Good morning, everyone. Welcome to Schrödinger's first Pipeline Day. I'd like to welcome everyone who's in the room and everyone who's joined the webcast. If you're on the webcast, you may have noticed that we launched our new website this week, which we're really excited about. During today's presentation, we are, of course, going to make forward-looking statements about our business, and these reflect our views as of today. Actual results may differ materially, and I encourage you to read the Risk Factors section in our SEC filings, including our most recent SEC filing, which was our 10-Q. Turning to our agenda, we're going to spend some time today doing a deep dive into our pipeline. That includes our MALT1 inhibitor, SGR-1505, our CDC7 inhibitor, SGR-2921, and our WEE1-MYT1 inhibitor, SGR-3515.
We're going to also bookend these scientific presentations with some commentary about the business. We're excited to have two physicians with us today. We have Dr. Timothy Yap, who's joining us here in the room, and we have Dr. Elie Traer, who's joining us remotely. We're going to wrap up with a Q&A session, and if you're in the room, you'll be able, of course, to ask your questions here. If you're joining us on the webcast, please note that there's a Q&A box. You can type in your questions. The IR team will be sure that they are asked on your behalf. And with that, I would like to turn the podium over to Ramy.
Thanks, Karen. Okay, and the green button advances. Great. Thank you so much, everybody, for coming. We're really excited to present to you at our first Pipeline Day, our proprietary programs, and so I will keep this very short. I think you know, I'm very excited. I would have loved to have been given an hour to talk about the platform and so on, but we did that last year at Platform Day, so I'm going to hand it over very quickly over to Karen and the team. But I have an allocation of just a few slides I wanted to go through. So let me first remind you about our highly synergistic and balanced business model. You know that we have developed a really extraordinary platform over the past 33 years.
We've been working on this for a long time, and we licensed that platform to life science companies and materials companies. You can see there how many customers we have. To address a question that Mike asked us this morning through his report, we are still very confident about the full year guidance that we gave, the 15-18%. You're-- he's taking notes there. And so really happy to be reporting that. Things are going very well in the software business. Now, we also leverage our platform in a number of other ways. You've heard us talk a lot about it. We're not going to talk too much about it today, so I'll just spend, you know, 30 seconds on it now.
We have a number of collaborations, both on the drug discovery side and also on the material science side. We have, as you see there, 19 active projects in drug discovery and material science, and you can see in the little tiny note there, I'm going to touch on this in a moment, we also have 13 other collaborations that are at the stage of either being in the clinic or in IND-enabling studies. And then, of course, what you're going to hear about today is our proprietary pipeline. You see there, there are at least seven programs. There are more. We will show that there are some undisclosed, but we've disclosed seven, and again, this is where we're going to focus. So I got to have one slide about the platform.
Not going to spend a lot of time on it, but I think it's important, and I think this is a nice view of sort of really the extraordinary progress that we've made since the company was founded in 1990, 33 years ago. I mean, this has been a really huge focus. We think we've developed a platform that is, that is powerful and really truly differentiated. And you can see here, and I won't go through all of these, but you can see we've had a number of, of breakthroughs over the year. These have had really profound impacts on, on the progression of our own programs, on our collaborative programs, and of course, also on our thousands of, of, of customers.
There's a lot of validation around that, which is, in some sense, maybe it's not necessary to dig deep into the platform. We can just look at the validation. So that's the next slide. I think this is really quite compelling. We have, at the moment, 8 programs that are in the clinic. You can see 3 of them are in Phase II, 5 are in Phase I. We even have a couple of marketed drugs from our collaboration with Agios that goes a ways back. We also have, and this is what I was alluding to on the first slide, 5 additional programs that are in IND-enabling studies and progressing and obviously expected to be in the clinic in due course. We also have, and again, we won't talk much about this...
Well, sorry, we won't talk at all about it today, but it's worth mentioning that we have quite a number of other drug discovery programs at various preclinical or discovery stages with the large number of partners that you see there at the bottom of the slide. So on my last slide, I promised you it would, it'd be short. On my last slide, I just wanted to take one more opportunity to talk about how the platform has really enabled some extremely important sort of processes in drug discovery. So all of these are a big deal, so I'm almost I probably will start each one of them by saying, "This is a big deal," but they are.
The first one is we are now at a point where we can pretty reliably and on a pretty large scale predict the structures of proteins, either protein structures that start off from maybe a low-resolution cryo-EM structure, or X-ray structure, or a homology model, or even a protein, let's say, a high-resolution protein, but there's no ligand bound. And we have developed all this technology for determining the structures of proteins. This is a really big deal because that's the input to the physics-based methods that we've developed. So this is. There's been a lot of work in this area. We continue to invest in it, but you'll see that's having a really big impact on our ability to essentially enable more and more targets for the technology. So our domain of applicability keeps increasing. That's very exciting.
We also have gotten to a point where we can very reliably assess the druggability of a target. What does that mean? That means, well, before you spend 5 years and $ millions and thousands of molecules made, it might be good to know before you spend a dollar, before you make a single molecule, is this—what's the best modality to go after a target? You can imagine how useful that is, and we have technology that now allows us to do that. It's quite reliable, and you can imagine the impact that's having.
Now, in the more obvious areas, of course, we've now developed technology, and it's gotten really reliable, where not only can we identify hits as starting points for drug discovery projects, but we can identify a diverse set, a large number of diverse, distinct chemical chemotypes, and that has a really big impact on having all these different starting points to identify the particular chemotype that's gonna be able to make it all the way and be able to produce a molecule that has all the properties that we're looking for. And then finally, and probably most importantly, although of course, all these are important, is we can now, with these physics-based methods, reliably and pretty rapidly, as you'll see, we're gonna talk about this, identify development candidates through multi-parameter optimization.
And these development candidates, again, as you'll see, have very well-balanced properties, the kinds of properties that are required to actually have a drug, and this is having a really big impact on our project. So when we combine all of this, you know, you, you'll see what we're talking about, you know, in the next couple of hours. And so just really quick preview, I'll spend just a second on this. Again, you're gonna hear a lot about this, but I just wanted to highlight the sort of impact that the thing I just described has had on at least these three most advanced programs.
You can see we've actually identified, in the case of MALT1, our SGR-1505, molecules that are considerably more potent than competitor molecules and have the necessary properties to differentiate them and to continue to be able to progress them. In this case, low drug-drug interaction potential, which enables what's pretty important, which is combinations in this case. With CDC7, again, we've identified highly potent selective inhibitors with low predicted dose. Obviously, that's important. And again, in this particular case, the extent that these programs are, you know, well suited for a combination, we've also dialed out the potential for drug-drug interaction.
Again, in WEE1, and you'll be hearing a lot about this, WEE1/MYT1, not only have we designed highly potent molecules and really extraordinarily potent molecules, but we've optimized the affinity for both of these targets to get that balance right, you know, to maximize the efficacy. Again, you're gonna hear a lot more about that. And again, drug-like properties, that's incredibly important. We're not just optimizing one or two properties. We're optimizing all of the properties using this platform. And so we have good properties, and in this case, again, low potential for drug-drug interactions, which is important in combinations. So I think that's a good time to hand it over to Karen.
Thank you.
Great. Thanks.
Thank you, Ramy, and good morning, everyone. It's great to see you all. So before we dive into the programs, I'm going to share a little bit about our strategy for how we select programs. First of all, foundational to the way we pick programs is human evidence. We believe it's very important for us to work on targets that have some kind of validation data. In addition, we focus on specific design challenges, and what I mean by that, and Ramy just alluded to it, is the potential to obtain more efficacy and safety from mechanisms that have either been in the clinic or novel mechanisms, where there's an opportunity for a first-in-class drug, and this really culminates in having a differentiated target product profile for the program. Finally, and perhaps most importantly, platform enablement.
This is absolutely key. You just heard from Ramy. We are able to have profound impact on programs, but first they have to be enabled for our platform, and that allows us, obviously, to solve some very difficult design challenges that in some cases have not been solved by prior molecules. Oops! Just going too far there. Sorry. So just pausing on the genetic validation. I won't go through this in exquisite detail, but just to say that there are three important features that we focus on, one of which is: is there evidence of a dose response from human genetics or from prior clinical trials?
In panel one, what you can see is a typical genotype, phenotype dose response, where we're looking for the relationship between either a gain of function relative to normal function or a loss of function, or in some cases, both, and I'll come back to that later on. The nice thing about these gene dose response relationships is that they do give you some insight, not just into how that target might be applied to a particular indication, but also give you insight perhaps into the safety or therapeutic index for that target, because some of these gain or loss of function mutations can give you signals in other tissues. Finally, the best stuff is when you're able to actually phenocopy the behavior that you see in these genotype, phenotype responses with a drug.
Obviously, that's the goal of many drug discovery programs, and we pay attention to this because it's been shown that actually targets that have this kind of genotype, phenotype relationship actually have a fourfold, if not greater, chance of success in the clinic. Another focus for us, particularly obviously in our oncology area, is thinking about how do we open up the window between normal cells and cancer cells? As you know, cancer cells are addicted to certain pathways, inactivation of tumor suppressors or activation of drivers, escalation of the impact on, of DNA damage and insufficient repair has recently, actually historically, but even more recently, become a very interesting area that we believe represents an opportunity to focus on cancer cell vulnerabilities.
In addition, our synthetic lethality, particularly conditional synthetic lethality, you'll hear more about that as we go through our WEE1, MYT1, and PRMT5/MTA programs, and also inhibition of compensation mechanisms. All of these approaches can be leveraged to open up the therapeutic index between a normal cell and a cancer cell. So I've told you that we leverage strong human genetics, either, genetic data or human evidence coming from clinical trials where there's prior pharmacology or efficacy data. I've told you about cancer cell intrinsic vulnerabilities, but in particular, I wanna also focus on what we believe is an important portion of our strategy, which is that each of the mechanisms we're going to share with you today offer opportunities for combinations to enhance efficacy.
Now, these mechanisms will have activity on their own, but we believe combinations and rational sequencing with standard of care agents is actually a really important opportunity to deepen responses and to allow for resilience to resistance mechanisms. So, having shared that, I can now bucket our programs in these three different conceptual pillars. We have now multiple programs in our oncology space that are based on established or emerging clinical data. First of all, gain-of-function mutants or drivers and resistance mechanisms, our MYT1 program, our EGFR C797S program, and our SOS1 program, which, as you know, was partnered with BMS some time ago.
In addition, our WEE1 MYT1 program and our CDC7 programs are in the DNA damage repair space, and actually, WEE1 MYT1 also has a synthetic lethality component that you'll hear more about today, and our most recent addition is our PRMT5/MTA program that we disclosed on our last call. As I said, and I'm just gonna highlight again, we believe that each of these programs offers important opportunities for combinations. I'll get into a couple of these in more detail, but just to say that in addition to having activity on their own, we believe that these co-compounds or these mechanisms will combine well, not just with existing standard of care, but also emerging products.
So if you think about the multiple generations of BTK inhibitors, recent mechanisms like KRAS, older mechanisms like MEK and BRAF, we think that in the pathways that we're pursuing, these validated pathways, there's opportunity for combination. Today, you'll hear from Hamish about CDC7 and some of the combination data that we've been able to generate there. And also, I would say with PRMT5, as well as our SOS1 EGFR, there's an interesting opportunity for combinations in lung cancer. So briefly, I think we're all very familiar, for those of you who've just come back from the ASH meeting, a lot of very well-known mechanisms here. MYT1, for those that don't know it, is an emerging mechanism. It drives proliferation of B-cell addicted lymphomas.
There's genetic validation for this target, actually, and it's sort of in this pathway that's pretty well understood at this point. So at the B-cell receptor level, we obviously have BTK downstream of that. We've got BCL-2 inhibitors that have been used in the treatment of lymphomas. MYT1 is part of a complex called the CBM complex, and what you'll see from our data that we're going to be sharing with you this morning, MYT1 has an important role in this signaling pathway. We've shown some activity, obviously pre-clinically, and I'm excited that we'll be sharing—Margaret will be sharing our first clinical data for this mechanism.
Looking at lung cancer, while there's a lot of mechanisms in lung cancer, obviously, most famously EGFR, it's important to note that while there are many mechanisms, 1.8 million patients every year are still dying from lung cancer, and 70% of patients who are treated actually don't last beyond 5 years. So we believe there are new, important opportunities in lung cancer, including limiting and treating brain metastases, and we believe our next-generation EGFR compound has an opportunity in that space. In addition, PRMT5/MTA, which you'll hear more about later on, also has an opportunity in lung because of the fact that lung cancer has these MTAP-deleted phenotypes, which allows you to target them with this synthetic lethality approach.
And again, here in this MTAP pathway, you can see that there's multiple mechanisms, EGFR, SOS1, PRMT5, which can be combined with existing approved drugs, KRAS, RAF, MEK, et cetera. Finally, if we look now to our non-oncology portfolio, I already alluded to the fact that human genetic evidence, human evidence is very important to us. And when we think about those non-oncology programs, I already described to you that there are certain targets that have gain-of-function and loss-of-function phenotypes. EGFR is an example of that, it's a very famous one. LRRK2 is an example of that. In fact, MYT1 also fits into this category. These represent three of our programs. And then on the gain-of-function side, there are targets where you have profound impact of gain-of-function. NLRP3 is such an example.
I think we're all familiar with CAPS, which is a rare immunological disease. And these targets, in our opinion, fall in categories where they have some very interesting neighbors that have proven to be very successful in drug development or are still the subject of a lot of effort in our industry because of the validation that they have from humans. So finally, I'm going to pivot now just to talk about the fact that we're making a big investment in, obviously, our platform. For the drug discovery efforts, it's really important that we have high-resolution structures. So for the targets that I've just touched on in this opening set of remarks, we obviously have structures for those. But what's not on this slide is what's coming behind. We're really excited about our investment in structural biology.
We have a team who are now solving structures for our next waves of targets that we won't be discussing today. In addition, for this safety optimization, we are also solving structures of what's called off-targets, and here are two examples: UGT1A1 and hERG. For those of you that don't know, these are targets that are very often challenging in drug discovery programs. UGT1A1 is a target that obviously is in the liver, which is an important area. Whether they're CYP enzymes or other enzymes, it's important to optimize against those targets. And then hERG is a channel that's expressed in the heart, and this is just the tip of the iceberg. There are a lot of off-targets that we believe if we have structures for those, not only can we optimize for the on-target, we can also optimize away from the off-target.
In closing, our proprietary pipeline is expanding. We have two Phase I programs now, two in the clinic, a third IND to be filed next year, and we're going to share with you an update on our emerging discovery programs that are heading towards the clinic in the future. With that, I think it's time to transition to talking about our MYT1 program in more detail. I'll be joined by Margaret Dugan, our CMO, as we go through our Phase I data. Before we do that, I'll just return again to this image of the B-cell. In addition to the well-known targets, it's important to focus on the fact that while we do have great drugs... and actually, again, for those that have come back from ASH, there's a lot of great drugs that are emerging for B-cell malignancies.
But we also know that, for example, in the BTK inhibitor space, there are resistance mutants. So the C481S and the L528W mutations are both associated with treatment failure. And what you can see here is that in addition to very interesting and approved drugs that are having a profound effect on these diseases, we are in a situation where resistance to those BTK inhibitors leaves open opportunity for additional small molecules, and MALT1 is downstream of this signaling pathway. In fact, there are many of these B-cell malignancies where MALT1 activity is constitutive, and you're seeing very upregulated NF-κB signaling, which drives proliferation of these cells. I also want to point to BCL-2.
We're going to show you some data that combining a MALT1 inhibitor with venetoclax, in this case, can lead to much more effective, inhibition of proliferation, and we believe this constitutes an opportunity for combinations or fixed-dose regimens to drive deeper responses. Over the last year or so, MALT1 inhibition via the protease site has been validated. So in addition to that genetic validation I spoke of for MALT1, we now have clinical data from third parties. The JNJ-6633 molecule established proof of concept for monotherapy and combination activity in human B-cell malignancies.
So in non-Hodgkin's lymphoma, I think it was at the EHA meeting earlier this year, we were able to understand that the J&J molecule has shown 28% ORR as monotherapy, and last year, there was data confirming that in CLL or SLL, combination with an exploratory BTK inhibitor led to 67% ORR. So this is the first clinical data for MALT1 in the patient population, the target patient population. We believe that based on the information we have, that I'm about to show you, that there is an opportunity for additional well-tolerated, potent, optimized inhibitors that have sustained target engagement in these indications. Finally, MALT1 has evidence from genetics in autoimmune disease, and we think this is a very interesting area that we will continue to explore. So coming back to SGR-1505, and now clinical-stage MALT1 inhibitor.
This compound shows excellent potency, not just in biochemical assays, but also in cell-based assays. So I'll very quickly walk you through this. You can see here that at the IC 50 is pretty potent, sub-100 nanomolar, even as low as a nanomolar in biochemical assays. And even when you move across to the, in the concentration it takes to provide 90% inhibition, we maintain very good potency. We've compared that now, and this was presented at ASH recently. We've compared that to J&J and the 6633 molecule that's been in the clinic. And I think what you can see is that as you move to that IC90 concentration required, you can see that there's a very big shift, in our hands, in our assays between our compound and J&J's.
Furthermore, in preparation for our clinical trials, we obviously had to identify a biomarker, and what you can see here on the panel on the left, I think it's the left from where you're sitting. We've been able to compare our compound to in preclinical studies as well as cell lines. And you can see that inhibition of IL-2 secretion in Jurkat cells, which is a T cell line, you can see very nice dose-dependent inhibition of IL-2. In addition, a sort of great way of checking whether you're inhibiting the CBM complex and NF-κB signaling is to look at IL-10. Data presented at ASH showed some time ago, actually, that we see very nice inhibition of plasma IL-10 in the efficacy models that we were testing.
Importantly, as we bridge to the clinic, we looked at human-derived, from human donors, T cells. What you can see in whole blood assays, when you're looking at whole blood cytokine release, we're able to determine that our molecule is indeed a lot more potent in human tissues, in this ex vivo assay, compared to the J&J molecule. We think this is very exciting. It gives us an opportunity to test this and further develop the compound. Finally, before I hand over to Margaret, just to remind you, we've shown you some of this data before. MYD88 inhibition in the context of SGR-1505 has very profound effects in a number of models.
So in a patient-derived tumor that's embedded into a preclinical model of ABC DLBCL, just as a sort of model that's been used by a lot of these compounds that have been approved. You can see that Schrödinger's compound, SGR-1505, in blue, has a very nice impact relative to ibrutinib. And when you combine those two agents, you're seeing very nice combination activity leading to regression. Similarly, in the MCL, you're seeing dose-dependent effects of our 1505 compound on tumor volume. So this is what we're looking at on these slides, is tumor volume over a time course.
And then finally, as I alluded to earlier on, for BCL-2 inhibitors, you're seeing SGR-1505 plus venetoclax, this time in a CDX model, having very nice, combination activity, on tumor volume. So with that, I will hand over to Margaret Dugan, our CMO, to take you through the Phase 1 data.
Thank you, Karen. The study in healthy subjects has been completed with a total of 73 patients that have been enrolled. The primary objective of that study was to assess the safety and tolerability of SGR-1505, with secondary endpoints to look at the pharmacokinetic characterization of single and multiple doses of 1505, and also to evaluate the effect of food and CYP3A4 inhibition on the pharmacokinetics of 1505. In addition, there were exploratory endpoints to assess the pharmacodynamic characterization of blood-based biomarkers and to evaluate a pharmacokinetic/pharmacodynamic analysis. The study population enrolled a mean age group of 30 years, ranging anywhere from 18 to 60 years. They were 62% male and 60% White, as well as 27% Asian. When we looked at the study, it enrolled sequentially into four parts.
Part A of the study was 5 ascending doses of a single dose, ranging from 25 milligrams all the way to 225 milligrams for a single dose, enrolling approximately 6 patients per each dose level. Part B was a multiple ascending dose, looking at drug dosing over 10 days, 75 milligrams and 150 milligrams once daily dosing, as well as a 100 milligram q12h dosing schedule as well, enrolling approximately 6 patients per dose level. In Part C, we set out to evaluate the effect of food on 1505 pharmacokinetics, where we enrolled patients in a 2-sequence crossover study.
Each sequence was either fasted, fed or fed, fasted, and eventually, we went on to Part D, which was to assess drug-drug interaction potential using a strong CYP3A4 inhibitor, posaconazole, where we dosed first with 1505 and then gave posaconazole over several days and then dosed with both drugs, 1505 and posaconazole. Looking now to the adverse events that happened on the trial, the human subject study, it was well tolerated across all of the doses treated in 73 subjects. There were 55% of subjects who experienced at least one treatment emergent adverse event, 96% of events were grade one, and 90% were not related to treatment.
One. There was 1 grade 3 treatment-emergent adverse event of neutropenia that was deemed not treatment-related in a patient who had a prior history of neutropenia, and there were no grade 4 treatment-emergent adverse events. Looking at the laboratory tests, the only ones there were, there were elevations, and these were not deemed to be clinically relevant, where bilirubin elevations occurred in 20% of the subjects. All were asymptomatic, predominantly grade 1, and none were grade 3 or 4. There were none that were associated with drug-related transaminase elevations, and all, most importantly, were reversible upon discontinuation of SGR-1505. There were no dose-limiting toxicities. Dose interruptions, 2 subjects had a single dose interruption due to an adverse event of nausea and H. influenzae infection, and 1 subject discontinued treatment due to COVID-19, which was deemed unrelated to study drug. No serious adverse events.
If we look now to the results of the single agent ascending dose pharmacokinetics, here you see in the figure represented were the time concentration plots, semi-log plots, looking at single agent ascending doses anywhere from 25 milligrams to 225 milligrams. Again, only one dose was administered. The results here are consistent that 1505 is rapidly absorbed with a Tmax anywhere from 2 to 4 hours, with a mean half-life ranging from 33 to 44 hours. In addition, there is dose proportional increase in 1505 exposure as measured by Cmax and AUC to infinity, up to the 100 milligram single dose.
Looking now at the results of the multiple ascending dose cohorts, you can see here pictured on the left, as you look at the screen, is the figure that represents the day 1 and day 10 concentration time semi-log plots for the multiple ascending doses of 75 milligrams and 150 milligrams. The data here presented shows that there is an approximate 2-fold increase in exposure on day 10 with the once daily dosing schedule. Looking at the plot on the right represents the concentration time semi-log plot for the 100 milligram Q12H dosing, and you can see here that there is an approximate 3.6-fold increase in exposure on day 10 when you administer it now on a Q12H dosing regimen. When we looked at our pharmacodynamic effects, as you can see here, MALT1 target engagement was established by IL-2 inhibition.
What we did was we looked at various cytokines, which are IL-2, interferon gamma, TNF alpha, as we excreted from activated T cells in patients at various time points in their treatment course, time to pharmacokinetic analysis. When we look at the graph as presented here, it's clear that at steady-state exposures achieved at 150 mg once daily or 100 mg Q12H, we have ≥75% inhibition of IL-2 secretion in the activated T cells. When we go to maintaining that inhibition, which we believe is the most important effect of our pharmacokinetics, we can see that maintaining greater than 90% IL-2 inhibition at Ctrough values was consistently achieved with 100 mg Q12H dosing versus what we saw similarly at once daily dosing. In summary, SGR-1505 has a differentiated preclinical profile.
We have had a very successful healthy subject study, which further informs us into our clinical development plans for our advanced cancer study. We received orphan drug designation approval in mantle cell lymphoma. We are now enrolling patients with relapsed or refractory B-cell malignancies into our Phase 1 study at sites both in the U.S. and Europe. There should be initial data expected in late 2024 or 2025. There are combination opportunities with standard of care agents, and we're looking for additional indications are under consideration. Thank you. I'd like to invite Dr. Timothy Yap, Professor of Investigational Therapeutics from MD Anderson, now to join, and he'll be speaking on WEE1. Tim?
Yeah. Thanks very much, Margaret.
Thank-
Thanks very much, Margaret, and, thanks to the Schrödinger leadership for the very kind invitation. So good morning, everyone, and, very nice to see many familiar faces around the room, and I'm sure online as well. So I've been asked to talk about how we're currently targeting the DDR, in cancer medicine today and really focus on WEE1 inhibitors. As, as many of you know, this is, an area that's very close to my heart, so, I might go on for a very long time. These are my disclosures. I'm kidding.
All right, so first of all, I thought it'd be good to just go back to the very beginning in terms of targeting the DDR, how we're really navigating a post-PARP inhibitor world, and we need to think about resistance, and then focusing really on WEE1 as a target. So as you know, we have four approved first-generation PARP inhibitors right now: olaparib, rucaparib, niraparib, and talazoparib. All approved on different indications, different settings, different molecular subtypes. So a very exciting area, but most importantly for me, it does provide proof of concept for a synthetically lethal approach in oncology, really validation of this approach. However, we know that the first-generation PARP inhibitors are associated with toxicities such as myelosuppression, GI toxicities, and these actually do limit their development. In addition to that, primary resistance is a problem.
Not all patients with BRCA-mutated cancers will respond. Secondary resistance is also an issue. Even if patients respond, resistance is unfortunately inevitable, and therefore, for myself as a physician, there's great responsibility, and really, I do strongly believe that there's great potential to really deepen the responses and to increase the durability of these patient benefit that we do see in patients. In addition to that, I think most excitingly for me as well, it's also the potential to widen the application of PARP inhibitors and other DDR agents that are currently out there, and as we're certainly seeing emerging data on this. So as I mentioned, we are in a post-PARP inhibitor world. We know that resistance to PARP inhibitors is complex. It is multifactorial, and it's because we don't really understand the underlying mechanisms very well.
And so we really need to focus our strategies to target resistance by thinking about new targets beyond PARP, to develop new drugs, to think about new predictive biomarkers beyond BRCA1 and BRCA2 mutations, and also to think about rational combinations moving forward. I'm a simple clinician, and I like to bucket things into three categories. So for me, in terms of PARP inhibitor resistance, here's my first category. First one is, as you know, is a well-known one. It's restoration of homologous recombination activity. So you've probably heard of BRCA reversions and other reversions of other alterations like RAD51, so on and so forth. There are also other mechanisms to restore homologous recombination activity. So that's bucket one for me. Bucket two, I think it's important, replication stress, and it is important because of the increased dependence on the ATR CHK1 replication checkpoint pathway.
It also gives us opportunities to target this, for example, with WEE1 inhibitors, with PKMYT1 inhibitors in the clinic. And then the third bucket is kind of my get-out clause. This is my catch-all bucket with everything else, right? Resistance through everything else. So you've got PK mechanisms, you've got other biomarkers like Schlafen 11, loss of EMT, so on and so forth. So what do we currently have, right now in the clinic that we can use to target some of these resistance mechanisms? Well, the good news is that the whole DDR therapeutic landscape has rapidly expanded beyond PARP inhibitors. You know, we now have 10 other classes or 11 other classes of agents that are currently out there, and this has really been facilitated through the discovery of novel precision targets that you've already heard about this morning.
This has been enabled through different technologies and advancements, such as genome sequencing, CRISPR technologies, so on and so forth. That's really allowed physicians like myself to use biomarker-driven patient selection strategies to really guide the clinical development of many of these drugs. These drugs include ATR, WEE1, ATM, DNA-PK, CHK1, the next generation PARP-1 selective drugs, CDC7, Pol theta, PKMYT1, USP1, and POLQ inhibitors. The list goes on because there are many in preclinical testing that are moving into the clinic. For me, taking a step back, you know, why I'm so excited by synthetic lethality is really the opportunity to go after untapped cancer lesions. The focus of precision oncology for the past 20, 30 years has really been focused on the usual gain-of-function alterations, EGFR, HER2, so on and so forth.
But that really comprises about 30% of the cancer lesions that we can potentially go after. And I'm thinking about lesions like CCNE1 amplification, going after tumor suppressor alterations as well. And to me, that untapped space comprises maybe about 71% of potential cancer lesions out there. And to raise the bar for our patients, I think we need to move into that, huge portion of that pie. I'm getting hungry now. So finally, thinking about WEE1, and as I think about WEE1, obviously, we now have multiple WEE1 inhibitors out there. I'm not gonna go through all of them, but it's really just to give you a flavor of the number of WEE1 inhibitors currently in development, and I guess one needs to think about how they're all differentiated from each other.
But as I think about the potential registration strategies for WEE1, again, categorizing things into different buckets, my first bucket are the monotherapy approaches, second bucket, potential combinations. Monotherapy, I think we need to select patients well. A good example for WEE1 inhibitors would be the CCNE1 amplified or cyclin E overexpressed tumors. Also, nice, strong signal in targeting uterine serous carcinoma. And then combination approaches, this is really vast, of course. We can think about ADC combinations, we can think about DDR combinations, IO combinations, and even what I call chemical BRCAness, where you use targeted agents to induce a BRCAness phenotype in HR-proficient tumors to try and synergize the drugs with a WEE1 inhibitor. So I thought I would talk a little bit about these different potential indications.
In terms of targeting CCNE1-high tumors, we know that CCNE1 amplification leads to cyclin E overexpression, and this is a key driver in many different tumors, as listed there on the top right. Uterine carcinosarcoma is certainly a real culprit there, and also ovarian, gastric, esophageal. This is because it promotes genetic instability, and we have shown that it does correlate with worse overall survival. And so, you know, the hypothesis here is that cancers harboring CCNE1 amplification will be highly sensitive and respond to WEE1 inhibitors. And to me, there's a great opportunity here because right now we have nothing that's approved for patients with tumors with CCNE1 amplification. And so monotherapy, I think that's a clear opportunity there. There's a clear biomarker. We have assays that measure CCNE1 amplification.
We're developing cyclin E IHC assays as well to do that. And I do think we are capturing patients. All right. CCNE1 amplification is estimated to be found in about 20%-30% of high-grade serous ovarian cancer and even higher with cyclin E overexpression. And we know that CCNE1 amplification is associated with platinum resistance and is different to BRCA mutations and the whole HRD landscape, if you like. And so I do think there's also great potential to think about other CCNE1 high tumors beyond ovarian cancer, such as uterine TNBC, gastric, esophageal, so on and so forth. So a big opportunity there.
In an investigator-initiated trial that was led by my colleague, Siqing Fu at MD Anderson, we conducted a study through the NCI using the WEE1 inhibitor adavosertib from AstraZeneca. This is monotherapy data. We did a tumor-agnostic approach, but every patient was required to have CCNE1 amplification. And you can see here that, you know, the overall response rate is nearly 30%. This is a heavily pretreated Phase 1 patient population. Overall survival is 9.9 months, PFS 4.1 months. The issue here was really the treatment-emergent adverse events, as you can see on the right. Don't worry, I'm not going to go through this, but it was really three areas of tox that we had seen: myelosuppression , fatigue, and GI toxicities.
So the key question is, you know, will the newer next generation WEE1 inhibitors widen the therapeutic window? And also, I think it also comes down to the clinical trial to really schedule and dose these drugs well enough such that one can actually avoid the toxicities that we do see and to try and widen the actual therapeutic window. So I do think that preclinical modeling is going to be absolutely critical. In addition to that, obviously, we know that there are emerging data as well with PKMYT1 inhibitors, also, CDK2 inhibitors in this space. Beyond CCNE1 amplification, uterine serous carcinoma is also a potential line of sight. This is a very aggressive form of endometrial cancer. We don't really have any good drugs for these unfortunate patients beyond first-line chemotherapy.
The hypothesis here is that because of cell cycle deregulation and high replication stress in these patients, in these tumors, this predicts for increased sensitivity to WEE1 inhibitors. Joyce Liu presented and has published now data in JCO, showing approximately 30% objective response rate, both confirmed and unconfirmed PRs, and also a duration of response of approximately 9 months. There's also another study, the U.K. study, FOCUS 4, Phase II study in newly diagnosed TP53 and KRAS-mutated metastatic colorectal cancer patients who are stable or responding to chemotherapy, who are then randomized either to receive the WEE1 inhibitor adavosertib versus active monitoring. You're probably asking why, and, you know, the hypothesis here is that DNA replication alterations that are seen in these tumor types will sensitize these tumors to WEE1 inhibitors.
It was a positive Phase II trial. The PFS, you can see there, was statistically significant versus active monitoring. In terms of combinations, I don't have time to go through all of the different types of combinations, but I certainly think a DDR/DDR combo makes a lot of sense. For example, combining WEE1 inhibitors with PARP inhibitors. We know that abnormal DDR and replication stress results in accumulation of DNA damage, and this leads to tumor progression. And we know separately, PARP inhibitors induce DDR replication stress, resulting in G2 arrest, while WEE1 inhibitors abrogate the cell cycle G2 arrest, allowing cells with unrepaired DNA damage to enter mitosis and undergo mitotic catastrophe and cell death. Thinking about a baggage claim conveyor belt that's gone out of control, you know.
We have done these trials, so we combined olaparib with adavosertib concurrently. We showed, you know, promising antitumor activity, ORR 30%, CBR nearly 90%, and a PFS in very advanced ovarian cancer patients of 6.4 months. These were all PARP inhibitor-resistant high-grade serous ovarian cancer patients. This was presented by my colleague, Shannon Westin. So the issue, though, is that while we did see promising activity, it was really the overlapping PARP inhibitor and WEE1 inhibitor toxicities when given concurrently. It made it really challenging to keep patients on drug for a long period of time. You can see the high dose reduction rates and also dose interruption rates. So we needed a better approach in terms of how to combine these drugs.
Gordon Mills, when he was still based at MD Anderson, looked at both concurrent dosing and also other schedules. Thinking outside the box, he then also tested a sequential dosing of a PARP inhibitor, followed by a WEE1 inhibitor. When I say sequential, I literally mean a week of PARP, week of WEE1, and then you just alternate those different drugs. What he found was that the efficacy with the sequential dosing was very similar to concurrent dosing, so giving both drugs together. The hypothesis here is that this is because in cancer cells with high basal replication stress, you can really get down and kill those cells. However, with the normal cells, they all have low basal replication stress, and this protects them from DNA damage and toxicities when you give these drugs sequentially.
And so because of that, we had seen, in at least in vivo models, improved tolerability while preserving a high rate of efficacy in vivo in these PDX models. And so we did this trial. So we brought these data into the clinic. This was an investigator-initiated trial that we started. We ran it through the NCI CTEP program, where we combined, you can see the schema there, the olaparib together with adavosertib sequentially. We gave it 5 days on, 2 days off, and then we alternated both drugs. Other endpoints are all pretty similar and standard for a Phase 1 trial. And you'll see that we saw no DLTs. Most of the toxicities were grade 1-2.
We were able to avoid a lot of the typical toxicities, such as myelosuppression, fatigue, and GI toxicities, and overall, pretty well tolerated, and patients were happy on, on this combination. The key question was, was whether or not we were gonna see efficacy, and even—I show here the escalation data. We saw responses, so confirmed versus PRs in post-PARP inhibitors patients, a BRCA2 ER-positive breast cancer patient who had a deep response, and also a patient with a BRCA2 platinum and PARP inhibitor-resistant ovarian cancer patient, who actually had a BRCA2 mutation reversion at baseline, who had a nice response, and I've got her slides on the next—scans on the next slide. We also saw responses in CCNE1-amplified ovarian cancer patients, and overall, the high disease control rate of approximately 66%, albeit in a small patient population.
And as mentioned, half of these patients had previously progressed on a PARP inhibitor. So promising results, and this is that ovarian cancer patient who had an inactivating BRCA2 mutation, but BRCA2 reversion alterations at baseline, and the patient had 2 prior PARP inhibitors, platinum, so on and so forth, came onto this trial and had a sustained PR, -50% GCIG CA125 response, and was on treatment for about 10 months, and was importantly, tolerated treatment well. Really great one, myelosuppression, and GI tox, and just grade 1-2 fatigue. So here are my take-home points. I, I really think we need to move on, and to build on the success that we've already seen with the first generation PARP inhibitors as monotherapy.
We now have different drugs against the different components of the DDR pathway, especially WEE1, ATR, PK MYT1, so on and so forth. Obviously, these are being explored in different patient populations or and are at different stages of development. There's still work to be done, and for me, it's about optimizing the pharmacology, selecting patients well, and also widening that therapeutic index. And as also mentioned earlier, combinations are certainly a key aspect of this development. And that's it. Thank you very much. Over to Karen.
All right. Thank you very much, Tim. So just sort of building on that wonderful presentation from Tim, our goal is really to now pursue several of these mechanisms where there is this opportunity to improve therapeutic index. Over the course of the next period in this presentation, you're going to hear about three programs. Our CDC7 program, where the vulnerability is DNA damage, where there is high replication stress in certain tumors. I won't go into this in detail. Hamish and Elie are going to cover that. This idea of conditional synthetic lethality, which, again, Tim covered in his presentation. We're gonna talk now about our WEE1/MYT1 program, and then later, you'll hear about the MTAP-deleted tumors in the context of our PRMT5/MTA program. Talking about WEE1, I'm not going to go through this in any detail.
I think Tim just covered it beautifully. Obviously, a very important and promising mechanism. We believe, though, that the opportunity for the broad impact of DDR, as Tim said, in 70% of cancers that aren't treated with targeted therapies, where you can see a lot of interesting responses, that opportunity requires drugs that have a better therapeutic index. We believe SGR-3515, where we combine WEE1 and MYT1 activity, provides that potential opportunity. We're looking here to share with you just a very limited amount of our preclinical data. We have not yet published any of this, so we'll be sharing the highlights and hopefully, this will be the subject of future presentations at conferences.
We believe that, getting to this durable activity, safely, maximizing the potential for efficacy, requires intermittent dosing, and I'll get into that in a moment. And actually, co-inhibiting MYT1, offers the opportunity to benefit from this synthetic lethal relationship. So we had the, opportunity to select from a large number of WEE1 inhibitors. These are incredibly novel. For those who've been paying attention to this field for some time, you'll be aware that a lot of these MYT1, sorry, WEE1 inhibitors are very chemically similar. We had multiple series to choose from, and what you can see here is that SGR-3515 has a very different profile compared to, AZD-1775 and ZN-c3, where clearly these are both very potent WEE1 inhibitors. We're very potent on both WEE1 and MYT1.
Further, you can see that from a target engagement point of view, we are engaging both WEE1 and MYT1, in cell lines, very potently. There has been discussion about PLK1. We were able to completely dial out, PLK1 activity, and further, because of the combination opportunity, we thought it was very important to have a drug that has low potential for DDI. Further, biochemical and biophysical characterization of our compound demonstrates something very important. SGR-3515 has extended target residence time because of its extreme potency and this, slow dissociation from the WEE1 target. You can compare that with the activity of Zentalis' molecule, where it's a much faster, eliminating from the target itself. How does that translate into in vivo results?
What you can see here is that we are able, because of this profile, obviously the potency, but also this long residence time at the target and also in the tumor, to go from continuous dosing, where, as Tim highlighted, yes, you have efficacy. This is a tumor growth inhibition model in a non-small cell lung cancer, well-used model for this mechanism. You can see that SGR-3515 at 20, 40 and 80 milligrams per kilogram has very nice anti-tumor activity. However, based on the data you can see in the lower panel, where you see red blood cell counts, there are lower levels, which indicates activity in the hematological compartment. And so that continuous dosing, we believe, would potentially translate into a narrow therapeutic index.
However, because of the profile of our drug, we're able to actually dose for 3 days in a 2-week cycle and actually maintain the efficacy that you saw from continuous dosing. And now, in this situation, the red blood cells are able to recover because of this intermittent dosing schedule. Further, we've explored now the impact of this intermittent schedule on tumor growth inhibition, again, in a lung cancer model. And what you're looking at here is the cumulative tumor volume over the course of a 28-day study. And what you can see, obviously, in the vehicle, the tumors continue to grow. And when you compare SGR-3515, either given daily or 2 days on, 12 days off, you can see a difference in the tumor volume between our compound and ZN-c3.
We're getting maximal killing of the tumors in the case of 3515, but when you go to that intermittent schedule with ZN-c3, the tumors begin to regrow. This is also expressed in terms of the tumor volume remaining at the end of the study. And what you can see here is that while ZN-c3 is able to suppress the tumors when you give them daily, when you go to that 2-day on, 12-day off cycle, the tumors actually return, you see 100% of the tumor remaining at the end of the study. In our case, because again, of this profile that we have, where we're hitting MYT1 and WEE1, we're able to actually maintain this very profound anti-tumor activity with this intermittent dosing schedule.
If you look now at body weight and hematological recovery, what you can see is that's reflected very nicely per the original study I showed you, where you can see that we are able, with this 2-day on, 12-day off cycle, we're able to actually spare the loss of body weight, and you can see a beautiful recovery while you're maintaining efficacy in this 2-day on, 12-day off intermittent schedule. We think that's a very exciting profile. We're very excited to take this program into the clinic. We've characterized the PK and the PD on route to obviously measuring target engagement in tumors in patients.
You can see that we're able to cover both MYT1 and WEE1, and indeed, we are able to engage these target engagement markers, p-CDK1 Y15, which is a representative of WEE1, and CDK1 T14, which is representative of MYT1. We can maintain and cover both of those targets through most of the day in our PK studies. And of course, on multiple dosing, we think that's going to be very important to cover the target at trough. So in summary, SGR-3515 exhibits a differentiated profile versus other WEE1 inhibitors. We have potent WEE1 MYT1 inhibition and long residence time in tumors, and we think this allows us, and this data we've just shared with you, confirms that we're able to optimize the dosing schedule preclinically to maintain anti-tumor activity and limit hematological toxicity.
This MYT1 co-inhibition, MYT1 actually, serves as a brake on WEE1. So when you inhibit it, you actually are able to add to that efficacy. That greater activity, we think, is part of this synthetic lethality between these two targets. And so again, we're excited to take this program forward. Our IND submission is planned for the first half of 2024, with Phase 1 initiation expected later in the year. With that, I would like to turn this over to our speaker who's joining us by video, Dr. Elie Traer. Dr. Traer is at OHSU. He is a physician scientist studying AML, and we're gonna transition to his presentation, followed by the CDC7 program overview. Hamish, I'll hand you the clicker because I think you'll be helping Elie with-
I'll work the clicker.
Hi, Elie. Can you hear us?
Yes, I can. Karen, thank you for the introduction. All right, I'll get started. Thank you for the introduction. My name is Elie Traer. I work at OHSU. I am a physician scientist. I work on leukemias. And I'll talk to you a little bit about AML, or acute myeloid leukemia, and myelodysplastic syndrome, or MDS, and some of our research projects with CDC7. So AML is a blood cancer. It's characterized by a block in normal white blood cell development, which is one of the key features of this disease. We often call these blasts or leukemia cells, but at any rate, they're very immature, and they look quite different from the normal white blood cells you have floating around in your blood.
and it's also characterized by uncontrolled growth, which is typical of most cancers. And what happens is that you have too many of these leukemia cells, they start to fill up the bone marrow, and then that impacts your normal marrow function. So you end up with decreased white blood cells, red blood cells, and platelets. So essentially, that makes you at higher risk for infection. You have anemia and fatigue, which is almost how all of my patients present. And then you also have an increased bleeding risk, which can be quite catastrophic for some types of leukemias. Next slide. And this is just a diagram of, sort of that immature state of AML cells.
So when you have a what we call a hematopoietic stem cell, or a stem cell that produces all your blood cells, there's this early split, and you can go either towards the myeloid lineage, which is white blood cells, sort of neutrophils, red blood cells, or you can go towards what we call the lymphoid, which is B cells, T cells, et cetera. So that ends up being sort of a very early split, and then if you have a mature maturation block or differentiation block, we get two different flavors of leukemias. One is acute lymphoblastic leukemia, or ALL, and the other is acute myeloid leukemia, or AML, and we'll focus on acute myeloid leukemia. That's the most common in adults, and increases significantly with age. Next slide.
So, blood cancers are not necessarily the most common cancer, although they are not uncommon either. However, they are one of the most deadly. So you can look at the survival curves here, and you can see that decade by decade, we've had actually very little improvement in survival. So there's about 21,000 cases of AML that are diagnosed per year. About half of those, or, well, not half of those, but 10,000 deaths per year. And so you can see if you run it out over a few years, you have less than 25% survival for most patients. So this is really a critical disease where we need more drugs, and treatments, and especially combinations, which we'll get into. Next slide. So this is how somebody like myself thinks about AML.
We think about this in mutations. And there's a lot of defining and recurrent mutations in AML, and that helps us characterize this into different subgroups. And so you can see the columns on this slide sort of show you the different types of groupings of AML based upon recurrent mutations. And we use these mutations quite a bit. It helps us predict response to current therapies, so this is what we call a prognostic mutation. And then more, and we're trying to do this as much as we can, we're also using mutations to be target for certain drugs. And there's a few different examples that I've listed here, FLT3 or FLT3, and then IDH1 and IDH2. And there's been some inhibitors specifically for these particular mutations that have developed in the past few years. Next slide.
And the way we use these prognostic mutations is diagrammed here. Again, these are survival curves. This is what all oncologists like to look at. We sort of see how long a patient survives over time with a certain type of mutation. And in the blue arrow, you can see this is a favorable risk. Many of these patients can be cured, and this is typically with chemotherapy alone. Whereas if you look at the red arrow with the adverse risk, you can see that no matter what we do, these patients do not have very good survival. Most of them die. And in particular, in the bottom, I'm pointing out the p53 subcomponent. So TP53 is a very common mutation in all types of lung cancers.
In AML in particular, it's been a very difficult disease to treat. We don't have any good therapies, and these patients uniformly do poorly and don't respond to everything we have. They're often characterized by what we call a complex karyotype, which is basically because p53 normally is considered the guardian of the genome, make sure that there's the chromosomes are intact. With each cell division, when you lose p53, you tend to get a lot of chromosomal abnormalities. So basically, a lot of damage can accumulate, and continue. Next slide. This is sort of lumping all of those different categories together. We end up with three different risk groups, and there's favorable, intermediate, and adverse. You can see here that really favorable is not too bad.
I mean, we can cure about 60% of these patients, not all. But unfortunately, this is the smallest subgroup of AML. This is only about 20% of AML patients. And I should mention, this is actually mostly for younger patients, with chemotherapy, not necessarily older patients, which is a very different story. But even for younger patients, 80% of them are gonna have intermediate or adverse risk, AML. And these patients are gonna need a bone marrow transplant, or what we now call allogeneic stem cell transplant, for cure. So basically, this is an immunotherapy type of approach where you have to replace their entire bone marrow with new stem cells from somebody else, which has quite a bit of morbidity and mortality. Next slide. So MDS is a related disease.
And so MDS is a little different from AML, although they're very, they're considered on a spectrum, one will go into the other. But MDS is characterized by abnormal white blood cell development. So in contrast to AML, you don't have as many of the immature cells. You have sort of this sort of dysplastic or abnormal-looking cells, sort of throughout all the white blood cell maturation stages. We call this, this is dysplastic when the pathologists look at it, and there's sort of distinctive shapes and features on the slide. So MDS also blocks production of normal blood cells because you get this marrow full of sort of poorly formed white blood cells.
That decreases your normal white blood cells, red cells, and platelets, which again, leads to increased risk of infection, anemia, fatigue, and bleeding risk. So because of this sort of transition, MDS has fewer blasts, whereas AML has more. We previously called MDS pre-leukemia, because it was just less than 20%, and then when it went to more, we called it AML. But now we call it myelodysplastic syndrome. However, it is a spectrum, and especially when you see... once you get close to 20%, we'll often treat those patients just like they're AML. Next slide. And so this is sort of on that diagram showing you where MDS predominantly affects the slide, cell production.
You can see that it starts basically at a higher level with those abnormal with the immature cells, the blasts. But actually, there's a continuation of production of more mature cells like neutrophils, red blood cells. However, they're abnormal at multiple stages, and so it's kind of a, it continues. It's not a very complete differentiation block. Next slide. Just like AML, MDS is really characterized by recurrent genetic mutations. Most of these carry over from an MDS to AML, and you can see that there's a wide variety of mutations. Some are what we call very low risk, and patients can go on for a decade with some of these types of MDS.
And then there's a very unfavorable, and so that would be something like TP53 again, and complex cytogenetics or complex karyotype. And these patients will progress relatively quickly. And again, we have a very few therapies for these. And so there's a lot of these mutations that are enriched in MDS, spliceosome, epigenetic transcription, and these carry over into AML. So we can often tell, even if we didn't know that a patient had MDS first, that they likely had a preceding disease before developing AML. Next slide. And this is a sort of a slide just to show you that, this sort of sequential nature of the disease as we've come to understand it over the last 10 years. And so mutations can actually start quite early, in your blood-forming cells.
Unfortunately, it can start as early as your forties, fortunately, unfortunately for many of us. But that tends to be just like a single mutation. Over time, it can expand, and then when you get additional mutations, it can either turn into an MDS, and then eventually, with more mutations, turn into AML, or you can get sort of a stronger driver of AML early, and then you get, go straight to AML, what we call de novo AML. And so a lot of these mutations are not necessarily, sort of drivers of disease, so you have to differentiate which mutations we go after. And then, all MDS and, and what we call myeloproliferative neoplasm, which is another variation of MDS, will eventually move into secondary AML.
If you advance one more slide or one more picture, that this is just like a diagram of showing you sort of this nature of cells. It either go to MDS and then eventually to AML, or this other disease called AML, or just go directly. So these are all related, but they're all also a little bit different. Next slide. This is current AML therapy and limitations, and I wanted to add this slide to the previous, just to really emphasize the fact that it's quite different depending on the age of the patient. For younger patients, and younger in this case is less than 65 or less than 60, depending on where you are, that's an intensive chemotherapy.
We put patients in the hospital, we give them very intensive chemotherapy, they're quite sick, hair comes out, but there is a chance of cure, particularly for those favorable risk patients. However, we tend to get almost all those patients into remission, which is basically defined by the fact that we can't see the leukemia cells anymore. But as you can sort of see on the right, the limit of our detection isn't necessarily good enough to sort of say with any assurance that they actually will be cured because we can reduce the cells to a low number, but if there's just a few of them left, they will eventually come back. It's difficult to do this. We call this minimal or measurable residual disease.
And that's what we use as our sort of best guess, is to try to predict who, which patients will relapse, and which won't. And then for older patients, we actually use less intensive chemotherapy. Very difficult to cure these patients, because they don't tolerate chemotherapy quite as well. So we can use stem cell transplants in these patients, although it's much more difficult when you're older. It's just harder to tolerate the therapy and especially after transplant with the steroid treatment in particular. And so, the median age of these patients is around 67, but this is actually the majority of AML, which happens. So most of AML happens in older patients, and we have even fewer therapies for these patients.
I think if you advance a couple clicks. Yeah, and this is just a diagram of that, another way of looking at that minimal residual disease. And you can see these are a few patients we had here, where you give chemotherapy, and it's called a FISH plot, and you can sort of see you compress that malignant clone. It seems to go away, but then a year later or so, all of a sudden, it grows back and expands again. So this is really an interesting cell population and from my perspective, an opportunity to try to treat the disease better before it comes back. Next slide.
So what makes this a little tricky, as I mentioned before, is that, even though we use mutations sort of to find prognosis, the reality is most leukemias have multiple mutations. This can make assessing the risk a little harder, but it also means that targeted treatment is more challenging. Because if a patient has multiple mutations and you're just targeting one, you're not really gonna cause the whole thing to go away. So we really need better combinations. And then if you can see this pie chart, this kind of... if you start to really look at combinations of mutations, you can see that we break AML into a wide number of different types of diseases, which makes therapy more challenging. Next slide.
But we have made progress, and there have been 12 drugs approved in AML since 2017, which, considering, where I started with AML about 10 years ago, this is really impressive. And even though we've made progress with all of these drugs, many of them are sort of single agents, some in combination, as you can see here. But the challenge really is: how do we best mix and match these, different drugs for different types of AML patients? Next slide. So, in general, these are some of the emerging targets, and therapies that are available. Chemotherapy, I mean, it's considered old, and it's not very sexy in terms of drug development, but that's still the cornerstone of what we use to cure chemo, to cure the favorable risk leukemia.
So chemotherapy still definitely plays a role. There's also things like kinase inhibitors or growth inhibition. And so there's a few different drugs that inhibit FLT3, in particular, that are listed here, including gilteritinib, which is a lot of the work we've done in our lab. There's also BCL-2 antagonists, which is BCL-2 is a protein that's upregulated in blood cells. Turns out, if you give a drug called venetoclax, you can really sensitize these cells. So it never really works by itself, but it works in combination with a lot of drugs. And then we have differentiation agents. Actually, it takes those immature cells, and it sort of forces them to become more mature, and then they die on their own.
And there's IDH inhibitors and menin inhibitors is another one that's recently been had some very good success in the clinic. And then there's also cell cycle inhibitors. All cells are defined by having this need to replicate and divide, and so, as you've seen earlier, you know, attacking this pathway is becoming a really promising area. Next slide. And I'll just leave you with a little bit of our research. This is a lot of work we've done and where I really got interested in CDC7 as a target. And so we had this model where we could take patient samples and cell lines, and we could treat them with different FLT3 inhibitors. We used gilteritinib and quizartinib, and they...
Essentially, if we treated them and kind of mimicked the bone marrow microenvironment, sort of where these residual cells hide out until they expand again, we found that they were, those cells could still stay alive, but they were uniquely dependent upon CDC7 and another related protein called Aurora kinase B here. And so when we treated these cells with CDC7 inhibitors, they became profoundly sensitive to the combination. Next slide. And then I think I'll move on to Hamish, and I'll get my lights to turn back on here. Thanks.
Thank you, Elie. All right, fantastic. Good morning, and welcome. I wanna share a little bit of background and data on our CDC7 inhibitor program, and so which we are pursuing initially for the potential treatment of relapsed/refractory AML and high-risk MDS. What you can see on the left-hand side is that cell division cycle seven or CDC7 is an S-Phase kinase. It's important in the initiation of DNA replication and also in managing the replication stress response and in DNA repair. On the right-hand side, you can see that DNA replication starts by the unwinding of DNA to form this Y-shaped structure called the replication fork. Stalling of DNA replication at the replication fork drives replication stress and the need for a replication stress response.
So proteins such as CDC7 are important in this. In this case, CDC7 phosphorylates certain substrates, it's able to manage and protect the DNA replication fork restart, DNA replication after it's repaired. Now, cancer cells differ from healthy cells in their ability to manage replication stress and manage DNA damage. And that's because cancer cells are characterized by having a very high level of sustained cellular proliferation. That sustained cellular proliferation requires access to certain enzymes, access to certain raw materials, like nucleotides, to make DNA. And when those things are limiting, the cells undergo a heightened level of replication stress. If that's not managed properly, these cells tip over into catastrophic DNA damage and cell death. So these cancer cells are increasingly dependent on replication stress response pathways.
On the right-hand side, what you're seeing is that tumor types differ in their intrinsic levels of replication stress. So AML is characterized by having higher replication stress and DNA damage relative to other cancers. Our therapeutic hypothesis then for our CDC7 inhibitor program is that cancer cells rely on replication stress response pathways to maintain DNA synthesis and maintain genomic integrity. By interdicting this with a CDC7 inhibitor, and driving these cancer cells through under-repaired damage and fork instability, fork collapse, these cancer cells ultimately accumulate genomic instability and ultimately die. Turning to our program, SGR-2921 is a selective and potent CDC7 inhibitor in Phase 1. It demonstrates better biochemical activity and target engagement relative to other CDC7 inhibitors. You can see that in the table on the right-hand side.
Those improvements in biochemical activity and target engagement are further amplified in a cell-killing assay in either the MOLM-16 or MV4-11 cells, as shown here. Now, we took a look at SGR-2921 across a suite of 300 cancer cell lines, in fact, and screened them for sensitivity to this compound. You can see a mixture of liquid and solid tumors here, but leukemia cells were most sensitive relative to the other cancer types. When we took a look at AML cell lines, we noticed that they were highly sensitive to SGR-2921. This is indicated by the single-digit nanomolar target engagement numbers.
You can see those across the table at the bottom, as well as the good, you know, double-digit nanomolar, generally, cell viability IC50s, bookended by the MOLM-16 and MV4-11 cell lines. We then moved into patient-derived samples. These are considered highly translational, and in this case, we're looking at one that incorporates this TP53 mutation that Dr. Traer just told us about. So we looked at sort of 17 patient-derived AML models, some of them with TP53 mutations, some of them with FLT3 mutations. You can see the hallmarks at the bottom in the table, as well as some of these patient models were relapsed refractory, some of them were naive to treatment.
And what you notice right away is that, the vast majority of these models are sensitive to SGR-2921, with IC50s below 100 nanomolar. On the right-hand side, you can see patient-derived p53 mutated AML models are particularly sensitive to SGR-2921, as shown in the red dots there. Okay, so then we established patient-derived xenograft models. So now we're looking at models, mouse models that harbor sort of this patient-derived AML. Essentially, profiled SGR-2921 across 3 different dose levels, using our clinical regimen of 5 days on drug and 9 days off drug, and took a look at that alongside azacitidine and venetoclax as a control arm.
You can see that the animals, so you can see the study scheme at the top of the slides, the animals were exposed to 2 rounds of therapy before their bone marrow and blood were harvested for flow cytometric analysis. And what you can see immediately is that there's a really nice dose-dependent reduction in the bone marrow AML blasts as a function of 2921, and a dramatic reduction in the AML blasts percentage in blood. And interestingly, this eradication of the bone marrow blasts was accompanied by a repopulation of the healthy white blood cells in the bone marrow in a dose-dependent fashion. So very, very encouraging data.
In addition, we've taken a look at SGR-2921 in AML cell lines that are resistant to certain standards of care. On the left-hand side, what you're seeing is across the 11 AML cell lines that I mentioned a moment ago, sort of a mixed picture of sensitivity and resistance as it relates to decitabine, venetoclax, and gilteritinib. You can see that the vast majority of these cell lines retain sensitivity to SGR-2921. On the right-hand side, these are some data from a collaboration that we have with Dr. Traer. So he mentioned the establishment of sort of cell lines where he'd studied gilteritinib, in this case, generating a gilteritinib-resistant clone.
So starting with the parental cell line on the left there, you can see that that clone is sensitive to gilteritinib. But when a gilteritinib, gilteritinib-resistant clone is generated from that, and then co-administered with 2921, so gilteritinib plus 2921, you can see that we restore or resensitize those gilteritinib-resistant clones. That's that leftward and downward shift of the pink curve on the right-hand side there of the slide. So these data really provide the foundation for our first-in-human trial. This is a Phase 1 study in relapsed/refractory AML and high-risk MDS. Our compound's being administered orally, once daily, on a 5 days on, 9 days off regimen with continuous 28-day cycles.
We have a number of objectives to evaluate safety, tolerability, identify a recommended Phase 2 dose, evaluate pharmacokinetics, and get some early signs of antitumor activity. We're going to explore PK/PD relationships and take a look for biomarker modulation. This trial is active. You can see the schema on the left-hand side of the slide. This study is active, enrolling in the U.S. with expansion planned in the E.U., and we expect Phase 1 data late in 2024 or in 2025. I think with that, I'll turn it over to Jean.
Thanks, Hamish. Okay, so you've just heard about our two hematology programs, and I'm going to switch it up and talk a little bit about solid tumor with our programs for EGFR and PRMT5. As Karen mentioned, EGFR is a major driver in lung cancer, so this is what this program will target. I'm going to talk a little bit first about the standard of care that's been used previously. The driver mutations that are associated with lung cancer in EGFR are the L858R and a deletion of exon 19. The drugs targeting these mutations had efficacy, but resistance developed because of largely because of a mutation at T790. This is targeted by osimertinib, a newer drug, which is now first-line therapy.
Not surprisingly, tumors have been able to become resistant to that therapy and through a variety of mechanisms, one of which is the EGFR mutation to C797. And this is the mutation that we're targeting in this program. We're looking for a CNS penetrant molecule because brain metastases are occurring in about 40% of lung cancers, and we're also looking to improve on wild type selectivity, kinome selectivity, and have a clean P450 profile to decrease the risk of drug-drug interactions. So the opportunities here, in a situation where osimertinib is first line and resistance developed, is to have a second-line EGFR C797S inhibitor, which will address the on-target resistance mechanisms, and can be also used in combination with inhibitors of other resistance mechanisms, such as c-Met inhibitors. And there may be possible future opportunities to move into combinations in first line with osimertinib.
So, using our platform, we were able to interrogate a vast number of chemical structures and fragments and identify hits where we have unique structures and are patentable. We have come down from a vast number of compounds to having lower than 100 nanomolar potency at the target. We've also incorporated evaluation of brain penetration in this program, because, as I mentioned, we're looking for CNS penetrant drugs. So one of the ways that we do this is to use a platform tool called Energy of Solvation. This is a quantum mechanics calculation that takes into account multiple aspects of the molecules to predict how the compound will get across the blood-brain barrier.
We can compare this to the in vivo data from the experiment where we dose compound in mice and measure the brain plasma ratio of the free drug. And as you can see from the plot on the right, using compounds from a variety of chemical classes in multiple programs, the ESOL numbers predict well with the in vivo experiment. So by using this, we can enrich for compounds that have the good predictive values and not have to do the in vivo studies on everything that we make that's potent. Another. In addition to brain penetration, another aspect that we're very serious about here is wild type selectivity, and we've got a way to measure this using a pharmacodynamic model in mouse. So the mouse is injected with tumor cells, which are allowed to grow in the mouse for two weeks.
After the tumor is established, the inhibitor compound is given, and in this case, we wait 24 hours and look at phospho-EGFR, which is a measure of EGFR activity that we're trying to inhibit in the tumor cells. So with vehicle treatment, there's no inhibition. When we look at our compound, you can see inhibition in the tumor, whereas the skin, there's a piece of skin from the ear taken as a wild-type control, and there is no reduction in phospho-EGFR. So this compares favorably with marketed drugs. And we're continuing to optimize in this program for a CNS penetrant molecule with high selectivity against the wild type and a good CYP profile so that we won't have drug-drug interactions. Next up is the PRMT5/ MTA program.... This program will also be important for lung cancer, but also for numerous other cancers.
Previously studied drugs have shown efficacy in some of these cancers. Some drugs which were studied previously inhibit PRMT5, but not specifically PRMT5/MTA. What's happened there is dose-limiting toxicity from hematological side effects, such as thrombocytopenia. The PRMT5/MTA strategy would be specific to tumor cells that have MTAP deletion. Again, in this program, we're looking for a clean P450 profile because agents will likely be used in combination, and we want to have low DDI potential. So a little background. PRMT5 is an enzyme that adds a methyl group to numerous proteins in healthy cells and is involved in multiple cellular functions. In tumor cells, they use PRMT5 to help with microenvironment signaling and to promote stemness.
We have a natural inhibitor of PRMT5, which is MTA, methylthioadenosine, which is sometimes in the cleft, but whose levels are tightly controlled and kept low by an enzyme called MTAP, which is part of the MTA catabolic cascade. If MTAP is missing, then MTA is very abundant within the system, and PRMT5 is often found in complex with MTA. Many cancers, about 10%-15% of cancers across multiple tumor types, have this MTAP deletion, and those are the tumors that this strategy would address. So we do this with our proprietary cryo-EM structures. We want to increase binding. We want to have binding in the cleft in the presence of MTA. We don't want to bind when MTA is absent.
By looking at these crystal structures and evaluating the interactions between the amino acids and MTA, we can identify compounds that sit in the cleft in cooperation with MTA. As Ramy mentioned, we don't just use our platform to get our initial hits, but we can also use it to optimize those hits into leads. And I'm gonna give this example of how we have a series where we took hits that were double-digit micromolar in potency and moved them to less than 0.1 nanomolar, a 10,000-fold increase in potency. We also evaluate these hits for cooperativity with the MTA in the site, and you can see on the left, compounds sitting in position with the MTA in purple next to it.
This is further evaluated in vitro in a model where we look at inhibition of cancer cell growth using cancers where MTAP is either knocked out or it's not, it's in the wild-type cells. We see a nice dose-dependent growth inhibition with the MTAP knockout cells that's not seen in the wild-type cells. A compound that isn't PRMT5/MTA selective will look similar in both cases and will not be wild-type sparing. We continue to optimize molecules in this program, again, looking for CNS penetrance, looking for selectivity, looking for a clean profile. The NLRP3 program will switch to from cancer to inflammatory disease, and these NLRP3, as Karen mentioned, has genetic validation through a disease called CAPS, which is a gain-of-function mutation in NLRP3.
There are multiple other diseases, some of which are listed here, which have been associated with elevated expression of NLRP3. Some of these diseases have shown response, some response to the biologics that target IL-1β. However, IL-1β-targeting agents do not reduce the IL-18, that's also induced by NLRP3. So if we look at the cell, NLRP3 senses various immune insults and triggers formation of the inflammasome with other proteins. In the inflammasome, pro-caspase-1 is activated, and it will then cleave pro versions of IL-1β and IL-18 into their active forms. So you get an immune response that way. In addition, Gasdermin D is cleaved by caspase-1 to an active form, leading to pyroptosis. So again, the IL-18 component adds utility of this therapeutic strategy to that of the IL-1β targeting mechanisms.
So one of the things that's really helped this program is our proprietary cryo-EM structures. We've rebuilt these structures from what's been available in the literature and been able to find unique binding modes. And in the cartoon to the right, the animation is illustrating the motion of the amino acid side chains in gray as they move from the unbound to the bound state with the compound shown in blue. Using these kinds of tools, we've been able to come up with structures that are diverse and different from the sulfonylurea structures that most NLRP3 early inhibitors were part of. So we can see that we've got three structural classes, and they bucket into different chemical space in this map that uses different chemical attributes to assess similarity of compounds. We've looked at a couple of these.
I'll show a couple of compounds from, from two series, and you can see that we've got good potency, we're avoiding the off-target possibilities, and we've got really nice PK that shows coverage on the target for close to or for 24 hours. And to further show that, we've got an in vivo pharmacodynamic experiment in mouse, showing efficacy at 24 hours. In this particular experiment, we treat the animals with LPS and ATP to get the inflammasome stimulated and produce that inflammatory response, and then plasma IL-1β is measured over time. And you can see that in green, our compound potently reduces plasma IL-1β, and it's got a durable response, which compares favorably with the standard control, MCC950. We do continue to advance these leads, and we are looking for a CNS penetrant molecule because of the opportunity in neurodegenerative diseases.
We're also on the road to getting our potent leads. So just to recap, these three programs, EGFR, PRMT5/MTA, and NLRP3, are in the works, and we hope to progress to candidate selection. We do continually evaluate our programs and our progress against the target profile and with the competitive landscape in mind as we come up with differentiated drug candidates. I'm gonna turn it back over to Karen.
Thank you. All right, home stretch. So I think what we've shared with you today is a few highlights from our portfolio. First of all, in the oncology space, we have programs in hematological cancers, lung cancer, and other solid tumors. We've described to you today our CDC7 program and our MALT1 program, that are both now in the clinic. We have emerging programs in, the EGFR C797S mutant-resistant program and also our PRMT5/MTA program. And we believe that WEE1/MYT1 and PRMT5/MTA offer opportunities in many other solid tumors. As we described, and as I think you heard from both of our invited speakers, all of these mechanisms have the potential to combine with standard of care agents, and the goal really is to improve outcomes for patients, move to more complete responses in these combinations.
While each of these has the potential for their own efficacy contribution, the goal really is to improve overall survival for patients. Beyond our oncology portfolio, we've introduced today a few new programs. We did not touch on our LRRK2 NextGen. That's for next time. In the immune space, Jean just introduced you to our NLRP3 program. And just to make some general remarks about our undisclosed programs, which we obviously didn't share today, that will be the subject for future reviews, we believe that the opportunity for large molecule switches to oral drugs is a really important space. We have several efforts in that space.
Again, outside of oncology, we believe that small molecule options allow for future combination opportunities, this time to extend disease control in certain immune diseases and push towards durable, symptom-free remission for patients. The outlook, we believe, is bright. Here we have been able to clear 2 INDs in 2022 and 2023, as we described, for MALT1 and CDC7, and next year it will be our WEE1/MYT1 program that we shared highlights of today. In 2025, we have numerous different opportunities that you've heard a little bit about today for an additional IND filing in 2025. We have multiple programs that we've advanced into development since 2018. We believe that in the 2024, 2025 window, we will see advanced programs producing POC data.
As I said, we're looking forward to additional IND opportunities in the future. With that, I will pass the podium to Geoff Porges. Thank you.
Thanks, Karen. And hello, everyone. Great to see you all. As CFO here, I'm in a difficult position today. I don't have any great science to share, and I'm the last speaker between our analysts and their Q&A, so I will try and move quickly. I'd like to share a little bit of, a few observations about our capital allocation strategy and how we see ourselves creating value out of our therapeutics portfolio. As you've heard, today and in prior calls, we've had a substantial and growing investment in our therapeutics business, since 2018, when we first started to develop a proprietary portfolio. This year, our total R&D investment is around $130 million.
Last year, it was $126 million, and we've indicated in recent quarters that roughly half of that investment is going towards our therapeutics business and portfolio. Now, we're offsetting much of that, that investment with cash generated from collaborations, and collaborations remain an important part of our business model. Year to date, our collaboration revenue is just over $52 million, and this is by design. The collaborations have their ups and downs, but we do think it's a very cost-effective way to build our capabilities, to build our portfolio, without investing all the cash necessary on our own account. Now, we have multiple approaches to creating value.
In addition to collaborations, we're realizing value from partnering, from equity positions, from distributions, from companies where we're a minority investor, and in the future, of course, we hope to realize more value from the proprietary programs that you've heard about today. We now have a robust portfolio of partnered and proprietary programs, and we're seeing the leading programs advancing into the clinic. Those programs are diversified across targets, therapeutic areas, different programs, and different stages of development, and we do believe that diversification reduces the risk of the investment we're making. We see positive returns now and in the future from what we regard as a fairly capital-efficient investment model. So let me just give you some of the numbers from the perspective of the CFO looking at this investment.
Our cumulative total R&D expense, this is the GAAP numbers, since the first part of 2018 through the third quarter of 2023, was $486 million. Now, much of this investment has been to support the platform, and we create value from the platform by both selling the software and developing our proprietary medicines. We don't break that R&D expense out, on a reported basis, and a significant part of that, in fact, most of that in the earlier period of this investment, was for the platform rather than for the therapeutics portfolio. In return, however, we've seen significant value created from the therapeutics investments that we've made. We've... I mentioned the revenue this year.
Our cumulative revenue from collaboration payments over this period of time is $163 million, and we've also received cash distributions from partners, where we own part of programs and/or of the company of $165 million over that same period of time. And lastly, we've sold equity, and we continue to hold equity in public companies, and that's worth $91 million as of the third quarter of 2023. So there's $419 million worth of value that's being realized from the proportion of the R&D expense that's been invested in the therapeutics business. And at the end of the day, we have what we consider to be a pretty exciting portfolio.
We have two clinical programs, we have one program approaching the clinic, and we have a number of DCs that some of which you've heard outlined today. Now, how do we think about what's the framework we use for allocating capital? Well, of course, we're aiming to generate positive returns by deploying our technology, our expertise, and our capital. We typically deploy those assets against a validated target or development goal. Sometimes those targets come from academia, sometimes they come from entrepreneurs, from investors, even from industry, sometimes even from competitors. We have to look at those opportunities and determine, are they amenable to our technology? Can they be accelerated by the application of computation? Does our team have the ability to improve on them and create value out of them? And is there some unique scientific, commercial or other insight that we can leverage?
In those cases that meet those criteria, we'll consider allocating our resources from our team, our technology, and in some cases, our capital, to create what we consider to be a future commercially useful innovation. Sometimes that's a proprietary medicine, sometimes it's a partnered program that's eligible for milestones and, and downstream royalties, and in other cases, it's an equity position in a, in a promising entrepreneurial company. So let's just look at how our equity investments have played out. The total value of realized and outstanding in current equity positions as of the end of the third quarter from for our investments is around $318 million. Remarkably, the actual capital we invested to create that value is only $16.5 million. Now, that's only a fraction of what we've actually invested to build that value.
I didn't account for, you know, the time that as professional staff, the technology we've deployed, the computational capabilities that we've invested in return for those equity positions. But in a pure capital-on-capital return, that 20x return is pretty attractive, and even when we estimate all of the other components of the investment that we made in these ventures, we think it's a very attractive return that we've generated for our shareholders. So just to summarize, I mentioned the cumulative total R&D expense, $486 million, and highlighted that that's spread between our platform and our therapeutics portfolio. We do see value accruing in multiple ways. We think that that's by design, and that lowers the risk of single-asset programs, for example, that of course are going to have the challenges.
We've created value in a multitude of ways, but a total value of $419 million, we think is pretty attractive compared to this investment. We do have what we consider to be a pretty attractive portfolio, and you've heard today that program... those programs are moving forward, and we think there are opportunities for creating even more value, or at least realizing even more value from those programs in the future. We are remaining disciplined. We do have a framework that we apply to all of the investment opportunities that are presented to us, and we're continuing to prioritize the most promising programs and equity opportunities for that further investment. So thank you. I'll turn the call over to Jaren for Q&A.
Thank you. Yes. Thank you. Yeah. Yes. At this time... Excuse me. I'd like to invite the Schrödinger team, as well as Dr. Yap, to come up and take the hot seat. And we're gonna spend some time on Q&A. I'm gonna open it first to people in the room. Just a couple of ground rules to ensure that people who are on the webcast can hear the people in the room. Raise your hand, please, so that someone on my team can come with the microphone. And if you wouldn't mind just stating your name and affiliation and then your questions. And we'll stop periodically to see what we have on the webcast as well. But I'm gonna start over on this side of the room with Mike.
Hi, thank you. It's Michael Yee from Jefferies. We had two questions. Maybe on MALT1, where you presented some Phase I healthy volunteer data, you could put into context how de-risked the safety profile is and what you learned, compared to what we sort of know from the competitor molecule, which has presented a lot of data, did have a lot of side effects and some efficacy. So how much de-risking in healthy volunteers could you read through here? Because I wouldn't think there would be significant toxicities between a cancer patient and a healthy patient. So just talk to that a little bit, and how much how important is that, that we saw today? And then maybe a second question is for Ramy or Geoff .
You obviously disclose a lot of information about targets and INDs, which are coming through in 2025. Should analysts be thinking about a significant acceleration in OpEx, which is really R&D, and how should we think about that? Because in this current environment, cash burning, you know, capital-intensive biotechs are not exactly in favor. So maybe just talk a little bit about that and whether you would seek to do a partnership, maybe offset that, and maybe that's a catalyst. Thank you.
Maybe start with Karen on the first question or Margaret? Yep. Yep.
Oh, you're right.
Thank you.
Yeah. So, from the healthy volunteer study, you know, very we had very limited Grade 1, Grade 2 toxicities. We had very low incidence of any toxicity, you can see. And the drug-related toxicities, we had one episode each of nausea, dysgeusia, fatigue, headache, and rash. So the headache was about 3 patients out of 79, so we have very little toxicity with the drug. We were able to look at the pharmacokinetics, the once-daily dosing versus the twice-daily dosing. Twice-daily dosing at the 100 milligrams, we got to three times the exposures of the once-daily. So there's really very limited toxicities. What it does is inform us and the investigators who will enroll patients onto the advanced cancer study.
You know, what we've seen is really minimal, and it's mainly adverse events that can be managed if it does turn out to be a little bit more higher frequency in the cancer patients.
And then...
Yep. Yeah.
Strategy question-
Yeah
about your partnership with ourselves.
Yes. Look, I think we're in pretty good position. Sorry. Yeah, now I'm on. We're in great shape for 2024. You can see we have three, potentially by the middle of the second half of the year, programs in Phase I. That's a manageable spend. I don't expect there to be any sort of challenges in terms of our capital position or in terms of the trajectory of our R&D investment. If we look to 2025, clearly there are significantly more opportunities. You know, some of the Phase I programs will continue, and perhaps even we'll be contemplating moving into larger trials, expansion cohorts, that sort of thing. And then some of the other programs that you heard about will be also moving into R&D.
I don't think that there's a need for a big step-up in 2025, but equally, we're looking at a portfolio that's sort of substantially increasing over a two-year period, and I don't think that we're contemplating advancing all of this portfolio, for example, into Phase II. So, you know, we'll be looking at ways to create value, and I sort of laid out different opportunities. We can create value through equity participation, through companies, venture formation. We can create value through partnering. In some cases, we can even create value through, for example, co-development. So we do have a lot of ways that we can continue to participate in our medicines without taking on all of the capital risk associated with funding expanded trials.
Let's go to the back of the room over here.
Hi there. Connor McKay, associate on Evan Seigerman's team. Just two questions from us. First one is: with Phase 1 data for your MALT1 and CDC7 assets in sick individuals coming, you know, late 2024, potentially early 2025, I guess, how are you thinking about, you know, the bar for safety and potentially early efficacy there? And then also, you know, we noticed in your earlier stage development pipeline, it looks like you're expanding a bit beyond oncology. So just curious, you know, strategically, are you thinking of maintaining oncology as sort of the cornerstone of your development pipeline, or, you know, potentially looking more towards targets that you can better optimize with your software platform? Thank you.
Yeah, so, I think you're asking again about the safety profile of what we saw in the healthy volunteers. I think, again, it's very minimal. I think we had reached very high exposures that we have not yet seen within our advanced cancer study, which is enrolling very well now. We've gone to more centers in the U.S. and E.U. So the expectation is that, you know, what we'll see in an advanced cancer patient population that have had prior many therapies, comorbidities, con meds, intercurrent illnesses, will reflect mainly what that part of the, you know, the patient profile is, rather than related to our study drugs. So we expect that toxicities that will be deemed related to our drug would be minimal.
And then Karen.
Yeah, on the second part, as you know, our platform allows us to be therapeutic area agnostic to some degree. We go after specific design challenges, and while we believe there's a huge unmet need in oncology, as you heard from our, our invited speakers across, both, liquid tumors and solid tumors, where we do intend to continue pursuing important mechanisms there, we also believe that in other therapeutic areas, there are some really great targets where there aren't particularly great drugs right now. And so I think we'll remain, very flexible about the targets that we go after, ensuring that there's a target product profile that we can solve for, where we think there's an unmet need, and obviously an opportunity, either for us or for a partner to proceed with those through development.
Kathy?
Hi, everyone. Oh, hi, Roger Su, part of Goldman Sachs. Two quick questions from us. On your MALT1 compound, can you talk a little bit about study design and dosing? You presented some data here on, you know, monotherapy and then, as monotherapy, as once daily and twice daily dosing. So is your expectation to also bring that over into the patients with B-cell malignancies? And then the second question, maybe for Geoff , can you comment a little bit on the business environment? Are you expecting any improvements into 2024 from more of the smaller businesses with contract values less than $1 million? Thanks.
Right. So currently on the current Phase 1 study as designed, we have only a once daily dosing, continuous dosing schedule. We're in accelerated titration design, only enrolling one patient per cohort, and we expect they'll be able to continue that for quite a bit before we might have to open it up, given the healthy volunteer data. We are amending it currently to include a BID dosing schedule, and we're gonna work that through the regulatory and IRB and ethical committee processes, as we go on into 2024.
And then-
Yeah
on the business environment, you heard Ramy reiterate our confidence in the outlook for 2023. In terms of the outlook for 2024, I think, for our present baseline assumption is gonna be very similar to 2023, with a sort of similar scope of opportunities and nature of those opportunities. Whether the smaller biotech segment of our business will recover depends, it depends really. I think the lead time on that is quite long. So what we observed previously was that the lag from a recovery and or a high level of funding activity and the emergence of companies that were rated by our software at scale was sort of 6-18 months.
And so the lag in the slowdown actually had that sort of effect, time course as well, from when financing stepped down and then when, when we saw it flow through in terms of companies not showing up. So I, I wouldn't anticipate a rapid reduction, a rapid recovery, I should say, in those types of accounts in the near future, even if the financing window opens up. I think it's likely there'd be a lagged effect in that sort of 6-18-month current time course.
Thank you.
Yeah, I think that's exactly right. But it's important to keep in mind that, as we've said, and it's why we reiterated our guidance, that, you know, the discussions with larger companies is very, very promising. There's clear excitement about using the technology. I mean, I think they're seeing these kinds of results, and there's real excitement about scaling up their usage and getting to the point where they're using the technology at the scale that we're using it. So this is the larger companies. I know you didn't ask about that, but that's still obviously a very important part of the business.
Geoff ?
Great, thanks. Joe Catanzaro, Piper Sandler. Thanks for taking my questions. Maybe first one, sticking with the healthy volunteer MALT1 data, wondering if you could say anything about whether there was a dose, exposure, or duration relationship to the elevated bilirubin levels that you saw? And then whether you could say how the 150 mg BID dose compares to where you might land in the oncology setting, and then I have a maybe couple follow-ups after that.
So looking at the bilirubin elevations, there does appear to be some kind of a dose exposure response for those. Again, they're all grade 1, grade 2, predominantly grade 1. In addition, we did have actually the fortunateness to have some patients who did have Gilbert's syndrome or the mutation in the UGT1A enzyme, which causes elevated bilirubins. So despite having those mutations and having less enzyme, they didn't have higher than grade 1, really grade 2 elevations in bilirubin. So we're very pleased to see that. Although we will hit the UGT1A enzyme inhibition, that we are not seeing any high-level toxicities for those patients moving forward. And the other question?
Question on the dose.
The 150 mg.
Oh, the 150 BID dose. We have no expectation that the anticancer patient should have any different PK exposure than what we see in the healthy volunteer, although we need to do that proper study to find that out. You know, anticancer patients are exposed to prior,
... not anti-cancer, but cancer patients are exposed to prior anti-cancer therapies. They have comorbidities, co-meds, so we are going to do that, pharmacokinetic dose escalation study. As I said earlier, we're going to do a BID dosing.
Great, if I could just squeeze in, two follow-ups. Karen, I think you mentioned the L528W resistance mutation for BTK. It sounds like that may be becoming a more relevant mutation. I think that's the kinase dead mutation.
Yes.
Do you know whether in that context there's greater dependency on MALT1 or less dependency? And then sort of similar but different for EGFR, do you guys know if your molecule covers the non-classical mutations? I think those are seen post-osimertinib, but also sort of de novo upfront. Thanks.
So first of all, on the L528, we have not studied that particular mutation in combination with our MALT1 inhibitor. But, we have seen that resistance models, both for BCL-2 and, BTK, inhibitors, we're seeing a really nice effect of MALT1. So that's a study that I think we should look at, is these now emerging resistance mutations that are coming from the second and third gen of BTK inhibitors. Clearly, MALT1, upregulation or the whole CBM complex is a, a path for escape, from treatment with both BCL-2 and BTK inhibitors. So I think the hypothesis is out there, it needs to be tested and, and demonstrated with data. And then on the EGFR, Jean, I don't know if you wanna take that one?
Yeah. We are specifically targeting the C797S and the-
Uh-huh
... two driver mutations, the arginine and the exon 19 deletion. As to other mutations, since we don't have a final molecule, it's difficult to say specifically, but more on that as we advance the program.
I'm going to pause and ask, my colleague, Matt, if we have any questions from the web.
Yep. Hello? All right, good. Yeah, we have a couple from the web and a couple from email. So first on the web, maybe more on the EGFR. Question related to sort of characterize some. There's been a lot of other approaches targeting resistance mutations and our perspective on maybe some of the challenges facing those approaches, and more importantly, how we think we can be positively differentiated. And then after that, I have one for Geoff .
Yeah. So, we hope to get differentiation in the clean P450 profile and the wild-type selectivity, durable responses. So I think that package will compare favorably. What was? Was there another part to that, Matt?
No, it was, it was just characterizing our perspective on the challenges of, you know, TKIs or ADCs, and then how we-
Uh
... will be positively differentiated. I think you-
Yeah, I mean, may-
You got it.
... maybe I can add on that I think a hallmark for the programs you saw today, including EGFR, is our ability to dial in this exquisite selectivity, right? And I think as you're pointing out, a lot of the prior EGFR next gen compounds have unfortunately hit wild type, which results in rash, as I think everybody is aware. And when you're going for combinations, either with other EGFR inhibitors like osimertinib, or you're going for a combination even with a bispecific, hitting wild type is not a good thing. So that's a key portion of our strategy that I think many other programs that are in chasing these resistance mutants have had challenges with.
and then general kinome selectivity is another one, and I think our WEE1 and CDC7 programs are just exemplars for how powerful our platform is at addressing those challenges. Not to mention CNS penetration, and you heard a little of that today. That's key for this program.
Matt, the question for Geoff ?
Yeah. Sure. Okay, good. So you talked a lot about different ways that we can create value from the portfolio. But, honing in a little bit more on partnering and partnering strategy in particular, just talk a little bit more about how you view the optimal timing to pursue a partnership in the event that partnership is the mechanism that we would opt to follow.
Yeah. Yeah, I think our experience in recent years has kind of validated the notion that clinical data is generally required for high-value partnerships. I don't think that's an exclusive statement, but I think it's generally required. And so you've seen us embark on the portfolio of Phase I trials, and I commented earlier that, you know, that's likely to continue for the next few years, and we have potential new Phase I candidates lined up for 2025. So I think that that's an understanding that we have and an assumption we have that's incorporated into our business model and our planning. Now, there's not a huge burden associated with the cost of Phase I trials, and I think you're seeing across the industry reasonably attractive terms for Phase I.
That's not, again, an exclusive statement on our part. I think you-- more attractive terms are still associated with Phase II proof of concept data. So on-- in the right circumstances, with the right opportunity, I think that we will still be interested in advancing
... to complete that proof of concept study. The next question then is, okay, well, so what about going all the way to a pivotal trial? And this is something that we're asked about frequently. Fortunately, it's not a decision that we have to make today or tomorrow or in the next year or so. But ultimately, if there is a circumstance in which it does make financial sense, where we can generate attractive returns, where we're not going to compromise our balanced business model, our relatively, you know, sort of, I think, capital-efficient approach. If we see those opportunities, then when we're going to be willing to explore them. But that's not our primary strategy, and it's not the assumption that we're making as we're embarking on those programs.
Ramy, your comment, do you want to add to that?
Very well said.
No, I mean, I think because of the combination opportunities, as you've already mentioned, co-development opportunities where the partner allows us access or collaborates with us to develop not just the combinations, but obviously also the breadth of indications that are the potential for many of these mechanisms, we see partnerships as a really great way to maximize the potential value of these programs.
Yeah, exactly.
Other questions in the room? Matt, any other questions on the webcast?
Sure. So one for Dr. Yap. Most cancer patients are still treated in the community, so how widely have the patient stratification approaches such as CCNE been adopted in the community?
Yeah, that's a great question. You know, NGS testing now is standard of care, right? It's paid for by insurance, it's covered by insurance, and so the uptake of NGS testing now is standard in all patients. And so patients with advanced solid tumors should have NGS testing. And this has led to the detection of all of these alterations that I mentioned earlier, CCNE1 amplification, you know, BRCA1, BRCA2, DDR alterations, so on and so forth. And so that's really important because now patients actually know their mutational status, their copy number status, and they will be asking their physicians, you know, "What next?" Right? "Where can I get these drugs?" And so, you know, as I always say, if you build it, patients will come.
If you get the word out, and nowadays with social media, patient advocacy groups really pushing for patients to be matched with the right drug, right? Getting the right drug to the right patient, not just based on tumor types, but really based on the molecular subtypes of patients. So I, I think, with the approval of NGS, that really has been a game changer in terms of getting patients from the community into big cancer centers, to actually offer them, drugs that were, you know, mentioned today.
Anything further from the web?
All right, here's another. So we have one on MALT, another MALT one, but this time, so there was a reference about immunology and looking to understand a little bit more about a development plan there, indications that may make sense and how we think the profile might look there.
Well, we're still assessing that. As I mentioned in the slide about the genetic alterations, we do know that there are gain-of-function mutations in that CBM complex, and we know that there is prior data demonstrating that MALT1 inhibition can have effects in a wide range of diseases, but in particular, there's a study in RA. Now, as you know, there are a lot of emerging mechanisms that are small molecule in nature for RA and psoriasis and other diseases. So we have to assess whether we think MALT1 inhibition is going to compete well with those other mechanisms. But we are particularly interested in these gain-of-function situations that would represent perhaps a more rare disease, and where potentially we might be able to assess this in a Phase I study.
But we don't want to commit to anything today because we're still evaluating this, and this will be the subject of further updates.
We also know that the BTK inhibitors have been tested in multiple immune disorders, including multiple sclerosis, with very nice results, so there is validation for the cascade in these diseases.
Okay. Seeing no other questions in the room, I'm going to do a last call for questions from the webcast audience.
I got two more.
Sure thing.
Okay. So on CDC7, the presentation talked about the potential for CDC7 in a number of different tumor indications, but the initial work is only being done in AML and MDS. So maybe you could talk a little bit about development strategy post or beyond those two indications. And then I have one more for either Karen or Geoff after this.
Sure. So I can start on the, on the CDC7 question. I mean, you know, there was a predecessor molecule from another company that explored CDC7 inhibition in solid tumors. You know, we believe that we have the most potent CDC7 inhibitor, provides us with the best opportunity to evaluate inhibition of the target. We also firmly believe that patient segmentation is going to be important. So we think that, you know, AML and MDS actually provides a fantastic opportunity to establish rapid proof of concept, based on sort of the, where that disease lies, and to extract some understanding around the therapeutic index from there. We'll be thinking about patient segmentation in solid tumors.
My last one, I'm expecting an incredibly precise answer here. When do you expect to partner the PRMT5 program?
When do we expect-
When will you partner PRMT5?
Oh, to partner it? So we're obviously always open to discussions around partnering. Boy, that's something that's impossible to predict. It sort of requires another party, so that's a hard one.
Yeah. Nonetheless, I'd say if we are able to achieve this wild-type and MTAP selectivity in the CNS brain penetration, we think we're going to have a super competitive program.
Thank you, Matt. Thank you everyone who joined us on the webcast today, and thank you to everyone who came in person. We hope that you found this morning, you know, useful and a productive use of your time. We look forward to updating you as our programs progress, and see many of you in the new year in San Francisco. Thank you.