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spk54: Thank you for standing by, and welcome to ATRECA's fourth quarter and year-end 2022 earnings call. At this time, all participants are in a listen-only mode. After the speaker presentation, there will be a question-and-answer session. To ask a question during the session, you will need to press star 1-1 on your telephone. I would now like to hand the call over to Head of Investor Relations, Alex Gray. Please go ahead.
spk55: Thank you, Operator, and thank you to those joining us today. We are pleased to host our year-end 2022 conference call and webcast, including updated data from our ongoing Phase 1B trial of ATRC 101. Joining me for the prepared remarks are John Orwin, CEO, Dr. Tito Serafini, Chief Strategy Officer and Atreka founder, Dr. Philippe Bishop, Chief Medical Officer, and Dr. Stephen Gould, Chief Scientific Officer. Also on the line is Herb Cross, Chief Financial Officer, who will be available during the Q&A session. For those joining by phone, I'd note that we are presenting slides as part of today's program, which can be viewed via the webcast link included in our earnings release and posted to the events and presentations section of our investor relations website at ir.otreka.com. An archived replay of today's webcast and the accompanying slides will be available on our IR site following the live presentation. During today's call, we will be making forward-looking statements based on current expectations. These statements are subject to a number of significant risks and uncertainties, and our actual results may differ materially. For a description of risks and factors that could affect our future financial results in business, please refer to the disclosure in the accompanying slides, our most recent Forms 10-K and 10-Q, and the report that we may file on Form 8-K with the Securities and Exchange Commission. All our statements are made as of today, March 29, 2023, based on information currently available to us. We can give no assurance that these statements will prove to be correct. We undertake no duty to update these statements except as required by law. I'll now turn it over to John Orlin. John?
spk36: Thank you, Alex. On today's call, TIDA will provide an update on our discovery platform and its evolution. Philippe will present data from the ATRC-101 monotherapy and pembrolizumab combination cohorts in our ongoing Phase 1b trial, and Stephen will then provide an overview of our preclinical pipeline. I will then discuss our financials and upcoming milestones before opening the line for Q&A. Shown on slide four is a broad overview of our platform and pipeline. As a reminder, Matrica has a proprietary platform that enables us to access novel antibodies binding to novel tumor targets that would unlikely be found via traditional discovery approaches. As Tito will discuss in more detail, we have continued to invest in the development of the platform, which has enabled us to find promising antibodies and identify their targets more efficiently. From the platform, we've generated a robust pipeline led by ATRC 101, which, as we'll discuss later, has demonstrated durable anti-tumor activity in the ongoing Phase 1b trial, and which we believe validates the ability of our platform to identify active tumor-targeting antibodies with therapeutic potential. We plan to provide an update on our clinical strategy for ATRC 101, including a go-no-go decision for Phase 2 development by the end of this year. advancing multiple promising preclinical programs, including APN 497444, which targets a novel tumor-specific bican and is advancing as an antibody drug conjugate, as well as APN 346958, which recognizes the cell surface RNA binding protein target and is advancing as a T cell engager in partnership with NCORP. We expect to nominate clinical candidates from both programs later this year. and begin clinical studies for additional oncology programs in 2025. I will now turn it over to Tito to briefly discuss our discovery platform and its evolution before we review the updated ATRC 101 data and preclinical pipeline.
spk29: Thanks, John. On slide five, our pipeline is generated by an approach in which the active immune response guides us to novel antibodies finding novel targets. On the top half of the slide, starting on the left, Our approach begins with blood samples from patients whose adaptive immune system is attacking tumor tissue. Moving to the right, via those samples, we access that immune response and, importantly, the active immune response by analyzing single B cells of a defined type to generate, at high fidelity, the natively paired heavy and light chains of the antibodies that are being generated in that patient at that point in time. Moving again to the right, we then analyze and select those antibody sequences in silico for synthesis and further evaluation in the laboratory. By screening these synthesized antibodies in vitro, we ask a simple question. Does this antibody, which comes from the immune response of one patient, bind to tumor tissue of other patients, that is, non-autologous tumor tissue, and does it do so preferentially over normal tissue? If the answer is yes, and the antibody also binds to the surface of a tumor cell line as measured by flow cytometry, we have a HIT antibody. On the bottom half of the slide, we then further evaluate and develop our HIT antibodies in order to turn them into clinical candidates, as I'll describe in a moment in more detail. Moving to slide six, this slide illustrates the biology behind why our approach works. The key point of this slide is that we generate antibodies from plasma blasts, those four B cells in the middle of the figure. Plasmablasts uniquely provide information on the antigens being processed and the antibodies being generated during an active immune response. In the blowup, we're showing as dots antibodies generated at two time points from one patient, before treatment in purple and after treatment in green. And we've circled groups of dots. These groups of plasmablast antibodies are clonal families derived from a single progenitor B cell. And these particular families, colored green, regenerated in this case as the patient was successfully attacking his tumor tissue to yield a partial response. By analyzing clonal families such as these, their appearance, persistence, disappearance, size, all of that enabled by our approach, as well as by analyzing antibody sequences more directly, we focus on and select particular antibodies for further evaluation in the laboratory. Our in-silical analysis delivers synthesized antibodies binding non-autologous tumor tissue approximately 50% of the time in our primary screens. And as noted at the bottom of the slide, our proprietary approach is protected by composition of matter claims in multiple jurisdictions worldwide, which goes beyond the more typical method of use claims often granted around processes. Moving to slide seven, this is the discovery platform that we have built in over a decade to execute on our approach. I'll focus on a few key points. Starting on the left, we run our own non-interventional studies in order to acquire samples from cancer patients, and we have generated a valuable sample repository now with over 1,700 clinically annotated samples from over 500 donors representing nearly 40 tumor types. Moving right, I've briefly described that we use these samples to generate, analyze, and select plasmablast antibodies for analysis by histology and polycytometry to generate hit antibodies. And then moving further right, turning these hit antibodies into leads requires their evaluation in vitro for tumor-acidal activity, but in a manner that provides information about which weaponization would be most suitable. And then with the active antibody in hand that also has positive histology data, we work to identify the target bound by the antibody and eventually the epitope on that target. Moving further right again, if an antibody meets our criteria, we then work to generate a clinical candidate from that antibody by engineering a final weaponized format and optimizing its sequence, by assuring a suitable safety profile, and by identifying biomarkers suitable for use during clinical development. Moving to slide eight, as we promised to do, we've evolved the platform over time to achieve greater efficiency in delivering pipeline assets. On this slide, I'm highlighting a few of the more salient advances that we've made. Starting in the top left, we've expanded our sample collection to new sites and indications. Moving down, we're operating our flow cytometry now at an industrial scale and speed. And below that, our histological analysis has now incorporated more automation to enable earlier evaluation of tumor and normal tissue expression of our antibody targets. Moving to the top right, We've implemented proprietary high-throughput assays to measure in vitro the activity relevant to weaponization. Next down, whole genome functional genomic screens were added to existing biochemical methods to remove a bottleneck that target identification had represented in our platform. And finally, but again not exclusively, we've implemented structure-based and unbiased lead optimization to generate candidates in multiple weaponization formats. Moving to slide nine, we'll quickly review our current pipeline, all the assets of which have been generated by our platform. On slide 10, you see a listing of our clinical and later stage preclinical assets. There's our clinical stage asset, ATRC 101, which Philippe will discuss in detail. You'll then hear from Stephen about the other currently preclinical pipeline assets. Turning it over to Philippe.
spk49: Thanks, Tito. And thank you, everyone, for joining the call today. On slide 12 is a top line summary of ATRC 101 Phase 1B study update I am presenting today, which includes information from 71 patients treated in the ongoing trial, 21 of whom were enrolled since our March 22 update. The primary objective of the study is to evaluate safety, and we're pleased to share that ATRC 101 continues to be well tolerated in the monotherapy and combination arms including at the highest dose level of 30 milligram per kilogram. We continue to see anti-tumor activity in patients that express TARGET. Furthermore, we're excited to report that in this heterogeneous and heavily pretreated participant group, we are seeing durable responses and stable diseases across several cancer types in participants treated with monotherapy and combination therapy. Before we discuss the data, I will briefly review the trial design, the baseline characteristics of participants treated, and the analysis set in the next three slides. As a reminder, and as shown on slide 13, this is a basket trial enrolling patients across multiple tumor types. The primary objective of the trial is to determine the safety and tolerability of ATR-C101 when administered as monotherapy or in combination with key additional objectives, including measuring clinical activity, analyzing target expression, and determining indications for expansion. The trial began with ATRC-101 administered as monotherapy every three or two weeks, followed by studying the combination with pembrolizumab every three weeks in patients who had progressed or, in the opinion of the treating physician, achieved a non-satisfactory response following an anti-PD-1 or PD-L1 therapy. The initial dose escalation cohorts included patients regardless of target expression. Last year, when early data suggested that target expression appeared to discriminate patients likely to respond, we amended the protocol and started to enrich based on target expression. To date, we have treated participants at five dose levels ranging from 0.3 to 30 milligram per kilogram. Having completed the dose escalation phases of the trial, we're now expanding enrollment at the 30 milligram per kilogram every three-week dose level for both monotherapy and combination cohorts. Slide 14 is an overview of the baseline characteristics of participants enrolled onto study. As of the data cutoff of February 17, 2023, 71 participants had enrolled overall, with 48 on the three-week monotherapy schedule, 14 on the two-week monotherapy schedule, and nine in the combination arm. The median age of participants was 62 years, with most having an equal performance status of one. You can see how patients enrolled in the study are distributed across cancer types. It is very important to note that the majority of participants enrolled in the study have metastatic disease and were heavily pretreated with a median of five prior line of therapy. Nearly half of the patients had prior exposure to one or more checkpoint inhibitor, and for those enrolled onto the combination arm, as per protocol, all patients had to have received prior therapy with a PD-1 or PD-1 agent and experienced an unsatisfactory response or disease progression following treatment. On slide 15, I would like to describe the pertinent data sets used in today's presentation. Beginning with the safety, today's results will include all 71 participants enrolled onto study who received at least one dose of ATRC-101. Although we studied five dose levels, we consider pharmacologically relevant doses to be at the 3, 10, and 30 milligram per kilogram, either as a monotherapy or in combination with pembrolizumab. Participants treated at these doses will be the focus of the interim analysis for activity presented today. For these analyses, there are 62 patients with a large number enrolled at the 30 milligram per kilogram dose. Of the 62 subjects, 50 were evaluable for a score that is defined as a composite score comprised of target expression intensity by immunohistochemistry and the proportion of cells positive for target expression. When examining target expression correlations to clinical activity, we will focus on the 45 who were evaluable for resist and age score, and the 49 who were evaluable for best overall response and target expression. For these results, we will present the monotherapy results separately from the overall population that include nine individuals who received combination therapy. Presented on slide 16 is the distribution of participants accessible for overall response and age score by cancer type. As you can see, the number of subjects enrolled with specific tumor types range from 18 to 0. As such, the small numbers make it difficult for conclusive inferences about ATRC 101 activity for a specific cancer type or indication. And although we are getting close to sufficient numbers in some of the tumor types, we believe it is important to continue enrollment of the study to provide additional insights and inform future development decisions. Moving to slide 17, ATRC continues to be well tolerated. Of the 71 participants enrolled and who received at least one dose of ATRC-101, most of the reported adverse events were grade 1 or 2 as shown by the dark and blue bars for the treatment emergent adverse events on the left and the treatment related adverse events on the right. Of the adverse events observed, there remains no pattern to suggest a particular toxicity profile nor were there a relationship between incidence of severity of adverse events with dose or incidence of adverse events with target expression. The most common treatment-related adverse events were pain, fatigue, and nausea, with no serious adverse events determined to be related to treatment with ATRC-101. Only two Grade III AEs were reported as potentially treatment-related, including one instance each of a headache and a small intestinal obstruction. Six patients experienced an AAE leading to dose interruptions. These included patients who had a grade two infusion reaction on cycle one, day one. The infusion was interrupted temporarily and the AAE managed as per protocol. The dosing was restarted without complication. Others included liver function laboratory abnormalities a grade 1 tachycardia, a grade 2 nausea, a grade 2 fatigue, and the grade 3 small intestinal obstruction that was noted earlier in my comments. No participant has had to come off study due to drug-related toxicity. Moving to slide 18, the interim assessment for activity once again supports the use of an H-score cutoff to predict the probability of observing disease control or tumor response to ATRC101. As noted previously, the H-score is obtained using a CAP-CLIA immunohistochemistry-based assay. An H-score can range from zero at the negative end to a maximum target expression score of 300. Based on prior analysis showing a correlation of H-score to response or disease control, the target positive H-score cutoff implies an H-score greater to or equal to 50. On the left bar graph, For patients who received monotherapy, 59% achieved disease control if their tumor expressed the target. This is in contrast to 25% of patients whose tumor had an age score below 50. The bar graph on the right includes patients treated with combination therapy and yielded a similar result. On slide 19 is another way of assessing anti-tumor activity associated with target expression. Here we are looking at individual patient data over time for patients whose tumor has a low age score. Those treated with monotherapy are shown on the left, and on the right, the graph also includes those treated with combination therapy. As is shown here, most patients' disease progression occurred early, soon after the first month following initiation of protocol therapy. Only four patients had stable disease going past 100 days, and all experienced a disease progression at 180 days or soon thereafter. On slide 20, we compared those with low target scores in the light blue lines to those with age scores of 50 or greater in the dark blue lines. And we can see that there is a greater number of patients experiencing a durable objective response or durable disease control. Several of them are well past 180 days after having initiated protocol therapy. In the model therapy cohort, the bottom curve shows a patient with 40% tumor size reduction that lasted for more than 300 days. This is the patient with mild small cell lung cancer we had previously reported to have achieved the PR. That patient's tumor has an age score of 80 and PFS was documented at study date 350. Including those who received combination therapy on the right, we can see the melanoma patient at the bottom that we had previously reported to have achieved a CR, and that patient had their most recent response assessment at day 418 following initiation of protocol therapy. That patient's tumor had an H score of 75 and to this day continues to remain on study. Slide 21 focuses on the durability of tumor response observed by cancer type. for all patients treated with ATRC-101 as monotherapy or in combination with PEMBRO and whose tumor was target positive. As shown by the different line colors depicting different cancer type, durable activity is seen across multiple tumor types including melanoma, non-small cell lung cancer, head and neck cancer, colon cancer, as well as breast cancer patients who had progression-free survival documented at study day 210. Another way of looking at the anti-tumor activity by tumor type and age score is shown in the waterfall plot on slide 22. On the left bar graph, patients with low target expression experience increase in the size of target lesions, except for one patient with ovarian cancer who had a small reduction in the size of her cancer. Patients who receive ATRC-101 alone are shown in the solid bars. Those who receive combination therapy are shown in the hash bars. This is in contrast to patients whose tumor had a higher target expression on the right bar graph. Here we see that several patients had tumor reductions in both the monotherapy cohort, the solid bars, and the combination therapy cohort, the hash bars. Slide 23 is a Kappelmeyer analysis measuring progression-free survival for patients treated as a function of H-score. On the left are the patients who receive monotherapy. On the right, the Kaplan-Meier analysis includes a patient treated with monotherapy or combination therapy. Patients with an H-score of 50 or greater in the dark line have a longer progression-free survival than patients with H-score less than 50 in the blue light lines. The curves separate early at 30 days and remain separated over time. For the monotherapy cohort, the hazard ratio is 0.47 for the difference of target positive and target negative patients, and is similar to the hazard ratio observed for all patients treated with ATRC-101. That also includes those who receive combination therapy. Here, the hazard ratio is 0.4 for the difference of target positive and target negative patients. Of interest are the small vertical censored line on the curve representing patients who have not experienced an event. These patients remain on study and are still receiving protocol therapy. As you can see, some patients have passed 180 days at the tail end of the dark progression-free survival curve. Now moving to the data summary and next steps on slide 24. This is a Phase 1b trial. and it has and continues to enroll patients that have, for the most part, exhausted standard of care. With this data update, ATRC 101 continues to be well tolerated. There were no DLTs up to the 30 milligram per kilogram dose level tested. What we are learning with this data update is that longer progression-free survival appears to be associated with ATRC 101 target expression in patients with cancer. While durable disease control was seen across several tumor types, it is too early to quantify and properly qualify the nature of these responses. To do so, we will need to enroll additional patients across cancer types, and our current recruitment efforts will need to focus on underrepresented patients. We continue to focus enrollment based on target expression at the 30 milligram per kilogram dose in both the monotherapy in combination with pembrolizumab cohorts. In the past several months, we opened the study at five new sites and close to, and we have contracted with nine additional sites in startup activities. In addition, we have seven sites undergoing feasibility. Going forward, a total of 28 centers are expected to participate and contribute to the study. In addition, we adapted the protocol eligibility criteria based on investigative feedback, and in some instances worked with specific clinical centers to overcome staffing issues post-pandemic. All these activities have already and are expected to continue to help increase enrollment onto study. Overall, we are targeting 30 to 40 new additional patients for recruitment distributed across indications to make adequate go-no-go decisions by year-end 2023. That said, because we're enriching for target expression, We have seen, not unexpectedly, screen failures due to restricting enrollment to patients whose tumor are target positive. The screen failures are in line with prior expectations to target prevalence. Finally, our recruiting efforts have already seen improvements. The additional data we expect to collect should position us well to enable a go-no-go decision for further development of ATRC 101 by year end. paving the way for determining a registration path with defined commercial opportunity for ATRC 101. I will now turn it over to Stephen to discuss our preclinical pipeline program.
spk27: Thank you, Philippe. I'll now review three of our late lead oncology programs moving toward candidate nomination. The first, highlighted on slide 26, is a novel tumor-specific anti-glycan antibody that we're advancing as an antibody drug conjugate or ADC. referred subsequently to as antibody 444. 444 is one of a growing number of anti-glycan antibodies that we are uncovering with our platform. This is exciting as aberrant glycosylation has long been recognized as a hallmark of cancer, but this class of targets has been difficult to address through standard methods. As I'll show you, 444 displays uniform and selective binding on tumors with high prevalence on colorectal cancer and is active as an ADC, both in vitro and in vivo. We're currently optimizing both the antibody portion of the molecule and the linker drug portion to yield a candidate, a clinical candidate, that we expect to nominate by year end, with an IND target for late 2024. The bar plot in the top left of slide 27 shows why we're so excited about this antibody. Morpho4 exhibits strong immunoreactivity, i.e. 2-plus and 3-plus staining, in greater than 70% of colorectal cancer. And I hope you can appreciate that this staining is very uniform in the images to the right where essentially all tumor cells are positive for the epitope. We also see high prevalence in gastric cancer with a lower prevalence in several indications, including uterine, pancreatic, esophageal, and lung cancer. Importantly, we do not detect membranous immunoreactivity on 27 normal fresh frozen tissues. The highest signal in normal tissue is moderate cytoplasmic staining in the stomach. which we suspect from data that I'll share in the coming slides is not accessible to the antibody. On slide 28, you can see that consistent with the abundant immunoactivity in colorectal and gastric cancer, 444 binds to cell lines derived from these tissues, highlighted in blue, and not to those derived from other tissues. We screen for ADC activity, shown on the right. 444 leads to cytotoxicity in cells that express high and low to moderate levels of target, in the case of LOVO and NUGZ4, respectively. On slide 29, you can see that 444, before any affinity maturation, when formatted as an ADC using ZymWorx ZymLink or a statin-based linker payload, leads to dose-responsive antitumor activity after a single dose in a LOVO xenograft model. This model expresses a relative relatively high level of target, but as shown to the right, the level of staining is comparable to what can be found in human cancer and therefore is a relevant model system. Importantly, 444 has been tolerated in both single and multiple dose studies in mice without body weight loss or histopathologic findings. 444 as an ADC has also been explored in initial PK tolerability assessment in rats and has been well tolerated up to 30 mg per kg with the Zymelink or statin linker payload. I should note that the moderate cytoplasmic staining I pointed out earlier in the human stomach is also observed in both mice and rats. The fact that the ADC is well-tolerated in both species suggests, again, that this intracellular pool of target is not accessible to the ADC. Moving now to slide 30. At this point in the project, we had a very interesting antibody with tumor-specific expression and intriguing anti-tumor activity, but we didn't know the target. Attempts to de-orphanize the antibody using standard approaches, such as commercial protein or glycan arrays, had failed to this point. And as Tito mentioned, we have now enabled whole genome CRISPR screens in-house, and 444 was one of the first antibodies we assayed with this approach. Using a CRISPR knockout approach, we knocked out genes individually and assessed which genes were essential for 444 binding to a flow-positive cell line. Three genes were identified as being required for 4-4-4 binding, two glycosycele transferases, beta-4-galan T3, and FUT4, as well as a fucose transporter. The fucose transporter makes sense in the context of FUT4, which requires fucose as a substrate. Interestingly, when one looks at the expression of the two glycosycele transferases at the RNA level in normal tissue, they're largely not co-expressed, a feature that helps explain the near absence of immunoreactivity in normal tissues. We validated that these two enzymes were required by expressing them in a cell line that did not express the target for 444. Upon co-expression, a dramatic right shift in the flow cytometry plot shown to the right suggests that these enzymes are required to present the glycan on the cell surface, at least in this context. Based on the substrate specificity of these two enzymes, we understand what glycan structure is likely required for binding and are confirming this through biochemical means. Advancing to slide 31, I alluded to the fact that 444 is one of a growing number of anti-glycan antibodies being discovered by our platform. In fact, half of the antibodies for which we have identified the target are anti-glycan antibodies. Our platform appears uniquely positioned to help uncover the potential of this underexploited class of antibodies. The platform, of course, also identifies antibodies to protein targets. And one theme that has emerged is the mislocalization of normal intracellular targets to the cell surface. A good example of this is our next late lead asset, 958, highlighted on slide 32. 958 recognizes an RNA binding protein that is normally sequestered in the nucleus but is mislocalized to the cell surface in tumors potentially via stress granules. 958 is advancing as a CD3 bispecific T-cell engager in collaboration with Zencore, where Atreca is taking the lead on the preclinical and clinical development. We expect to nominate a clinical candidate by year end and are targeting an IND submission by early 2025. On slide 33, similar to the anti-glycan antibody 444, the native antibody of 958 straight from the patient shows preclinical activity. In this case, however, we formatted the antibody as a T-cell engager using XENCOR's ECMAB CD3 bispecific platform. As shown on the left, the 958 bispecific leads to tumor stasis in a target positive prostate cancer xenograft model in the blue line. We're currently optimizing the antibody to further enhance the potency to match or beat the positive control T-cell bispecific used in this study, which is directed against a well-known prostate cancer target, PSMA, shown in orange. On the right, you can see that 958 leads to the expected pharmacodynamic effects for molecules with this mechanism of action, including robust immune activation as evidenced by an increase in interferon gamma levels in plasma and expansion of CD8 positive T cells in blood. 958 is the first molecule to advance as part of our collaboration with Zancor, the details of which are described in more detail on slide 34. In this collaboration, Atreca will provide antibodies against novel targets, and Zancor will engineer bispecific antibodies using their XMAP CD3 platform. The two companies will mutually select up to two joint programs for further development and commercialization, with each partner sharing 50% of the costs and profits. While each company will lead one of the joint programs, the agreement allows each partner to pursue up to two programs independently. The last oncology lead I will review is highlighted on slide 35. 597 is our anti-FA2 antibody, which targets a novel, well-conserved membrane proximal epitope on FA2, a validated oncology target that is overexpressed in a range of tumor types. We have generated a series of antibody variants with a range of affinities to FA2 and have tested these in various weaponization schemes where they're broadly active. Previously, we advanced a high affinity variant as an ADC and are now evaluating antibody variants in CD3 T cell engager format based on the in vivo activity we've observed. Moving to slide 36, I hope you share our excitement about the molecules I highlighted for you today. We're equally excited about molecules coming from the platform, which are at an earlier stage. As Tito mentioned at the beginning of the presentation, We believe investments we've made across our platform, especially around target identification with the implementation of CRISPR screening, have eliminated common bottlenecks and made the platform even more productive. We believe Atreca is well positioned to capitalize on the discovery and development of novel oncology targets. Finally, while not an internal pipeline molecule, we wish to highlight another exciting asset, Atreca's anti-malaria antibody, ATRC501, on slide 37. ATRC 501 is an engineered version of an ATRECA discovered antibody designed to prevent malaria infection. The antibody is licensed to the Gates Medical Research Institute, which is preparing to file an IND this year. ATRECA retains rights in the U.S., Europe, and parts of Asia with potential product development opportunities, including prophylaxis for those traveling to malaria-endemic regions. And with that, I'll hand it back over to John to discuss our upcoming milestones and provide an overview of our financials and IP.
spk36: Thank you, Steven. Slide 39 is an overview of our upcoming milestones. As Philippe noted, we are planning to provide updated data and a go-no-go decision for Phase II development of ATRC 101 later this year and potentially begin Phase II studies next year. On the preclinical side, we expect to nominate clinical candidates in the 444 and 958 programs later this year and are targeting INDs in late 2024 and early 2025, respectively. And behind those, our early stage discovery and lead generation efforts are ongoing. Finally, Gates MRI continues to advance ATRC 501 and is expecting to file an IND this year. Returning to slide 40, This addresses our financials and intellectual property. As of December 31st of last year, we had $70.5 million in cash equivalents and investments, which is expected to fund operations through the end of this year. We have a strong IP position with patents issued covering critical aspects of a trade discovery platform, as well as ATRC 101 and related antibodies with pending applications covering other pipeline assets. That concludes today's prepared remarks. We'd like to thank our trial participants and their families, as well as investigators and research staff at our clinical sites. Thanks again to everyone who joined the conference call and webcast today. With that, operator, could you please open the line for the Q&A?
spk54: As a reminder, to ask a question, you will need to press star 1 1 on your telephone. Again, that's star 1 1 on your telephone to ask a question. Please stand by while we compile the Q&A roster. Our first question comes from the line of Divya Rao of Cohen. Your question, please, Divya.
spk21: Hi, guys. Thanks for taking our question for Phil. Just based on your experience, when you're trying to enrich for high age score patients, what would you say is the percent of patients that fit that eligibility criteria? And then I guess as a follow up, how does that change in terms of indications that maybe you're not seeing as many patients enrolled in?
spk49: Yes, well, thank you. So as you know, in the preclinical assessment of the program, we had done some prevalence assessments in microarrays. So these are tumors in microarrays looking at the presence of target on these tumors. And we had assessed that somewhere in the neighborhood of between 30% to 50% of the tumors that we were looking across all the indications were expressing the target. What we're observing in the clinical trial is similar to that. It's consistent with that prevalence data that we had generated previously. And depending which indication we're looking, for the most part, we're seeing about 50% of the tumors expressing the target.
spk20: That's helpful. Congrats on all of the data. Well, thank you very much.
spk54: Thank you. Our next question comes from the line of Roger Song of Jefferies. Your question, please, Roger.
spk51: Great. Thanks for the data update and taking our questions. A couple from us. So the first one is, you know, for this you know the patient, you have median five prior lines. Can you just help us to conceptualize what is the expected OR or PFS in this population from, you know, standard of care or whatever the care, whatever the therapy available to those patients?
spk45: Yes.
spk49: So, Roger, the It depends which indication you're looking at. For some patients, as you may be aware, such as lung cancer, breast cancer would be another example. As you begin to exhaust standard of care, the expected progression-free survival gets shorter and shorter with subsequent lines of therapy. There are some other indications of where You can observe from time to time indolent disease. I would think some colorectal cancers are like that. And as you know, with melanoma as well, we have seen with the advent of immunotherapy, individuals now are having longer periods where you see progression-free survivals occurring. I think for the most part in our study, with the patients we are looking at, they come in already heavily pretreated. They tend to have an ECOG performance status of 1, which also predicts worse outcome for these individuals. And so for them, I think Looking at the data, I think it's important to note anyone that would go past the six-month mark. I think the PFS at six months is an important landmark. The PFS at four months for some of those indications may also be equally interesting to look at.
spk36: Yeah, I'd probably just add to that, Roger, that I think, you know, given the heterogeneity of these patients, different tumor types, and the, you know, sort of open-label of the trial, I think we certainly need to have more patients before we could really draw conclusions about the efficacy or the activity that we're seeing and how it compares with standard care. I think we are encouraged by the fact that where we do see more disease control and where we have seen responses is primarily in the context of patients who are expressing target. So that does give us some encouragement that what we're seeing is real and a function of HRC 101. But clearly we'll need more patients, and that's why we're continuing to enroll, adding additional centers, and hope to have sufficient data by the end of this year to really be in a position to make a decision about, you know, whether and where to go to Phase II or HRC 101.
spk51: Okay, great. Maybe just that leads to my next question. Regarding the additional patient, about 40 to 50 patients, would you expect those patients will be slightly different from what you have in terms of the tumor type and the prior line of therapy? And just remind us, what is the breakdown between the monotherapy versus the the combination therapy, and when you make the go-no-go decision, what will be the key efficacy endpoint you were looking at, like the disease control or OR or PFS? Sorry for the long, long questions here.
spk49: So I'll try to address all the questions and points that you have raised. I think for the patients that are going to be enrolling, the 30 to 40 patients that we expect to enroll that will be new, and with the changes that we have made going to centers that are more adept to enrolling Phase II patients as opposed to Phase I, as you know, Phase I units are highly specialized. And here what we have done is gone to centers that are hybrid between academic centers and community centers where we're seeing patients, a greater number of patients that would be eligible for our trial. So that's one point to make. And what we expect to see there is a distribution across the various tumor types that we're seeking to enroll into. Some of those centers are more likely to enroll individuals, for example, with lung cancer, others with breast cancer, but we're also looking at centers that can help augment our database for head and neck and urothelial cancers as well. So we're looking, our recruitment efforts are targeted at this point, and we're looking to try to supplement those underrepresented patient populations. And the goal for that is really for us to be able to look at where our strongest signal comes from. And there we'll be looking at, I think, response rates, obviously, responders. As you know, we have the lung cancer and the melanoma patients that have been durable. I think that's... That's notable. But what is new with the data that we're presenting today is really this notion of disease control and the ability to see patients staying on study for a longer period of time. So we'll be incorporating a component of disease control into our decision algorithm. And we plan to update you at some point about how we're going to approach that and and base it, of course, on sound analytic principles. So with regards to the type of patients that we're planning to see, the eligibility criteria remains as it is and will continue to remain as is for the time being. So we don't really expect that the patients that we'll be seeing coming on to study will be much different. They will be individuals that have exhausted, for the most part, standard of care and have either advanced or metastatic disease. So we would think that these patients will be similar to the ones that we've enrolled to date. We're continuing to enrich for target as of today, and those patients are getting enrolled at the 30 milligram per kilogram dose cohort.
spk36: And in terms of, I think, what we objectively need in terms of our response rate or durability, of either responses or disease control or generally, I think it depends also on the tumor type, right? As Philippe alluded to, you know, some of these are tumor types where it's not entirely uncommon to see patients with, you know, indolent disease. And then there are other settings if we take our, you know, our response with a 50% tumor reduction in lung cancer, that's, you know, fifth line lung cancer, that's a setting where we wouldn't expect to see influenza disease. But then we have to overlay on top of that, what's the unmet need? What would the regulatory hurdle be? Because the whole point of that randomized phase two trial is to really set up what could be a potential registration. So I think it'll be taking all of those things into consideration and applying relatively high bar, particularly in any setting where there's a well-established standard of care.
spk51: Got it. Yeah, thanks for the thorough answer. Just to clarify, what is the breakdown between the monotherapy and the combination therapy for the new 30 to 40 patients enrollment?
spk49: So this will be obviously considered with the eligibility criteria. So for patients that would be considered to continue on PEMBRO or to receive a PEMBRO-containing regimen. Those indications are, as you know, based on the PEMBRO label. So there we have some differences with the monotherapy. And the monotherapy, as you know, was based on our earlier recommendations. data showing that there was a high prevalence of target in these various tumor types. So, if the physician thinks that PEMBRO is not indicated or the patient had already received PD-1 or PD-L1 agent and unlikely to respond, it is likely that they'll be brought on to the immunotherapy. if they meet eligibility. And for those for whom the physician believes that continuing on PEMBRO would be suitable, we would probably see those coming onto the combination arm. And I should point out that urothelial malignancies, esophageal malignancies, the head and neck malignancies, and subset of breast cancer, the triple negative breast cancers, and the hepatocellular carcinoma would be indications that we would see in the combination arm that would not be appropriate for the monotherapy arm based on eligibility criteria.
spk36: Yeah, and I think even in a setting where we have cohorts open for monotherapy and combo with pembrolizumab, I think we would likely... need to show more single suggestion of single agent activity for the FDA anyway. So to some extent we'd like to see more combination patients, but to some extent we also benefit from more monotherapy, because I think that's something that, you know, that individual contribution is something that probably the FDA would want us to answer. But at this point, those centers, most of them would have basically the choice and use their own discretion. At least for breast, lung, ovarian, colorectal.
spk51: Gotcha. Yeah, that makes sense. Okay, thank you.
spk37: Thank you, Roger.
spk54: Thank you. Our next question comes from the line of John Newman of Canaccord. Your question please, John.
spk30: Hi, guys. Thanks for taking my question. Just wondering, with the currently ongoing Phase 1 study for 101, how much follow-up time will be allotted? Just wondering if you'll be able to follow the study longer term for things like overall survival, where perhaps there's a signal that shows up that doesn't initially show up in the response rate.
spk32: Thanks.
spk49: Yes, so right now the data that is being collected obviously is response rates, and we're looking at progression pre-intervals. Survival is collected when that event occurs for patients that are on study during the period of follow-up, but we're not following patients once they come off study. So the overall survival data would not be something that we would expect to report on with this trial. I think what we're looking at is for response rate and disease control to give us an idea of the signal and help us prioritize which indication is most likely to be seeing or deriving some kind of benefit from being treated with ATRC-101. And that sets the stage really for the Phase II study that John was talking about where they're in a more formal way and ideally in the controlled fashion with an appropriate control, we would be assessing what a true treatment effect would be for Phase III in order to appropriately design the Phase III trial. And that Phase II could include collecting survival data.
spk31: Okay, great. Thanks. Thanks, John.
spk54: Thank you. Our next question comes from the line of Tony Butler of EF Hutton. Your line is open, Tony.
spk28: Yes, thanks very much. So if I understand correctly, preclinical work had demonstrated that ATRC 101 actually remodeled the tumor microenvironment, if I'm correct in that. If that's true, one of the questions that comes to mind is this notion of combination where, as I think you stated, utilizing PEMBRO with 101 was really related to those indications where PEMBRO was already indicated. If that's true, that's fine, and I'm respectful of that. But the real question is, in cold tumors, for example, in CRC and or ovarian where PEMBRO just has no effect, there may be, if in fact you do get TME remodeling, there may be some really decent signals here where in those tumors, that combination could then therefore be advantageous. And so, for example, it wouldn't take a lot from a response rate to really demonstrate in a late-line CRC patient that you really have something of benefit. I am respectful that in monotherapy you may have modest benefit, but yet certainly in combination there is at least a question there that, gee, if you could show anything better than regrafinib, you really have an opportunity set. And I'm just throwing this out as a thought. if it's directionally correct, or maybe what you think about it. Thank you.
spk36: Yeah, maybe you want to address that from the preclinical side, and then, I don't know, maybe we have some further thoughts. Thanks for the question, Tony.
spk29: Yeah, Tony. So, you know, you are right, you know, in the sense that if the mechanism is directed towards the innate immune system, then that's upstream of the of agents that act on T cells, like anti-PD1 or PD-L1 checkpoint inhibitors. And so, yes, in principle, that converting, you know, tumors that normally don't have much of a, you know, an immune response with ATR-C11 is possible. And we all know that, as you point out, CRC is one of those tumor types.
spk49: Yeah, from a clinical end, you raise, I think, a very provocative thought and question that I think would be at some point worth addressing, you know, in a clinical setting. I think, as you know, the individuals with mismatch repair or MSI high colon cancer are more likely to to have a response with pembrolizumab or the PD-1 or PD-L1 agents. And I think this concept of cold and converting a cold tumor to something that is more likely to respond is something that is worth investigating for sure.
spk54: Thanks very much.
spk35: Good suggestion, Tony. Thank you for raising it.
spk54: Thank you. Our next question comes from the line of Stephen Willey of Stifel. Your question, please, Stephen.
spk07: Yeah, good afternoon, guys. Thanks for taking the question. I think I've asked you this before, but I'm going to ask it again. And just curious if in this incremental patient data set, you were able to somehow look at longitudinal H-score expression. just as a way to assess the stability of target expression over time.
spk49: So, thank you for the question. We are collecting biopsies, well-owned studies for patients that consent to it. And we are planning to do some analysis longitudinally for those matched biopsies that we've obtained. As you know, there are studies that are not that easy to conduct. And with small numbers, we have to be careful with inferences. To date, what we have is the baseline data. We've batched the specimens. and plan to analyze this at the final analysis. So we have not looked at the serial biopsies yet for those, for the patients whom have given us, you know, permission to go ahead and sample again. And just for clarity, we do it during, at baseline, we do it during the first cycle, and we do it also at the disease progression.
spk07: Okay. And then I think, Eligibility for the combo cohort required either progression on a PD-1 or L1 targeting MAP and or stable disease on a PD-1 or L1 targeting MAP. I'm just curious if you know offhand if the incremental patients enrolled into the combo cohort either fit the progression definition or if there were some patients in there who also fit the stable disease definition?
spk49: Yes, so I think the eligibility criteria is worded slightly differently. It's an unsatisfactory response while on PD-1 or PD-L1 agent. and or disease progression. So there in the opinion of the physician, the response that was obtained while on the PD-1 or PD-L1 would have to be unsatisfactory and require the institution of new therapy. What we have is for the most part looking at those nine individuals The reason for the last therapy was really a lack of efficacy and progressive disease. So looking at those individuals, I would say that most of them would have had progressive disease.
spk07: Okay. And just with respect to the goal of enrolling an additional 30 to 40 patients before the end of this year, I know you've kind of talked about some of the the headwinds that a lot of these phase one sites are facing, and we've heard that from other companies as well. But I guess would you still – is the 30 to 40 incremental amount of patient data, is that requisite for making a no-go decision before year end, or is that something that is a little bit fungible in terms of timelines? Yes.
spk49: So as you know, the trial is currently set up as an assignment two-stage study with criteria for expansion within specific indications. I think like early phase one studies, as you learn about your drug and you begin to collect information, adapting your approach and incorporating what you're learning along the way is something that is done by most companies and certainly encouraged even by health authorities. So early in trial development, we tend to be Bayesian, if you will. We tend to adapt as we learn more about our drug, either on the safety side or on the activity side or even sometimes with pharmacokinetics. We can certainly modify the way we approach looking at this data. What is new with today's presentation is the notion of disease control or stabilization of disease or durability of response. And I think that's a very important new information that we have today. If we think about a higher bar for making decisions, I think applying a bar that not only looks at response rate but also looks at some form of disease control would allow us to prioritize indications for moving forward. And for that, I don't think we would need to expand each one of those indications as we had planned earlier. And we can probably make those decisions based on sound analytic principles using Bayesian statistics with fewer patients in each one of the categories.
spk07: Okay. And then maybe just lastly, just in terms of I thought it was interesting that you disclosed that about half of the antibodies that you're disclosing are actually against these glycan targets, which I know from, as you mentioned, kind of the conventional immunization perspective have been really hard. These are carbohydrates. Just curious as to kind of where you think your progress puts you from a collaborative position. just kind of given the amount of interest there has been around this target class historically.
spk29: Hi, Steven. So I'll take that one. So we're in a number of discussions about programs, obviously. The profile of 444, as Steven described it, is proving to be quite attractive. and garnering a great deal of interest. You have something that's, you know, binding a target expressed at fairly high levels in the majority of colorectal cancer patients where there's huge unmet need, and yet you see great potency and, you know, lack of a safety signal so far, even with an FV that has not yet been optimized. And so, yeah, I think you're right. You know, there are a couple of anti-glycan antibodies that have reached commercial stage. And part of the problem there is huge black box warnings is they're not specific to tumor. They attack peripheral nerve, for example. And what I believe you're hearing today in Stephen's part of the presentation is that our platform is delivering what you might expect. It's glycans that you can't really find through molecular biology tricks. You just can't do it that easily with glycans. And they are fairly specific. And as you point out, we have a very nice IgG antibody recognizing that glycan simultaneously.
spk06: Great. Thanks for taking the questions, Jeff.
spk22: Thanks, Dean. We have time for one more question.
spk54: Yes, sir. Our final question comes from the line of Kemp Dolliver of Brookline. Your line is open, Kemp.
spk43: Thank you. I have a couple questions there. Some of them are pointed and quick. I'll be respectful of your time, but quickly with regard to the incremental enrollment, what would be the assume data cutoff to make a decision in the timeframe you're thinking?
spk49: So, yeah, obviously we're going to enroll and collect data until the study comes to fruition. I think we will report on, you know, when it's appropriate by the end of the year what our most up-to-date results would be. And I think, you know, the data cutoff for that typically requires, you know, a few weeks for us to be able to analyze that data and put it together.
spk36: Yeah, I think maybe one of the challenges you might be alluding to, and I think it's an important one, is having sufficient follow-up, you know, to be able to assess durability of response. So I think it might be a little bit easier in a way to make a no-go decision than it is a go decision. The no-go decision would be based on not seeing a level of activity for a given indication or for the program overall that would lead you to not move forward in phase two. A go to phase two decision is a clinical decision, but it's also a business decision. And I think that you could imagine a scenario where you've got responders or long-term stable disease and you want to give a little bit more time before making the decision to pull the trigger on an expensive Phase II program. But I think, you know, our commitment is really to try to, you know, provide fairly regular update and get to a crisp decision, you know, by the end of this year, plus minus, when we basically don't want to leave the study just open enrollment patients without making a decision to go to phase two, or possibly end the program. I think we all feel pretty encouraged by the data that we're seeing, the durability of the responses, the PFS that seems to favor patients who express target, but I also think it's important for us to get to because there's an opportunity cost here when you look at the other molecules that we have that are going to IND in the next 18 months.
spk42: I will stop there. Thank you.
spk36: Okay, great. Well, thanks a lot. Much appreciated, Kemp. Thanks, everyone, for your questions today and for joining the call. and I look forward to additional updates in the future.
spk54: Thank you. This concludes today's conference call. Thank you for participating. You may now disconnect.
spk31: Thank you. Thank you. Hello. Thank you. Music.
spk00: Thank you.
spk54: Thank you for standing by, and welcome to ATRECA's fourth quarter and year-end 2022 earnings call. At this time, all participants are in a listen-only mode. After the speaker presentation, there will be a question-and-answer session. To ask a question during the session, you will need to press star 1-1 on your telephone. I would now like to hand the call over to Head of Investor Relations, Alex Gray. Please go ahead.
spk55: Thank you, Operator, and thank you to those joining us today. We are pleased to host our year-end 2022 conference call and webcast, including updated data from our ongoing Phase 1B trial of ATRC 101. Joining me for the prepared remarks are John Orwin, CEO, Dr. Tito Serafini, Chief Strategy Officer and a Traeger founder, Dr. Philippe Bishop, Chief Medical Officer, and Dr. Stephen Gould, Chief Scientific Officer. Also on the line is Herb Cross, Chief Financial Officer, who will be available during the Q&A session. For those joining by phone, I'd note that we are presenting slides as part of today's program, which can be viewed via the webcast link included in our earnings release and posted to the events and presentations section of our investor relations website at ir.otreka.com. An archived replay of today's webcast and the accompanying slides will be available on our IR site following the live presentation. During today's call, we will be making forward-looking statements based on current expectations. These statements are subject to a number of significant risks and uncertainties, and our actual results may differ materially. For a description of risks and factors that could affect our future financial results in business, please refer to the disclosure in the accompanying slides, our most recent Forms 10-K and 10-Q, and the report that we may file on Form 8-K with the Securities and Exchange Commission. All our statements are made as of today, March 29th, 2023, based on information currently available to us. We can give no assurance that these statements will prove to be correct. We undertake no duty to update these statements, except as required by law. I'll now turn it over to John Orlin. John?
spk36: Thank you, Alex. On today's call, Tito will provide an update on our discovery platform and its evolution. Philippe will present data from the ATRC-101 monotherapy and Pembrolizumab combination cohorts in our ongoing Phase 1b trial, and Stephen will then provide an overview of our preclinical pipeline. I will then discuss our financials and upcoming milestones before opening the line for Q&A. Shown on slide four is a broad overview of our platform and pipeline. As a reminder, Matrica has a proprietary platform that enables us to access novel antibodies binding to novel tumor targets that would unlikely be found via traditional discovery approaches. As Tito will discuss in more detail, we have continued to invest in the development of the platform, which has enabled us to find promising antibodies and identify their targets more efficiently. From the platform, we've generated a robust pipeline led by ATRC 101, which, as we'll discuss later, has demonstrated durable anti-tumor activity in the ongoing Phase 1b trial, and which we believe validates the ability of our platform to identify active tumor-targeting antibodies with therapeutic potential. We plan to provide an update on our clinical strategy for ATRC 101, including a go-no-go decision for Phase 2 development by the end of this year. advancing multiple promising preclinical programs, including APN 497444, which targets a novel tumor-specific BICAN and is advancing as an antibody drug conjugate, as well as APN 346958, which recognizes the cell surface RNA binding protein target and is advancing as a T cell engager in partnership with NCORP. We expect to nominate clinical candidates from both programs later this year. and begin clinical studies for additional oncology programs in 2025. I will now turn it over to Tito to briefly discuss our discovery platform and its evolution before we review the updated ATRC 101 data and preclinical pipeline.
spk29: Thanks, John. On slide five, our pipeline is generated by an approach in which the active immune response guides us to novel antibodies finding novel targets. On the top half of the slide, starting on the left, Our approach begins with blood samples from patients whose adaptive immune system is attacking tumor tissue. Moving to the right, via those samples, we access that immune response, and importantly, the active immune response, by analyzing single B cells of a defined type to generate, at high fidelity, the natively paired heavy and light chains of the antibodies that are being generated in that patient at that point in time. Moving again to the right, we then analyze and select those antibody sequences in silico for synthesis and further evaluation in the laboratory. By screening these synthesized antibodies in vitro, we ask a simple question. Does this antibody, which comes from the immune response of one patient, bind to tumor tissue of other patients, that is, non-autologous tumor tissue, and does it do so preferentially over normal tissue? If the answer is yes, and the antibody also binds to the surface of a tumor cell line as measured by flow cytometry, we have a HIT antibody. On the bottom half of the slide, we then further evaluate and develop our HIT antibodies in order to turn them into clinical candidates, as I'll describe in a moment in more detail. Moving to slide six, this slide illustrates the biology behind why our approach works. The key point of this slide is that we generate antibodies from plasma blasts, those four B cells in the middle of the figure. Plasmablasts uniquely provide information on the antigens being processed and the antibodies being generated during an active immune response. In the blowup, we're showing as dots antibodies generated at two time points from one patient, before treatment in purple and after treatment in green. And we've circled groups of dots. These groups of plasmablast antibodies are clonal families derived from a single progenitor B cell. And these particular families, colored green, regenerated in this case as the patient was successfully attacking his tumor tissue to yield a partial response. By analyzing clonal families such as these, their appearance, persistence, disappearance, size, all of that enabled by our approach, as well as by analyzing antibody sequences more directly, we focus on and select particular antibodies for further evaluation in the laboratory. Our in-silical analysis delivers synthesized antibodies binding non-autologous tumor tissue approximately 50% of the time in our primary screens. And as noted at the bottom of the slide, our proprietary approach is protected by composition of matter claims in multiple jurisdictions worldwide, which goes beyond the more typical method of use claims often granted around processes. Moving to slide seven, this is the discovery platform that we have built in over a decade to execute on our approach. I'll focus on a few key points. Starting on the left, we run our own non-interventional studies in order to acquire samples from cancer patients, and we have generated a valuable sample repository now with over 1,700 clinically annotated samples from over 500 donors representing nearly 40 tumor types. Moving right, I've briefly described that we use these samples to generate, analyze, and select plasmablast antibodies for analysis, by histology and polycytometry to generate hit antibodies. And then moving further right, turning these hit antibodies into leads requires their evaluation in vitro for tumor-sidal activity, but in a manner that provides information about which weaponization would be most suitable. And then with the active antibody in hand that also has positive histology data, we work to identify the target bound by the antibody and eventually the epitope on that target. Moving further right again, if an antibody meets our criteria, we then work to generate a clinical candidate from that antibody by engineering a final weaponized format and optimizing its sequence, by assuring a suitable safety profile, and by identifying biomarkers suitable for use during clinical development. Moving to slide eight, as we promised to do, we've evolved the platform over time to achieve greater efficiency in delivering pipeline assets. On this slide, I'm highlighting a few of the more salient advances that we've made. Starting in the top left, we've expanded our sample collection to new sites and indications. Moving down, we're operating our flow cytometry now at an industrial scale and speed. And below that, our histological analysis has now incorporated more automation to enable earlier evaluation of tumor and normal tissue expression of our antibody targets. Moving to the top right, We've implemented proprietary high-throughput assays to measure in vitro the activity relevant to weaponization. Next down, whole genome functional genomic screens were added to existing biochemical methods to remove a bottleneck that target identification had represented in our platform. And finally, but again not exclusively, we've implemented structure-based and unbiased lead optimization to generate candidates in multiple weaponization formats. Moving to slide nine, we'll quickly review our current pipeline, all the assets of which have been generated by our platform. On slide 10, you see a listing of our clinical and later stage preclinical assets. There's our clinical stage asset, ATRC 101, which Philippe will discuss in detail. You'll then hear from Stephen about the other currently preclinical pipeline assets. Turning it over to Philippe.
spk49: Thanks, Tito. And thank you, everyone, for joining the call today. On slide 12 is a top line summary of ATRC 101 Phase 1B study update I am presenting today, which includes information from 71 patients treated in the ongoing trial, 21 of whom were enrolled since our March 22 update. The primary objective of the study is to evaluate safety, and we're pleased to share that ATRC 101 continues to be well tolerated in the monotherapy and combination arms including at the highest dose level of 30 milligrams per kilogram. We continue to see anti-tumor activity in patients that express target. Furthermore, we're excited to report that in this heterogeneous and heavily pre-treated participant group, we are seeing durable responses and stable diseases across several cancer types in participants treated with monotherapy and combination therapy. Before we discuss the data, I will briefly review the trial design, the baseline characteristics of participants treated, and the analysis set in the next three slides. As a reminder, and as shown on slide 13, this is a basket trial enrolling patients across multiple tumor types. The primary objective of the trial is to determine the safety and tolerability of ATR-C101 when administered as monotherapy or in combination with key additional objectives, including measuring clinical activity, analyzing target expression, and determining indications for expansion. The trial began with ATRC-101 administered as monotherapy every three or two weeks, followed by studying the combination with pembrolizumab every three weeks in patients who had progressed or, in the opinion of the treating physician, achieved a non-satisfactory response following an anti-PD-1 or PD-L1 therapy. The initial dose escalation cohorts included patients regardless of target expression. Last year, when early data suggested that target expression appeared to discriminate patients likely to respond, we amended the protocol and started to enrich based on target expression. To date, we have treated participants at five dose levels, ranging from 0.3 to 30 milligram per kilogram. Having completed the dose escalation phases of the trial, we're now expanding enrollment at the 30 milligram per kilogram every three-week dose level for both monotherapy and combination cohorts. 514 is an overview of the baseline characteristics of participants enrolled onto study. As of the data cutoff of February 17, 2023, 71 participants had enrolled overall, with 48 on the three-week monotherapy schedule, 14 on the two-week monotherapy schedule, and nine in the combination arm. The median age of participants was 62 years, with most having an equal performance status of one. You can see how patients enrolled in the study are distributed across cancer types. It is very important to note that the majority of participants enrolled in the study have metastatic disease and were heavily pretreated with a median of five prior line of therapy. Nearly half of the patients had prior exposure to one or more checkpoint inhibitor, and for those enrolled onto the combination arm, as per protocol, all patients had to have received prior therapy with a PD-1 or PD-1 agent and experienced an unsatisfactory response or disease progression following treatment. On slide 15, I would like to describe the pertinent datasets used in today's presentation. Beginning with the safety, today's results will include all 71 participants enrolled on to study who received at least one dose of ATRC-101. Although we studied five dose levels, we consider pharmacologically relevant doses to be at the 3, 10, and 30 milligram per kilogram, either as a monotherapy or in combination with pembrolizumab. Participants treated at these doses will be the focus of the interim analysis for activity presented today. For these analyses, there are 62 patients with a large number enrolled at the 30 milligram per kilogram dose. Of the 62 subjects, 50 were evaluable for a score that is defined as a composite score comprised of target expression intensity by immunohistochemistry and the proportion of cells positive for target expression. When examining target expression correlations to clinical activity, we will focus on the 45 who were evaluable for resist and age score, and the 49 who were evaluable for best overall response and target expression. For these results, we will present the monotherapy results separately from the overall population that include nine individuals who received combination therapy. Presented on slide 16 is the distribution of participants accessible for overall response and age score by cancer type. As you can see, the number of subjects enrolled with specific tumor types range from 18 to 0. As such, the small numbers make it difficult for conclusive inferences about ATRC 101 activity for a specific cancer type or indication. And although we are getting close to sufficient numbers in some of the tumor types, we believe it is important to continue enrollment onto study to provide additional insights and inform future development decisions. Moving to slide 17, ATRC continues to be well tolerated. Of the 71 participants enrolled and who received at least one dose of ATRC-101, most of the reported adverse events were grade 1 or 2 as shown by the dark and blue bars for the treatment emergent adverse events on the left and the treatment related adverse events on the right. Of these adverse events observed, there remains no pattern to suggest a particular toxicity profile. nor were there a relationship between incidence of severity of adverse events with dose or incidence of adverse events with target expression. The most common treatment-related adverse events were pain, fatigue, and nausea, with no serious adverse events determined to be related to treatment with ATRC-101. Only two Grade III AEs were reported as potentially treatment-related, including one instance each of a headache and a small intestinal obstruction. Six patients experienced an AAE leading to dose interruptions. These included patients who had a grade two infusion reaction on cycle one, day one. The infusion was interrupted temporarily, and the AAE managed as per protocol. The dosing was restarted without complication. Others included liver function laboratory abnormalities, a grade one tachycardia, a grade two nausea, a grade two fatigue, and the grade three small intestinal obstruction that was noted earlier in my comments. No participant has had to come off study due to drug-related toxicity. Moving to slide 18, the interim assessment for activity once again supports the use of a NAIT score cutoff to predict the probability of observing disease control or tumor response to ATRC101. As noted previously, the H-score is obtained using a CAPRIA immunohistochemistry-based assay. An H-score can range from zero at the negative end to a maximum target expression score of 300. Based on prior analysis showing a correlation of H-score to response or disease control, the target positive H-score cutoff implies an H-score greater to or equal to 50. On the left bar graph, For patients who received monotherapy, 59% achieved disease control if their tumor expressed the target. This is in contrast to 25% of patients whose tumor had an age score below 50. The bar graph on the right includes patients treated with combination therapy and yielded a similar result. On slide 19 is another way of assessing anti-tumor activity associated with target expression. Here we are looking at individual patient data over time for patients whose tumor has a low age score. Those treated with monotherapy are shown on the left, and on the right, the graph also includes those treated with combination therapy. As is shown here, most patients' disease progression occurred early, soon after the first month following initiation of protocol therapy. Only four patients had stable disease going past 100 days, and all experienced a disease progression at 180 days or soon thereafter. On slide 20, we compared those with low target scores in the light blue lines to those with age scores of 50 or greater in the dark blue lines. And we can see that there is a greater number of patients experiencing a durable objective response or durable disease control. Several of them are well past 180 days after having initiated protocol therapy. In the model therapy cohort, the bottom curve shows a patient with 40% tumor size reduction that lasted for more than 300 days. This is the patient with not small cell lung cancer we had previously reported to have achieved the PR. That patient's tumor had an age score of 80 and PFS was documented at study date 350. Including those who received combination therapy on the right, we can see the melanoma patient at the bottom that we had previously reported to have achieved a CR and that patient had their most recent response assessment at day 418 following initiation of protocol therapy. That patient's tumor had an H score of 75 and to this day continues to remain on study. Slide 21 focuses on the durability of tumor response observed by cancer type. for all patients treated with ATRC-101 as monotherapy or in combination with Bambro and whose tumor was target positive. As shown by the different line colors depicting different cancer type, durable activity is seen across multiple tumor types, including melanoma, non-small cell lung cancer, head and neck cancer, colon cancer, as well as breast cancer patients who had progression-free survival documented at study day 210. Another way of looking at the anti-tumor activity by tumor type and age score is shown in the waterfall plot on slide 22. On the left bar graph, patients with low target expression experience increase in the size of target lesions, except for one patient with ovarian cancer who had a small reduction in the size of her cancer. Patients who receive ATRC-101 alone are shown in the solid bars. Those who receive combination therapy are shown in the hash bars. This is in contrast to patients whose tumor had a higher target expression on the right bar graph. Here we see that several patients had tumor reductions in both the monotherapy cohort, the solid bars, and the combination therapy cohort, the hash bars. Slide 23 is a Kappelmeyer analysis measuring progression-free survival for patients treated as a function of each score. On the left are the patients who receive monotherapy. On the right, the Kaplan-Meier analysis includes a patient treated with monotherapy or combination therapy. Patients with an H score of 50 or greater in the dark line have a longer progression-free survival than patients with H score less than 50 in the blue light lines. The curves separate early at 30 days and remain separated over time. For the monotherapy cohort, the hazard ratio is 0.47 for the difference of target positive and target negative patients, and is similar to the hazard ratio observed for all patients treated with ATRC-101. That also includes those who receive combination therapy. Here, the hazard ratio is 0.4 for the difference of target positive and target negative patients. Of interest are the small vertical censored line on the curve representing patients who have not experienced an event. These patients remain unstudied and are still receiving protocol therapy. As you can see, some patients have passed 180 days at the tail end of the dark progression-free survival curve. Now moving to the data summary and next steps on slide 24. This is a Phase 1b trial. And it has and continues to enroll patients that have, for the most part, exhausted standard of care. With this data update, ATRC 101 continues to be well tolerated. There were no DLTs up to the 30 milligram per kilogram dose level tested. What we are learning with this data update is that longer progression-free survival appears to be associated with ATRC 101 target expression in patients with cancer. While durable disease control was seen across several tumor types, it is too early to quantify and properly qualify the nature of these responses. To do so, we will need to enroll additional patients across cancer types, and our current recruitment efforts will need to focus on underrepresented patients. We continue to focus enrollment based on target expression at the 30 milligram per kilogram dose in both the monotherapy in combination with pembrolizumab cohorts. In the past several months, we opened the study at five new sites and close to, and we have contracted with nine additional sites in startup activities. In addition, we have seven sites undergoing feasibility. Going forward, a total of 28 centers are expected to participate and contribute to the study. In addition, we adapted the protocol eligibility criteria based on investigative feedback, and in some instances worked with specific clinical centers to overcome staffing issues post-pandemic. All these activities have already and are expected to continue to help increase enrollment onto study. Overall, we are targeting 30 to 40 new additional patients for recruitment distributed across indications to make adequate go-no-go decisions by year-end 2023. That said, because we are enriching for target expression, We have seen, not unexpectedly, screen failures due to restricting enrollment to patients whose tumor are target positive. The screen failures are in line with prior expectations to target prevalence. Finally, our recruiting efforts have already seen improvements. The additional data we expect to collect should position us well to enable a go-no-go decision for further development of ATRC 101 by year-end. paving the way for determining a registration path with defined commercial opportunity for ATRC 101. I will now turn it over to Stephen to discuss our preclinical pipeline program.
spk27: Thank you, Philippe. I'll now review three of our late lead oncology programs moving toward candidate nomination. The first, highlighted on slide 26, is a novel tumor-specific anti-glycan antibody that we're advancing as an antibody drug conjugate, or ADC. referred subsequently to as antibody 444. 444 is one of a growing number of anti-glycan antibodies that we are uncovering with our platform. This is exciting as aberrant glycosylation has long been recognized as a hallmark of cancer, but this class of targets has been difficult to address through standard methods. As I'll show you, 444 displays uniform and selective binding on tumors with high prevalence on colorectal cancer and is active as an ADC, both in vitro and in vivo. We're currently optimizing both the antibody portion of the molecule and the linker drug portion to yield a candidate, a clinical candidate, that we expect to nominate by year end, with an IND target for late 2024. The bar plot in the top left of slide 27 shows why we're so excited about this antibody. Morpho4 exhibits strong immunoreactivity, i.e. 2 plus and 3 plus staining, in greater than 70% of colorectal cancer. And I hope you can appreciate that this staining is very uniform in the images to the right, where essentially all tumor cells are positive for the epitope. We also see high prevalence in gastric cancer, with lower prevalence in several indications, including uterine, pancreatic, esophageal, and lung cancer. Importantly, we do not detect membranous immunoreactivity on 27 normal, fresh-frozen tissues. The highest signal in normal tissue is moderate cytoplasmic staining in the stomach. which we suspect from data that I'll share in the coming slides is not accessible to the antibody. On slide 28, you can see that consistent with the abundant immunoactivity in colorectal and gastric cancer, 444 binds to cell lines derived from these tissues, highlighted in blue, and not to those derived from other tissues. We screen for ADC activity, shown on the right. 444 leads to cytotoxicity in cells that express high and low to moderate levels of target, in the case of LOVO and NUGZ4, respectively. On slide 29, you can see that 444, before any affinity maturation, when formatted as an ADC, using ZymWorks ZymLink or a statin-based linker payload, leads to dose-responsive antitumor activity after a single dose in a LOVO xenograft model. This model expresses a relative... relatively high level of target, but as shown to the right, the level of staining is comparable to what can be found in human cancer and therefore is a relevant model system. Importantly, 444 has been tolerated in both single and multiple dose studies in mice without body weight loss or histopathologic findings. 444 as an ADC has also been explored in initial PK tolerability assessment in rats and has been well tolerated up to 30 mg per kg with the Zymlink or statin linker payloads. I should note that the moderate cytoplasmic staining I pointed out earlier in the human stomach is also observed in both mice and rats. The fact that the ADC is well-tolerated in both species suggests, again, that this intracellular pool of target is not accessible to the ADC. Moving now to slide 30. At this point in the project, we had a very interesting antibody with tumor-specific expression and intriguing anti-tumor activity, but we didn't know the target. Attempts to de-orphanize the antibody using standard approaches, such as commercial protein or glycan arrays, had failed to this point. And as Tito mentioned, we have now enabled whole genome CRISPR screens in-house, and 444 was one of the first antibodies we assayed with this approach. Using a CRISPR knockout approach, we knocked out genes individually and assessed which genes were essential for 444 binding to a flow-positive cell line. Three genes were identified as being required for 4-4-4 binding, two glycosycele transferases, beta-4-galan T3, and FUT4, as well as a fucose transporter. The fucose transporter makes sense in the context of FUT4, which requires fucose as a substrate. Interestingly, when one looks at the expression of the two glycosycele transferases at the RNA level in normal tissue, they're largely not co-expressed, a feature that helps explain the near absence of immunoreactivity in normal tissues. We validated that these two enzymes were required by expressing them in a cell line that did not express the target for 444. Upon co-expression, a dramatic right shift in the flow cytometry plot shown to the right suggests that these enzymes are required to present the glycan on the cell surface, at least in this context. Based on the substrate specificity of these two enzymes, we understand what glycan structure is likely required for binding and are confirming this through biochemical means. Advancing to slide 31, I alluded to the fact that 444 is one of a growing number of anti-glycan antibodies being discovered by our platform. In fact, half of the antibodies for which we have identified the target are anti-glycan antibodies. Our platform appears uniquely positioned to help uncover the potential of this underexploited class of antibodies. The platform, of course, also identifies antibodies to protein targets, And one theme that has emerged is the mislocalization of normal intracellular targets to the cell surface. A good example of this is our next late lead asset, 958, highlighted on slide 32. 958 recognizes an RNA binding protein that is normally sequestered in the nucleus, but is mislocalized to the cell surface in tumors, potentially via stress granules. 958 is advancing as a CD3 bispecific T-cell engager in collaboration with Zencore, where Atreca is taking the lead on the preclinical and clinical development. We expect to nominate a clinical candidate by year end and are targeting an IND submission by early 2025. On slide 33, similar to the anti-glycan antibody 444, the native antibody of 958 straight from the patient shows preclinical activity. In this case, however, we formatted the antibody as a T cell engager using XENCOR's ECMAP CD3 bispecific platform. As shown on the left, the 958 bispecific leads to tumor stasis in a target positive prostate cancer xenograft model in the blue line. We're currently optimizing the antibody to further enhance the potency to match or beat the positive control T cell bispecific used in this study, which is directed against a well-known prostate cancer target, PSMA, shown in orange. On the right, you can see that 958 leads to the expected pharmacodynamic effects for molecules with this mechanism of action, including robust immune activation as evidenced by an increase in interferon gamma levels in plasma and expansion of CD8 positive T cells in blood. 958 is the first molecule to advance as part of our collaboration with Zancor, the details of which are described in more detail on slide 34. In this collaboration, Atreca will provide antibodies against novel targets, and Zancor will engineer bispecific antibodies using their XMAP CD3 platform. The two companies will mutually select up to two joint programs for further development and commercialization, with each partner sharing 50% of the costs and profits. While each company will lead one of the joint programs, the agreement allows each partner to pursue up to two programs independently. The last oncology lead I will review is highlighted on slide 35. 597 is our anti-FA2 antibody, which targets a novel, well-conserved membrane proximal epitope on FA2, a validated oncology target that is overexpressed in a range of tumor types. We have generated a series of antibody variants with a range of affinities to FA2 and have tested these in various weaponization schemes where they're broadly active. Previously, we advanced a high affinity variant as an ADC and are now evaluating antibody variants in CD3 T cell engager format based on the in vivo activity we've observed. Moving to slide 36, I hope you share our excitement about the molecules I highlighted for you today. We're equally excited about molecules coming from the platform, which are at an earlier stage. As Tito mentioned at the beginning of the presentation, We believe investments we've made across our platform, especially around target identification with the implementation of CRISPR screening, have eliminated common bottlenecks and made the platform even more productive. We believe Atreca is well positioned to capitalize on the discovery and development of novel oncology targets. Finally, while not an internal pipeline molecule, we wish to highlight another exciting asset, Atreca's anti-malaria antibody, ATRC501, on slide 37. ATRC 501 is an engineered version of an ATRECA discovered antibody designed to prevent malaria infection. The antibody is licensed to the Gates Medical Research Institute, which is preparing to file an IND this year. ATRECA retains rights in the U.S., Europe, and parts of Asia with potential product development opportunities, including prophylaxis for those traveling to malaria-endemic regions. And with that, I'll hand it back over to John to discuss our upcoming milestones and provide an overview of our financials and IP.
spk36: Thank you, Steven. Slide 39 is an overview of our upcoming milestones. As Philippe noted, we are planning to provide updated data and a go-no-go decision for Phase II development of ATRC 101 later this year and potentially begin Phase II studies next year. On the preclinical side, we expect to nominate clinical candidates in the 444 and 958 programs later this year and are targeting INDs in late 2024 and early 2025, respectively. And behind those, our early stage discovery and lead generation efforts are ongoing. Finally, Gates MRI continues to advance ATRC 501 and is expecting to file an IND this year. Returning to slide 40, This addresses our financials and intellectual property. As of December 31st of last year, we had $70.5 million in cash equivalents and investments, which is expected to fund operations through the end of this year. We have a strong IP position with patents issued covering critical aspects of a trade discovery platform, as well as ATRC 101 and related antibodies with pending applications covering other pipeline assets. That concludes today's prepared remarks. We'd like to thank our trial participants and their families, as well as investigators and research staff at our clinical sites. Thanks again to everyone who joined the conference call and webcast today. With that, operator, could you please open the line for the Q&A?
spk54: As a reminder, to ask a question, you will need to press star 1 1 on your telephone. Again, that's star 1 1 on your telephone to ask a question. Please stand by while we compile the Q&A roster. Our first question comes from the line of Divya Rao of Cohen. Your question, please, Divya.
spk21: Hi, guys. Thanks for taking our question for Phil. Just based on your experience, when you're trying to enrich for high age score patients, what would you say is the percent of patients that fit that eligibility criteria? And then I guess as a follow-up, how does that change in terms of indications that maybe you're not seeing as many patients enrolled in?
spk49: Yes, well, thank you. So as you know, in the preclinical assessment of the program, we had done some prevalence assessments in microarrays. So these are tumors in microarrays looking at the presence of target on these tumors. And we had assessed that somewhere in the neighborhood of between 30% to 50% of the tumors that we were looking across all the indications were expressing the target. What we're observing in the clinical trial is similar to that. It's consistent with that prevalence data that we had generated previously. And depending which indication we're looking, for the most part, we're seeing about 50% of the tumors expressing the target.
spk20: That's helpful. Congrats on all of the data. Well, thank you very much.
spk54: Thank you. Our next question comes from the line of Roger Song of Jefferies. Your question, please, Roger.
spk51: Great. Thanks for the data update and taking our questions. A couple from us. So the first one is, you know, for this uh you know the patient you have median five prior lines can you just help us to conceptualize what is what is the expected or or pfs in this population from you know uh standard care or whatever the care whatever the therapy available to those patients uh yes so um roger the
spk49: It depends which indication you're looking at. For some patients, as you may be aware, such as lung cancer, breast cancer would be another example. As you begin to exhaust standard of care, the expected progression-free survival gets shorter and shorter with subsequent lines of therapy. There are some other indications of where You can observe from time to time indolent disease. I would think some colorectal cancers are like that. And as you know, with melanoma as well, we have seen with the advent of immunotherapy, individuals now are having longer periods where you see progression-free survivals occurring. I think for the most part in our study with the patients we are looking at, they come in already heavily pretreated. They tend to have an ECOG performance status of one, which also predicts worse outcome for these individuals. And so for them, I think Looking at the data, I think it's important to note anyone that would go past the six-month mark. I think the PFS at six months is an important landmark. The PFS at four months for some of those indications may also be equally interesting to look at.
spk36: Yeah, I'd just add to that, Roger, that I think, you know, given the heterogeneity of these patients, different tumor types, and the, you know, sort of open-label of the trial, I think we certainly need to have more patients before we could really draw conclusions about the efficacy or the activity that we're seeing and how it compares with standard care. I think we are encouraged by the fact that where we do see more disease control and where we have seen responses is primarily in the context of patients who are expressing target. So that does give us some encouragement that what we're seeing is real and a function of HRC 101. But clearly we'll need more patients, and that's why we're continuing to enroll, adding additional centers, and hope to have sufficient data by the end of this year to really be in a position to make a decision about whether and where to go to Phase II or HRC 101.
spk51: Okay, great. Maybe just that leads to my next question. Regarding the additional patient, about 40 to 50 patients, would you expect those patients will be slightly different from what you have in terms of the tumor type and the prior line of therapy? And just to remind us, what is the breakdown between the monotherapy versus the the combination therapy, and when you make the go-no-go decision, what will be the key efficacy endpoint you were looking at, like the disease control or OR or PFS? Sorry for the long, long, long questions here.
spk49: So I'll try to address all the questions and points that you have raised. I think for the patients that are going to be enrolling, the 30 to 40 patients that we expect to enroll that will be new, and with the changes that we have made going to centers that are more adept to enrolling Phase II patients as opposed to Phase I, as you know, Phase I units are highly specialized. And here what we have done is gone to centers that are a hybrid between academic centers and community centers where we're seeing patients, a greater number of patients that would be eligible for our trial. So that's one point to make. And what we expect to see there is a distribution across the various tumor types that we're seeking to enroll into. Some of those centers are more likely to enroll individuals, for example, with lung cancer, others with breast cancer, but we're also looking at centers that can help augment our database for head and neck and urothelial cancers as well. So we're looking, our recruitment efforts are targeted at this point, and we're looking to try to supplement those underrepresented patient populations. And the goal for that is really for us to be able to look at where our strongest signal comes from. And there we'll be looking at, I think, response rates, obviously, responders. As you know, we have the lung cancer and the melanoma patients that have been durable. I think that's That's notable. But what is new with the data that we're presenting today is really this notion of disease control and the ability to see patients staying on study for a longer period of time. So we'll be incorporating a component of disease control into our decision algorithm. And we plan to update you at some point about how we're going to approach that and how and base it, of course, on sound analytic principles. So with regards to the type of patients that we're planning to see, the eligibility criteria remains as it is and will continue to remain as is for the time being. So we don't really expect that the patients that we'll be seeing coming on to study will be much different. They will be individuals that have exhausted, for the most part, standard of care and have either advanced or metastatic disease. So we would think that these patients will be similar to the ones that we've enrolled to date. We're continuing to enrich for target as of today, and those patients are getting enrolled at the 30 milligram per kilogram dose cohort.
spk36: And in terms of, I think, what we objectively need to see in terms of our response rate or durability, of either responses or disease control or generally, I think it depends also on the tumor type, right? As Philippe alluded to, you know, some of these are tumor types where it's not entirely uncommon to see patients with, you know, indolent disease. And then there are other settings if we take our, you know, our response with a 50% tumor reduction in lung cancer, that's, you know, fifth line lung cancer, that's a setting where we wouldn't expect to see influenza disease. But then we have to overlay on top of that what's the unmet need, what would the regulatory hurdle be, because the whole point of that randomized phase two trial is to really set up what could be a potential registration. So I think it'll be taking all of those things into consideration and applying a relatively high bar, particularly in any setting where there's a well-established standard of care.
spk51: Got it. Yeah, thanks for the thorough answer. Just to clarify, what is the breakdown between the monotherapy and the combination therapy for the new 30 to 40 patients enrollment?
spk49: So this will be obviously considered with the eligibility criteria. So for patients that would be considered to continue on PEMBRO to receive a PEMBRO-containing regimen. Those indications are, as you know, based on the PEMBRO label. So there we have some differences with the monotherapy. And the monotherapy, as you know, was based on our earlier data. data showing that there was a high prevalence of target in these various tumor types. So if the physician thinks that PEMBRO is not indicated or the patient had already received PD-1 or PD-L1 agent and unlikely to respond, it is likely that they'll be brought on to the monotherapy if they meet eligibility. And for those for whom the physician believes that continuing on PEMBRO would be suitable, we would probably see those coming onto the combination arm. And I should point out that urothelial malignancies, esophageal malignancies, the head and neck malignancies, and subset of breast cancer, the triple negative breast cancers, and the hepatocellular carcinoma would be indications that we would see in the combination arm that would not be appropriate for the monotherapy arm based on eligibility criteria.
spk36: Yeah, and I think even in a setting where we have cohorts open for monotherapy and combo with pembrolizumab, I think we would likely need to show more single suggestion of single agent activity for the FDA anyway. So to some extent, we'd like to see more combination patients, but to some extent, we also benefit from more monotherapy because I think that's something that, you know, that individual contribution is something that probably the FDA would want us to answer. But at this point, those centers, most of them would have basically the choice and use their own discretion. At least for breast, lung, ovarian, colorectal.
spk51: Got you. Yeah, that makes sense. Okay, thank you.
spk37: Thank you, Roger.
spk54: Thank you. Our next question comes from the line of John Newman of Canaccord. Your question please, John.
spk30: Hi, guys. Thanks for taking my question. Just wondering, with the currently ongoing Phase 1 study for 101, how much follow-up time will be allotted? I'm just wondering if you'll be able to follow the study longer term for things like overall survival, where perhaps there's a signal that shows up that doesn't initially show up in the response rate.
spk32: Thanks.
spk49: Yes, so right now the data that is being collected obviously is response rates, and we're looking at progression-free intervals. Survival is collected when that event occurs for patients that are on study during the period of follow-up, but we're not following patients once they come off study. So the overall survival data would not be something that we would expect to report on with this trial. I think what we're looking at is for response rate and disease control to give us an idea of the signal and help us prioritize which indication is most likely to be seeing or deriving some kind of benefit from being treated with ATRC-101. And that sets the stage really for the Phase II study that John was talking about where they're in a more formal way and ideally in the controlled fashion with an appropriate control, we would be assessing what a true treatment effect would be for Phase III in order to appropriately design the Phase III trial. And that Phase II could include collecting survival data.
spk31: Okay, great. Thanks. Thanks, John.
spk54: Thank you. Our next question comes from the line of Tony Butler of EF Hutton. Your line is open, Tony.
spk28: Yes, thanks very much. So, if I understand correctly, preclinical work had demonstrated that ATRC 101 actually remodeled the tumor microenvironment, if I'm correct in that. If that's true, one of the questions that comes to mind is this notion of combination where, as I think you stated, utilizing PEMBRO with 101 was really related to those indications where PEMBRO was already indicated. If that's true, that's fine, and I'm respectful of that. But the real question is, in cold tumors, for example, in CRC and or ovarian where PEMBRO just has no effect, there may be, if in fact you do get TME remodeling, there may be, you know, some really decent signals here where in those tumors, that combination could then therefore be advantageous. And so, for example, it wouldn't take a lot from a response rate to really demonstrate in a late-line CRC patient that you really have something of benefit. I am respectful that in monotherapy you may have modest benefit, but yet certainly in combination there is at least a question there that, gee, if you could show anything better than regrafinib, you really have an opportunity set. And I'm just throwing this out as a thought. if it's directionally correct, or maybe what you think about it. Thank you.
spk36: Yeah, maybe you want to address that from the preclinical side, and then, I don't know, maybe we have some further thoughts. Thanks for the question, Tony.
spk29: Yeah, Tony. So, you know, you are right, you know, in the sense that if the mechanism is directed towards the innate immune system, then that's upstream of the of agents that act on T cells, like anti-PD1 or PD-L1 checkpoint inhibitors. And so, yes, in principle, that converting, you know, tumors that normally don't have much of a, you know, an immune response with ATR-C11 is possible. And we all know that, as you point out, CRC is one of those tumor types.
spk49: Yeah, from a clinical end, you raise, I think, a very provocative thought and question that I think would be, at some point, worth addressing in a clinical setting. I think, as you know, the individuals with mismatch repair or MSI high colon cancer are more likely to to have a response with pembrolizumab or the PD-1 or PD-L1 agents. And I think this concept of cold and converting a cold tumor to something that is more likely to respond is something that is worth investigating for sure.
spk35: Thanks very much. Good suggestion, Tony. Thank you for raising it.
spk54: Thank you. Our next question comes from the line of Stephen Willey of Stifel. Your question, please, Stephen.
spk07: Yeah, good afternoon, guys. Thanks for taking the question. I think I've asked you this before, but I'm going to ask it again. And just curious if in this incremental patient data set, you were able to somehow look at longitudinal H-score expression. just as a way to assess the stability of target expression over time.
spk49: So, thank you for the question. We are collecting biopsies, well-owned studies for patients that consent to it. And we are planning to do some analysis longitudinally for those matched biopsies that we've obtained. As you know, there are studies that are not that easy to conduct. And with small numbers, we have to be careful with inferences. To date, what we have is the baseline data. We've batched the specimens. and plan to analyze this at the final analysis. So we have not looked at the serial biopsies yet for those, for the patients whom have given us, you know, permission to go ahead and sample again. And just for clarity, we do it during, at baseline, we do it during the first cycle, and we do it also at the disease progression.
spk07: Okay. And then I think, Eligibility for the combo cohort required either progression on a PD-1 or L1 targeting map and or stable disease on a PD-1 or L1 targeting map. I'm just curious if you know offhand if the incremental patients enrolled into the combo cohort either fit the progression definition or if there were some patients in there who also fit the stable disease definition?
spk49: Yes, so I think the eligibility criteria is worded slightly differently. It's an unsatisfactory response while on PD-1 or PD-L1 agent. and or disease progression. So there in the opinion of the physician, the response that was obtained while on the PD-1 or PD-L1 would have to be unsatisfactory and require the institution of new therapy. What we have is for the most part looking at those nine individuals The reason for the last therapy was really a lack of efficacy and progressive disease. So looking at those individuals, I would say that most of them would have had progressive disease.
spk07: Okay. And just with respect to the goal of enrolling an additional 30 to 40 patients before the end of this year, I know you've kind of talked about some of the the headwinds that a lot of these phase one sites are facing, and we've heard that from other companies as well. But I guess would you still – is the 30 to 40 incremental amount of patient data, is that requisite for making a no-go decision before year end, or is that something that is a little bit fungible in terms of timelines? Yes.
spk49: Well, so as you know, the trial is currently set up as an assignment two-stage study and with criteria for expansion within specific indications. I think like early phase one studies, as you learn about your drug and you begin to collect information, adapting your approach and incorporating what you're learning along the way is something that is done by most companies and certainly encouraged even by health authorities. So early in trial development, we tend to be Bayesian, if you will. We tend to adapt as we learn more about our drug, either on the safety side or on the activity side or even sometimes with pharmacokinetics. We can certainly modify the way we approach looking at these data. What is new with today's presentation is the notion of disease control or stabilization of disease or durability of response. And I think that's a very important new information that we have today. If we think about a higher bar for making decisions, I think applying a bar that not only looks at response rate but also looks at some form of disease control would allow us to prioritize indications for moving forward. And for that, I don't think we would need to expand each one of those indications as we had planned earlier. And we can probably make those decisions based on sound analytic principles using Bayesian statistics with fewer patients in each one of the categories.
spk07: Okay. And then maybe just lastly, just in terms of I thought it was interesting that you disclosed that about half of the antibodies that you're disclosing are actually against these glycan targets, which I know from, as you mentioned, kind of a conventional immunization perspective have been really hard. These are carbohydrates. Just curious as to kind of where you think your progress puts you from a collaborative position. just kind of given the amount of interest there has been around this target class historically.
spk29: Hi, Steven. So I'll take that one. So we're in a number of discussions about programs, obviously. The profile of 444, as Steven described it, is proving to be quite attractive. and garnering a great deal of interest. You have something that's, you know, binding a target expressed at fairly high levels in the majority of colorectal cancer patients where there's huge unmet need, and yet you see great potency and, you know, lack of a safety signal so far, even with an FV that has not yet been optimized. And so, yeah, I think you're right. You know, there are a couple of anti-glycan antibodies that have reached commercial stage. And part of the problem there is huge black box warnings is they're not specific to tumor. They attack peripheral nerve, for example. And what I believe you're hearing today in Stephen's part of the presentation is that our platform is delivering what you might expect. It's glycans that you can't really find through molecular biology tricks. You just can't do it that easily with glycans. And they are fairly specific. And as you point out, we have a very nice IgG antibody recognizing that glycan simultaneously.
spk06: Great. Thanks for taking the questions, Jeff.
spk22: Thanks, Dean. We have time for one more question.
spk54: Yes, sir. Our final question comes from the line of Kemp Dolliver of Brookline. Your line is open, Kemp.
spk43: Thank you. I have a couple questions there. Some of them are pointed and quick. I'll be respectful of your time, but quickly with regard to the incremental enrollment, what would be the assume data cut off to make a decision in the time frame you're thinking?
spk49: So yeah, so obviously we're going to enroll and collect data until the study comes to fruition. I think we will report on the, you know, when it's appropriate by the end of the year, what our most up-to-date results would be. And I think, you know, the data cutoff for that typically requires, you know, a few weeks for us to be able to analyze that data and put it together.
spk36: Yeah, I think maybe one of the challenges you might be alluding to, and I think it's an important one, is having sufficient follow-up, you know, to be able to assess durability of response. So I think it might be a little bit easier in a way to make a no-go decision than it is a go decision. The no-go decision would be based on not seeing a level of activity for a given indication or for the program overall that would lead you to not move forward in phase two. A go to phase two decision is a clinical decision, but it's also a business decision. And I think that you could imagine a scenario where you've got responders or long-term stable disease and you want to give a little bit more time before making the decision to pull the trigger on an expensive Phase II program. But I think, you know, our commitment is really to try to, you know, provide fairly regular update and get to a crisp decision, you know, by the end of this year, plus minus, when we basically don't want to leave the study just open enrollment patients without making a decision to go to phase two, or possibly end the program. I think we all feel pretty encouraged by the data that we're seeing, the durability of the responses, the PFS that seems to favor patients who express target, but I also think it's important for us to get to because there's an opportunity cost here when you look at the other molecules that we have that are going to IND in the next 18 months.
spk42: I will stop there. Thank you.
spk36: Okay, great. Well, thanks a lot. Much appreciated, Kemp. Thanks, everyone, for your questions today and for joining the call. And I look forward to additional updates in the future.
spk54: Thank you. This concludes today's conference call. Thank you for participating. You may now disconnect.
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