Thank you for standing by. My name is Lowella, and I will be your conference operator today. At this time, I would like to welcome everyone to ALX Oncology ASPEN-06 phase II Clinical Trial Data Results Conference Call. All lines have been placed on mute to prevent any background noise. After the speaker's remarks, there will be a question-and-answer session. If you would like to ask a question during this time, simply press star followed by the number one on your telephone keypad. If you would like to withdraw your question, press star one again. Thank you. I would now like to turn the conference over to Jason Lettmann, CEO of ALX Oncology. You may begin. Hi. Thank you all for joining. I'm Jason Lettmann, CEO of ALX Oncology. Joined here with Dr. Sophia Randolph as well, who is our CMO. We are very excited today to be presenting data from our randomized ASPEN-06 trial in HER2-positive gastric cancer. And as many of you know and have been tracking closely, ALX is leading the field in CD47. We're focused on developing Evorpacept or Evo, which is a CD47 blocker that has the potential to both be a first-in-class and best-in-class IO agent. This data today is particularly exciting for us. I know it's exciting for many of you, exciting for the clinical community, and most importantly, for cancer patients, as this represents a couple of big firsts. It's the first randomized data to read out in a prospective randomized clinical study in solid tumors in the CD47 space. As we're going to walk through here shortly, ASPEN-06 is the first randomized data ever to demonstrate both a tolerable safety profile and the first randomized trial to report a clear and durable improvement over a standard of care. So what's really exciting, of course, about today's new news here is not only the compelling data in gastric and GEJ cancers, but the fact that for us, it just truly validates our truly unique approach to blocking CD47 and validates Evo's broad potential when combined with any Fc-active antibody across multiple tumor types in addition to gastric. So the plan today is for me to first walk you through the program and a reminder of our mechanism. I'll then hand it over to Sophia to walk through specifically the data that we're seeing with the ASPEN-06 top-line results and then wrap it up with where we're going from here. So first on slide three is a quick reminder of the biology and the mechanism of evorpacept. What you can see here on the left is how CD47, or the don't-eat-me signal, works. It is one of the primary markers of self, and it's upregulated by tumors to evade the immune system. And what you can see here is how CD47 signals the don't-eat-me signals don't-eat-me to both cancer as well as healthy. And this is what's been really challenging for the field to solve. On the right is our molecule, again, evorpacept, which has a very high affinity CD47 binding domain, as well as an inactive or dead Fc, which is a truly unique attribute of evorpacept. On slide four, this next slide shows how evorpacept works and how we selectively target cancer while sparing the on-target toxicity that has led to other failures in the space. On the left, Evo drives a potent blockade of CD47 signaling. Because there is no positive, there's no eat-me signal, if you will, the macrophage will not attack either cancer or healthy cells. In this middle panel here, you can see that when combined with an anticancer antibody, which is seen in green here, this together will cause a macrophage to attack cancer. This attack is targeted specifically to cancer as the targeted antibody partner provides that specificity. And that's what then drives what you see on the right, which is a very targeted, selected killing of tumors. And importantly, and a particularly fundamental concept to recall throughout today is that a macrophage will need both. It needs to have the don't-eat-me signal blocked as well as a positive eat-me signal. And that together is what makes up our mechanism. So when you turn to slide five, you can see how this is different than conventional CD47 targeting. It is, as you can see on the left, the conventional CD47 blocker tries to provide both of these signals on the same molecule and effectively tries to use CD47 as a tumor-targeting antigen. But unfortunately, because CD47 is not specific to tumor cells, this also results in ADCP or phagocytosis activity against normal cells like red blood cells or platelets, resulting in CD47-targeted destruction of both normal and cancer cells and then results in associated toxicity. Additionally, and as we've observed now in the clinic, these toxicities can prevent the exposures needed for full CD47 blockade and limit the effective dose. And because conventional CD47 blockers may compete for the Fc receptor, it presents a significant challenge. And the ultimate result is what you see on the right, which is broad and indiscriminate targeting of both cancer and healthy. So that brings us to where we are today on slide six and what we're really excited about sharing with you all. Again, ASPEN-06 represents a few key firsts for the field. It's the first prospective randomized study in solid tumors in the space and the first randomized study to read out both a strong ORR gain as well as a durable improvement versus standard of care. In terms of the full population, and as Sophia will dive into, we are seeing a 40.3% ORR on treatment compared to 26.6% on the control arm, which is nearly a 14% delta versus control. Importantly and really exciting for us is what we're seeing in terms of durability with a median duration of response of 15.7 months, which is more than double the 7.6 months that we've seen on the RamPac control arm. What we're also going to dive into today and what we're really excited about is what we're seeing as it relates to HER2 expression. Again, very important for us mechanistically to have both. In patients with fresh HER2-positive biopsies, which is indicative of patients with the strongest HER2 expression, we're seeing a 54.8% ORR compared to 23.1% for the control arm, which is over a third. Hello everyone. This is the operator. Due to a technical issue, we will be changing the start time to 5:00 P.M. Eastern Time. Again, that's 5:00 P.M. Eastern Time for the start of this conference call. Thank you so much. You will be hearing a hold music if you're going to stay in the line with us. Please bear with us while we fix this technical issue. Thank you. Thank you for standing by. My name is Lowella, and I will be your conference operator today. At this time, I would like to welcome everyone to ALX Oncology ASPEN-06 phase II Clinical Trial Data Results Conference Call. All lines have been placed on mute to prevent any background noise. After the speaker's remarks, there will be a question and answer session. If you would like to ask a question during this time, simply press star followed by the number one on your telephone keypad. If you would like to withdraw your question, press star one again. Thank you. I would now like to turn the conference over to Jason Lettmann, CEO of ALX Oncology. You may begin. Hi. Thank you all for joining. I'm Jason Lettmann, CEO of ALX Oncology. Joined here with Dr. Sophia Randolph as well, who is our CMO. We are very excited today to be presenting data from our randomized ASPEN-06 trial in HER2-positive gastric cancer. And as many of you know and have been tracking closely, ALX is leading the field in CD47. We're focused on developing evorpacept or Evo, which is a CD47 blocker that has the potential to both be a first-in-class and best-in-class IO agent. This data today is particularly exciting for us. I know it's exciting for many of you, exciting for the clinical community, and most importantly, for cancer patients, as this represents a couple of big firsts. It's the first randomized data to read out in a prospective randomized clinical study in solid tumors in the CD47 space. And as we're going to walk through here shortly, Aspen 6 is the first randomized data ever to demonstrate both a tolerable safety profile and the first randomized trial to report a clear and durable improvement over a standard of care. So what's really exciting, of course, about today's new news here is not only the compelling data in gastric and GEJ cancers, but the fact that for us, it just truly validates our truly unique approach to blocking CD47 and validates Evo's broad potential when combined with any Fc-active antibody across multiple tumor types in addition to gastric. So the plan today is for me to first walk you through the program and a reminder of our mechanism. I'll then hand it over to Sophia to walk through specifically the data that we're seeing with the ASPEN-06 top-line results and then wrap it up with where we're going from here. So first on slide 3 is a quick reminder of the biology and the mechanism of evorpacept. What you can see here on the left is how CD47, or the don't-eat-me signal, works. It is one of the primary markers of self, and it's upregulated by tumors to evade the immune system. What you can see here is how CD47 signals don't-eat-me to both cancer as well as healthy. This is what's been really challenging for the field to solve. On the right is our molecule again, Evorpacept, which has a very high affinity CD47 binding domain, as well as an inactive or dead Fc, which is a truly unique attribute of Evorpacept. On slide four, this next slide shows how Evorpacept works and how we selectively target cancer while sparing the on-target toxicity that has led to other failures in the space. On the left, Evo drives a potent blockade of CD47 signaling. Because there is no positive, there's no eat-me signal, if you will, the macrophage will not attack either cancer or healthy cells. But in this middle panel here, you can see that when combined with an anticancer antibody, which is seen in green here, this together will cause a macrophage to attack cancer. And this attack is targeted specifically to cancer as the targeted antibody partner provides that specificity. And that's what then drives what you see on the right, which is a very targeted, selected killing of tumors. And importantly, and a particularly fundamental concept to recall throughout today is that a macrophage will need both. It needs to have the don't-eat-me signal blocked as well as a positive eat-me signal. And that together is what makes up our mechanism. So when you turn to slide five, you can see how this is different than conventional CD47 targeting. It is, as you can see on the left, the conventional CD47 blocker tries to provide both of these signals on the same molecule and effectively tries to use CD47 as a tumor-targeting antigen. Unfortunately, because CD47 is not specific to tumor cells, this also results in ADCP or phagocytosis activity against normal cells like red blood cells or platelets, resulting in CD47-targeted destruction of both normal and cancer cells and then results in associated toxicity. Additionally, as we've observed now in the clinic, these toxicities can prevent the exposures needed for full CD47 blockade and limit the effective dose. Because conventional CD47 blockers may compete for the Fc receptor, it presents a significant challenge. The ultimate result is what you see on the right, which is broad and indiscriminate targeting of both cancer and healthy. So that brings us to where we are today on slide 6 and what we're really excited about sharing with you all. Again, ASPEN-06 represents a few key firsts for the field. It's the first prospective randomized study in solid tumors in the space and the first randomized study to read out both a strong ORR gain as well as a durable improvement versus standard of care. In terms of the full population, and as Sophia will dive into, we are seeing a 40.3% ORR on treatment compared to 26.6% on the control arm, which is nearly a 14% delta versus control. Importantly and really exciting for us is what we're seeing in terms of durability with a median duration of response of 15.7 months, which is more than double the 7.6 months that we've seen on the RamPac control arm. What we're also going to dive into today and what we're really excited about is what we're seeing as it relates to HER2 expression. Again, very important for us mechanistically to have both. In patients with fresh HER2-positive biopsies, which is indicative of patients with the strongest HER2 expression, we're seeing a 54.8% ORR compared to 23.1% for the control arm, which is over a 30% delta. Last, and certainly not least, given some of the challenges in the field, we continue to see a safety profile, which is consistent with the over 500 patients that we've treated to date as Evo was well tolerated versus control. Of course, that's an important component when we think about taking this drug forward. Turning to the next slide on slide 7, this is just a reminder of our registration strategy and how we got here. We first tested evorpacept in gastric cancer in our ASPEN-01 study. This provided a very strong signal. In this same combination with the trastuzumab-RamPac backbone, provided proof of principle for us and a strong signal of activity. That then formed the basis for what you see in the middle, which is what we're going to be reporting on today, which is our ASPEN-06 study. This is a key proof of concept study for us, again, testing the exact same combination, but this time versus the control of trastuzumab-RamPac to really isolate what is the contribution of evorpacept. Then last is that this is again a phase II/III design where we have agreement with FDA as to what it will take to drive registration. On the right, you can see the phase III design, which will then compare Evo TRP versus the global standard of care of RamPac or RP. With that, turning to slide 8, this just touches quickly on the unmet need in gastric cancer. It is truly a global disease, a challenging disease to treat with a global unmet need. It's really an area where we need more novel and better tolerable treatment options. While the incidence is highest in Asia and has a significant presence in Europe, the Americas, and other global regions, and it is really characterized by a relatively poor five-year overall survival, which can be as low as 7%. On the right, you can see the standard of care by line of therapy. You have the trastuzumab plus chemo doublet in the front line, as well as pembro now, which is approved in front-line patients. Second line is either RamPac or in HER2. Again, we are targeting the second and third line here as part of this study. Turning to the next slide on slide nine, this is just a reminder as to what are the benchmarks in the field. The first is the RAINBOW study. RAINBOW really established RamPac as a global standard of care in the second line. In that study, it showed about a 28% ORR versus a 16% in terms of paclitaxel alone. Following that, the DESTINY-Gastric01 study in the third line reported a 40.5% ORR within HER2 versus physician's choice chemo. Both of these studies demonstrated a survival benefit of one year or less and really has highlighted where we see the unmet need going forward. So with that, I'll turn it over to Sophia here to walk through the mechanism briefly that we're testing within gastric and then share our ASPEN-06 data. Great. Thanks, Jason. And for all, I'm very happy to take you through our final analysis of the ASPEN-06 randomized phase II study. And first up on slide 10, you can see, as Jason mentioned earlier, Evorpacept binds to CD47 on the cancer cell. And this allows it to inhibit the SIRP-alpha CD47 myeloid checkpoint. And so in this mechanistic figure, you can see that in combination with an anticancer monoclonal antibody here, trastuzumab, which binds to the Fc gamma receptor on the macrophage, you can see that the two drugs are able to fully activate the macrophage, directing the ADCP activity against the HER2-expressing gastric cancer cell. So on slide number 11, here we can see the randomized phase II design of the ASPEN-06 study of evorpacept in combination with TRP or Traz-RamPac. In this study, patients were enrolled with second or third line HER2-positive gastric cancer that had progressed upon an anti-HER2 agent. They were randomized to receive either treatment arm, the Evo TRP or the TRP. Eligible patients must have had no prior treatment with an anti-CD47 or SIRP-alpha agent nor ramucirumab. All patients, as I mentioned, must have been treated with prior anti-HER2 therapy. And as such, prior treatment within HER2 was allowed, as was prior checkpoint inhibitor therapy as well. So 127 patients were randomized in a 1:1 fashion to receive either of the two study regimens. The primary study endpoints were investigator-assessed overall response rate with key secondary endpoints of durability of response, progression-free survival, as well as safety. So we've previously presented data from a pre-specified interim analysis of 54 randomized patients at the end of last year. And today, we're now presenting the top-line data from the final analysis of the 127 randomized patients. So this study had two primary objectives. The first was to look for a 50% improvement over an assumed historical RamPac objective response rate of 30% in this HER2-positive population. The second was to establish the contribution of evorpacept to the TRP backbone. Here, we were looking for a clinically meaningful magnitude difference between the two arms of greater than 10%. So these two objectives were evaluated in the full intent to treat randomized population. These were patients who were identified as HER2-positive based upon a tissue biopsy that could be obtained at any time during the course of their previous disease, as well as in a subset of patients whose HER2-positive gastric cancer was recently identified based upon a fresh biopsy obtained after prior anti-HER2 therapy. The second population was of particular interest to us because HER2 expression, we know, varies greatly in gastric cancer. We wanted to prospectively evaluate a population of patients who were more likely to be enriched for HER2-positive disease at the time of the study's start. On slide 12, on the next slide, the study was conducted in 13 countries, and patients were randomized across 90 sites. The dose of evorpacept in this study was 30 mg/kg administered once every two weeks. Trastuzumab was administered with a 6 mg/kg loading dose followed by a 4 mg/kg dose once every two weeks. Ramucirumab and Paclitaxel were dosed according to their label in a 28-day cycle. All patients enrolled had received a prior anti-HER2 therapy, and there were several stratification factors that were used to balance the patient characteristics across the two treatment arms. These included cancer type, fresh versus archival biopsies, Asia versus ex-Asia region, the line of treatment, HER2 IHC score, and then use of prior anti-HER2. On slide 13, the demographics of the patients randomized are shown here. The majority of patients were male and Asian or white. Ethnicity was missing in a proportion of patients, as some countries do not collect this particular demographic. The patient characteristics were generally well balanced across treatment arms. There were, however, some features which did differ between the population that contributed to the interim analysis and those who were enrolled in the latter half of the study after the interim analysis. Post-interim analysis, there were fewer patients enrolled using a fresh biopsy. 46% of the patients were randomized based off of a fresh biopsy in the interim population versus 32% in the more recently enrolled post-interim patients. Also, patients on the Evo TRP arm who enrolled into the study after the interim analysis did have characteristics suggestive of more aggressive disease, such as a higher ECOG score, faster time to their first progression, and overall, just a shorter prior disease course. And then lastly, it's noted there that patients who did enroll based upon fresh biopsies had those biopsies on average within one month of coming on study, and that's within the screening window, whereas those using archival samples came from biopsies obtained really over a year before enrolling on this study. Evo's safety profile is shown on the next slide, 14, and it was consistent with the prior experience of evorpacept in over 500 patients that we've treated to date. Evo plus TRP was generally well tolerated. The incidence of adverse events by grade due to any cause was comparable by arm, and there were no on-study treatment-related deaths on either arm. On slide 15, you can see a summary of all causality grade 3, 4, 5 adverse events by arm. These events were, again, generally well balanced across both treatment arms. There was some increase in neutropenia on the Evo TRP arm. However, as we'll show you in the subsequent slide, this increase may be explained by the fact that as many patients stay on the Evo-containing treatment arm for longer periods of time, they have more opportunity to experience cytopenias, certainly in a regimen that contains chemotherapy as part of its backbone. There were 3 on-study deaths due to sepsis across both study arms. However, these were not considered related to either treatment regimen. On slide 16, here we see in the full intent to treat population, the addition of evorpacept to TRP demonstrated an ORR of 40.3%, which compared favorably to the assumed historic RamPac overall response rate of 30% with a p-value of 0.095. Evo contributed a clinically meaningful benefit. This was our secondary objective of more than the pre-specified 10% delta in ORR over the TRP arm. When an additional analysis was performed comparing Evo TRP to the observed control TRP overall response rate, and that within the study was 26.6%, there was a p-value observed of 0.027. Responses were durable with a median duration of response in the Evorpacept combination arm of 15.7 months compared to the TRP arm control of 7.6 months. The activity of Evo TRP compared favorably as well with published data of available therapies in the second- and third-line gastric populations. So in slide 17, as shown in the waterfall plot, you can see there's substantial tumor shrinkage seen in patients who received Evo TRP compared to TRP. On slide 18, when we look at the overlay of those waterfalls, it becomes really important that you can see the relative greater depth of tumor shrinkage seen in the Evo TRP arm, again, supporting the contribution of Evorpacept to that TRP backbone and the subsequent clinical benefit of the regimen seen in this trial. When combining with Trastuzumab on slide 19, Evorpacept's mechanism of action depends upon the expression of the HER2 receptor in order to drive that maximum phagocytosis activity against the gastric tumor cells. In fact, HER2 expression is an important biomarker for Evo TRP response. When we look at the activity on slide 20 of Evorpacept plus TRP in the pre-specified population of patients who were enrolled into the study based upon fresh HER2-positive biopsies, we see that Evorpacept more than doubled the tumor response in patients when compared to the TRP control. This improved benefit in this pre-specified population of patients who are enriched for recent HER2 overexpression underscores the importance of this biomarker in Evo TRP response. It continues to validate evorpacept's mechanism of action. As is shown, you can see patients with recent HER2 positivity demonstrated an ORR of 54.8% compared to 23.1% for the TRP control. That had an observed p-value of 0.0038. Now, as shown on slide 21, this was no surprise, as in gastric cancer, HER2 expression is highly variable. As shown in this slide from a recent paper of Shitara et al. based off of the DESTINY-1 experience, HER2 expression in gastric cancer can vary over time due to downregulation of the receptor after treatment with an anti-HER2 therapy and can even vary from tissue sample to sample within the original tumor and its metastases. This does seem to be more specific to gastric cancer than to other HER2 overexpressing tumors, such as breast cancer, where there's more homogeneous expression of HER2 throughout the tumor. This has been well documented by others. In gastric cancer, having a fresh HER2-positive biopsy can allow for the identification of a population enriched for HER2 expression. This is certainly consistent with the data that we've seen in this study. Shown a different way on slide 22, and again, consistent with Evo's mechanism, patients had a greater response if they were identified using a fresh biopsy. In contrast, you can see that patients receiving TRP and who are being now retreated with trastuzumab did not see much benefit beyond the backbone of RamPac, regardless of HER2 expression or whether a fresh biopsy was used to characterize their current HER2-positive status. So again, this would be consistent with earlier reports, notably from the T-ACT study, that HER2-positive patients who have recently progressed upon trastuzumab are likely resistant to trastuzumab and do not benefit from trastuzumab retreatment in the context of systemic therapy. On slide 23, the mechanism of how Evo works with trastuzumab in combination is fundamentally different from how trastuzumab works by itself. So without blockade of the CD47 SIRP-alpha checkpoint, minimal phagocytosis of cancer cells using macrophages activated by trastuzumab will occur. And again, this is consistent with the ASPEN-06 TRP arm data. However, when combined with evorpacept's CD47 blockade, an Fc-active antibody such as trastuzumab can drive phagocytosis of the cancer cell, translating into real clinical anti-tumor response. And I think that's seen on our ETRP arms within this study. So there continues to be much to learn from this clinical trial. We thank the patients, the investigators, and the clinic staff for their contributions and support of this study. Now I will turn it back to Jason for final remarks. Jason. Great. Thanks so much, Sophia. I think, as Sophia mentioned, what we've demonstrated here is really how evorpacept can harness and engage the innate response. It's really a first-in-class molecule here that, as Sophia said, we continue to learn about, but continue to also be incredibly excited about. I think what we feel we know now is that we have an active agent. We have a very strong signal, a response rate that is robust, and that is clearly durable, and one that is also clearly different than a HER2-targeted agent like Herceptin. On the durability front, to see a DOR of more than double and knowing that there's typically a tight correlation between DOR and PFS, we're encouraged by what we're seeing there as well. To the point that Sophia just made, what we're seeing is in line with our mechanism. As we've talked about here, I've talked about at length over the last decade or so of this company, is just the importance of both the blockade of CD47 and the positive signal. And we feel what we're seeing is that TRAS by itself is doing very little and that Evorpacept is bringing something new to the table that's fundamentally different in driving benefit. In the population where we were patients that had the most recent biopsy, which again should be indicative of HER2 expression, to see a 54.8% delta versus 21.1% on the controller over a 30% gain truly helps validate the mechanism for us. From a safety perspective, again, as Sophia walked through, we continue to see safety in line with our prior experience. It continues to be a very tolerable agent that is well-behaved in the clinic. Then last is just to highlight again the novelty of what we're doing. This is truly a novel IO agent that has the potential to be first and best in class. To see this data come through in a randomized study for the first time is very compelling. On the next slide, again, this just pieces together the why. On slide 25, it speaks to how evorpacept was designed. We have a very potent CD47 blockade molecule, which is resulting in less anemia, allowing us to drive much higher dose. And again, this is why we think we are seeing what is truly the first CD47 to see solid tumor efficacy and now to do so in a randomized setting. All of these things are what's working together to create this effect, and I think really helps validate where we're going from here. So on the next slide touches on that. Again, there's two mechanisms at play, two mechanisms that we are now testing in the clinic. The first on the top left is what we focused on today, which is how does evorpacept help harness the innate immune system. And we're also testing how CD47 signals to the adaptive immune system. That's the second mechanism here where we're going to have over 300 patients randomized reading out also Q4 or Q1, which will be another big event for the company. But with this data, with ASPEN-06, this now adds yet another positive clinical readout. We now have 6 positive clinical studies, now with randomized data to support the single-arm studies that we delivered in the past. And for us, this really does de-risk and drive our development going forward as we think about combining evorpacept with other Fc-active antibodies across multiple tumor types. So certainly excited about next steps with gastric, but also excited about what this means for other malignancies where we can combine with an antibody across both heme and solid. So again, excited about the data. Thank you all for the time and frankly support of us and of this company and this molecule. As Sophia mentioned, a big thank you to our clinicians and an even bigger thank you to the patients who participated here. So with that, we'll open it up to questions. Thank you. The floor is now open for questions. If you have dialed in and would like to ask a question, please press star one on your telephone keypad to raise your hand and join the queue. If you would like to withdraw your question, simply press star one again. If you are called upon to ask your question and are listening via loudspeaker on your device, please pick up your handset and ensure that your phone is not on mute when asking your question. Again, press star one to join the queue. Your first question comes from the line of Michael Yee with Jefferies. Please go ahead. Hey, guys. Good afternoon. Thank you for the call. I think there are two areas I would like to ask important questions on. It seems that perhaps the first half of the study did better for the interim if you go back to the data. And everyone can do math around the second half of the study in terms of the incremental patients. And you can see that the response rates are more evenly balanced in the second half, i.e., the incremental patients. They're very similar, 32% and 30%. So without just looking at response rates, can you tell us, is the duration of response in the second half of the study much better for the drug arm versus the control arm? Appreciating overall it was double. But is the second half of the study, the duration of response, also better, much better in the drug arm versus the control arm? And then on PFS, which would also be important, can you please clarify why it's not mature? Because math would imply that certainly a lot of events have happened and should be mature. So appreciating that it could be all driven by the first half of the study, tell us, is the second half of the study, PFS, also very different and there's a big separation? Thank you. Yeah. Great. Thanks, Mike. Appreciate the question. And apologies to everybody on the technical difficulties here. But we'll take those in reverse order, both good questions. I think fundamentally we do see a difference in the population between interim and the post-interim population. We can talk about that. I think first, just to address PFS, obviously that's important and a metric we're very focused on. I think as we touched on, what we're excited about, I think, is a couple of things. One is that PFS is tightly correlated to DOR. And we're seeing that play out in our earlier patients. And so when you look at our DOR versus control, and it's more than double, and it's better than the benchmarks, we think it's really compelling. We have a DOR here of over 15 months. As a reminder, and as you know, Mike, the RAINBOW study showed 4.4 months on RamPac versus 2.8 months. The DESTINY study within HER2 showed about 11 months versus 4 months on the chemo arm. So again, 15 months is significant here. And when you look at what we reported on the interim to now, it has remained that way. So we think that's really important. And then the second point I would make is just around enrollment. And again, this won't be lost on you, but we did see enrollment accelerate. We over-enrolled this study to 127 patients. So it tells you something about the bolus of patients that came in relatively late here. So we just have a number of patients that are still early here and haven't progressed. But again, I think DOR should correlate tightly. And that's what we're really encouraged by. Sophia, do you have anything you add to that on the clinical front? No, no. It's exactly what you said. Actually, with the sort of exponential accrual on the back end of the study, the follow-up on that population is actually fairly short. It's almost the same as just having had two rounds of imaging. So the first half of the study is definitely more mature. But again, we'll continue to follow this out. But the follow-up on the second half is much less. Okay. So let me clarify the. And then to your. Response rate. Go ahead. Thanks. Okay. So the duration was to wrap up on duration response. The duration response is very clearly different in the first half. But in the second half, those responders, 12 for the drug, 11 for the control, it's immature. So the swimmer plots are still going on for those in the second half. That's what you're seeing on duration response. Yeah. Absolutely. And I mean, our hope and our expectation is that it will follow the first half. But it's just too early to tell from right now. Then therefore, how does that relate to PFS, I guess, was the second question. So similar. I think it should be tightly correlated. But go ahead, Sophia. Yeah. No. I was going to say the same thing. So it's just the follow-up is short. In a way, it's good. It means that patients are benefiting from the combination. But more details on that will be presented. But for right now, the follow-up time for those time-to-event type metrics, it's just very short in the second half of the study. Okay. Thank you. So then, just to your first question, Mike, I think you talked about just the interim versus post-interim population. I think we highlighted two really important factors there. One, just the rate of fresh biopsy, which was roughly half of the population at interim. That number dropped significantly in the second half. Then, as Sophia touched on, the second really important point, which isn't a huge surprise when you put up data like we did at the interim, is just what happened in terms of overall disease status, if you will. When you look at the Evo arm in particular post-interim, it's pretty clear that we have just a more aggressive patient population. We do think that's a significant factor. So those two things working together are what's different. But again, overall, we've seen a 14% delta here, which is more than our bar, certainly of 10%. And then we look at this fresh population with an over 30% delta. That is just a very, very strong signal. So I think that's what's driving a lot of our enthusiasm here. Your next question comes from the line of Chris Raymond with Piper Sandler. Please go ahead. Hey, thanks. Yeah, two from me. Maybe the first one to follow up on the subject matter from the first question. Just on the characteristics of patients in the second half of the study. So can you maybe help quantify the variability, I guess, in the characteristics between the interim and the post-interim patients? I understand the dynamic there of enrollment accelerating and you getting sicker patients. But any sort of color you can give in terms of the difference between control arm and active drug arm that sort of drove that ORR being pretty much the same in the second half. Anything that you can do to sort of characterize that? Maybe, I guess, a question on that is how did that escape your sort of balancing for enrollment? Then just also on the stats, can you just confirm? I'm just looking at slide 16. The p-value was 0.027. Can you just confirm the bar for stat sig was 0.05, correct? Thanks. Yeah. Sure. So thanks, Chris. Appreciate it. Both good questions. I think on the differences, we highlighted, again, just the importance of fresh here. And I do think that tilt, if you will, will have an important factor on what we're seeing post-interim. And I think, as Sophia mentioned, on disease severity, it's always tricky to quantify that with one metric. But when we see ECOG and time-to-progression on a prior line, etc., all going the same direction, which is really the direction of suggesting it's a very severe population, I think that tells us something. And to your last question there, again, this was a well-randomized global study. We had six stratification factors across line, Asia, and HER2 use, etc. So very well-randomized. However, we didn't randomize or stratify across these two populations. So I think, again, it was randomized. It was well-randomized and well-conducted. As can happen, patient characteristics can change over time. I think that was your first question. On your second question, can you just remind me what that one was again? Yeah. Yeah. Sure. So I just want to clarify the stats. Just the ETRP, the p-value versus TRP was 0.027. Can you just clarify, was 0.05 the bar for stat sig? Just clarify that. Yeah. So we had two objectives here. One was to show benefit versus historical control. And that was RamPac, right? And that's where we used the 30% number. And we did not hit statistical significance on that. Again, we'd argue that is not as important as the second objective, which was to compare versus our control. And that is the 0.027 number that you highlighted. And again, our bar was to show a 10% delta there, which we achieved in getting close to 14%. So happy about that. And again, we think that's the most important way to look at a randomized study. But what was the stat sig bar? Was it some number other than 0.05? That's my question. Well, so 0.025 was what we used for the bar. Right. Yeah. Thanks. Your next question comes from the line of Li Watsek from Cantor. Please go ahead. Hi, guys. Thanks for taking my questions. Also, a couple here. Maybe a follow-up to the question about the patients enrolled in the second half of the study tends to be a little bit sicker. So, wanted to understand, was that driven by perhaps the interim data that you put out and physicians may be more comfortable putting sicker patients in the trial? Or was there any other factors that may be contributing to this? And also, could that potentially introduce any bias into the study? Yeah. We think those are all great theories, Li. I think. And sharing the interim, that was a pre-specified futility analysis. And to see the data that we did, we certainly thought it was worthy of sharing with the street and communicating externally. I think with that decision, of course, when you're actively enrolling a study and have months to go to complete enrollment, that is going to drive physician interest. We certainly saw it in our enrollment. And now we're seeing it in our data. And so I think that is a valid question. Again, I would just say we're early at looking at these things. This data is relatively fresh for us as well. But we do think that was a factor. Sophia, anything you want to add on that front? Yeah. Yeah. I mean, I would just add that I would say it is unclear. I think that for sure, when we think about the stratification factors that we identified upfront, those are balanced, whether it's from the beginning of the study or the end of the study. Those are balanced across the treatment arms in the full subset or excuse me, in the full population. When it comes to these other things, so things like time-to-progression, time-to-overall disease course, these are not things that you can obviously stratify. Whether it's because of the interim being out there, I don't think we can say that conclusively. I mean, sometimes it's just as you get to the end of the study and there's a rush for folks to get patients on study, somehow sometimes the type of patient changes or what's out there in terms of other trials that are available to accrue. So there's a lot of different factors that go into it, not necessarily seeing the data at the interim. There are other, obviously, it's a complex data set. We're just plowing through it. How these things impact response versus how they impact time-to-event endpoints is also not completely known. So I think it's a little bit early, but there are definitely ideas that we're all contemplating. But unclear if that is truly the driving factor or not. Okay. I have another question on the HER2 expression. Is there a plan to maybe go to the FDA and then try to implement fresh HER2 biopsy into the phase III study? Can you also comment on the feasibility of using that? Yeah. I think it's a good question. I just would highlight two things quickly and then kick it over to Sophia. One, I think if you look at the Shitara paper, this phenomenon around HER2 flippage, if you will, is pretty well established. And that's why the DESTINY study, for example, is requiring fresh. So it does lead to the question as well, why didn't we do that? And I think the second point of my answer is just in terms of enrollment pace and what that would have meant to do so. And I think the good news here now is we have a very valuable biomarker. And again, we know we're doing something different here than a HER2-targeted agent like Traz. And so to know this information really informs where we go from here. Sophia, do you want to comment more on how we may think about next steps in the phase III? Yeah. I mean, I think in a phase III setting, I mean, ideally, you'd want to be able to enroll the enriched population, a larger population in the enriched and the all-comers. So for example, if you look at RamPac or other labels, you're really looking at patients who are identified based off of their most recent biopsy. Currently, having a post-anti-HER2 therapy biopsy is not standard of care, right? So there are a lot of reasons that go into that. But being able to enroll off of the most recent biopsy is currently kind of the standard for many of the available therapies out there. As Jason alluded to, getting a second biopsy can decrease the pace of your study. It makes for a much longer study because it isn't standard of care. So these are the things that we have to balance. What we definitely want to be able to do is have a reasonable proportion of patients with fresh biopsies to really, I think, test out that data that's coming out of our randomized phase II. It will definitely inform the phase III. It may not be limited to that population, but we definitely want to enrich for that population. Great. Thanks. Your next question comes from the line of Sam Slutsky with LifeSci Capital. Please go ahead. Hey, good evening, everyone. Thanks for taking the questions. A couple for me. I guess based on what you're seeing, when do you anticipate that PFS and OS will be mature enough to report? And then maybe I missed it, but what was the duration of response differences for the subgroup of patients with fresh biopsies? And I have one follow-up. Yeah. Thanks, Sam. I think on the PFS and OS, it's just going to depend on the data. I think what we looked at, and we looked at it in a pretty objective way in terms of just the percent of events where patients were on their censoring. And again, this is all informed by DOR. Of course, when you have durable responses, you're going to have less progression. So our goal as a company is really to be patient and let it mature. Of course, we don't want to be in a spot where we're walking things back. So we want to ensure that we have an event rate that's north of half at least and are able to make some definitive statements there. So again, I'd say DOR should correlate with PFS, encouraged by what we're seeing and more to come. On the second question on DOR, Sophia, do you want to take that one? Yeah. It most certainly is driven by the patients who were enrolled for the first half of the study, right, because they've been on the longest. So even whether it's in the context of fresh versus any time, you're still looking at about a 15- vs. 7-month difference or DOR by arm. So I think it kind of tracks with the fact that the patients who had the fresh biopsies in the first half of the study were the ones who had the greatest response. The good news is if you had a response, it does seem to be durable, so regardless of where you fall in the study. So that's really encouraging. But I think ultimately, the data needs to mature so that we can get a better assessment of that second half of the study, whether it's on the HER2 positive, meaning the fresh biopsies, or the biopsies taken at any time. Okay. And then anything you're able to elaborate on data differences based on if a patient had prior on HER2 or checkpoint inhibitors or not? No. I think on the subgroup front, what we've said is that we know those groups are balanced across the two. And again, I think that's the most important thing in terms of, is that driving a bias? And again, prior HER2 use was a stratification factor, and we don't feel mechanistically there should be any difference on patients that saw HER2 and then enter our study. So we don't see that as a factor here. Okay. Thanks. Your next question comes from the line of Ting Liu with UBS Financial Services. Please go ahead. Hi. Thank you for taking our question. So I want to ask, how's the geographic distribution in patient pool before and after the interim analysis? Were there more or less patients from the North American clinical sites after the interim? Then overall, how much geographical impacts on these HER2-positive gastric trials? You mentioned fresh biopsies. So ethnicity is apparently different too. And also standard of care for frontline, different. The U.S. may have more immunotherapy penetrations in frontline. So yeah, asking all this because DESTINY-Gastric01 was a Japan-South Korean study, right? HER-RAM was a South Korean study. DESTINY-Gastric04 is a non-U.S. study too. So how should we think of all the moving pieces here on the overall geographic impacts? And I have a follow-up question, if I may. Thank you. Thanks for that. Sophia, you want to take that one? Yeah. So I think when we think about the geography and how patients enrolled before and after the interim, that piece has been fairly consistent. So when we think about, for example, Asia versus Europe versus North America, just given the footprint of the disease, Asia certainly was the predominant enroller. And that was the same whether it was before the interim or after the interim. And you can see in the demographics slide on, I think it's slide number 13, we had most of the patients coming into the study were from Asia. So we had about 49% and 48%. So that was something that we definitely wanted to make sure was balanced coming from the Asia region versus ex-Asia region. Now, having said that, when we look at the subgroup analyses, which again, we're digging into really today was really just more about presenting the top-line reports. But we will be looking at how these different subgroups performed. I can at least say historically, and it's probably consistent with this study as well, patients from Asia, there's nothing different about the biology of the disease. And so whether you're looking at DESTINY-1, which was all done in Asia, or DESTINY-2, which was done in the U.S. and E.U., although that was a single-arm study in second line, the results there were remarkably similar to the Enhertu arm of DESTINY- 1, which was, as you mentioned, performed only in Japan and Korea. So again, we formally look at it, but at least based off of the historical experience between DESTINY- 1 and DESTINY-2, we wouldn't expect too much of a difference. Yeah. Those are really helpful. Thank you, Sophia. So if I may squeeze a quick question. So if evorpacept plus TRP will be primarily used in the post anti-HER2 setting, what's the size of the HER2-positive gastric population we'll be looking then? So again, a lot of those details will be presented at an upcoming medical meeting. But I think probably the more relevant question is going to be, were they balanced? And as those were stratification factors prior anti-HER2 use, we'll be able to see any effect of post-anti-HER2 was balanced across the treatment arms. I do think, though, one of the main things that did come out of this study, which really is a little bit broader of an idea, not just in HER2, but just that the patients who had their biopsies taken after a prior HER2-directed therapy—so that would include Enhertu or trastuzumab or Zanidatamab or margetuximab or any of these anti-HER2 therapies—as long as they had that recent or were enriched for that recent HER2 positivity, that was the population that had the greatest benefit, even though there was benefit seen across the full trial set. Yeah. And just to add to that on the. Oh, go ahead. I'm sorry. Oh, sorry. Yeah. I think I was more asking on the epidemiology front because the overall HER2-positive gastric population is about, in U.S., maybe 6,000, 7,000. So if potentially this regimen will be preferred by doctors to use in the post-HER2 setting, then what patient population are we looking then? Yeah. I think that remains to be seen, right? There's two factors. One is how do we stack up within HER2? And I think if you look at what we're seeing from a DOR perspective and what you hope when you develop an IO agent, it's to see a long tail, right? That's certainly different than what can be accomplished with an ADC. So I think how we stack up is important and an open question that we're encouraged by when we look at DOR. I think the second thing about where in HER2 sits is it is currently sitting in the second line. And I think, as most folks know, it has aggressively moved earlier and earlier in lines of therapy in breast, for example. And we know that there's data coming at ESMO with first-line in HER2 data in gastric. So again, we think, as Sophia mentioned, we'll be able to benefit patients post-in-HER2. We are looking at how we can combine within HER2, as you all know, with the I-SPY study. So we think there's multiple ways in which to go forward here as it relates to in HER2. Gotcha. Yeah. Thank you. Thank you. That's all my questions. Your next question comes from the line of Brad Canino from Stifel. Please go ahead. Hi. Thank you. And just one for me. I might have missed this during the call on next steps. So I just wanted to clarify if ALX Oncology is committing to advancing to the phase III portion of the study based on the data as they are disclosed today. Thank you. Yep. Thanks, Brad. I think what we're doing right now is digesting the data. And the immediate next step for us, as we've communicated, is to then get regulatory input here. So this is a phase II/III design. The phase III design is dependent, of course, on what assumptions we're making. And so we're going to need to talk to FDA, and I've always planned to talk to FDA about that. So that's the next step. And then once we do that, we'll have a clear sense as to what the path forward is. Your last question comes from the line of Swayampakula Ramakanth from H.C. Wainwright & Co. Please go ahead. Thank you. This is okay. Thanks for doing this call, Jason and Sophia. Just thinking through the patient population in the second half of the trial, which is after the interim analysis, were there any new centers that were added in that were not there or that did not have any patients before the interim analysis? And the other question I have is, on the HER2 expression itself, how does the - what's the waxing and waning of the expression as the disease progresses? So if you had a higher population of third-line patients, would their expression be anything different from the second line? And would that have any impact at all in your ITT population analysis? Yeah. So. Sure. Go ahead, Sophia. Yep. Nope. Just to say that in terms of your first question, okay, in terms of were there any sites that were new to the study? We're always opening sites over the course. There are always sites that are opening up a little bit later in the study compared to the beginning of the study. But most notably was Japan. Japan did not contribute to the interim analysis, but it did contribute to the final analysis. That was as we were doing some preliminary work on safety and PK that was required by their health authority. Having said that, though, it doesn't actually look like there was much of an impact on the type of patient that was enrolled that was any different from the rest of Asia. But that is something that we'll be going back and, as we kind of slice and dice this as many different ways as we can to take that into account. But again, at first look, it doesn't appear that that was a major factor. The second question around the line of therapy, so third line versus second line. So again, that would have been a stratification factor. So any impact by arm would have been handled just with the stratification. I think that answers your question. Is that sufficient? Yeah. I was just thinking about the HER2 expression between the third line and the second line. Oh, okay. So okay. So yeah. So for HER2 expression, and that kind of goes back to the slide 22, at least in this data set, where we see more of an impact on level of HER2 expression is actually more on the—I think the learnings was actually more on the TRP arm, where no matter what the level of expression, so 3+ 2+, when you're in that trastuzumab insensitive population, it really doesn't matter. You're just not going to see much of an effect of TRP in that population. In contrast, when you're looking at the patients that are enriched for HER2 positivity, there was quite a bit more benefit, whether you were 3+ or 2+. So just being HER2 positive with this mechanism of action or enriched for HER2 positivity, that population with the combined mechanism of action of ALX plus Evo plus trastuzumab, that seemed to be the most important determining factor. Okay. Thanks, Sophia, for answering my questions. I appreciate it. Thank you. That concludes our Q&A session. I will now turn the conference back over to Jason Lettmann for closing remarks. Please go ahead. Great. Just thanks again for the time and the great questions here. Appreciate that. We're excited about what we're seeing here with the data. And we have a lot of additional data here coming over the next 6-9 months, not least of which with ASPEN-03 and ASPEN-04, which we're also excited about. So thanks again for the time, and look forward to the next steps here with our program. Appreciate it. This concludes today's conference call. You may now disconnect.