as well as an androgen receptor modulator. Second, we learned that in these combinations, ORIC-101 was capable of achieving clinical exposures in patients sufficient to cover and inhibit the target glucocorticoid receptor. We could measure this effect of GR target shutdown and patient samples longitudinally over the course of treatment. So if we were hitting and shutting down the target, then why did we not see clinical effect. From the translational work we performed as part of both studies, the tumor genomic profiling suggested that an answer may lie in tumor heterogeneity and/or redundancy of resistance mechanism. By tumor heterogeneity, I mean differences within tumor lesions and between tumor lesions in the relevance of GR as a resistance pathway. In a single tumor, some cells may indeed be relying upon GR as a resistance pathway, but other cells in that same tumor may be relying upon alternate non-GR mechanisms. A similar difference could also be present between two separate tumors within a single patient. We would expect ORIC-101 would only affect the cells with GR as a resistance mechanism, while not affecting the other cells, resulting in absence of measurable clinical benefit. In addition, resistance pathways may be redundant within a cell. In such a setting, one or more coexisting resistance pathways in addition to GR may be sufficient to drive tumor progression when GR is inhibited. Such tumor complexity may be a possible explanation for the lack of clinical benefit seen in these two clinical trials. And then finally, it’s possible that the GR pathway itself is not a key tumor dependency in patients. And so observations made in the lab don’t transfer to patients in a clinical setting. We’re obviously disappointed that the results from these two clinical trials didn’t meet our bar for clinical benefit and further development. Negative trials are not uncommon in oncology drug development, especially when studying novel target biology, which doesn’t always translate into the clinic. For that reason, we designed these studies with clearly defined patient populations to enable us to get to an answer as quickly and as efficiently as possible. I think we achieved that. The studies were well run, and they delivered sufficient data to enable us to make the tough, but right decision to discontinue the ORIC-101 program. We expect to share more details on these clinical studies in future publications. In conclusion, I would like to thank the ORIC-101 team, the study investigators and the study support staff at all our participating clinical sites, and most of all the patients who participated in the trials and their families. With that, let me hand it back to Jacob.
Jacob Chacko: Thank you, Pratik. Now turning to Slide 13. At ORIC, our mission is overcoming resistance in cancer in inherently challenging goal. It’s for that reason that we have adhere to certain core principles to guide our journey. First, our patients are battling for their lives. So we’re going to continue tackling areas of high unmet need, where we can have a meaningful impact. Second, we will continue to design trials that allow us to make data-driven decisions and get to an answer as efficiently as possible. So we can allocate resources into our most promising programs. And finally, we’ve been explicit about our intent to assemble a pipeline through both internal discovery and external BD that has a mixture of novel first-in-class targets that rely on differentiated biological insights, as well as potentially best-in-class chemistry approaches to validated targets in order to strike the right aggregate risk profile across the entire pipeline. Last year, we filed three INDs or equivalents for single agent trials been initiated this here for ORIC-533 in multiple myeloma, or ORIC-114 in EGFR/HER2 cancers and ORIC-44 in prostate cancer. With data from all three programs expected in the first half of 2023. In just the first quarter of this year, we’ve enrolled our first patient on ORIC-533, we’ve cleared our CTA and initiated multiple clinical sites in Korea for ORIC-144, and we’re in the process of activating sites for ORIC-944. Beyond these three clinical stage programs, our discovery research team last year advanced two programs in the lead optimization, one of which we recently introduced as our PLK4 program, focused on novel highly selective inhibitors, targeting asynthetic lethality approach as a potential treatment for breast cancer. In short, although 101 is not progressing to the next stage, our pipeline is one of the most robust and small cap biotech, and we remain committed to our goal of developing life-changing therapies for patients with cancer. Now, let me turn it over to Dominic to summarize our financials, revised cash, runway and upcoming milestones.
Dominic Piscitelli: Thanks, Jacob. Turning to Slide 14, operating expenses for the fourth quarter of 2021 totaled $22.8 million, resulting in a net loss of $22.8 million. For the full year 2021, [Author ID1: at Tue Mar 22 04:48:00 2022 ]operating expenses totaled $78.9 million, resulting in a net loss of $78.[Author ID1: at Tue Mar 22 04:48:00 2022 ]7 million.[Author ID1: at Tue Mar 22 04:49:00 2022 ] Net cash used in operating activities for the 12 months ended December 31,[Author ID1: at Tue Mar 22 04:49:00 2022 ] 2021 totaled approximately $60 million. We ended the year with $280.4 million in cash and investments. As a result of the discontinuation of ORIC-101, we now expect our cash runway to extend into the second half of 2024, which is well beyond the expected initial data disclosures from our three clinical programs in the first half of 2023. Please see our press release and 10-K for additional details about our fourth quarter and full year 2021 financial results. We’ll wrap up our prepared remarks on Slide 15. We’re very proud of the team and pipeline that we’ve assembled here at ORIC. While we are disappointed that ORIC-101 won’t be advancing, we’ve always been committed to making rapid and data-driven decisions and we are excited about the robust pipeline of potential best-in-class and first-in-class molecules that we have assembled. We expect to provide data updates from our three ongoing clinical programs in the first half of 2023. These include initial Phase 1 data from ORIC-533 in patients with multiple myeloma, initial Phase 1 data from ORIC-114 in EGFR/HER2-driven cancers, and initial phase one data from ORIC-944 in patients with prostate cancer. Before we open it up to Q&A, I’d like to thank all the investigators and the entire ORIC team who’ve worked throughout the COVID pandemic, to continue tackling our mission on behalf of patients. And mostly – most importantly, I’d like to thank our patients and their families, whom we hope to help overcome resistance in cancer. With that, let’s open it up to Q&A.
Operator: [Operator Instructions] Our first question will come from the line of Anupam Rama from JPMorgan. You may begin.
Anupam Rama: Hey, guys, thanks so much for taking the question. I know on Slide 11, you guys outlined the potential reasons for lack of benefit with ORIC-101. But I guess, more mechanistically like where do you think the thesis broke down here given Corcept had stat SIG results in ovarian cancer? And you guys showed some interesting sort of stable disease duration benefits in PDAC previously? Thanks so much.
Jacob Chacko: Hey, Anupam, thanks for the question. I’ll have Pratik take that.
Pratik Multani: Hey, Anupam. So good question. I think it’s a little bit hard for us to comment on the Corcept data in their, especially in their ovarian cancer study, because we don’t have full insight into their study beyond some of the top line results in their conference presentation from last year. But I do think the two populations theirs and ours are likely different and we’re treated differently. Our study, as we’ve emphasized, required patients to have received and progressed on a taxane continuing regimen. And we don’t know how that compares with the Relic correlate studies, they require platinum resistance. But we’re silent on taxane progression. Also, if you look at their presentation from last year, their population had 2.5 prior therapies in the ovarian cancer study, whereas ours, it’s for prior therapy. So certainly, we had a more refractory population and by design, we wanted patients who are taxane refractory because we wanted to demonstrate in ORIC-101 effect and not a taxane retreatment effect, which can be seen in ovarian cancer. We don’t have the taxing interaction with ORIC-101, the PK interaction, but the Relic correlate molecule does. And we don’t know that PK across the three arms of their study. And then finally, we’ve also worked hard to develop a regimen that did not require growth factor support prophylactically, which is kind of the standard of care in this patient population, the course of regimen does require that, however, in their control arm that only got the Abraxane, only half the patients got GCSF versus 100% on the experimental arm. So, we don’t – we think that the two studies really can’t be compared side by side because of the difference in patient populations and and how they were treated.
Jacob Chacko: Yeah. So, Anupam, just adding to what Pratik mentioned, I think we very deliberately set ourselves up for a high bar in to find signal in terms of taking on a late line patient population. But that was important in – for a combination regimen in a single arm study, we had to set that kind of a high bar, so that we could clearly call the question of whether or not there was signal. And in terms of managing our resources prudently, that’s why we did that, so that we can make this decision as quickly as possible and that’s why we’ve come to the conclusion that we did today. And a separate point, as Pratik mentioned about the use of GCSF, we felt that it was pretty important from a both a patient care perspective, as well as just what would be commercially viable to be able to thread that needle without GCSF. So again, that was an explicit decision that we made in charting out a longer-term potential path here.
Anupam Rama: Thanks so much for taking our question.
Jacob Chacko: Thank you.
Operator: Our next question will come from the line of Kevin DeGeeter from Oppenheimer. You may begin.
Kevin DeGeeter: Okay, great. Thanks for taking our questions. Appreciate the Relic transparent release today. Pratik, in the interest of transparency, can you just comment on the tumor agnostic basket, any findings in there that you think could be hypothesis generating for others who may explore the field subsequently?
Jacob Chacko: Sure, happy to do so. So we did have – we treated 20 patients across seven tumor types, and that other tumor basket. And we saw one partial response in a patient with ovarian or with a esophageal cancer and nothing else.
Kevin DeGeeter: Got it. Thanks for that. And then with regards to the PLK4 program, can you just talk a little bit about target product profile there in terms of selectivity of the compound for PLK4, and just how we sort of think about breast cancer as the optimal population to explore that hypothesis?
Jacob Chacko: Yeah, Kevin, I can talk it at a very high level about it, just because I don’t want to front run the preclinical poster we’ve got coming out of ACR here in a couple of weeks. But essentially, the TPP is aiming to be very potent, and very selective. It is a key synthetic lethality pathway, and it’s in the tumor type that’s of high interest to us in breast cancer. So it fits with everything else that we do in like Target wise internally. But I’d ask you to maybe hold off for a few weeks or a month or so here until we present the poster in ACR, and then we can get into more detail on that.
Kevin DeGeeter: Great, thanks for taking our questions.
Jacob Chacko: Thank you, Kevin.
Operator: Our next question comes from the line of Collen Kusy from Baird. You may begin.
Collen Kusy: Great. Good afternoon. Thanks for the updates and thanks for taking your questions. So first one on ORIC-101 and prostate. I think the last updated that triple conference, you had four patients that were still on treatment at that time. Give me an update on what their time on treatment was?
Jacob Chacko: Yeah, so we had six patients in that bucket at the time and four were ongoing at the time of the triple conference presentation. They have all since progressed, based on radiographic progression, their time on treatment, 2 or 3.7 months, one at 7.1 months and one at 9.2 months. So they all have come off sunset press.
Collen Kusy: Okay, that’s helpful. Thank you. And you had made a comment in the presentation about how the PFS for the selected patients and the unselected patients were similar. How should we understand what the outcome was there?
Jacob Chacko: Sure. That’s a good question. Let me sort of expand on that the. The patients with the air resistance variants and the lineage plasticy markers did progress very rapidly. So these were the patients who had signs of their tumor already being AR resistance. So enzalutamide and returning sensitivity enzalutamide wasn’t going to do provide any benefit to them. And so that was not part of our target patient population. And so when we did exclude them that did push up the PFS of the remaining group, and so then we subset of the remaining patients by baseline GR expression status, because we’re interested in patients who had high GR expression. But there were patients who for whom we did not have information on GR expression. And the reason was that there were no tumor cells in their biopsy specimen. And this group had a relatively longer PFS, and it’s likely because they had an overall lower tumor burden. So when we removed the GR unknown group, the PFS in the GR high group went back down. And so that’s why we – overall didn’t see a difference between the two selected and unselected populations.
Collen Kusy: That’s interesting. Thank you. And last one, for me. I think prostate is also going to be a focus for ORIC-944. So are there any learnings you think you can take from this development and kind of apply that to future trials of prostate cancer?
Jacob Chacko: Sure. So this is an entirely different target. And rather than reversing resistance, of nine for four has the potential for single agent activity. And we’ve demonstrated that in multiple enzalutamide resistant prostate cancer models is something we didn’t have with ORIC-101, which going into the clinic didn’t have the potential for single agent activity. In addition, EED inhibition represents a novel mechanism of action and it’s relevant while tumor as tumors evolve. While for ORIC-101, we were essentially trying to revive enzalutamide activity, a mechanism which the cell had already become resistant to. So we think that EED is taking sort of a fresh pass at the cancer cell. And despite the fact that there are potential resistance mechanisms in these late-light patients, EED would be novel for those cells and potentially clinically active. That said, we do have as we had in our work one on one studies and extensive translational components to look at tumor heterogeneity and other resistance mechanisms. So we can characterize the patients on study more fully, and potentially come up with a target patient subset that would be more amenable to EED inhibition.
Collen Kusy: Great. Thanks for taking our questions.
Jacob Chacko: Thanks, Collen.
Operator: Our next question comes from line of Maury Raycroft from Jefferies. You may begin.
Maury Raycroft: Hi, thank you for taking my questions, too. I was going to ask one on ORIC-101 and then one on 533. I guess for one on one, can you expand on what you saw with tumor heterogeneity and discuss an example of tumor heterogeneity you observed in the study?
Jacob Chacko: Sure. So we probably have the best data from a prostate study. We were able to do baseline and on study biopsies as well as circulating tumor DNA profiling, so we could watch the tumors evolve while the patients were on the study. And so, in that trial, we saw multiple examples of patients who, despite being within our target patient population, so they did not have AR resistance variants or markers of lineage plasticity, and were GR high at baseline. They gained one or more of these resistance mechanisms or other potential resistance factors while on study, such as gaining AR-V7 or MiC or a loss of P10, or TP53. And some of these patients these alternate clones were minor at baseline, but grew while on study. And so that was the heterogeneity and redundant resistance mechanisms I was referring to earlier.
Maury Raycroft: Got it. Okay, interesting. And for 533, the monotherapy data in triple class refractory myeloma, that’s not expected until first half of 2023. But can you comment if you’re in discussions with pharma partners to evaluate combo regimens in myeloma and other tumor types run in parallel?
Jacob Chacko: Not, more than this, Jacob, I can’t comment specifically. But I’ll just tell you generically that we have lots of conversations along those lines with lots of pharma partners on the various programs in our pipeline. But we don’t really comment on specific discussions of individual programs.
Maury Raycroft: Got it. And for combo strategy, is there anything additionally you’re saying at this point on that?
Jacob Chacko: The one thing and I think your question highlights it is, we’re absolutely in the mindset that for 533, we’re not planning to run out a single agent trial over a long period of time, and then decide at that point, whether we’re going to green light a combo or not. It’s pretty clear here that in that triple quad, Penta refractory population, if we see even modest activity as a single agent, that we got to quickly explore that in combinations. And you’ll remember that Ken Anderson in the call that we hosted in December at ASH, Dr. Anderson, you mentioned exactly that point that as soon as you see model single agent activity, you ought to test combinations, you probably had to test multiple combinations, in terms of combination partners, meaning that the preclinical models don’t give you great evidence of one specific combo class to combine with. So we probably will combine with multiple of the combination classes that you might think of doing. And we would do that pretty much, I mean, almost in parallel with the single agent studies that are going on provided that we’ve seen that modest activity that I mentioned.
Maury Raycroft: Got it. Okay. Thank you for taking my question.
Jacob Chacko: That’s where you were driving your question about recessions we may or may not be happy. Yeah.
Maury Raycroft: Right. Thank you.
Jacob Chacko: Yeah. Thanks, Maury.
Operator: Our next question comes from the line of Yigal Nochomovitz from Citi. You may begin.
Unidentified Analyst: Hi, team, this is Asha Mubarak on to results. Thanks for taking my question and sorry to hear about the discontinuation. I think you alluded to this in the previous question, but can you discuss a little more what secondary pathways of resistance are hypothesizing may have contributed to the lack of resensitization?
Jacob Chacko: So some of these were ones that we screened out at baseline, but developed while on study. So AR-V7 would be a resistance pathway, that secondary alternate that restore GR inhibition wouldn’t address that. P-10 loss, TP53 loss are also associated with resistance. So those are the other mechanisms that we saw, and we saw others as well as those are examples.
Unidentified Analyst: Okay, got it. And then maybe switching to the CD73, have you guided to when you expect to complete enrollment in the Phase 1b? And maybe what does that imply about what kind of follow-up you might present extra?
Jacob Chacko: We haven’t guided at this point. It’s just too early, just given the trial initiated literally this quarter. So we have not provided that guidance yet.
Unidentified Analyst: Okay. Got it. Thank you very much.
Operator: Our next question will be from the line of Michael Schmidt from Guggenheim. You may begin.
Yige Guo: Hey, good afternoon. This is Yige on for Michael. Thanks for taking our questions. Two questions on your pipeline programs. The first one on your new PLK4 program, can you maybe help us understand the opportunity and the size of the TRIM37 amplification? And secondly, on 114, you initiated the Phase 1 study. Help us understand how you plan to measure 114 CNS activity in the Phase 1 study? And will you plan to enroll active premed patients in the future? Thank you.
Jacob Chacko: Hey, thanks. I’ll take the first and I’ll ask Pratik to take the second. So on the first, as I mentioned earlier to Kevin, we probably – we’ve got a poster coming up at ACR on PLK4. So I probably defer the specific answers around market size and just differentiation until then. I think the main thing to point out on PLK4 is, it’s totally consistent with what our strategy has been from the beginning. We plan to put forward programs that are both from our internal discovery programs, as well as through external opportunistic BD. In this case, it’s one that came from our internal discovery efforts. single agent potential mechanism of action, like I said, a synthetic lethality pathway that’s relevant to breast cancer, plus a couple other tumor types. And importantly, and we’ve been explicit about this, as well as we’ve always wanted our pipeline to have a mix of first-in-class targets that rely on differentiated biological insights, and then potentially best-in-class targets that rely on chemistry or biological insights. And in this case, this is we believe a potential first-in-class opportunity. Our team got to jump on this target a while back ahead of a paper that was published in nature that came out last year. And so we’re pretty excited about it because it’s a finishing first-in-class opportunity, like I said, with a single agent hypothesis in the tumor type that we care a lot about. So stay tuned for the poster at ACR and then we can get into more specifics at that point.
Pratik Multani: Hi, this is Pratik. To your question about 114 and CNS activity. So we are more liberal in our Phase 1 eligibility criteria in terms of allowing patients into the study not just with treated unstable brain mets, which is what most other studies allow, but also allowing patients with active brain mets as well, that are asymptomatic. So we are allowing untreated pre mets into even our Phase 1.
Yige Guo: All right. Thank you very much.
Jacob Chacko: Thanks, Yige.
Operator: Thank you. I’m not showing any further questions in the queue. That will conclude our conference call for today. Thank you so much for your participation, and your interest in ORIC. You may now disconnect. Everyone, have a great day.