Good morning, everyone, and thank you for joining us to hear about our third quarter 2025 results and corporate progress as many of you have heard me say in the past computational and ai driven approaches are increasing their presence and usage at both large and emerging pharma companies for all facets of drug discovery and development lantern's leadership in the innovative efficient and pragmatic use of ai and machine learning to transform the process of developing precision oncology therapies should yield significant returns for investors and for patients as our industry matures and adopts an AI-centric, data-first approach to drug development. This past quarter has been transformative in many respects for Lantern Pharma, a quarter where we have met many clinical, regulatory, and validation milestones. And we have also significantly advanced the commercial availability and launch of our AI modules. The third quarter of 2025 represents a pivotal inflection point for Lantern Pharma. We've made significant advancements across our clinical stage portfolio, while simultaneously expanding the capabilities of our proprietary AI platform, Radar. And we've also set up the future of our CNS-focused subsidiary, Starlight Therapeutics. These achievements position us well for multiple value-creating catalysts in the coming quarters and years. let me share with you some of the more notable achievements this past quarter let me start with what i believe is our most significant milestone to date clinically our lp184 phase 1a clinical trial successfully achieved all primary endpoints demonstrating a 48 clinical benefit rate in a valuable cancer patients who received doses at or above the therapeutic threshold what's particularly exciting is that we observed marked tumor reductions in patients harboring DNA damage repair mutations, specifically in CHEP2, ATM, and STK11 KEAP1 genes. This validates our AI-driven precision medicine approach and the hypothesis of synthetic lethality and DNA damage repair that guided this program from the start. On the regulatory front, we completed a productive FDA Type-C meeting for our subsidiary starlight therapeutics by companies focused entirely on cns cancers the agency provided clear guidance and pathway clarity for our planned pediatric cns cancer trial targeting an ultra rare brain cancer atrt importantly the fda confirmed our strategy to combine lp184 which we will call star 001 in this indication with spinolactone based on our preclinical synergy data we also made important progress across our broader pipeline. Preliminary Phase 2 data from our LP300 harmonic trial were presented at the 66th Annual Meeting of the Japan Lung Cancer Society. We're planning a more comprehensive data update via webinar this December. For LP284, our non-Hodgkin's lymphoma program, we showcase clinical data at the 25th Annual Lymphoma, Leukemia, and Myeloma congress the presentation generated interest from both biopharma companies and clinical investigators and we've initiated several discussions around combination therapy opportunities building on the phase 1a results from lp184 we're now positioned to advance lp184 into multiple targeted phase 1b phase 2 trials our precision biomarker driven strategy will focus on four four high-value indications, triple negative breast cancer, non-small cell lung cancer with KEAP1 or STK mutations, bladder cancer with DNA repair deficiencies, and first recurrent GBM. Collectively, these indications represent a combined annual market potential exceeding 7 billion. To provide additional insight into the LP184 data and our development plans, we're hosting a KOL-led scientific webinar on November 20th at 4.30 Eastern. Dr. Igor Astyassarov from Fox Chase Cancer Center will join us to discuss the clinical results and what they mean for the future of this program. Beyond our clinical programs, we demonstrated the commercial readiness of our radar AI platform at the inaugural AI for Biology and Medicine Symposium. We showcase several platform modules as deployable, highly scalable, web-accessible AI tools that can be licensed to biopharma partners and research centers. It's an important step in our strategy to monetize the technology that powers our drug discovery efforts. Finally, I want to emphasize our continued commitment to disciplined capital management. As of September 30th, we had approximately $12.4 million in cash, cash equivalents, and marketable securities. Based on our current operating plans, we expect this provides runway into approximately the third quarter of 2026. Before we turn to the financials, let me provide some color and details around our programs, both our drug programs and our growing program of AI modules, which we believe have the market potential of several hundred million on their own as AI tools and services. First, some context. On the Phase 1a trial, this is a first in human study that enrolled 63 patients, a fairly large number, given that we started at a very low dose and escalated upwards. This was in advanced solid tumors who had exhausted all standard treatment options, which is fairly normal for Phase 1 studies. These were heavily pretreated cancers, oftentimes and very difficult to treat tumors. The trial, which you can find on clinicaltrials.gov, as NCT05933265, successfully met all of its primary endpoints. The headline number that I want you to focus on is this. We observe clinical benefit in 48% of the valuable patients who are treated at or above the therapeutic dose threshold. In a Phase I-A trial in heavily pretreated patients with advanced disease, that's a unique and promising signal of activity. But what's even more compelling is where we saw that activity. The data validated our core hypothesis about synthetic lethality. Patients whose tumors harbored specific DNA damage repair mutations, particularly in CHECK2, ATM, and also STK KEAP1, and actually also BRCA, showed marked tumor reductions. This is what exactly what our radar platform predicted well before starting this trial. and seeing it play out in actual patients is tremendously validating, but also very uplifting for our team, where we can see how AI is being used for good and having a real-world impact on improving and changing outcomes. For us, this also gives us a very clear safety standpoint. LP184 demonstrated a favorable profile with minimal dose-limiting toxicities. This is critical because it gives us flexibility we can now pursue both monotherapy approaches and combinations with agents that we have identified as synergistic such as PARP inhibitors and immunotherapy also spironolactone both these are all have been predicted through our ai platform again as i know before the trials even began let me give you a few clinical examples that really illustrate the potential here in recurrent gbm one of the most aggressive and treatment-resistant cancers, two out of 16 patients showed disease stabilization despite prior exposure to multiple therapies such as TMZ, lamustine, and radiation. In GBM, as you will learn during our webinar on the 20th, we had the flexibility to modulate and enhance the efficacy of LP184 by a factor of 3 to 6x, a potentially game-changing improvement. Even more encouraging, two patients that are dose level 10 have now maintained disease control for over eight months and remain on treatment today. This is much more durable than has been expected for most phase one studies. We also saw durable clinical benefit in other notoriously difficult tumor types, gastrointestinal stromal tumors and thymic carcinoma. These aren't common cancers, but they're devastating when they occur and options are extremely limited. Our work in these rare cancers has also encouraged us to double down on our desire to transform the world of rare cancers and develop an open access tool for rare cancer drug development, codenamed WITHZETA, which I'll talk about a little later this morning. Transitioning to clinical expansion. So the obvious question is this, what do we do with these results? And this is where our AI-driven development strategy really shines and demonstrates its value. Rather than pursuing a traditional broad phase two basket type trial. We're taking a precision medicine approach. We're positioning to launch in four targeted phase one B phase two trials. Each one focused on a specific biomarker defined patient population where LP 184 has the highest probability of success and the best synergy agent for that particular tumor indication. Through one of these trials in Denmark in recurrent advanced bladder cancer is an investigator-led study. We have made this molecule into a portfolio of opportunities using data and precision oncology approaches. So let me walk through these quickly. The first one is in triple negative breast cancer. It's our largest market opportunity, almost $4 billion. We're pursuing two parallel approaches, one in monotherapy with DNA repair gene mutations and a combination study with a PARP inhibitor, Olaparib, specifically in BRCA-mutated patients. We've already received FDA fast-track designation, which will expedite our development timeline. We expect to enroll approximately 60 patients across both arms upon full enrollment. Second, non-small cell lung cancer with KEAP1 or STK11 mutations. This is a genetically defined subset of lung cancer who typically have very poor responses to immunotherapy. We're combining LP184 with nivolumab and ipilumab, two checkpoint inhibitors in patients with low PD-L1 expression. This represents, we believe, just in the U.S. close to 2 billion and probably closer to 3 plus billion globally. Again, we have an FDA fast track designation submission and process, and this trial will enroll approximately 34 patients. Third, an investigator-led trial in bladder cancer, recurrent advanced bladder cancer. This is being led by Dr. Papot at Riggs Hospitalite in Denmark. It's focused on patients with advanced urothelial carcinoma who have specific markers indicating DNA repair deficiency. This represents, we believe, about a 500 million-plus global market opportunity, and we expect to enroll about 39 patients. Finally, first recurrent GBM, which we're pursuing through Starlight Therapeutics. Here we're combining LP184, which we will call Star001, and CNS indications with spironolactone. This combination showed synergistic activity in our preclinical models. We have both FDA fast track and orphan drug designation for this indication. This trial will use assignment two-stage design with two separate arms based on idh mutation status we expect to enroll about 38 to 40 patients and represents what we believe is about a billion dollars in u.s market and probably closer to 2 billion globally when you add up these indications they represent a combined market opportunity exceeding 7 billion and critically each trial is designed biomarker driven enrollment criteria that increase our probability of success in fact as you've probably heard me say in the past biomarker-driven cancer trials increase the success by 4 to 12x. Now, rather than pursue a broad basket-like development, we're taking a very directed approach, investing our resources exclusively in patient populations where the phase one data and our AI-driven radar insights predict meaningful clinical benefit and where there is real commercial opportunity and patient need. This is precision oncology at its best, using AI to identify the right patients in the right indications with the right combination drugs. And it all flows directly from what we learned in the phase 1a trial, which was also heavily supported and predicted by the in silico AI work of our team and with multiple publications prior to that. Now let me turn to our LP300 program and the harmonic trial, which addresses a significant growing need in lung cancer, lung cancer in never-smokers that have progressed after treatment with TKIs. This is an important distinction. In Asia, never-smokers represent 33 to 40 percent of all cases, compared to only about 15 to 16 percent in the U.S. and Europe. This demographic reason is one of the reasons why we expanded this trial into Japan and Taiwan. It gives us access to the patient population, and it gives access to pharmas who want to develop therapies for this population. The market opportunity here is substantial globally, approaching $4 billion annually, and there are no current therapies approved for this patient population. But it is a space that more companies are interested in, and are developing interest and are trying to approach it with various targeted combination opportunities. There's a real white space here that we're going after, and a potential even to get to an earlier line of treatment. We completed enrollment in Japan this past quarter at five clinical sites. and we presented data at the 66th annual meeting in the Japan Lung Cancer Society, which was presented by Dr. Jonathan Dowell from UT Southwest. Now, the preliminary data from this trial, which we've already shared publicly, showed 86% clinical benefit rate, which is very encouraging, and we have one patient who has demonstrated a durable, complete response with survival continuing for nearly two years, a remarkable outcome. I think we have another patient, which is now approaching a year. Now we're planning a more comprehensive webinar in December before the year closes where we'll present additional patient follow-up data and clinical readouts from both the Asian and U.S. cohort. This will give us an opportunity to discuss the data in much greater depth and provide regulatory strategy insight and positioning moving forward. I should also mention that during the third quarter we made a strategic change in our clinical operations in Asia. We transitioned our CRO services in Taiwan with a specific focus on cost reduction and operational efficiency. In Japan, we supplemented our team by bringing more activity in-house. This is part of a broader commitment to disciplined capital management and efficiency while maintaining the quality and integrity of the trial. The strategic positioning of Harmonic also opens doors for potential regional partnerships in Asia and co-development opportunities where the never-smoker population is most prevalent. Now let me turn to LP-284, our program targeting recurrent non-Hodgkin's lymphoma, which has generated interest from clinical communities and also from biopharma to approach combination approaches. This is our first in-human trial for LP-284, which we expect to enroll about 30 to 35 patients with aggressive recurrent non-Hodgkin's lymphoma including mantle cell and high-grade B cell, where we have orphan indications for both. This represents a global market opportunity, about 3 billion, and with patients who have failed multiple prior lines of therapy and have very limited options. In fact, in October, excuse me, we presented clinical data from this ongoing trial at the 25th Annual Lymphoma Leukemia Myeloma Congress in New York City. The cornerstone of that presentation was a heavily pretreated patient with aggressive grade three b-cell lymphoma specifically dlbcl who had exhausted standard therapies and we saw a complete metabolic response with lp-284 as monotherapy after two doses two cycles this is exactly the kind of signal we're hoping to see and validates many of our preclinical hypothesis for this drug it also validates the mechanistic insight and we saw complete metabolic response and the lesions around the hips and spine completely went away. This patient has now remained cancer-free since we initially reported this result in July Q2 of this year. LPA284 has a novel mechanism of action. It demonstrates particular lethality in cells with DDR, a targetable vulnerability that's common in non-Hodgkin's lymphoma. This mechanistic differentiation is what's driving interest from partners. Now, following this presentation, we've started discussions with investigators and companies around opportunities for combination therapy development with existing FDA-approved agents, post-immunotherapy treatment strategies, and leveraging the 284 mechanism where current therapies are failing, especially in what's exciting, indications beyond lymphoma. Based on preclinical data, we're evaluating 284 and rituximab as a potential alternative to cyclophosphamide and methotrexate in lupus, systemic lupus SLE. Our preclinical models showed that 284 reduced urinary microalbumin and kidney damage, which is a key marker of kidney damage in lupus, by approximately tenfold and depleted B cells by fourfold when combined with rituximab we saw even greater b cell depletion when both agents were used together this suggests lp-284 could become a next generation b cell depleting therapy in number of autoimmune diseases which would dramatically expand the commercial opportunity for this asset lp-284 also benefits from strong intellectual property protection we have composition of matter patents granted in US, Europe, Japan, India, and Mexico, providing exclusivity through at least 2039. The molecule, as I mentioned, also has orphan drug designation in mantle cell and high grade B cell lymphomas. We're now focused on recruiting additional sites with a focus on non-Hodgkin's lymphoma and high grade B cell lymphomas. The momentum we're seeing with LP 284, both clinically and in terms of partner interest, reinforces our view that this asset has significant opportunity both standalone as a wholly owned program or as part of a strategic collaboration and we're very open to those discussions both again in combination in non-hodgkins or in other autoimmune categories now transitioning to our ai platform discussion as i mentioned earlier i want to shift gears and talk about what i believe is an increasingly important value driver for lantern our radar ai platform and the commercial opportunities it represents independent of our drug development programs for those less familiar with radar it's our proprietary ai and machine learning platform and it's not just a tool we use internally it's now a commercial asset with its own revenue potential which is growing the platform has demonstrated over 80 prediction success across multiple use cases and now it's been validated in natural clinical trials through programs like LP184, LP284, and also with Actuate Therapeutics. In all cases, it's correctly predicted biomarker responses, and in many cases, combination synergies before we've even actually enrolled a patient. We've developed eight distinct AI-powered modules that address critical pain points in oncology drug development, and we've developed cases for these pain points, which are now developing into modules for the broader drug development community. In October, we showcased the commercial readiness of two radar modules at the inaugural AI Biology and Medicine Symposium. We demonstrated that our AI platform, Predict BBB, achieves a 94% accuracy for BBB permeability prediction, and it can screen 200,000 molecular candidates in under a week. To put that in context, our Our algorithms currently hold five of the top 11 positions on the therapeutic data commons, and that's a best-in-class performance. We also presented our LBX AI liquid biopsy platform, which has achieved 86 to 90% accuracy in predicting treatment response, initially in non-small cell lung cancer, which will be very useful for us, and now we're extending it through collaborations with research centers into other indications as well. Both of these opportunities, we believe, are significant. Blood-brain barrier technology market alone is predicted to be close to a billion dollars. And when you consider very few percentage, two to six percent of the molecules actually cross the BBB, there is a need for better predictive tools, one that don't take weeks or months and end up destroying animals. So the need there is obvious and urgent. The interesting thing with the predict BVB, is that it also gives us access to a lot of other molecular characteristics of that compound. And we can predict a lot of other drug-like features that are important, both for drug manufacturing and also predicting potential drug activity once delivered internally. Now let me introduce Zeta. It's our multi-agentic AI platform for rare cancers. very excited about this and what connects directly to our experience with both LP 184 and 284 and rare tumors like gastrointestinal and thymic carcinoma it's our newest initiative we're calling it with zeta it's a multi-agentic co-scientist now here's the fundamental challenge in rare cancer research and drug development which often comes after molecules developed it often comes much later the critical insights in rare cancers are scattered across disconnected data sources a researcher a clinician trying to understand treatment options for a patient with a rare sarcoma or rare pediatric brain tumor has to manually search through clinical trial databases pubnet genomic databases drug interaction databases molecular feature databases it's fragmented time consuming and inevitably incomplete for drug developers this fragmentation slows discovery increases cost and often means that promising connections between existing molecules or indications and rare cancer vulnerabilities are simply never found or never pursued. What Zeta does, it's a multi-agentic AI system. Think of it as a co-scientist that addresses this problem head on, or actually a series of co-scientists. We've integrated, curated rare cancer databases and ontologies across 500,000 clinical trials, 250,000 publications with over 1.2 million knowledge objects into an agentic large language model architecture that uses recursive reasoning loops to transform fragmented biomedical knowledge and insights into an interconnected investigational platform and it interacts with you in plain english so and it's an ai system that thinks like a scientist connects dots across disparate data sources and can answer complex questions in minutes about rare cancers these are things that would otherwise take researchers weeks or months to investigate manually we'll dig into more of the details about zeta in the coming days and we'll have more information as but the key is that it'll help you design and improve and optimize molecules that can target vulnerabilities or mechanisms across these hundreds of rare cancers so you can ask questions to zeta like what existing molecules would blood brain But existing molecules with blood-brain barrier penetration have shown activity against mutations commonly found in a specific pediatric brain tumor, and it'll search, reason, and provide evidence-based answers with citations, and you'll be able to have it quickly pick potential combination regimens as well for that rare cancer benchmarked against successful and not successful trials across drug classes that you can help Zeta understand, and it actually also predict potential efficacy in subtypes of that rare cancer and give you considerations that can then be taken to the lab from an industry and business value perspective wood zeta delivers several things speed smarter decision making novel discovery and potential for improved patient outcomes faster and most importantly massive cost and time savings across the rare cancer drug development cycle i like to think about with zetas strategically is that we're positioning lantern as a unified team of ai co-scientists always available always updated for rare cancer research and drug development a unified ai interface for complex scattered data and models that accelerates and improves novel therapy discovery and trial design this is a tool that can shorten development timelines um by months and years particularly in rare cancers where that data is sparse and every delay means challenges and time and lives lost. By making Zeta available to researchers and clinicians over the next month, we'll establish Lantern as a central hub for rare cancer drug development and insights. This creates network effects, brings more users and data into our ecosystem, and positions us as a trusted partner when those researchers need to take the next step, whether it's preclinical development, biomarker validation, clinical trial design, or code development. Now, let me briefly discuss how we're scaling our AI infrastructure to support Zeta and RADAR's continued expansion. We're establishing dedicated machine learning and data engineering teams in India, which will allow us to double or triple our technical team size while maintaining our current cost structure. This gives us round-the-clock development capabilities, access to world-class machine learning talent and reduce costs and the scalability to support multiple drug programs and additional biopharma partnerships simultaneously. When you connect the dots, our clinically validated radar platform, the commercial ready modules we're deploying, and with Zeta positions us as a hub for not only rare cancer, but cancer drug development and the infrastructure to scale. Now we believe our AI tools and services in the future can represent several hundred million dollars in standalone market potential and will attract a lot of interest in the broader big tech community but most importantly lower the risks and costs associated with creating cancer drugs and that's a very powerful complement to our drug development strategy now i'll turn over the call to our cfo david margrave we'll provide details on our financial results for the quarter
thanks david as you know we have a number of catalysts and objectives that continue into 26 um which you can see on the slide but we'll be talking about those um in follow-up meetings with investors as well but as you can see by integrating our capabilities in ai and bringing them to the public we're not just building better tools we're actually fundamentally reimagining what's possible in precision oncology an era that i call the golden age of ai in medicine as we advance into 2026 we're laser focused on executing our dual engine strategy we've got really two powerful engines of the company. One is the ability to generate new molecules that are very precise and focused on very unique cancers. And the second engine is the engine of our AI platform that we're now ready to commercialize and make available. So we're advancing our clinical assets while simultaneously scaling our platform for commercial deployment. So I want to thank our exceptional team, our partners, and our shareholders for their continued support. Together, we're lighting the way toward precision oncology solutions, solutions that can improve outcomes for cancer patients, while very importantly, transforming the economics of drug development. With that, I'd like to open the call to questions and also thank our team for helping to prepare us for these calls and preparing the content. So we have a question about tracking toward an interim event analysis. for LP300 trial. At the December webinar, we do not believe we'll be at the 31 events, which is good news because that means that patients are coming off of the trial. So the positive news is that patients are on the trial longer, but we will report out data, clinical data and insights that have resulted. We expect 31 events right now we're tracking to be sometime in early 26 which we think is actually a positive very positive news um we do expect to see the denmark trial there's a question for the denmark trial we do that has now been approved irbs are set project manager has been assigned we expect that to start sometime either in late december or early january at one site which is investigator-led in denmark Another question is that we've guided for an IND submission for the Pediatric CNS Program. Yes, now that the FDA is kind of back in business and looking and renewing new INDs, we're already prepared to submit that and expect that submission to happen here in the next few weeks. In terms of when we anticipate initial patient dosing, hard to say. We're already beginning discussions with sites, but I expect that to be sometime in early 26. There's a question about the with Zeta portion of our AI platform. We will have additional news next week on with Zeta, which is very exciting. Like most software, you know, we expect the early rollout to be interesting and bumpy. We'll learn a lot from it. We've already begun using it internally. In fact, we'll talk about this next week, but we've got a number of really exciting programs that have already been designed and are now being tested. as a result of with zeta but it'll be available as select demo to collaborators and select partners and so december will be a lot of demo and learning and broader rollout throughout january and february and q1 next question is for 184 yes for the indications we do plan on figuring out what is the best of those indications where we're getting the biggest impact and move that into larger scale trials ideally with partners as i mentioned boris all those indications are very exciting indications and we've had interest from pharma companies of course you know they want to see some of the early phase 1b phase 2 data but all those are potentially partnerable next question is zeta yes zeta was initially developed as a culmination of our internal efforts to develop drugs initially 184 and 284 for rare cancers we wanted to go after categories where there was no therapy approved categories there was high need categories where we thought the mechanism would work and could be exploited as we did that and we gathered information about some of these cancers we said well we can do it for all rare cancers there's no tool out there in fact when we talked to other rare cancer experts many cancers were pursuing it was scattered papers were hard to get, hard to get in front of experts, hard to get data. Trials were oftentimes took way too long and standards of care often changed or the best drug often changed. We said, this is part of the frustration in these cancers and that's why they take time and too much money. What if you actually have one source and then train that source to think in the way that a drug developer thinks? So yes, it was an internal effort and now it's going to be a front-facing natural language interface tool. And I'm happy to give you, Boris, if you'd like a peek at it and even an early demo, happy to provide that to you. Another great question on the STAR001 trial design for pediatric brain tumors. Yes, I do believe that the trial design allows for inclusion of other pediatric high-grade gliomas. Yes, we designed it to allow for that, including specifically diffuse midline cleomas. Okay, if there are no further questions, I want to thank everyone for joining and very importantly for listening in this morning. We know it's a little past the market open, so appreciate all of you staying online. Thank you very much for your time and I appreciate everyone's effort and also more importantly your support as the Lantern Pharma but continues to transform drug development in oncology. Thanks a lot.
