Annual Healthcare conference. I'm Jeff Jones, one of the Biotech Analysts here on the team, and I'm delighted to welcome Dave Lennon, CEO of Whitehawk Therapeutics. Dave, you are now live, and there we go. Dave, I will let you take it away.. Great! Well, thank you, Jeff. Really thank you to Oppenheimer for allowing us to join this conference today and present our story here at Whitehawk. I'm Dave Lennon. I'm the CEO here at Whitehawk Therapeutics, really excited to share with you the story that we've been developing over the course of the last year, since we launched earlier in 2025. Just a reminder, today, I'll make some forward-looking statements that are only our opinions as of today, February 25th. At Whitehawk, we were founded, initially started as a company that launched with the in-licensing of a 3 ADC portfolio from WuXi Biologics. We founded this company based on those assets, as well as a number of important attributes to the company, including an experienced leadership team and really the capital strength to move this company forward effectively. Our three asset ADC portfolio, I'm really happy to report that our first two assets are now in the clinic, and so we are a clinical stage company developing two important assets, 1 called HWK-007, which is a PTK7-ADC directed, and HWK-016, a MUC16-directed ADC for gynecological cancers. Our founding team has deep experience in the ADC world and a track record of operational excellence, as well as M&A success. We are well-capitalized with $160 million as of the end of Q3 last year, and importantly, that cash runway allows us to operate into 2028, which is plenty of time for us to generate clinical data from our first two programs, which I mentioned are already in the clinic, as well as our third program, which is going into the clinic in Q3 of this year. The foundation of Whitehawk really starts with our belief in the ability to engineer better ADCs. We've in-licensed and optimized next generation ADC platform that's really designed for differentiation in the field. Now, importantly, there are three components that we look at that are important to the design of in the competitive field of ADCs. The first aspect is targeting. We really look at the opportunity for our monoclonal antibodies that comprise the targeting component of our ADCs, to really hone in on the target through high-affinity antibody selection and clever target selection. The targets that we select are clinically validated, meaning that there have been prior molecules that have been utilized against these targets and shown some initial early response, but we've actually improved upon those with targeting methods, utilizing that I'll go through in a few slides on the different targets themselves. Additionally, we use an attenuated FC portion of our monoclonal antibodies, which allows us to reduce nonspecific uptake, particularly by immune cells, thereby limiting the potential for specific toxicities that are associated or often associated with ADCs, like interstitial lung disease or ILD. The second component of our underlying platform technology is a step that's often overlooked within ADC companies, and that's bioconjugation. The vast majority of the ways that ADCs are made are adding linkers to antibodies through a process called bioconjugation. This step is often overlooked because people use very similar technologies across most of the field. Today, about 95% of ADCs are made through single-chain, partial site-specific bioconjugation techniques that have been around for a few decades. In Whitehawk's case, the underlying issue with that approach is that when adding linker payloads onto the ADCs through this bioconjugation process, standard approaches utilizing this single chain approach are open to liabilities once released into the circulation or introduced into the circulation in patients. This can lead to loss of free payload in circulation and breakdown of the ADC overall. That's because actually to add linker payloads onto the ADC itself, our competitors actually break the disulfide bonds that typically hold the interchain components of a monoclonal antibody together. In our case, what we do is we actually use a paired carbon-bonded linker payload that adds onto the ADC and reconstitutes the bonds that are typically broken through single chain processes. This dual chain or paired chain bioconjugation approach optimizes and stabilizes the ADC in a much better configuration than traditional approaches to bioconjugation. That allows us to improve stability of the ADC overall and reduce free payload that's released into the circulation. The third component of our technology is really the business end of any ADC, which is the linker payload component that actually attacks and kills the tumor. In our case, we use a first process of PEG masking to actually hide that cytotoxic payload while it's in circulation and only release it through a intracellular tripeptide cleavage site once it's inside the cell. We then release a proprietary Topo 1 payload that's based upon exatecan-like molecules, but is really designed to minimize toxicity and maximize tumor killing. It's through this smart delivery, stable construction and selective release of our payload that we really drive for maximal tumor killing while minimizing the overall toxicity. It's really optimized ADC that's really, we believe, differentiated in the field. What does that look like when you compare that upon non-clinical parameters that are often utilized to first select ADCs? There are three components that we really look at to say, "How is our ADC performing relative to competition?" Even before we went into the clinic. The first is on tumor potency, and here we see 3-10x greater potency of our ADC platform than your average Topo 1 inhibitor ADC. A lot of that potency is driven by the increased stability that we see, where we are 5-25 times more stable than the typical Topo 1 ADC, and 2-3 times higher in safety margin when you test that in non-human primate models of ADC safety. Overall, this ADC stability is driving greater potency, greater safety margin overall, and improved therapeutic index, which should lead to better outcomes for patients in the clinic, which we are now testing. This underlying platform has been applied across our portfolio of three ADC assets that we in-license, so it's the same technology for each program. Our first target is PTK7, so our HWK-007 program, our James Bond program, if you like to call it that, is targeting a broad array of potential tumors. PTK7 is a really interesting target, which I'll go through in a second, but importantly, had a precedent molecule that showed high effectiveness in a number of tumor targets that are shown, like lung cancer and ovarian cancer, where we'll be investigating in our initial phase I dose-escalation studies. There are multiple opportunities to expand upon that. The second program is against MUC16, so HWK-016, and we had submitted that IND in December 2025, and I'm happy to say we're now recruiting patients into that Phase I dose-escalation trial. A really important tumor target in gynecological cancers, and our initial focus will be on ovarian and endometrial cancer with this program. The third program is SEZ6, or HWK-206 ADC, which is targeting that SEZ6 protein. Now, SEZ6 is also known as Seizure protein 6 and is expressed in the central nervous system and is overexpressed in cancers of neuroendocrine origin. Those are things like small cell lung cancer, as well as neuroendocrine neoplasias and certain CNS and then other head and neck tumors. That IND is expected to be filed by mid-year, and we'll be starting our phase I in Q3. Let me just focus in a little bit on each of the targets that we are developing with for our portfolio. The first target, as I mentioned, HWK-007, is targeting PTK7. This is a broadly expressed tumor target, and you can see on the left-hand side of this chart, the expression profile across a whole range of really important cancers out there. PTK7 is often highly expressed. Actually, on the right-hand side, you can see when you compare it to other ADC tumor targets that are in development, like HER3, HER2, Trop-2, c-Met, B7H3, PTK7 is one of the most highly and broadly expressed tumor targets across a whole range of tumors, and you can really consider it a top three tumor target out there. It's probably the most underdeveloped tumor target that is so broadly expressed to date. Importantly, we are initially focusing on a couple of tumor targets, and I'll talk about why, based on this data. This data is coming from Pfizer's first-generation ADC, called cofetuzumab pelidotin, that was targeting a PTK7. Now, this used a first-generation technology, utilizing the tubulin inhibitor as a payload called the MMAE, and some earlier bioconjugation technology that often led to free payload being in the circulation of patients. While these programs, you can see in the top part of this graph, showed really interesting initial efficacy in phase I trials, so 46% overall response rate in ovarian cancer for high PTK7-expressing patients, which would be a really robust response. This program was limited by toxicities associated with the payload, MMAE, including a range that you've seen there. Ultimately, the program was discontinued in favor of other programs that Pfizer and their partner, AbbVie, in this case, had in the pipeline. This forms the foundation of validation and clinical validation for this target. We know this is a target that can be active within tumors, at least in ovarian cancer and non-small cell lung cancer. We think this is a really important opportunity for us to build upon as we go into the clinic with our HWK-007 program. How does HWK-007 stack up relative to cofetuzumab pelidotin? This is some preclinical data where we tested HWK-007 versus directly versus Cofep, and in the light green graphs, you can see the dose range or dose response to cofetuzumab in a xenograft model of transplanted small cell lung cancer tumors into mice. You get some regressions, you know, starting around 4 mg per kg in this model with that. However, when you look at HWK-007. Actually, you start to see really significant regressions at 1 mg per kg, and certainly, really excellent suppression by 4 mgs per kg. This is a molecule that's already showing that it's, you know, 1 to 4 times improved, or sorry, 4 times improved upon cofetuzumab pelidotin, so more potent overall. We also know that it has a high safety and therapeutic index based on our preclinical work. Really a program that we're excited about because it improves upon the potency and therapeutic index of cofetuzumab, which is a clinically validated target. As I mentioned, this program is now in the clinic and enrolling patients. Our second program is against the target MUC16, we like to say MUC16 is a super expressor, a program that is highly expressed across a range of gynecological tumors. This is on the left-hand side of this chart, is really the ovarian cancer example here, when we look at MUC16 expression against a range of ovarian ADC cancer targets like NaPi2b, FR-alpha, where there's actually approved therapies for ovarian cancer against FR-alpha, eight with FR-alpha ADCs, as well as even PTK7 and some others you may hear about in the pipeline, like CDH6 and B7H4. In these cases, MUC16 is anywhere from 3 to 10 times more highly expressed. When we think about attacking this tumor with this MUC16 target, it really has a super high expression to go after, which gives us a much higher starting point for attacking these kind of tumors. There's additional expansion potential for MUC16 beyond gynecological tumors, including places like mesothelioma, non-small cell lung cancer, and pancreatic cancer. This program also builds on clinical validation from a precedent molecule. In this case, this was a Genentech program called DMUC4064A. This DMUC program also showed some really interesting response rates, as you see in the top part of this chart. Genentech was seeing at an intended dose of 5.2 mgs per kg, about a 42% initial response rate in their phase 1 studies. A very robust response within the ovarian cancer, a late-line ovarian cancer patient population. Unfortunately, similar to the story I told you with cofetuzumab, what you're seeing with this DMUC program was ocular toxicities and other toxicities, which limited their ability to move forward with this program, and was ultimately discontinued due to the safety profile of this program. A tantalizing result for if you are able to target this MUC16 without inducing those kind of AEs. One of the things that's really interesting about the MUC16 target is it's actually cleaved, and it's cleaved into a circulating biomarker called CA125. CA125, if you ask any gynecological oncologist, they will know this biomarker because it's often utilized to measure disease progression, as well as response to therapy. Because it's so highly expressed, when it's cleaved, it actually circulates within the blood and can be measured as a blood-based biomarker. The CA125 is also a highly antigenic portion of the molecule, meaning that it's easy and often seen as best to raise antibodies against it. Actually, Genentech's antibody was targeting this cleaved portion of MUC16. The problem that that created is that there's so much CA125 circulating in the blood of these patients, that it actually was sopping up the ADC before it was able to reach the tumor. Actually, Genentech postulated that they had to push to such a high dose, which created some of their toxicity issues, because they had to overcome this limitation, and clearance, and ultimately, what's called an antigen sink effect, of the CA125 in patients' blood. What we've done in this case is actually designed an antibody that targets a different portion of MUC16. It targets the portion of MUC16 that's below the cleavage site and remains at the surface of the cell and is not in circulation. This targeting approach, the utilizing a high-affinity antibody, is one of the ways we've designed an improved version of a MUC16 targeting ADC. We've combined this targeting approach with our linker payload, we tested that in animal models of ovarian cancer with high circulating CA125 levels. That's shown on the right-hand side of this graph. What you can see is that at 1 mg per kg, which is a really low dose and highly potent dose in this case, but really a low dose utilized in these experiments, you can see that the DMUC original program, the DMUC ADC antibody, really has no effect in the orange lines here. It's the same as the control. Tumors grow in these mice without any suppression. However, when we switch over to the HWK-016 antibody, that antibody that targets the membrane-bound portion of the molecule, we start to see suppression, and that's the dark boxes that you see on the lower part of the graph, where you start to see suppression and some growth back towards the end of this evaluation period. That's utilizing the same payload that Genentech was utilizing. You already see the benefit of the antibody and that great reduction in tumor suppression. We also took the improved antibody and switched over to our platform. That's labeled as Topo 1 here in the light blue, and you can see further suppression of those and regression of those tumors in the mice, showing just the increased potency, both of now the antibody and the platform itself. We really think here we've designed a truly optimized ADC to go after this MUC16 target, which, again, is the most highly expressed tumor target within gynecological cancers like ovarian cancer. Ultimately, this program is also now in the clinic, we take an approach with our phase 1 studies in a highly competitive space of ADCs, of really trying to demonstrate what we believe is best-in-class efficacy and safety in homogeneous patient populations already during dose escalation. Our clinical trials are on selected populations. In HWK-007 case, that's non-small cell lung cancer, ovarian cancer, and endometrial cancer, which is highly expressive of the PTK7 target. This allows us, by focusing on those unique indications, to develop a true perspective of how well this asset can perform competitively, without exploring all the other indications that we could do for PTK7, but where there isn't really validation yet for this target. We take the same approach with HWK-016. In this case, we're limiting it to ovarian cancer and endometrial cancer in the first instance. As I mentioned, both of those programs are now enrolling patients in their phase 1 dose escalation phase. We anticipate readouts in the first half of 2027. Really look for that robust data set to be able to provide clarity of what we believe will be best-in-class profiles for these assets in their respective indications. Our third program is HWK-206, which is a biparotopic SEZ6-directed ADC. Biparotopic antibodies bind to their antigen in two different sites, which in this case allows for concatemerization and clustering of the target at the surface of the cell, improved internalization. That's what's shown in this chart. Here there already is a competitive program, ABBV-706, targeting the SEZ6 molecule, and what we've done is designed a better and improved targeting approach versus the ABBV-706 molecule, and you can see that in the binding and internalization, which should lead to better efficacy overall with our HWK-206 program, and we believe allow us to improve upon some pretty reasonable results that have been seen with the ABBV-706 molecule already. This program, as I mentioned, has an IND in the middle of this year, and we'll start clinical trials in Q3. Overall, we believe we've developed a portfolio here that has the potential to be really transformative for patients. We've selected clinically validated but broadly overexpressed tumor targets, and really, I optimize the targeting of each of those individually, to build best-in-class ADCs. We've coupled that with the technology that I described in the beginning, our underlying linker payload technology, that is the same across every program, which allows us for read-throughs across programs, as well as clarity of differentiation as we move forward. We have cash runway to fund operations into 2020 to 2028, allowing us to have those readouts in early 2027, with sufficient cash on hand to continue to prosecute each of these assets. It's really three shots on goal over the next year that we're really excited about revealing as we enroll patients and uncover the potential of these agents to be best in class. With that, Jeff, I'll end and turn it over. Thanks. Thanks, Dave, and great run through the really intriguing portfolio that you have. You know, you highlighted a little bit of preclinical data that you guys have generated here across all three programs, and, you know, the upcoming clinical data, which will be in 2027. How are you thinking about packaging and update, releasing that preclinical data that has supported these three programs? Is that something we might see in 2026? For sure. I think that we are, you know, we were keen to make sure we got into the clinic and really had these programs running. It is a highly competitive space. We have some great profiles to share for each of these on their non-clinical packages. We'll look to do that in the spring, as we approach now, the thawing of winter. You'll see those coming out over the next few months. Great. Yeah, unfortunately, snowing here this morning again. Yeah, great. We're really looking forward to the preclinical data sets. As you've hinted at, these really look like differentiated candidates versus the profiles that have validated these targets. Really looking forward to those preclinical data, and of course, as these trials continue to enroll and, you know, periodic updates on enrollment. With that, I think we are up on time. Dave, thank you very much for the presentation, and I hope you have some great meetings today. Thank you, Jeff. Great to see you. Talk to you soon. All right, take care.