Lantern Pharma Inc.

We will open the call for questions and answers after our management's presentation.

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 market opened today, summarizing our financial results and progress across the company for the second quarter ended June 30, 2026. 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, 2025, which is on file with the SEC and available on our website. Forward-looking statements made on this conference call are as of today, August 14, 2026, 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 CEO, Panna Sharma, and CFO, David Margrave. Panna will start things off with 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.

Good morning, everyone, and thank you for joining us to discuss our second quarter 2026 results. As I've said before, AI and computationally driven approaches are now becoming central to how both large and emerging biopharma companies discover and develop drugs, but also how they allocate their resources and think about staffing their scientific teams. Today, we're at an inflection point that's actually accelerating, not just for Lantern, but for how science itself will be conducted. And we are watching it happen in real trials with real patients at Lantern. The golden age of artificial intelligence in medicine isn't beginning. It's actually accelerating. And this quarter, that idea has resulted in the development of a new company, Open Medicine AI. In August, we established Open Medicine AI as a separate company with commercial licenses and agreements with Lantern in place to take the AI data models to the next level. I'll spend some real time on that today because I think it's the most consequential structural decision we've made since starting Lantern. But let me first walk you through what got us here. A clinical signal that sharpened into a defined patient population, a signal that was actually validated in using big data, a European regulatory clearance in a challenging recurrent cancer. and allowed patent on a patient selection method for one of our most valuable assets, LP184, and a FDA cleared trial in triple negative breast cancer that's moving toward launch. All of these were backed by numerous observations in our trials, the LP300 trial, the LP184 trial, and even the LP284 trial. What those observations were is that the mechanistic insights gained during our preclinical work actually have real-world parallels, and they could be the basis for meaningful activity in actual cancer patients. The remainder of 2026 is a defining year for Lantern Pharma, and especially as we launch into 2027. We've achieved clinical validation across multiple programs while establishing the foundation for our next phase of growth in both of our engines, our drug development engine and also now our AI engine. In addition, our mid-year financial results reflect highly disciplined execution with a 25% reduction in total operating expenses year over year, even as we advanced multiple clinical programs through key inflection points and launched an entirely new company into one of the most promising and disruptive areas of AI, medicine. Our AI-driven clinical pipeline now encompasses multiple drug candidates across solid tumors, blood cancers, and now pediatric oncology with a combined annual market potential estimated at over 15 billion. Let's start with our phase two program, LP300 and the harmonic trial and never smokers, non-small cell lung cancer who progress after TKI therapy. We believe there's about 400 to 500,000 patients diagnosed globally each year that have no specific therapy aimed at never smokers that progress after TKI. In Asia, it's about 35 to 40 plus percent of non small cell lung cancer cases. In US and Europe, it's between 15 and 20%. In June, we reported emerging data as of the May 11th cutoff, and it shows something we didn't expect to see this clearly, but the benefit of LP300 deepens the longer patients stay on it. Among L858R patients who completed six cycles, Median progression-free survival reached 8.9 months. That's nine patients, three of whom hadn't progressed that analysis. Across the full cohort of L858R patients, median PFS was 8.4 months. The hazard ratio for that group was 0.37 with a confidence interval of 0.15 to 0.89. So that means more than seven, also more than 70% of the L858R patients saw target lesion reduction and some of the responses sustained beyond two years. We've had a 77% clinical benefit rate, which is phenomenal for that line of therapy. I'll be direct, these are small exploratory cohorts, not powered for statistical significance yet, and a median from nine patients can move up or down. But what makes us take it very seriously is that a Cox regression controlling for race, gender, TP53 status, which is very important, confirmed L858R as an independent predictor. This is not a demographic or statistical artifact and safety was comparable between four and six cycles with no added toxicity from longer exposure. So a drug that helps more the longer you stay on it without costing you more in side effects is a drug worth extending, especially where there's no other great therapy for these patients. And that's actually the science and the data behind what we did next. We had a successful type C meeting where no objections were raised to our key proposed amendments. We've concentrated the enrollment now on the L858R patients. These patients actually tended to do worse on current therapy regimens. That's why we also think there's a great need. We've extended the treatment from now six to up to eight cycles, and we've moved into a single arm design, which should be more efficient and less costly. The trial continues enrolling in the US and Taiwan, and we've used this data set and other observations, of course, about the future of the program in active partnering discussions. Let's talk a little bit about LP184 this quarter. We've made several advances, all of which were driven by data and AI leverage methodologies. First, the EMA clearance. In July, We got clearance for an investigator-initiated phase 1b2 trial in advanced bladder cancer. This is in Copenhagen at Denmark's National Referral Center for Urologic Cancers, Riggs Hospital, Taut. And this is with Professor Rorber and Pappet. They're the coordinating investigators. This will be a 39-patient trial and very uniquely on two biomarker, a dual biomarker strategy. One on PTGR1 overexpression and then combining that with DNA damage repair deficiency. And we're hoping to enroll patients, very importantly, that our platform has predicted should respond and more importantly, have a mechanistic basis to be helped by that drug. Second major milestone is the 184 monotherapy in relapsed or refractory triple negative breast cancer. That'll be a phase 1B2 trial. That protocol has been FDA cleared and is now moving toward launch with a number of sites. We've also applied for grants for that trial, for that study as well, which we're pretty excited about. This drug targets tumors of DNA damage repair alterations. and Simon TwoStage Efficacy Read. Thank you very much. So that's a patent on the selection logic itself, which is one of the hardest parts of this to replicate and then map that directly to a credible therapeutic intervention where safety is known and mechanism is beginning to be more and more observable. This all built on our 63 patient trial that we did for 184. And now that we have a dose of 0.39 mg per kg. And very importantly, what we saw in that trial is that we saw tumor reduction in patients that were carrying these DNA repair deficiency genes, CHECK2, ATM, BRCA1, STK11, KEAP1. Those alterations conferred exceptional sensitivity to the drug. Unlike conventional chemotherapies and other DNA damaging agents that indiscriminately target dividing cells, both LP184 and 284 exploit specific genomic vulnerabilities in cancer cells. and that precision is the thread that runs parallel through both programs and which we expect to give our programs a meaningful advantage in their development. LP284 continues in hematologic malignancies and in adult soft tissue sarcomas, where we got orphan designation earlier this year. And Starlight, briefly on the science, Star001, which is LP184 in brain cancers, our radar platform identified that those particular brain tumors would be very sensitive if ERCC3 was removed as a protein. because that's involved in the repair mechanism. Well, what we did is we characterized that with our group at Johns Hopkins that we collaborate with. And we're using spironolactone, which is already well characterized, safe in pediatric and adults. And it actually does exactly that. It degrades the ERCC3 protein and shuts down the repair route. And we've had great preclinical data. And now we're taking that now into the clinic. We're taking it into disease designations where we have orphan designations and also rare pediatric, such as ATRT, hepatoblastoma, rhabdomyosarcoma, and malignant rhabdoid tumors. Bear in mind that each of these is independently eligible for a priority review voucher upon approval, and they've recently transferred for $150 to $200 million or more, and Lantern holds four of those. On the pediatric program specifically, I'm very excited and I want to give you an update. We're actively working with several pediatric oncology consortia to determine the best and most expedited path to bring these into a trial as soon as possible. We've got two consortia that we're working with and we'll have more data in this coming quarter. We're also working closely to enable compassionate use for the drug, especially in some of these Thank you for joining us. Now, going back to Open Medicine, and this is, we believe, the structural news of the quarter. In August, we formally established Open Medicine, OMAI, as a separate company, executed our board-approved commercial licensing agreements, and more importantly, OMA AI now can operate the multi-agentic AI co-scientists that we launched as with Zeta and use it in the commercial setting. Here's the logic. Most people using AI drug development today ask one model a question and get an answer. We now see that things are moving well beyond a single line of questioning or querying. So we built an orchestrated system and this orchestra brings together specialized agents for literature synthesis, medicinal chemistry, pathway analysis, data curation, literature analysis, portfolio prioritization, clinical trial development and they challenge each other and they pass information and ideas and they cross validate before delivering hardened results or ask the scientist or drug developer to get more engaged and ask them questions and this we believe is multi-agentic Thank you very much. and in their own large quantitative models is critical. And more importantly, it can generate publication quality results with a full audit trail. As a platform gets smarter and more users use it and data flows through it, each engagement for a user will feed the next. And this is exactly the kind of dynamic that deserves its own capital structure. Clinical drug development and enterprise software are priced by different investors and different metrics. Held inside a clinical stage oncology company, a software business may or may not get the credit for what it's worth because investors who price AI and software generally don't own clinical stage biotech and vice versa. That's the entire rationale for separating and racing forward with open medicine AI. Open Medicine AI is 100% owned by Lantern today. It intends to raise capital at its own level in exchange for open medicine equity. With the longer-term objective of becoming a separately listed company, Lantern expects to remain one of its largest shareholders. So Lantern continues to retain the rights, the full access to the platform for our own drugs. And this changes nothing about those programs' priority or timing. And we believe that the market there is much, much larger than just early oncology companies like ourselves. Analysts project the market to reach about $10 billion by 2030, 2031. Oncology is one of its largest segments. Even doing my own bottoms-up analysis on companies and drug discovery, drug discovery technology, AI-enabled, I expect it to easily reach $9 to $10 plus billion by 2031. will host a dedicated informational call in mid-September on Open Medicine AI's Market Opportunity Platform Roadmap Commercial Model. But putting all this together, a clinically validated platform with three drugs and trials, a commercially accessible AI platform and software company with models and state-of-the-art tools, and a drug pipeline, these all feed each other. You get a business model that extends well beyond just the clinical assets. We think it's a very powerful complement to have both of these engines. An AI engine that can be separated and power dozens of companies and drug assets that are going after meaningful, challenging, rare, and aggressive diseases. And we think these are very complementary. The AI tools and services we think can grow to being several hundred million dollars in standalone value as part of this larger $10 billion market. We think a nice chunk of that $10 billion market will be agentic. Peter Nara, Panna Sharma, David Margrave dig into the details behind the non-cash expenses that are related to warrants that drive a higher net operating loss than what's actually underneath the hood. So David, I'll turn it over to you.