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Good morning and welcome to our second quarter 2026 earnings call. As a reminder, this call is being recorded and all attendees are in a listen-only mode. 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 defer materially form 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 defer materiall from those in the forward- looking statements can be found in our annual report on Form 10-K for the year ended December 31st, 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 14th, 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 and 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 and 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, an 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, theLP184 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 27. 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 2 program, LP300 and the harmonic trial in 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 PKI. In Asia, it's about 35 to 40 plus percent of non-Small Cell Lung Cancer cases. In the US and Europe, it is between 15 and 20%. In June, we reported emerging data as of the May 11th cutoff, and it showed something we didn't expect to see this clearly, but that 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 at 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 L859R 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 tend 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 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 Rohrberg and Papet. They're the coordinating investigators. This will be a 39-patient trial and very uniquely on two biomarker, a dual biomarkers 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, homologous recombination deficiency, or genomic loss of heterozygosity. We expect to enroll up to 40 patients across two dose cohorts, and we'll follow by Simon two-stage efficacy read. Third, very important, is that we received a notice of allowance in July covering our three-gene selection, where we used three genes, PTGR1, PTPN14, and ASPH for selection of patients most likely to respond to LP at 184. We issued a notice of allowance in four tumors, ovarian, liver, kidney, and thyroid cancer. 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 expedient 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 rare pediatric brain tumors where there's an exceptional need. Again, Starlight is 100% owned by Lantern. We expect to raise additional funding for it as a separate funding, holds its own INDs down, its own regulatory designations. And it's not just a program status. is actually a way to monetize it independently of the rest of Lantern. And more importantly, it's a template. We're about to use that same template again, this time with the underlying platform itself. 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 OMAII now can operate the multi-agentic AI co-scientist 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, this multi-agentic non-monolithic model is really the standard infrastructure for specialized domains that are multi-disciplinary. And we think it will be the standard structure for a drug discovery. And I think it's going to be this is something that will be critical. In addition to that, we believed that the computational biology model and the computational chemistry model that run deep 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 a 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 to 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, we'll 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 in nature, and open medicine will have a real chance at grabbing a significant piece of that. So these are two great growth engines in the company. And I'll let David talk a little bit, David Margrave, to discuss our financials, our key metrics, and also 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. Thank you, Pana. And good morning, everyone. I'll now share some financial highlights from our second quarter into June 30, 2026. Before getting into the details of the quarter, I want to note that this quarter was different from prior quarters because we had a substantial non-cash expense related to the issuance of warrants in connection with our May financing transaction, and the way those warrants are treated for accounting purposes. I'll discuss this topic in detail later in my discussion. Cash, cash equivalents, and marketable securities were approximately $7.4 million at June 30, 20 ticks, consisting of approximately $6.7 million in cash and cash equivalents and approximately $0.7 million in marketable securities, compared to approximately $10.1 million in cash, cash equivalence, and marketable security as of December 31, 2025. Funding received during the second quarter of 2026 consisted of approximately $4.4 million in gross proceeds from our registered direct offering that closed on May 14, 2026. Additional funding is a top priority, and we intend to pursue additional capital raises, collaborations, and other opportunities to extend our operating runway. R&D expenses were approximately $1.8 million for the three months into June 30, 2026, compared to approximately $3.1 million for the three-months ended June 30 2025. This was a decrease of approximately $ 1.3 million or 42%. The decrease was primarily attributable to reductions of approximately $1 million in research studies and materials expenses relating to the conduct of our clinical trials and decreases of approximately $0.3 million in salaries and benefit expenses. G&A expenses were approximately $ 1.7 million for the three months ended June 30, 2026, compared to approximately $1.6 million for the three months ended June 30, 2025. This was an increase of approximately $0.13 million, or 8%. The increase was primarily attributable to increases in business development and investor relations expenses of approximately 0.36 million dollars, and salaries and benefit expense increases of approximately $0.14 million, offset in part by decreases in other professional fees of approximately 0.35 million dollars. Loss from operations was approximately $3.5 million for the three months into June 30, 2026, compared to a loss from operations of approximately $4.7 million for the three months into June 30, 2025, representing a decrease of approximately 25%. In connection with our May 2026 registered direct offering, in which we raised approximately $ 4.4 million in gross proceeds, the company issued investor warrants to purchase up to 2,135,923 shares of common stock at an exercise price of $2.27 per share and placement agent warrants to purchaseup to 106,796 shares of common stock and an exerciseprice of $ 2.575 cents per share these warrants are accounted for as liabilities due to a settlement feature that may be triggered in the event of a fundamental transaction. During the three months into June 30, 2026, the company recorded an aggregate of approximately $3.6 million of expense related to these warrants. The main component of this was non-cash expense arising from an increase in the fair value of the warrants that was driven primarily by a substantial increase in a company's stock price between the May 14, 2026 warrant issuance date and June 30, 2027. In June 2026, other components related to warrant expense were loss on issuants of the warrants and warrant issurance costs. After including the non-cash and other items related to warrants, our net loss was approximately $7.1 million or $0.57 per share for the three months into June 30, 2026, compared to a net loss of approximately $4.3 million or 0.40 cents per share. for the three months ended June 30, 2025. For the six months ended June 30th, 2026, our net loss was approximately $10.4 million or $0.88 per share compared to a net loss of approximately $8.9 million or $.82 per share for the six months ended Jun 30, 2025. From a capitalization standpoint, as of June 30, 2026, the company had 12,759,146 shares of common stock outstanding. And as we described, in May 26, we closed a registered direct offering and concurrent private placement comprising 1,454,175 shares of Common Stock, pre-funded warrants to purchase up to 681,748 shares of common stock. Investor warrants to purchase up to 2,135,923 shares of commonstock at an exercise price of $2.27 per share. And placement agent warrants to purchase up to 106,796 shares of common stock at an exercise price of $2.575 per share. There was no activity under our ATM sales facility during the three months ended June 30, 2026. I'll now turn the call back over to Pana for an additional update on our programs and operations. Pana? Thank you, David. So two closing points. First number I want all of you to remember is that we advanced programs from AI-derived insights to first-in-human clinical trials in a timeline under three years, and roughly two to three years at approximately two to three million dollars each. The industry norm to reach that same point is five to ten years at 25 to 100. We have three molecules in clinical trials of dose to over 100 patients, and at the same time have been able to advance an AI platform that's launching commercially. Those numbers are not a marketing claim. It's actually our operating model, and it's a key part of our core advantage. Secondly, what we now have structurally that we didn't have just in April is a lung cancer trial refined around a specific patient population, LA58R mutations. We have European clearance for a dual biomarker trial, which will be led by investigators in Denmark in a challenging recurrent bladder cancer setting, an FDA-cleared second trial in triple-negative breast cancer, post-PARP refractory patients moving toward launch, and an AI and software company with executed licenses, multiple engineering centers, and a growing user base. As David just walked you through, we actually did all that while our actual operating losses or loss from operations were down approximately 25% year over year. And we did all of this while continuing to advance both engines of growth. We believe that's a really important and smart way to build, and that's the argument for continuing to operate this way. We're not just building better tools, we're reimagining what's possible in precision oncology and building the tools to support it. We believe this will be the standard for the rest of the industry. And more importantly, it's the platform that we think will be positioned to scale. I want to thank our team, our investigators, and our shareholders as we light our way through precision oncology solutions. And we expect to have a lot of great additional results over the coming quarters. And I want especially thank our own team here at Lantern, especially a longtime member of our team who's moving on to a new leadership opportunity in media and technology after five years with us, five years of building this company's brand, voice, communications, and also being an amazing colleague. So thank you very much. With that, I'd like to now open the call to questions. You can type your question using the QA tool or raise your hand, and we'll try to unmute your line and repeat your question. I think, Michael, you should be unmuted. Can you hear me? Yeah. Good morning. Two questions, Pana. One on LP300 and then the other on OMI. Just on LP 300, can you talk about what, where are you in the data analysis? you know, it's obviously nice to see the PFS stretching out a little bit more, but how mature is this data set? Will it mature further? When do you plan to update us again and any other? Well, and then the next question related to that is, now that you got the protocol amendment in place, have any patients been enrolled under the new protocol? All right, A lot of questions. But once we had sufficient confidence that the protocol would be amended and the data was trending that way, we wanted to get the new IRBs approved at all the sites. And that's all been done now. So we expect enrollment to resume under the new eight cycles, which is important. We think that'll extend durability and maybe even deepen response. So we expect to be enrolling patients in Taiwan and the U.S. specifically under the new amended protocol. We hope to expect, you know, another 15, 16 patients. That'll give us meaningful data, and we expect enroll those over the next, you now, four to six months, both in U. S. and Taiwan. That's the initial focus. Will there be any other updates coming on the current cohort? uh i we might we may have an update toward the end of the year i mean i think other than just extending pfs um you're really relying on the next batch of patients coming in to see what kind of responses that we continue getting okay very good thanks for that update and then uh just on open medicine can you talk about i think uh you know most of us that come from sort of therapeutics background or not, AI experts, most of the technology is a black box because the companies, like in silico medicine and others, don't open their kimono to see what's actually operating internally. Maybe you can help us understand what your system looks like, or how it compares, how should we think about it in the context of the other tools that are out there that the pharma industry seems to be taking advantage of? Yeah, so there's actually, I'm working on something for our mid-September webinar, but the AI cycle in drug development, you know, we're kind of on our fourth cycle. I mean, if you go back to early days of supercomputers and molecular modeling and large install bases, it was kind of like the first wave, limited compute resource, but infrastructure heavy. We're almost at the opposite end of that now where we have almost limitless compute resource and infrastructure install super light. And there are two waves caught in between that. And we really didn't have the capability to kind of get the transparency that you would want real time until after a algorithm was run. And oftentimes those algorithms would take days or weekends or long-term but now those can be done in seconds and so you can get real time you know what is the process that happened we also didn't have the software and tools to do large-scale algorithm mapping and analysis you know because it was just extra overhead but now we have the ability to do that so we get transparency that we didn't have that was a luxury in the past now it's commonplace and people expect it and so a lot of the large-scale AI providers, including the anthropics and open AIs of the world, and even to some extent, Kimmy3 and DeepSeeks have made some levels of transparency into how the system operates more expected. And that is something that we rest on the shoulders of. We can do it very differently. And so that's a platform that we've built. And more importantly, once you see it's the transparency you as an enterprise user or end user can actually tweak it and alter it and that just didn't exist before um so yeah we're in a different wave of how ai and i expect i'll mention this in the in the webinar in september is that the the people who are going to be hit the hardest are going to be two number one people who provide professional knowledge labor basically and then second it's going to Be the existing install base of software providers into pharma. Those days of going in and being able to charge 100 grand, 500 grand, 300 grand for some very, very specific functionality of an install, those days are going to be gone. They're all going to go to providers like OpenMedicine. And also, you're not going to hire teams of bioinformaticians and teams of data analytics people. It's just, you can do all that now in the cloud with one smart engineer, data science person. And you can launch swarms of people, swarms of agents doing this work for you. And that's especially what we've proven with open medicine. So I think that's the future. And I thinkthat's where leading-edge providers like Claude Science and others are going toward. People are going to expect greater transparency. And if you really want to democratize the development of drugs, you're going to have to be able to allow people to go to a URL, You can go to an app and start their inquiry. And that's exactly where I see open medicine playing, is a new category that just hasn't been valued in price. I'm writing a piece you'll see by mid-September. It's called The Deflation of Discovery and the Birth of a New Category. And that specifically talks to agentic AI in drug development and drug discovery. Thank you. And, you know, large pharma will have to partner with agentic AI to make it commonplace. I mean, it's transforming the economics of early development and also late stage development. So, yes, very, very much increasing interest. The more marketing, more dollars we can put behind driving awareness of open medicine and with Zeta, the more I expect. the one thing that we've seen that has been solid is that once we put the tool in front of people it gets very sticky so yes thank you so uh this is another question is our models we expect will be standards in computational biology and drug development um what are you doing to ensure that and that other competitors don't copy your methods um well i first of all everyone will copy one another. And that's part of putting open medicine separately is to allow it to move faster or further and have its own independent balance sheet to ensure that you always stay one or two steps ahead. Companies, there are definitely companies that have more capital. More capital doesn't necessarily mean you're going to be the surviving entity. You know, you can look at any industry. And category by category, but capital efficiency is important long-term, which we've proven to be very capital efficient at. But we're at a point where it needs to be a separate entity and raise its own capital to stay ahead of the curve. The things that we're doing in addition to continuing to train our models and try to grow intelligently using our center in Bangalore, India, those are things that we're doing we're also constantly benchmarking like we did with our BBB algorithm like we're dealing with our biocomputational tools we're trying to pick some of the toughest challenges and go deep as opposed to go broad and that's one of the things that we are big components of is going deep in certain categories versus broad across all of science I don't think we ever would have claimed hey we're going to be Claude science and do all of science. I think that just makes no sense to me. You can pick specific categories like rare cancers, specific areas like biocomputational tools, specific problems like blood-brain barrier or penetration into any tissue type and do it and resolve it really, really well. So we're going to go after certain diseases that we think require that kind of depth and then march forward in that fashion. But yeah, capital, no doubt, more capital is needed to drive that. All right, Dave, I'll ask a question on what does adoption and feedback look like. Adoption is very sticky. Like I said before, once we get it in front of users, we were taking certain measures to make sure that users get the benefit of the full platform. We've introduced a new code called WithZeta14 that people can sign up for and get the full professional edition. People who play with the professional edition, especially generative chemistry, biocomputational tools, the investigator mode, it tends to be very, very sticky. So that's the exciting news. Key is getting them to that point. So we're also beginning to implement some more aggressive email campaigns to drive the awareness and specialized codes for certain larger pharma companies. But yeah, great question. Okay. Another question is anonymous. What would you contemplate the biggest benefit of the open medicine spin out will be for shareholders? Well, Lantern owns 100% of open medicine today. We think it's poised to be very disruptive. Disruptive companies are usually valued, can be valued higher. and we're going to raise capital. Lantern will continue being the largest shareholder, we think, for a while. And we may explore ways to distribute the underlying shares to all shareholders in Lantern. So those are things that we're talking about and potentially distribution of the shares of Open Medicine to all Lantern shareholders. Again, we're having discussions. We're looking at the most efficient ways to do that. But I expect Lantern shareholders to continue being beneficiaries of that asset as we monetize it, both in private financings and, very importantly, as it potentially goes into an exchange. Okay. I think we're coming up to almost 45 minutes into the call. And we look forward to answering questions and one-on-ones as it continues. I know we have a couple of requests for some one-on-one follow-up meetings. We'll take those as well. And thank you guys for participating. I want to thank all the Lantern investors, people who are interested. And I look forward to giving you guys more updates as the year continues. Thank you. And I thank you again to our team as well." Thanks a lot.