Earnings Call Transcript
Lantern Pharma Inc. (LTRN)
Earnings Call Transcript - LTRN Q3 2025
Operator, Operator
Good morning, and welcome to our third quarter 2025 earnings call. As a reminder, this call is being recorded. A webcast replay of today's conference call will be available on our website at lanternpharma.com shortly after the call. We issued a press release before the market opened today, summarizing our financial results and progress across the company for the third quarter ended September 30, 2025. A copy of this release is available through our website at lanternpharma.com, where you will also find a link to the slides management will be referencing on today's call. We would like to remind everyone that remarks about future expectations, performance, estimates and prospects constitute forward-looking statements for purposes of safe harbor provisions under the Private Securities Litigation Reform Act of 1995. Lantern Pharma cautions that these forward-looking statements are subject to risks and uncertainties that may cause actual results to differ materially from those anticipated. A number of factors could cause actual results to differ materially from those indicated by forward-looking statements, including results of clinical trials and the impact of competition. Additional information concerning factors that could cause actual results to differ materially from those in the forward-looking statements can be found in our annual report on Form 10-K for the year ended December 31, 2024, which is on file with the SEC and available on our website. Forward-looking statements made on this conference call are as of today, November 13, 2025, and Lantern Pharma does not intend to update any of these forward-looking statements to reflect events or circumstances that occur after today, unless required by law. The webcast replay of the conference call and webinar will be available on Lantern's website. On today's webcast, we have Lantern Pharma's CEO, Panna Sharma; and CFO, David Margrave. Panna will start things off with introductions and an overview of Lantern's strategy and business model and highlight recent achievements in our operations, after which David will discuss our financial results. This will be followed by some concluding comments from Panna, and then we'll open the call for Q&A. I'd now like to turn the call over to Panna Sharma, President and CEO of Lantern Pharma. Panna, please go ahead.
Panna Sharma, CEO
Good morning, everyone, and thank you for joining us to discuss our third quarter 2025 results and corporate progress. As I have mentioned before, computational and AI-driven methods are becoming more prevalent at both large and emerging pharmaceutical companies for all areas of drug discovery and development. Lantern is leading the way in the innovative and efficient application of AI and machine learning to enhance the development of precision oncology therapies, which we believe will provide substantial benefits for both investors and patients as the industry moves toward an AI-centric, data-driven approach to drug development. This past quarter has been transformative for Lantern Pharma, marking significant progress in our clinical, regulatory, and validation efforts, alongside crucial advancements in the commercial deployment of our AI modules. The third quarter of 2025 marks a pivotal moment for Lantern Pharma, with significant progress across our clinical stage portfolio and an expansion of our proprietary AI platform, RADR. Additionally, we have established the future direction for our CNS-focused subsidiary, Starlight Therapeutics. These achievements set the stage for multiple value-creating opportunities in the upcoming quarters and years. I would like to highlight some of our notable achievements from this past quarter, starting with what I believe is our most significant clinical milestone to date. Our LP-184 Phase Ia clinical trial successfully met all primary endpoints, showing a 48% clinical benefit rate in evaluable cancer patients who received doses at or above the therapeutic threshold. Notably, we observed significant tumor reductions in patients with DNA damage repair mutations, specifically in the CHK2, ATM, and STK11/KEAP1 genes. This outcome validates our AI-driven precision medicine approach and the hypotheses of synthetic lethality and DNA damage repair that have guided this program from the beginning. On the regulatory front, we had a productive FDA Type C meeting for our subsidiary, Starlight Therapeutics, which focuses exclusively on CNS cancers. The agency provided clear guidance for our planned pediatric CNS cancer trial targeting ATRT, an ultra-rare brain cancer. Importantly, the FDA supported our strategy to combine LP-184, referred to as STAR-001 for this indication, with spironolactone, based on our preclinical synergy data. We also made significant progress across our broader pipeline. Preliminary Phase II data from our LP-300 HARMONIC trial were recently presented at the 66th Annual Meeting of the Japan Lung Cancer Society, with plans for a more comprehensive data update via webinar this December. For LP-284, our non-Hodgkin's lymphoma program, we shared clinical data at the 25th Annual Lymphoma, Leukemia and Myeloma Congress, which drew interest from biopharma companies and clinical investigators, prompting discussions about combination therapy opportunities. Building on the Phase Ia results from LP-184, we are now ready to advance LP-184 into several targeted Phase Ib and Phase II trials. Our biomarker-driven strategy will concentrate on 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 an annual market potential exceeding $7 billion. To provide further insight into the LP-184 data and our development plans, we are hosting a KOL-led scientific webinar on November 20 at 4:30 Eastern. Dr. Igor Astsaturov from Fox Chase Cancer Center will discuss the clinical results and their implications for the program's future. In addition to our clinical programs, we showcased the readiness of our RADR AI platform at the inaugural AI for Biology and Medicine Symposium. We presented several deployable, highly scalable AI modules that can be licensed to biopharma partners and research centers, marking an important step in our strategy to monetize the technology driving our drug discovery efforts. Lastly, I want to reiterate our commitment to disciplined capital management. As of September 30, we had approximately $12.4 million in cash and cash equivalents. Based on our current operational plans, we expect this runway to extend into approximately the third quarter of 2026. Before we move on to the financials, I would like to elaborate on our drug programs and our growing portfolio of AI modules, which we believe hold the potential for several hundred million in their own right as AI tools and services. To put things into perspective, the Phase Ia trial enrolled 63 patients, a substantial number given that we began at a low dose and increased accordingly. These patients had advanced solid tumors and had exhausted all standard treatment options, a common scenario for Phase I oncology studies. The trial, listed on clinicaltrials.gov as NCT05933265, successfully met all primary endpoints. A pivotal figure to note is that we observed a clinical benefit in 48% of evaluable patients who were treated at or above the therapeutic dose threshold. This level of activity in heavily pretreated patients with advanced disease is a significant and promising indication. More compelling, however, is where we observed this activity. The data confirmed our core hypothesis about synthetic lethality: patients with tumors containing specific DNA damage repair mutations, particularly in CHEK2, ATM, STK/KEAP1, and even BRCA, exhibited significant tumor reductions. This aligns perfectly with predictions made by our RADR platform prior to the trial, and witnessing this validation in real patients has been incredibly uplifting for our team, demonstrating how AI can have a positive impact on outcomes. Importantly, LP-184 displayed a favorable safety profile with minimal dose-limiting toxicities, providing us flexibility to explore both monotherapy and combination treatment approaches with synergistic agents like PARP inhibitors, immunotherapy, and spironolactone. Let me share a few clinical examples that highlight this potential. In the case of recurrent GBM, one of the most aggressive and treatment-resistant cancers, two out of 16 patients showed disease stabilization despite prior treatments such as TMZ and radiation. As mentioned earlier, we have robust data indicating that we can enhance LP-184's efficacy, achieving improvements of 3 to 6 times, a potentially transformative advancement. Encouragingly, two patients at dose level 10 have maintained disease control for over eight months and continue treatment today, demonstrating durability that exceeds typical expectations from Phase I studies. Furthermore, we observed durable clinical benefits in other challenging tumor types, including gastrointestinal stromal tumors and thymic carcinoma. These are rare cancers with limited treatment options, underscoring our commitment to addressing the unmet need in this area and our intent to develop an accessible tool for rare cancer drug development, codenamed withZeta, which I will discuss shortly. As we look toward clinical expansion, the natural question arises: what will we do with these promising results? This is where our AI-driven development strategy really shines. Rather than opting for a traditional broad Phase II basket trial, we are adopting a precision medicine approach. We are set to launch four focused Phase Ib and Phase II trials, each targeting a specific biomarker-defined patient population where LP-184 presents the highest likelihood of success along with the most synergistic agents. One of these trials, in Denmark, is an investigator-led study targeting recurrent advanced bladder cancer. We are creating multiple opportunities from this molecule through data-driven and precision oncology strategies. Let’s quickly review these trials. First, triple-negative breast cancer represents our largest market opportunity, nearly $4 billion. We are implementing two parallel approaches: one as a monotherapy for DNA repair gene mutations and another as a combination study with the PARP inhibitor olaparib specifically for BRCA-mutated patients. We have already secured FDA Fast Track designation to expedite our development timeline, seeking to enroll around 60 patients across both arms. The second study targets non-small cell lung cancer with KEAP1 or STK11 mutations, a genetically defined subset typically exhibiting very poor responses to immunotherapy. We are combining LP-184 with the checkpoint inhibitors nivolumab and ipilimumab in patients with low PD-L1 expression, representing a market opportunity of approximately $2 billion in the U.S. and potentially $3 billion worldwide. Again, we have an FDA Fast Track submission in process, and this trial plans to enroll approximately 34 patients. The third trial, led by Dr. Pappot at Rigshospitalet in Denmark, focuses on patients with recurrent advanced bladder cancer and specific markers indicating DNA repair deficiency, estimated to represent a global market opportunity of over $500 million with an expected enrollment of about 39 patients. Finally, in our first recurrent GBM study through Starlight Therapeutics, we will combine LP-184, known as STAR-001 for CNS indications, with spironolactone. This combination exhibited synergistic effects in our preclinical models, and we have obtained both FDA Fast Track and Orphan Drug Designation for this indication. This trial is designed in a Simon 2-stage manner with two separate arms based on IDH mutation status, aiming to enroll around 38 to 40 patients, with an estimated U.S. market potential of $1 billion and closer to $2 billion globally. Altogether, these trials represent a substantial combined market opportunity exceeding $7 billion, with each trial structured using biomarker-driven enrollment criteria to enhance our success probability. As I have mentioned before, biomarker-driven cancer trials have demonstrated success rates that can increase by four to twelve times. Instead of pursuing broad, basket-like development, we are focusing strongly on the patient populations where Phase I data and insights from our AI-driven RADR predict substantial clinical benefits, ensuring our efforts are targeted at real commercial opportunities and patient needs. This epitomizes precision oncology, employing AI to determine the right patients, indications, and combination therapies. All these insights derive directly from our Phase Ia trial experience, significantly supported by our team's AI analysis and prior publications. Now, turning to our LP-300 program and the HARMONIC trial, aimed at addressing a growing need in lung cancer, particularly among never-smokers who progress after treatment with TKIs. This demographic distinction is crucial, with never-smokers representing 33% to 40% of lung cancer cases in Asia, compared to only 15% to 16% in the U.S. and Europe. This factor prompted us to extend the trial to Japan and Taiwan, allowing us to access the relevant patient population and engage pharma interested in developing therapies for them, creating a significant global market opportunity nearing $4 billion annually, with no current therapies approved for this demographic. Although various companies are starting to show interest in this area, we see an important gap to address, even considering a shift to earlier lines of treatment. We wrapped up enrollment in Japan this past quarter across five clinical sites and presented data at the 66th Annual Meeting of the Japan Lung Cancer Society, delivered by Dr. Jonathan Dowell from UT Southwestern. Preliminary data from the trial showed an impressive 86% clinical benefit rate, with one patient maintaining a durable complete response and surviving nearly two years. We have another patient approaching the one-year mark. We're planning a more detailed webinar in December to share additional follow-up data and insights from both Asian and U.S. cohorts, which will allow us to discuss the data thoroughly and outline our regulatory strategy going forward. Additionally, during the third quarter, we made a strategic change in our clinical operations in Asia, transitioning our CRO services in Taiwan to focus on cost reduction and operational efficiency, while enhancing our team in Japan to maintain quality and integrity in the trial. The strategic positioning of HARMONIC also opens potential regional partnerships and co-development opportunities in Asia, where the never-smoker population is most concentrated. Now I will shift to LP-284, targeting recurrent non-Hodgkin's lymphoma, a program that has garnered interest from clinical communities and biopharma for combination therapy approaches. This represents our first human trial for LP-284, with expectations to enroll about 30 to 35 patients suffering from aggressive recurrent non-Hodgkin's lymphoma, including mantle cell and high-grade B-cell, both recognized as orphan indications. This presents a global market opportunity estimated at about $3 billion, targeting patients who have undergone multiple lines of therapy with very limited options. In October, we shared clinical data from this ongoing trial at the 25th Annual Lymphoma, Leukemia and Myeloma Congress in New York City. A key highlight from that presentation was the response from a heavily pretreated patient with aggressive grade 3 B-cell lymphoma, specifically DLBCL, who had exhausted standard therapies and demonstrated a complete metabolic response with LP-284 as monotherapy after just two doses. This aligns perfectly with the signals we hoped to observe, validating our preclinical hypotheses. This patient remains cancer-free since we reported this result in July of this year. LP-284 displays a novel mechanism of action, showing particular effectiveness in cells with DNA damage repair vulnerabilities, a common target in non-Hodgkin's lymphoma, which has drawn interest from potential partners. Following this presentation, we have engaged in discussions with investigators and companies about opportunities for combination therapy development with existing FDA-approved agents and post-immunotherapy strategies. We are evaluating the potential of 284 in systemic lupus erythematosus as an alternative to cyclophosphamide and methotrexate, based on preclinical data showing significant kidney damage reduction and B-cell depletion when LP-284 is combined with rituximab. This could position LP-284 as a next-generation therapy in several autoimmune diseases, thus broadening its commercial potential. LP-284 also enjoys strong intellectual property protection, with granted composition of matter patents in the U.S., Europe, Japan, India, and Mexico, ensuring exclusivity until at least 2039. The molecule has obtained Orphan Drug Designation in mantle cell and high-grade B-cell lymphomas, and we are focused on recruiting additional sites for non-Hodgkin's lymphoma and high-grade B-cell studies. The momentum surrounding LP-284, both clinically and in terms of partner interest, reinforces our belief that this asset has significant potential, either as a standalone program or within strategic collaborations. We are very receptive to those discussions, both in terms of combinations in non-Hodgkin's lymphoma and its applications in other autoimmune categories. Now, I want to pivot to our discussion on the AI platform. Previously, I touched on the growing importance of our RADR AI platform and the commercial potential it presents independent of our drug development efforts. For those who may be unfamiliar, RADR is our proprietary AI and machine learning platform that extends beyond an internal tool; it has become a commercial asset with revenue-generating potential that is expanding. The platform has maintained over 80% prediction accuracy across various applications and has now been validated in natural clinical trials with programs such as LP-184, LP-284, and Actuate Therapeutics. In these instances, it has accurately predicted biomarker responses, often identifying combination synergies even before patient enrollment. We have created eight distinct AI-powered modules aimed at addressing key challenges in oncology drug development, and we’re developing these into modules for the broader drug development community. In October, we demonstrated the commercial readiness of two RADR modules at the inaugural AI for Biology and Medicine Symposium, showcasing PredictBBB, which achieves a 94% accuracy in predicting blood-brain barrier permeability and can screen 200,000 molecular candidates in under a week. Additionally, our LBx-AI liquid biopsy platform has shown an 86% to 90% accuracy rate in predicting treatment response, initially in non-small cell lung cancer, a valuable asset that we are extending through collaborations into other indications. Both of these opportunities are significant, with the blood-brain barrier technology market expected to approach $1 billion, especially given that only 2% to 6% of molecules can penetrate it. Consequently, there is an immediate need for more effective predictive tools that can expedite the screening process without incurring delays common with animal testing. Furthermore, PredictBBB also provides insights into other molecular characteristics important for drug development and manufacturing. I am excited to introduce Zeta, our multi-agentic AI platform for rare cancers, connecting our experiences with LP-184 and LP-284 in addressing rare tumors like gastrointestinal and thymic carcinoma. Zeta is designed to tackle a fundamental issue in rare cancer research and drug development, where critical insights are often scattered across disparate data sources. Researchers or clinicians looking for treatment options for rare sarcomas or pediatric brain tumors face the challenge of sifting through fragmented clinical trial databases, genomic databases, and drug interaction databases, which can be a laborious and incomplete process. This fragmentation decelerates discovery, increases costs, and can result in missed connections between promising treatments and rare cancer vulnerabilities. Zeta functions as a multi-agentic AI scientist, integrating curated rare cancer databases and ontologies from over 500,000 clinical trials, 250,000 publications, and 1.2 million knowledge objects into a cohesive platform that uses advanced reasoning to transform fragmented biomedical knowledge. It allows users to interact in plain English, providing actionable insights and answers to complex queries about rare cancers in a fraction of the time tasks would take manually. We will delve deeper into Zeta in the coming days, but fundamentally, it aims to streamline research and enhance drug development for rare cancers. By being able to ask questions like which existing molecules with blood-brain barrier penetration are effective against mutations typically found in specific rare tumors, Zeta can quickly provide evidence-based answers along with supporting citations. It can also suggest potential combination regimens benchmarked against successful trials across various drug classes. From a business perspective, Zeta delivers speed, improved decision-making, novel discovery, expedited patient outcomes, and substantial cost savings throughout the rare cancer drug development cycle. Strategically, we aim to position Lantern as a unified team of AI co-scientists, continuously updated for rare cancer research and drug development, serving as a central hub for insights and data, thereby creating network effects that bring additional users into our ecosystem. We believe our AI tools and services could potentially generate hundreds of millions in standalone market value, attracting significant interest from the broader technology community while reducing the risks and costs of developing cancer therapies. This is an invaluable complement to our drug development strategy. Now, I will hand the call over to our CFO, David Margrave, who will outline our financial results for the quarter.
David Margrave, CFO
Thank you, Panna, and good morning, everyone. I'll now share some financial highlights from our third quarter ended September 30, 2025. Our R&D expenses were approximately $2.4 million for the third quarter of '25, down from approximately $3.7 million for the third quarter of 2024. The decrease was primarily due to decreases in research study and materials expenses relating to the conduct and support of clinical trials as well as decreases in consulting expenses and in payroll and compensation expenses. Our general and administrative expenses were approximately $1.9 million for the third quarter of 2025 compared to approximately $1.5 million in the prior year period. The increase was primarily attributable to increases in business development and investor relations expenditures as well as increases in other professional fees and increases in patent costs. We recorded a net loss of approximately $4.2 million for the third quarter of 2025 or $0.39 per share compared to a net loss of approximately $4.5 million or $0.42 per share for the third quarter of 2024. Our cash position, which includes cash equivalents and marketable securities was approximately $12.4 million as of September 30, 2025. We believe our cash, cash equivalents and marketable securities on hand as of the date of this earnings call will enable us to fund our anticipated operating expenses and capital expenditure requirements into approximately Q3 2026. We will need substantial additional funding in the near future, and one of our key objectives is to pursue additional funding opportunities. In July of this year, we entered into an ATM sales agreement with ThinkEquity as sales agent, pursuant to which Lantern may offer and sell up to $15.53 million of its common stock from time to time in at-the-market offerings to or through our sales agent. During the quarter ended September 30, 2025, we sold 212,444 shares of common stock under the ATM for gross proceeds of approximately $989,000. Between October 1, 2025, and the date of this earnings call, we've sold an additional 144,204 shares of common stock under the ATM for gross proceeds of approximately $634,000. As of September 30, 2025, we had 11,040,219 shares of common stock outstanding with outstanding options to purchase 1,218,828 shares and no warrants outstanding. These outstanding options, combined with our outstanding shares of common stock, give us total fully diluted shares outstanding of approximately 12.26 million shares as of September 30. And I'll now cover some near-term milestones that we think will accelerate value for investors. And these are several value-creating catalysts that we see in the near future. In the immediate near term, in this November, and Panna talked about this earlier, and we're very excited about this discussion. Next week, November 20, at 4:30 p.m. Eastern, we're going to have a KOL-hosted scientific webinar on LP-184 Phase Ia details from the clinical study and clinical development strategy. And in December of this year, we'll be giving for LP-300, an interim patient follow-up and additional clinical data. And then also in this upcoming quarter, we'll be discussing continued commercial developments for the AI platform modules, including the multi-agentic system that Panna discussed about withZeta for rare cancer development. And I'll now turn things back to Panna for some closing remarks.
Panna Sharma, CEO
Thanks, David. As you know, we've had a number of catalysts and objectives that continue to '26, which you can see on the slide, but we'll be talking about those 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 got really 2 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, 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've a question about tracking toward an interim event analysis for LP-300 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 very positive news. We do expect to see the Denmark trial. There's a question for the Denmark trial. 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 I 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 withZeta portion of our AI platform. We will have additional news next week on withZeta, which is very exciting. Like most software, we expect the early rollout to be interesting and bumpy. We'll learn a lot from it. We've already begun using it internally. And 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 withZeta. But it will 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, all those indications are very exciting indications, and we've had interest from pharma companies. Of course, they want to see some of the early Phase Ib, Phase II data, but all of 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 where 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 talk to other rare cancer experts, many of the cancers we're 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. And we said, this is part of the frustration in these cancers, and that's why they take time or too much money. What if you could 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 a preview, if you’d like a peek at it and even an early demo, happy to provide that to you. Another great question on STAR-001 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 gliomas. 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 I 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 Lantern Pharma continues to transform drug development in oncology.
David Margrave, CFO
Thanks a lot.