NASDAQ:LTRN Lantern Pharma Q1 2025 Earnings Report $3.22 +0.03 (+0.94%) Closing price 04:00 PM EasternExtended Trading$3.22 0.00 (0.00%) As of 05:06 PM Eastern Extended trading is trading that happens on electronic markets outside of regular trading hours. This is a fair market value extended hours price provided by Polygon.io. Learn more. ProfileEarnings HistoryForecast Lantern Pharma EPS ResultsActual EPS-$0.42Consensus EPS -$0.49Beat/MissBeat by +$0.07One Year Ago EPS-$0.51Lantern Pharma Revenue ResultsActual RevenueN/AExpected RevenueN/ABeat/MissN/AYoY Revenue GrowthN/ALantern Pharma Announcement DetailsQuarterQ1 2025Date5/15/2025TimeBefore Market OpensConference Call DateThursday, May 15, 2025Conference Call Time9:00AM ETUpcoming EarningsLantern Pharma's Q2 2025 earnings is scheduled for Thursday, August 7, 2025, with a conference call scheduled at 4:30 PM ET. Check back for transcripts, audio, and key financial metrics as they become available.Conference Call ResourcesConference Call AudioConference Call TranscriptSlide DeckPress Release (8-K)Quarterly Report (10-Q)Earnings HistoryCompany ProfileSlide DeckFull Screen Slide DeckPowered by Lantern Pharma Q1 2025 Earnings Call TranscriptProvided by QuartrMay 15, 2025 ShareLink copied to clipboard.There are 4 speakers on the call. Operator00:00:00Good morning, and welcome to our first quarter twenty twenty five 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 the market opened today summarizing our financial results and progress across the company for the first quarter ended 03/31/2025. Operator00:00:35A 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 12/31/2024, which is on file with the SEC and available on our website. Operator00:01:44Forward looking statements made on this conference call are as of today, 05/15/2025, and Lantern Pharma does not intend to update any of these forward looking statements to reflect events from 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, Pana Sharma, and CFO, David Margrave. Pana 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 Pana, and then we'll open the call for q and a. Operator00:02:34I'd now like to turn the call over to Pana Sharma, president and CEO of Lantern Pharma. Pana, please go ahead. Speaker 100:02:52Good morning. Hello, everyone. Thank you for joining us to hear about our first quarter twenty twenty five 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 machine learning to transform the process of developing precision oncology therapies should yield significant returns for investors and patients as our industry matures and adopts an AI centric data first approach to drug development. Speaker 100:03:30The first quarter of twenty twenty five 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 RADAR AI platform to over 200,000,000,000 oncology focused data points. These achievements position us well for multiple value creating catalysts in the coming quarters. Let me organize today's remarks around three strategic pillars. First, our clinical pipeline progress second, our AI platform advancements and third, our initiatives to maximize shareholder value. Speaker 100:04:08Starting with our clinical pipeline, we continue to advance multiple programs that have the potential to address significant unmet patient needs for cancer patients globally. Our Phase 1a trial for LP-one hundred eighty four has progressed well with enrollment now through cohort 12. We expect to complete enrollment with 62 60 five patients across a wide range of solid tumors by the June 2025. Importantly, we're beginning to see early indications of clinical activity at higher dose levels, which aligns with our preliminary pharmacokinetic data. This quarter, our safety review committee made the decision to backfill doses level ten and eleven to ensure clarity on determining the maximum tolerated dose while maintaining patient safety. Speaker 100:04:56What distinguishes our synthetic lethal approach is its mechanistic precision. Unlike conventional chemotherapies and targeted agents that indiscriminately target dividing cells, LP-one 84 and LP-two eighty four exploit specific genomic vulnerabilities in cancer cells, particularly those with deficiencies in DNA damage repair pathways. The pharmacokinetic data from these trials suggest we're approaching concentration levels that correlate with the nanomolar potency observed in preclinical models. This is a critical inflection point that could demonstrate definitive proof of mechanism in patients, and pave the way for future trials and partnerships. With LP-one hundred eighty four now holding dual fast track designations for both glioblastoma and triple negative breast cancer, plus four rare pediatric disease designations, we've positioned this molecule for accelerated development across multiple high value meaningful indications. Speaker 100:05:56The FDA has also recently cleared two clinical trial protocols that can provide paths toward regulatory approvals, especially in triple negative breast cancer, where we also have a Fast Track designation. The first of these two protocols that has been cleared recently is a Phase 1btwo study in TNBC evaluating LP-one hundred eighty four both as monotherapy and in combination with the PARP inhibitor olaparib. With an estimated annual market potential exceeding $4,000,000,000 in metastatic TNBC, this represents a major significant opportunity. The second, a Phase 1btwo study in a biomarker defined subset of drug resistant non small cell lung cancer with STK11 and or KEAP1 mutations, a patient population with particularly poor prognosis, and a market opportunity exceeding 2,000,000,000 annually. Additionally, an investigator led exploratory clinical trial for LP-one hundred eighty four in recurrent bladder cancer is planned to begin in Denmark during Q3 twenty twenty five, which could create a pathway toward commercial clinical usage in the third line setting. Speaker 100:07:06Based on work we have done with Dana Farber and the Danish Cancer Research Group and in other published research, about twenty five percent to thirty percent of bladder cancers have DNA damage repair mutations at presentation and over forty percent at recurrence. Now turning to our HARMONIC phase two trial for LP300, we continue to make strong progress with enrollment in Japan and Taiwan, where never smokers represent about thirty three percent to forty percent of new non small cell lung cancer cases, compared to about fifteen percent to seventeen percent in The US. Following our compelling preliminary data, showing an eighty six percent clinical benefit rate and forty three percent objective response rate in the safety lead in cohort, additional patient data from the expansion cohort continues to support a similar positive trend. We look forward to sharing updated results, including data from patients in our Asian expansion cohort during Q3 and data from the ongoing benefits from our initial lead in cohort. Through our wholly owned subsidiary, Starlight Therapeutics, we're advancing STAR-one indications in CNS and brain cancers. Speaker 100:08:19Recently, our collaborators at Johns Hopkins have provided independent confirmation of hypersensitivity in rare pediatric brain tumors to LP-one hundred eighty four, supporting our planned clinical trial with the pediatric consortium focused on CNS tumors. A Phase IbII trial in recurrent GBM is anticipated to begin in late twenty twenty five, subject to successful additional protocol clearance and funding. Also bear in mind that LP-one hundred eighty four has multiple pediatric disease designations that upon approval in that indication can yield a priority review voucher, which can then be marketed and sold for 100,000,000 to $150,000,000 each. And Lanturn and Starlight have the potential and pathway for four of those opportunities. Starlight, which is 100% owned by Lanturn, will have the potential to be another very positive impact on our investors as we monetize this unique asset, the patents, and the clinical indications and insight. Speaker 100:09:17The dosage and safety data obtained in the Phase I trial for LP-one hundred eighty four will be used to advance the central nervous system indications as STAR001 for future Phase Ib and Phase II trial sponsored by Lantern's wholly owned subsidiary Starlight Therapeutics. Globally, the annual market potential for LP-one hundred eighty four's target indications is estimated to be about 14,000,000,000, consisting of $4,000,000,000 5 billion dollars for CNS cancers, both primary and secondary, and about $10,000,000,000 for other solid tumors. Turning now to our second pillar, which is our AI platform. Let's talk about the expansion and commercialization now of our RADAR AI platform. This quarter, our proprietary RADAR platform grew to approximately 200,000,000,000 oncology focused data points. Speaker 100:10:05The platform continues to deliver value across multiple dimensions from drug candidate optimization and developing combination strategies to biomarker signature development and mechanism of action clarification. We have made an important and exciting decision to open up the RADAR AI platform on a module by module basis to the broader scientific and research community. We expect to initially do this as a freemium type approach, which will be expected to drive collaborations and economics to Lantern. The large scale and highly inexpensive evolution of Rag and AgenTeq technologies has completely changed the ability for small emerging companies like Lantern to use cloud infrastructure to open up algorithms and unique processes to a broader community at a scale cost and level of complexity unimaginable in the past. A milestone this past first quarter was a strengthening of our AI intellectual property portfolio with the PCT publication of our proprietary blood brain barrier penetration prediction patent application. Speaker 100:11:12This technology received a favorable PCT search report indicating no significant prior art, And our algorithms currently hold five of the top 10 positions on the Therapeutic Commons leaderboard, a remarkable achievement demonstrating our leadership in AI drug development. This will be one of the first modules that we make publicly available in the coming quarters. Our BBB permeability prediction tool can process up to a hundred thousand molecules per day with industry leading accuracy, and the algorithm continues to evolve and improve. This technological advantage has profound implications for accelerating CNS drug discovery and the ability to predict in a domain that's been notoriously challenging. But 98% of small molecules historically have failed to effectively penetrate the blood brain barrier, and our algorithm's unprecedented accuracy enables us to identify promising CNS penetrant compounds and also optimize existing compounds with extraordinary efficiency, potentially reducing traditional discovery timelines by months while dramatically increasing success probabilities. Speaker 100:12:19This computational capability doesn't merely enhance our existing programs. It opens up entirely new therapeutic development possibilities across not only cancer but other neurological indications for many other drug development teams. We're particularly excited about our plans to make this and other RADAR AI modules commercially available to the scientific and research community this year. This represents a new potential revenue stream, an opportunity to foster collaborative open source innovation in cancer drug development. We've also expanded RADAR with an innovative AI powered module to improve the precision, cost, and timeline of antibody drug conjugate development. Speaker 100:12:58This multi omic approach leverages proprietary algorithms to design and optimize target selection, payload efficiency, and tumor selectivity, addressing a rapidly growing segment of the oncology market that has been notoriously difficult and very time consuming. Our AI powered antibody drug conjugate development module represents a fundamental reinvention of a traditionally resource intensive high risk development process. By identifying promising targets and target indication combinations, we've established a robust pipeline of opportunities in one of oncology's most rapidly growing therapeutic modalities. The technical implications for this are substantial. Iterative testing of antibodies, linkers, and payloads, which can take years and consume tens of millions of dollars, can be narrowed down, streamlined, and derisked. Speaker 100:13:49Our computational approach, we believe, can reduce these timelines by 30 to 50% and preclinical costs by up to two thirds while simultaneously enhancing target selection and understanding of real world target availability in an involved cancer environment. This efficiency advantage positions us to rapidly advance our own candidates with exceptional selectivity profiles, but also to enable other companies to take advantage of this. This module will also be one of the many modules we place into an agentic interface and framework for use by our collaborators and partners. We'll talk about this more later this quarter and probably host a specific call talking about the evolution of our AI platform to a more public facing commercial opportunity. AI and platform driven insights continue to guide our clinical development strategy. Speaker 100:14:41For l p one eighty four, we've also developed a qPCR assay for p t g r one, which, as we know, is the bioactivation agent for l p one eighty four. And by measuring p t g r one levels, we can help guide patient stratification and also at the same time, indications that may be very promising. For LB-two eighty four, we've also used our platform to identify promising combination strategies, for example, rituximab, which have shown compelling preclinical synergy. Moving on to our third strategic pillar to maximize shareholder value through we've done this now through disciplined capital management and a number of strategic initiatives. We've maintained our disciplined approach to capital deployment, ending the quarter with approximately $19,700,000 in cash, cash equivalents and marketable securities, providing an expected operating runway through at least May next year. Speaker 100:15:36Our quarterly net loss decreased to approximately $4,500,000 compared to $5,400,000 in the same period last year, reflecting our continued focus on operational efficiency. Want to bear in mind that the company's last capital raise was in January of twenty twenty one. So we've maintained tremendous fiscal discipline in getting our molecules into clinical trials, into meaningful inflection points, and executing on our dual strategy of advancing clinical programs while expanding vastly our AI platform capabilities. And now we're going to enter into, we believe, productive discussions with potential biopharma partners, whether through licensing agreements, technology partnerships, or co development. Now I'll turn the call over to our CFO, David Margrave, who will provide more details on the financial results for the quarter. Speaker 200:16:29Thank you, Pana, and good morning, everyone. I'll now share some financial highlights from our first quarter twenty twenty five ended 03/31/2025. Our general and administrative expenses were approximately $1,510,000 for the first quarter twenty twenty five compared to approximately $1,480,000 in the prior year period. R and D expenses were approximately $3,300,000 for the first quarter of twenty twenty five, down from approximately $4,300,000 in the first quarter of twenty twenty four. The decrease was primarily due to reductions in CRO and clinical site costs for LP-one 84, which also reflected our objective to accomplish more with our internal clinical operations team. Speaker 200:17:22We recorded a net loss of approximately $4,500,000 for the first quarter of twenty twenty five or $0.42 per share compared to a net loss of approximately $5,400,000 or $0.51 per share for the first quarter of twenty twenty four. Our cash position, which includes cash equivalents and marketable securities, was approximately $19,700,000 as of 03/31/2025. Based on our currently anticipated expenditures and capital commitments, we believe that our existing cash, cash equivalents, and marketable securities as of 03/31/2025 will enable us to fund our operating expenses and capital expenditure capital expenditure requirements for at least twelve months from today's date, May 15, so until at least mid May twenty twenty six. We will need additional funding in the near future, and one of our key objectives is to pursue additional funding opportunities. As of 03/31/2025, we had 10,784,725 shares of common stock outstanding, outstanding warrants to purchase 70,000 shares, and outstanding options to purchase 1,242,378 shares. Speaker 200:18:49These warrants and options combined with our outstanding shares of common stock give us a total fully diluted shares outstanding of approximately 12,100,000.0 shares as of 03/31/2025. Our team continues to be very productive under our hybrid operating model. We currently have 23 employees focused primarily on leading and advancing our research and drug development efforts. I'll now turn the call back over to Pana for additional updates and closing remarks. Pana? Speaker 200:19:23Thank you. Speaker 100:19:27Thank you, David. Our leadership in the innovative use of AI and machine learning to transform costs and timelines in the development of precision oncology therapies has allowed us to bring three important molecules to market with teams, cost, and efficiency that is only beginning to make massive year over year improvements. During the first part of twenty twenty five, we achieved our goal of reaching nearly 200,000,000,000 data points, growing that cancer focused data more in six months than we had in the prior three years. And more of this data growth and data ingestion campaigns will be automated, freeing up our team to focus on intelligent curation, analysis of the data, and creating upstream engineered solutions and frameworks to solve specific problems that can then be transformed into autonomous agents. Now we're entering a transformative phase where RADAR will be will leverage agentic AI capabilities, autonomous systems capable of making complex decisions, automating intricate biological data sets, and executing sophisticated workflows without constant super human human supervision. Speaker 100:20:37This next generation platform represents a fundamental shift in drug development methodology, moving from reactive, human limited analytics to proactive, continuously learning systems capable of identifying non obvious patterns and opportunities across multiple therapeutic dimensions simultaneously. We're strategically positioning our AgenTeq radar platform not only to drive internal pipeline growth, but also as a valuable collaborative asset for biopharma partners seeking to overcome drug development bottlenecks. The golden age of AI in medicine, as many of you have heard me say in the past, isn't just beginning. It's accelerating exponentially. By integrating agentic capabilities, RADAR will transform from an analytical analytical platform to a true development partner, one capable of operating continuously across multiple dimensions, connecting insights across previously siloed areas, and ultimately delivering helping to deliver life changing therapies to patients faster than ever thought possible. Speaker 100:21:36The speed will also drive reduced costs. We aren't just building better tools. We're fundamentally reimagining what's possible in precision oncology. As we continue this journey, our agentic radar platform positions us at the forefront of an entirely new paradigm in drug development, one where AI doesn't really assist human researchers but actively drives discovery forward through autonomous continuous learning and insights that can be tested in laboratories and then deployed safely into the clinic for patients. As we advance through 2025, we at Lantern are laser focused on the following key value creating milestones. Speaker 100:22:16First, completing our LP one eighty four phase one a trial enrollment in June with comprehensive data rate readouts after that, including biomarker correlations, potentially establishing proof of mechanism for our synthetic lethal approach, and setting up pivotal future trials. This is an opportunity that we believe represents over $10,000,000,000 in annual spend that l p one eighty four is well poised to take a great share of. Second, delivering expanded harmonic trial results that include our Asian expansion cohort, further validating our never smoker non small cell lung cancer thesis for LP300. We expect this to occur also in Q3 in July. Third, initiating our FDA cleared phase 1b and two trials for LP-one hundred eighty four in both TNBC and a biomarker defined subset of non small cell lung cancer, which is drug resistant, and we believe we can leverage our fast track status to accelerate development and potentially partner in those those trials and those indications with large pharma companies. Speaker 100:23:26Fourth, commercialize our initial modules from RADAR to the scientific community, beginning with our industry leading BBB permeability prediction tool and then moving on to other modules on a select basis. Fifth, strategically advancing partnership discussions that could accelerate our pipeline, whether they be through geographic rights for certain assets or co development rights in certain indications or spinning out assets such as our CNS and STARLIGHT focused capability or monetizing our AI platform capabilities. This quarter's progress while maintaining fiscal discipline and a focus on bringing our assets closer to patients and approval reinforces what makes Lantern unique in the oncology landscape. We're not just developing drugs. We're pioneering a fundamental transformation in how cancer therapies are discovered, developed, and delivered to patients using AI for an approach that is both efficient and focused. Speaker 100:24:25Our dual engine approach, clinical assets plus an AI platform, provides shareholders with multiple value creation paths. Each clinical advance demonstrates our AI platform's power, while every platform enhancement accelerates our pipeline and creates new partnership opportunities. As Agentic AI capabilities emerge in our radar platform, we're not merely participating in this AI revolution in drug discovery. We're helping to build it. I wanna express my sincere gratitude to our exceptional team, partners, and shareholders. Speaker 100:24:57Together, we're lighting a path and a way toward precision oncology solutions that we believe can fundamentally improve outcomes for patients while transforming the economics and timeline of cancer drug development. With that, I'd like to now open the call to any questions or clarifications. Operator00:25:17If Speaker 100:25:23you'd like to ask a question, you can do so in one of two ways. You can type your question using the QA tool, or you can click on the raise hand tool to speak directly, and we will unmute your line. Okay. I think Chad has his hand raised. Okay. Speaker 100:26:19I think we've got two hands raised. Speaker 300:26:29Can you hear me now? Speaker 100:26:30Yep. Yep. Sorry for the delay there. Speaker 300:26:34Alright. Good. Sorry. I I'll I'll I'll start up. I had a couple of questions. Speaker 300:26:40The first on making AI modules commercially available. It sounds like the blood brain barrier penetration module might be one of the lead candidates there. It's a very interesting sounding module. What are the sort of broader plans to, you know, to to roll this out? Are we gonna charge a fee for access to these? Speaker 300:27:02Are we gonna make some free and hope that, you know, people kinda get hooked and really like these modules and it leads to, you know, broader collaborations? And then, I guess, also, besides just money when other people start using these modules, of course, they will have data they wanna put in there, and that, of course, could benefit the the the platform overall. So just, you know, do you, you know, do do you intend to aggregate additional data and strengthen the platform that way? What are the what are the plans there? Speaker 100:27:35Yes. Great questions. I do think we're gonna start with a freemium type approach to get people used to getting questions answered this this using this method. The challenge that we've seen with a lot of the existing AI tools out there answering some of these questions is just, you know, they're slow. They're not scalable. Speaker 100:27:57You can't count on the quality of the data. So I think that we're gonna take an approach initially where the tool is kind of a freemium model with a drive towards collaboration so that we can continue to monitor closely the type of data and use that the research community has. We have a road map that we'll be discussing, probably toward the end of this quarter or early next quarter on what that road map is and also some of the business models underlying bringing RADAR into kind of an agentic life form module by module. Of course, we'll pick the easier modules we think can be readily scaled and then go into the more complex workflow enabling modules over time. But bear in mind, you know, we are primarily focused on advancing our pipeline at this time, and our goal is to introduce these modules to drive a larger tech partnership. Speaker 300:29:00Yep. That that makes a lot of sense. It's just sort of folds into your business model and approach well. And then just on the harmonic trial, very excited to be getting another data update there. You you refer to the, Asian patients as a as a cohort at least once. Speaker 300:29:23I just I wanna make sure I understand the design here. Is that cohort like, are we still enrolling more patients in The US, I guess, is one question. Speaker 100:29:33So, yeah, maybe not technically a cohort. So what we did is when we started the l p 300 trial, we obviously knew of the the numbers in East Asia. But as you know, for a small US Biopharma company, it's expensive and costly and introduces management risk to do trials, in Japan and you know, which is also very expensive. So our goal was to make sure we got a quality signal in a population that we could have ready ready access to. So the lead in cohort was the seven patients in The US, and six out of seven of them responded, which to us was fantastic. Speaker 100:30:12And the initial objective response rate was very positive. And we had one patient over a year on the drug with, you know, fifty seven percent tumor volume reduction. So by almost all measures, it was positive. And also the underlying population, was also pretty mixed. We had Hispanic. Speaker 100:30:34We had white. We had some Asian. It was more male than female. So and we also had multiple TKIs, right, not just EGFR. So we looked at that. Speaker 100:30:43We said we had a good heterogeneous population. We had an 86 clinical benefit rate, forty three percent objective response rate, a nice set of tumors that had about fifty percent reduction. It gave us confidence that now we can go ahead and spend time and money and energy on expanding to where there was a higher a bigger amount of patients. Now that after that seven, it goes into what is called the expansion cohort. The expansion cohort will be both US and Asian, but the expansion cohort is randomized. Speaker 100:31:13So it's two to one randomization. So it's not the Asian cohort. It's just the Asian patients as part of the expansion cohort, if that makes sense. Speaker 300:31:24Yes. Okay. Appreciate that appreciate that clarification. Operator00:31:27Thank you. Speaker 100:31:28And and and for us, it's important because I I don't think it would have made a lot of sense to spend all that money getting set up and operating and getting all the things done in Asia unless we were certain that, hey. This is gonna head in the right direction. Speaker 300:31:41Alright. Thank you. Speaker 100:31:44Thank you, Chad. I think John has a question. John, do you wanna John? I think, John, for some reason, we cannot hear you. Okay. Speaker 100:32:19We have one more question coming in on 184. Yeah. So 184, we expect the trial to be fully enrolled next month. This is now a 60 to 65 patient trial. I believe we'll be, we're almost concluded with now. Speaker 100:32:45We're over mid fifties, high fifties, and, we believe that enrollment will be completed next month. And, we'll have preliminary data after we start getting the clinical data, the biomarker correlations, etcetera, shortly after that. Next question is on FDA and using AI. I that's a great question. I wanna believe that the FDA, will definitely have to use AI in its evaluation of scientific literature, data, and perhaps better come through mechanistic inputs from companies on the evaluation of the safety and direction of their new molecules. Speaker 100:33:44So I think, yes, I think they will do it. I think they'll do it in, you know, pretty quick scale over the next twelve months. I think it'll help to bring down some of the costs of the FDA and hopefully speed things up. But as the as John pointed out, it does introduce some risks. I I can't say I'm an expert on all those risks, but I think it'll ultimately, I think the trade off is going to be improvements in cost and improvements in speed. Speaker 100:34:12In terms of the risk, I do think that there'll probably be a period in which they evaluate these methods in parallel to the existing methods. And I don't think they're gonna roll out anything across the board until they're have concluded, like, six months to one year of these efforts. So I think I would give this at least two years. By that time, the risks will be well known and pointed out obviously by the industry and probably easily addressed. Next question is about, new funds in AI. Speaker 100:34:49That's exactly one of the reasons why we also have decided to go directly to market on opening up these modules. I've seen a lot of the AI work that's being offered by many AI first companies in drug development, and, they lack some of the precision or focus or they have a lot of noise. But AI funds are very aggressively looking at AI, which I think will help our long term profile and also attract new investors into the company or into our efforts. Thank you for that question. Well, no further questions at this time. Speaker 100:35:31We're always open to having discussions with investors and shareholders. I'd like to thank members of our team for helping us prepare for this call, and I look forward to talking with all of you in the near future. Thank you. Speaker 200:35:43Thanks a lot.Read morePowered by Key Takeaways Lantern’s Phase 1a trial for LP-184 has enrolled through cohort 12 and is expected to complete enrollment of ~65 patients by June 2025, with early indications of clinical activity and dual Fast Track designations in glioblastoma and triple-negative breast cancer. In the HARMONIC Phase 2 trial for LP-300 in never-smoker NSCLC, the safety lead-in cohort showed an 86% clinical benefit rate and 43% objective response rate, and a randomized expansion cohort across the US and Asia is underway with data expected in Q3 2025. The proprietary RADAR AI platform now holds ~200 billion oncology-focused data points, and Lantern plans to launch a freemium module rollout—beginning with its top-ranked blood–brain barrier permeability tool—aimed at driving collaborations and new revenue streams. Financially, Lantern Pharma reported a Q1 net loss of $4.5 million (down from $5.4 million YoY) and ended the quarter with $19.7 million in cash, cash equivalents, and marketable securities, providing an operating runway through at least mid-May 2026. Management is focused on leveraging agentic AI capabilities, pursuing biopharma partnerships, and strategically commercializing AI modules to accelerate drug development timelines and create multiple paths for shareholder value. AI Generated. May Contain Errors.Conference Call Audio Live Call not available Earnings Conference CallLantern Pharma Q1 202500:00 / 00:00Speed:1x1.25x1.5x2x Earnings DocumentsSlide DeckPress Release(8-K)Quarterly report(10-Q) Lantern Pharma Earnings HeadlinesHere's Why We're Watching Lantern Pharma's (NASDAQ:LTRN) Cash Burn SituationMay 31 at 11:39 AM | finance.yahoo.comLantern Pharma Inc. (LTRN)’s LP-184 Shows 345% Survival Gain in Rare Pediatric Brain Tumor ModelsMay 30, 2025 | insidermonkey.comTrump Makes Major Crypto AnnouncementPay close attention to what I'm about to share… Most investors think Trump's pro-crypto policies will lift all boats equally. They're wrong. One project stands to benefit more than any other – not by accident, but seemingly by design. June 3, 2025 | Crypto 101 Media (Ad)Lantern Pharma's LP-184 Shows Promising In Vivo Activity in Atypical Teratoid Rhabdoid Tumors (ATRT) at SNO Pediatric Conference, Further Validating Rare Pediatric Disease Designation and Pathway to Clinical TrialsMay 29, 2025 | businesswire.comBrokers Set Expectations for Lantern Pharma FY2025 EarningsMay 24, 2025 | americanbankingnews.comLTRN: First Quarter 2025 Financial ResultsMay 20, 2025 | finance.yahoo.comSee More Lantern Pharma Headlines Get Earnings Announcements in your inboxWant to stay updated on the latest earnings announcements and upcoming reports for companies like Lantern Pharma? Sign up for Earnings360's daily newsletter to receive timely earnings updates on Lantern Pharma and other key companies, straight to your email. Email Address About Lantern PharmaLantern Pharma (NASDAQ:LTRN), a clinical stage biotechnology company, focuses on artificial intelligence, machine learning, and genomic data to streamline the drug development process. Its product pipeline comprises LP-300, which is in phase 2 clinical trial in combination therapy for never-smokers with non-small cell lung cancer adenocarcinoma; LP-184, which is in phase 1 clinical trial for the treatment of solid tumor, such as pancreatic, breast, bladder, and lung cancers, and glioblastoma and other central nervous system cancers; and LP-284, which is in phase 1 clinical trial for the treatment of non-Hodgkin's lymphomas, including mantle cell lymphoma and double hit lymphoma. The company develops STAR-001, which is in preclinical development for the treatment of glioblastoma, brain metastases, atypical teratoid rhabdoid tumors, and pediatric rare disease designation. In addition, it provides ADC program, an antibody drug conjugate therapeutic approach for cancer treatment. Further, the company's artificial intelligence platform RADR uses big data analytics and machine learning for combining molecular data. Lantern Pharma Inc. has a strategic AI-driven collaboration with Oregon Therapeutics to optimize the development of its first-in-class protein disulfide isomerase inhibitor drug candidate XCE853 in novel and targeted cancer indications. The company was incorporated in 2013 and is headquartered in Dallas, Texas.View Lantern Pharma ProfileRead more More Earnings Resources from MarketBeat Earnings Tools Today's Earnings Tomorrow's Earnings Next Week's Earnings Upcoming Earnings Calls Earnings Newsletter Earnings Call Transcripts Earnings Beats & Misses Corporate Guidance Earnings Screener Earnings By Country U.S. Earnings Reports Canadian Earnings Reports U.K. Earnings Reports Latest Articles Ollie’s Q1 Earnings: The Good, the Bad, and What’s NextBroadcom Earnings Preview: AVGO Stock Near Record HighsUlta’s Beautiful Q1 Earnings Report Points to More Gains Aheade.l.f. Beauty Sees Record Surge After Earnings, Rhode DealCrowdStrike Stock Slips: Analyst Downgrades Before Earnings Bullish NVIDIA Market Set to Surge 50% Ahead of Q1 EarningsAdvance Auto Parts: Did Earnings Defuse Tariff Concerns? 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There are 4 speakers on the call. Operator00:00:00Good morning, and welcome to our first quarter twenty twenty five 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 the market opened today summarizing our financial results and progress across the company for the first quarter ended 03/31/2025. Operator00:00:35A 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 12/31/2024, which is on file with the SEC and available on our website. Operator00:01:44Forward looking statements made on this conference call are as of today, 05/15/2025, and Lantern Pharma does not intend to update any of these forward looking statements to reflect events from 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, Pana Sharma, and CFO, David Margrave. Pana 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 Pana, and then we'll open the call for q and a. Operator00:02:34I'd now like to turn the call over to Pana Sharma, president and CEO of Lantern Pharma. Pana, please go ahead. Speaker 100:02:52Good morning. Hello, everyone. Thank you for joining us to hear about our first quarter twenty twenty five 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 machine learning to transform the process of developing precision oncology therapies should yield significant returns for investors and patients as our industry matures and adopts an AI centric data first approach to drug development. Speaker 100:03:30The first quarter of twenty twenty five 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 RADAR AI platform to over 200,000,000,000 oncology focused data points. These achievements position us well for multiple value creating catalysts in the coming quarters. Let me organize today's remarks around three strategic pillars. First, our clinical pipeline progress second, our AI platform advancements and third, our initiatives to maximize shareholder value. Speaker 100:04:08Starting with our clinical pipeline, we continue to advance multiple programs that have the potential to address significant unmet patient needs for cancer patients globally. Our Phase 1a trial for LP-one hundred eighty four has progressed well with enrollment now through cohort 12. We expect to complete enrollment with 62 60 five patients across a wide range of solid tumors by the June 2025. Importantly, we're beginning to see early indications of clinical activity at higher dose levels, which aligns with our preliminary pharmacokinetic data. This quarter, our safety review committee made the decision to backfill doses level ten and eleven to ensure clarity on determining the maximum tolerated dose while maintaining patient safety. Speaker 100:04:56What distinguishes our synthetic lethal approach is its mechanistic precision. Unlike conventional chemotherapies and targeted agents that indiscriminately target dividing cells, LP-one 84 and LP-two eighty four exploit specific genomic vulnerabilities in cancer cells, particularly those with deficiencies in DNA damage repair pathways. The pharmacokinetic data from these trials suggest we're approaching concentration levels that correlate with the nanomolar potency observed in preclinical models. This is a critical inflection point that could demonstrate definitive proof of mechanism in patients, and pave the way for future trials and partnerships. With LP-one hundred eighty four now holding dual fast track designations for both glioblastoma and triple negative breast cancer, plus four rare pediatric disease designations, we've positioned this molecule for accelerated development across multiple high value meaningful indications. Speaker 100:05:56The FDA has also recently cleared two clinical trial protocols that can provide paths toward regulatory approvals, especially in triple negative breast cancer, where we also have a Fast Track designation. The first of these two protocols that has been cleared recently is a Phase 1btwo study in TNBC evaluating LP-one hundred eighty four both as monotherapy and in combination with the PARP inhibitor olaparib. With an estimated annual market potential exceeding $4,000,000,000 in metastatic TNBC, this represents a major significant opportunity. The second, a Phase 1btwo study in a biomarker defined subset of drug resistant non small cell lung cancer with STK11 and or KEAP1 mutations, a patient population with particularly poor prognosis, and a market opportunity exceeding 2,000,000,000 annually. Additionally, an investigator led exploratory clinical trial for LP-one hundred eighty four in recurrent bladder cancer is planned to begin in Denmark during Q3 twenty twenty five, which could create a pathway toward commercial clinical usage in the third line setting. Speaker 100:07:06Based on work we have done with Dana Farber and the Danish Cancer Research Group and in other published research, about twenty five percent to thirty percent of bladder cancers have DNA damage repair mutations at presentation and over forty percent at recurrence. Now turning to our HARMONIC phase two trial for LP300, we continue to make strong progress with enrollment in Japan and Taiwan, where never smokers represent about thirty three percent to forty percent of new non small cell lung cancer cases, compared to about fifteen percent to seventeen percent in The US. Following our compelling preliminary data, showing an eighty six percent clinical benefit rate and forty three percent objective response rate in the safety lead in cohort, additional patient data from the expansion cohort continues to support a similar positive trend. We look forward to sharing updated results, including data from patients in our Asian expansion cohort during Q3 and data from the ongoing benefits from our initial lead in cohort. Through our wholly owned subsidiary, Starlight Therapeutics, we're advancing STAR-one indications in CNS and brain cancers. Speaker 100:08:19Recently, our collaborators at Johns Hopkins have provided independent confirmation of hypersensitivity in rare pediatric brain tumors to LP-one hundred eighty four, supporting our planned clinical trial with the pediatric consortium focused on CNS tumors. A Phase IbII trial in recurrent GBM is anticipated to begin in late twenty twenty five, subject to successful additional protocol clearance and funding. Also bear in mind that LP-one hundred eighty four has multiple pediatric disease designations that upon approval in that indication can yield a priority review voucher, which can then be marketed and sold for 100,000,000 to $150,000,000 each. And Lanturn and Starlight have the potential and pathway for four of those opportunities. Starlight, which is 100% owned by Lanturn, will have the potential to be another very positive impact on our investors as we monetize this unique asset, the patents, and the clinical indications and insight. Speaker 100:09:17The dosage and safety data obtained in the Phase I trial for LP-one hundred eighty four will be used to advance the central nervous system indications as STAR001 for future Phase Ib and Phase II trial sponsored by Lantern's wholly owned subsidiary Starlight Therapeutics. Globally, the annual market potential for LP-one hundred eighty four's target indications is estimated to be about 14,000,000,000, consisting of $4,000,000,000 5 billion dollars for CNS cancers, both primary and secondary, and about $10,000,000,000 for other solid tumors. Turning now to our second pillar, which is our AI platform. Let's talk about the expansion and commercialization now of our RADAR AI platform. This quarter, our proprietary RADAR platform grew to approximately 200,000,000,000 oncology focused data points. Speaker 100:10:05The platform continues to deliver value across multiple dimensions from drug candidate optimization and developing combination strategies to biomarker signature development and mechanism of action clarification. We have made an important and exciting decision to open up the RADAR AI platform on a module by module basis to the broader scientific and research community. We expect to initially do this as a freemium type approach, which will be expected to drive collaborations and economics to Lantern. The large scale and highly inexpensive evolution of Rag and AgenTeq technologies has completely changed the ability for small emerging companies like Lantern to use cloud infrastructure to open up algorithms and unique processes to a broader community at a scale cost and level of complexity unimaginable in the past. A milestone this past first quarter was a strengthening of our AI intellectual property portfolio with the PCT publication of our proprietary blood brain barrier penetration prediction patent application. Speaker 100:11:12This technology received a favorable PCT search report indicating no significant prior art, And our algorithms currently hold five of the top 10 positions on the Therapeutic Commons leaderboard, a remarkable achievement demonstrating our leadership in AI drug development. This will be one of the first modules that we make publicly available in the coming quarters. Our BBB permeability prediction tool can process up to a hundred thousand molecules per day with industry leading accuracy, and the algorithm continues to evolve and improve. This technological advantage has profound implications for accelerating CNS drug discovery and the ability to predict in a domain that's been notoriously challenging. But 98% of small molecules historically have failed to effectively penetrate the blood brain barrier, and our algorithm's unprecedented accuracy enables us to identify promising CNS penetrant compounds and also optimize existing compounds with extraordinary efficiency, potentially reducing traditional discovery timelines by months while dramatically increasing success probabilities. Speaker 100:12:19This computational capability doesn't merely enhance our existing programs. It opens up entirely new therapeutic development possibilities across not only cancer but other neurological indications for many other drug development teams. We're particularly excited about our plans to make this and other RADAR AI modules commercially available to the scientific and research community this year. This represents a new potential revenue stream, an opportunity to foster collaborative open source innovation in cancer drug development. We've also expanded RADAR with an innovative AI powered module to improve the precision, cost, and timeline of antibody drug conjugate development. Speaker 100:12:58This multi omic approach leverages proprietary algorithms to design and optimize target selection, payload efficiency, and tumor selectivity, addressing a rapidly growing segment of the oncology market that has been notoriously difficult and very time consuming. Our AI powered antibody drug conjugate development module represents a fundamental reinvention of a traditionally resource intensive high risk development process. By identifying promising targets and target indication combinations, we've established a robust pipeline of opportunities in one of oncology's most rapidly growing therapeutic modalities. The technical implications for this are substantial. Iterative testing of antibodies, linkers, and payloads, which can take years and consume tens of millions of dollars, can be narrowed down, streamlined, and derisked. Speaker 100:13:49Our computational approach, we believe, can reduce these timelines by 30 to 50% and preclinical costs by up to two thirds while simultaneously enhancing target selection and understanding of real world target availability in an involved cancer environment. This efficiency advantage positions us to rapidly advance our own candidates with exceptional selectivity profiles, but also to enable other companies to take advantage of this. This module will also be one of the many modules we place into an agentic interface and framework for use by our collaborators and partners. We'll talk about this more later this quarter and probably host a specific call talking about the evolution of our AI platform to a more public facing commercial opportunity. AI and platform driven insights continue to guide our clinical development strategy. Speaker 100:14:41For l p one eighty four, we've also developed a qPCR assay for p t g r one, which, as we know, is the bioactivation agent for l p one eighty four. And by measuring p t g r one levels, we can help guide patient stratification and also at the same time, indications that may be very promising. For LB-two eighty four, we've also used our platform to identify promising combination strategies, for example, rituximab, which have shown compelling preclinical synergy. Moving on to our third strategic pillar to maximize shareholder value through we've done this now through disciplined capital management and a number of strategic initiatives. We've maintained our disciplined approach to capital deployment, ending the quarter with approximately $19,700,000 in cash, cash equivalents and marketable securities, providing an expected operating runway through at least May next year. Speaker 100:15:36Our quarterly net loss decreased to approximately $4,500,000 compared to $5,400,000 in the same period last year, reflecting our continued focus on operational efficiency. Want to bear in mind that the company's last capital raise was in January of twenty twenty one. So we've maintained tremendous fiscal discipline in getting our molecules into clinical trials, into meaningful inflection points, and executing on our dual strategy of advancing clinical programs while expanding vastly our AI platform capabilities. And now we're going to enter into, we believe, productive discussions with potential biopharma partners, whether through licensing agreements, technology partnerships, or co development. Now I'll turn the call over to our CFO, David Margrave, who will provide more details on the financial results for the quarter. Speaker 200:16:29Thank you, Pana, and good morning, everyone. I'll now share some financial highlights from our first quarter twenty twenty five ended 03/31/2025. Our general and administrative expenses were approximately $1,510,000 for the first quarter twenty twenty five compared to approximately $1,480,000 in the prior year period. R and D expenses were approximately $3,300,000 for the first quarter of twenty twenty five, down from approximately $4,300,000 in the first quarter of twenty twenty four. The decrease was primarily due to reductions in CRO and clinical site costs for LP-one 84, which also reflected our objective to accomplish more with our internal clinical operations team. Speaker 200:17:22We recorded a net loss of approximately $4,500,000 for the first quarter of twenty twenty five or $0.42 per share compared to a net loss of approximately $5,400,000 or $0.51 per share for the first quarter of twenty twenty four. Our cash position, which includes cash equivalents and marketable securities, was approximately $19,700,000 as of 03/31/2025. Based on our currently anticipated expenditures and capital commitments, we believe that our existing cash, cash equivalents, and marketable securities as of 03/31/2025 will enable us to fund our operating expenses and capital expenditure capital expenditure requirements for at least twelve months from today's date, May 15, so until at least mid May twenty twenty six. We will need additional funding in the near future, and one of our key objectives is to pursue additional funding opportunities. As of 03/31/2025, we had 10,784,725 shares of common stock outstanding, outstanding warrants to purchase 70,000 shares, and outstanding options to purchase 1,242,378 shares. Speaker 200:18:49These warrants and options combined with our outstanding shares of common stock give us a total fully diluted shares outstanding of approximately 12,100,000.0 shares as of 03/31/2025. Our team continues to be very productive under our hybrid operating model. We currently have 23 employees focused primarily on leading and advancing our research and drug development efforts. I'll now turn the call back over to Pana for additional updates and closing remarks. Pana? Speaker 200:19:23Thank you. Speaker 100:19:27Thank you, David. Our leadership in the innovative use of AI and machine learning to transform costs and timelines in the development of precision oncology therapies has allowed us to bring three important molecules to market with teams, cost, and efficiency that is only beginning to make massive year over year improvements. During the first part of twenty twenty five, we achieved our goal of reaching nearly 200,000,000,000 data points, growing that cancer focused data more in six months than we had in the prior three years. And more of this data growth and data ingestion campaigns will be automated, freeing up our team to focus on intelligent curation, analysis of the data, and creating upstream engineered solutions and frameworks to solve specific problems that can then be transformed into autonomous agents. Now we're entering a transformative phase where RADAR will be will leverage agentic AI capabilities, autonomous systems capable of making complex decisions, automating intricate biological data sets, and executing sophisticated workflows without constant super human human supervision. Speaker 100:20:37This next generation platform represents a fundamental shift in drug development methodology, moving from reactive, human limited analytics to proactive, continuously learning systems capable of identifying non obvious patterns and opportunities across multiple therapeutic dimensions simultaneously. We're strategically positioning our AgenTeq radar platform not only to drive internal pipeline growth, but also as a valuable collaborative asset for biopharma partners seeking to overcome drug development bottlenecks. The golden age of AI in medicine, as many of you have heard me say in the past, isn't just beginning. It's accelerating exponentially. By integrating agentic capabilities, RADAR will transform from an analytical analytical platform to a true development partner, one capable of operating continuously across multiple dimensions, connecting insights across previously siloed areas, and ultimately delivering helping to deliver life changing therapies to patients faster than ever thought possible. Speaker 100:21:36The speed will also drive reduced costs. We aren't just building better tools. We're fundamentally reimagining what's possible in precision oncology. As we continue this journey, our agentic radar platform positions us at the forefront of an entirely new paradigm in drug development, one where AI doesn't really assist human researchers but actively drives discovery forward through autonomous continuous learning and insights that can be tested in laboratories and then deployed safely into the clinic for patients. As we advance through 2025, we at Lantern are laser focused on the following key value creating milestones. Speaker 100:22:16First, completing our LP one eighty four phase one a trial enrollment in June with comprehensive data rate readouts after that, including biomarker correlations, potentially establishing proof of mechanism for our synthetic lethal approach, and setting up pivotal future trials. This is an opportunity that we believe represents over $10,000,000,000 in annual spend that l p one eighty four is well poised to take a great share of. Second, delivering expanded harmonic trial results that include our Asian expansion cohort, further validating our never smoker non small cell lung cancer thesis for LP300. We expect this to occur also in Q3 in July. Third, initiating our FDA cleared phase 1b and two trials for LP-one hundred eighty four in both TNBC and a biomarker defined subset of non small cell lung cancer, which is drug resistant, and we believe we can leverage our fast track status to accelerate development and potentially partner in those those trials and those indications with large pharma companies. Speaker 100:23:26Fourth, commercialize our initial modules from RADAR to the scientific community, beginning with our industry leading BBB permeability prediction tool and then moving on to other modules on a select basis. Fifth, strategically advancing partnership discussions that could accelerate our pipeline, whether they be through geographic rights for certain assets or co development rights in certain indications or spinning out assets such as our CNS and STARLIGHT focused capability or monetizing our AI platform capabilities. This quarter's progress while maintaining fiscal discipline and a focus on bringing our assets closer to patients and approval reinforces what makes Lantern unique in the oncology landscape. We're not just developing drugs. We're pioneering a fundamental transformation in how cancer therapies are discovered, developed, and delivered to patients using AI for an approach that is both efficient and focused. Speaker 100:24:25Our dual engine approach, clinical assets plus an AI platform, provides shareholders with multiple value creation paths. Each clinical advance demonstrates our AI platform's power, while every platform enhancement accelerates our pipeline and creates new partnership opportunities. As Agentic AI capabilities emerge in our radar platform, we're not merely participating in this AI revolution in drug discovery. We're helping to build it. I wanna express my sincere gratitude to our exceptional team, partners, and shareholders. Speaker 100:24:57Together, we're lighting a path and a way toward precision oncology solutions that we believe can fundamentally improve outcomes for patients while transforming the economics and timeline of cancer drug development. With that, I'd like to now open the call to any questions or clarifications. Operator00:25:17If Speaker 100:25:23you'd like to ask a question, you can do so in one of two ways. You can type your question using the QA tool, or you can click on the raise hand tool to speak directly, and we will unmute your line. Okay. I think Chad has his hand raised. Okay. Speaker 100:26:19I think we've got two hands raised. Speaker 300:26:29Can you hear me now? Speaker 100:26:30Yep. Yep. Sorry for the delay there. Speaker 300:26:34Alright. Good. Sorry. I I'll I'll I'll start up. I had a couple of questions. Speaker 300:26:40The first on making AI modules commercially available. It sounds like the blood brain barrier penetration module might be one of the lead candidates there. It's a very interesting sounding module. What are the sort of broader plans to, you know, to to roll this out? Are we gonna charge a fee for access to these? Speaker 300:27:02Are we gonna make some free and hope that, you know, people kinda get hooked and really like these modules and it leads to, you know, broader collaborations? And then, I guess, also, besides just money when other people start using these modules, of course, they will have data they wanna put in there, and that, of course, could benefit the the the platform overall. So just, you know, do you, you know, do do you intend to aggregate additional data and strengthen the platform that way? What are the what are the plans there? Speaker 100:27:35Yes. Great questions. I do think we're gonna start with a freemium type approach to get people used to getting questions answered this this using this method. The challenge that we've seen with a lot of the existing AI tools out there answering some of these questions is just, you know, they're slow. They're not scalable. Speaker 100:27:57You can't count on the quality of the data. So I think that we're gonna take an approach initially where the tool is kind of a freemium model with a drive towards collaboration so that we can continue to monitor closely the type of data and use that the research community has. We have a road map that we'll be discussing, probably toward the end of this quarter or early next quarter on what that road map is and also some of the business models underlying bringing RADAR into kind of an agentic life form module by module. Of course, we'll pick the easier modules we think can be readily scaled and then go into the more complex workflow enabling modules over time. But bear in mind, you know, we are primarily focused on advancing our pipeline at this time, and our goal is to introduce these modules to drive a larger tech partnership. Speaker 300:29:00Yep. That that makes a lot of sense. It's just sort of folds into your business model and approach well. And then just on the harmonic trial, very excited to be getting another data update there. You you refer to the, Asian patients as a as a cohort at least once. Speaker 300:29:23I just I wanna make sure I understand the design here. Is that cohort like, are we still enrolling more patients in The US, I guess, is one question. Speaker 100:29:33So, yeah, maybe not technically a cohort. So what we did is when we started the l p 300 trial, we obviously knew of the the numbers in East Asia. But as you know, for a small US Biopharma company, it's expensive and costly and introduces management risk to do trials, in Japan and you know, which is also very expensive. So our goal was to make sure we got a quality signal in a population that we could have ready ready access to. So the lead in cohort was the seven patients in The US, and six out of seven of them responded, which to us was fantastic. Speaker 100:30:12And the initial objective response rate was very positive. And we had one patient over a year on the drug with, you know, fifty seven percent tumor volume reduction. So by almost all measures, it was positive. And also the underlying population, was also pretty mixed. We had Hispanic. Speaker 100:30:34We had white. We had some Asian. It was more male than female. So and we also had multiple TKIs, right, not just EGFR. So we looked at that. Speaker 100:30:43We said we had a good heterogeneous population. We had an 86 clinical benefit rate, forty three percent objective response rate, a nice set of tumors that had about fifty percent reduction. It gave us confidence that now we can go ahead and spend time and money and energy on expanding to where there was a higher a bigger amount of patients. Now that after that seven, it goes into what is called the expansion cohort. The expansion cohort will be both US and Asian, but the expansion cohort is randomized. Speaker 100:31:13So it's two to one randomization. So it's not the Asian cohort. It's just the Asian patients as part of the expansion cohort, if that makes sense. Speaker 300:31:24Yes. Okay. Appreciate that appreciate that clarification. Operator00:31:27Thank you. Speaker 100:31:28And and and for us, it's important because I I don't think it would have made a lot of sense to spend all that money getting set up and operating and getting all the things done in Asia unless we were certain that, hey. This is gonna head in the right direction. Speaker 300:31:41Alright. Thank you. Speaker 100:31:44Thank you, Chad. I think John has a question. John, do you wanna John? I think, John, for some reason, we cannot hear you. Okay. Speaker 100:32:19We have one more question coming in on 184. Yeah. So 184, we expect the trial to be fully enrolled next month. This is now a 60 to 65 patient trial. I believe we'll be, we're almost concluded with now. Speaker 100:32:45We're over mid fifties, high fifties, and, we believe that enrollment will be completed next month. And, we'll have preliminary data after we start getting the clinical data, the biomarker correlations, etcetera, shortly after that. Next question is on FDA and using AI. I that's a great question. I wanna believe that the FDA, will definitely have to use AI in its evaluation of scientific literature, data, and perhaps better come through mechanistic inputs from companies on the evaluation of the safety and direction of their new molecules. Speaker 100:33:44So I think, yes, I think they will do it. I think they'll do it in, you know, pretty quick scale over the next twelve months. I think it'll help to bring down some of the costs of the FDA and hopefully speed things up. But as the as John pointed out, it does introduce some risks. I I can't say I'm an expert on all those risks, but I think it'll ultimately, I think the trade off is going to be improvements in cost and improvements in speed. Speaker 100:34:12In terms of the risk, I do think that there'll probably be a period in which they evaluate these methods in parallel to the existing methods. And I don't think they're gonna roll out anything across the board until they're have concluded, like, six months to one year of these efforts. So I think I would give this at least two years. By that time, the risks will be well known and pointed out obviously by the industry and probably easily addressed. Next question is about, new funds in AI. Speaker 100:34:49That's exactly one of the reasons why we also have decided to go directly to market on opening up these modules. I've seen a lot of the AI work that's being offered by many AI first companies in drug development, and, they lack some of the precision or focus or they have a lot of noise. But AI funds are very aggressively looking at AI, which I think will help our long term profile and also attract new investors into the company or into our efforts. Thank you for that question. Well, no further questions at this time. Speaker 100:35:31We're always open to having discussions with investors and shareholders. I'd like to thank members of our team for helping us prepare for this call, and I look forward to talking with all of you in the near future. Thank you. Speaker 200:35:43Thanks a lot.Read morePowered by