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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 introductions and an overview of Lantern's strategy and business model and highlight recent achievements in our operations, after which David will discuss our financial results. This will be followed by some concluding comments from Panna, and then we'll open the call for Q&A. I'd now like to turn the call over to Panna Sharma, President and CEO of Lantern Pharma. Panna, please go ahead.

Good afternoon, and thank you for joining us today to hear about our fourth quarter and fiscal year 2025 results and corporate progress. As many of you have heard me say in the past, computation and AI-driven approaches are increasing their presence and usage at both large and emerging pharma companies for all facets of drug discovery and fundamental biomedical research. The future of medicine is going to be intimately involved with AI technologies and AI models. Our leadership in the innovative use of AI and 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. 2025 was a defining year for Lantern Pharma. We achieved clinical validation, we believe, across multiple programs while establishing the foundation for our next phase of growth.

We believe that we had encouraging and a unique development with LP-300 in the phase II HARMONIC observations, combined with also a successful phase I-A completion for our LP-184 clinical trial, and most recently, an FDA IND clearance for a pediatric CNS cancer program through Starlight Therapeutics. We believe all these represent transformational milestones that validate and strengthen our AI-driven approach to precision oncology. Today, we're sitting at a point in time where all of our initial ideas and concepts regarding our molecules have now been dosed to patients successfully in some manner in both phase I and phase II trials. Also, our full-year financial results reflect disciplined execution with a 19% reduction in total operating expenses year-over-year, even as we advanced multiple clinical programs through key inflection points and also introduced a highly unique multi-agentic system aimed at conquering rare cancers.

As we move into 2026, we are positioning to advance our clinical programs, expand our RADR platform's commercial reach and revenue potential globally through our new AI Center of Excellence in India, and further strengthen our balance sheet. Our AI-driven clinical pipeline now encompasses multiple drug candidates across solid tumors, blood cancers, and pediatric oncology, with a combined estimated annual market potential exceeding $15 billion and approaching $20 billion. On average, our newly developed drug programs have been advanced from initial AI insights or concepts to first-in-human clinical trials in 2.5-3 years and at approximately $ a few million per program.

It is very important to note that we have dosed over 100 patients across our programs and seen clear linkage to mechanisms and patient value that we believe can yield future medicinal opportunities in a range of cancers that we are continuing to advance. Before moving on, I want to take a moment to directly address some malicious and fake news that has been circulated online falsely claiming that I am departing Lantern Pharma or have stepped down as CEO. This is categorically untrue and appears to be rooted in a deliberate and perhaps malicious attempt to manipulate our stock price. This disinformation has caused real harm to our company, to the mission we are pursuing on behalf of cancer patients, and to our investors, and we intend to pursue all appropriate civil, criminal, and legal recourse against those responsible.

Let me share with you now, more importantly, the more notable achievements over the last year, past year and quarter, where we are heading into 2026. Let me start with our LP-300 program, the HARMONIC trial, which addresses a significant and growing unmet need in lung cancer. HARMONIC is focused exclusively on never smokers and non-small cell lung cancer who have progressed after treatment on TKIs. In Asia, never smokers represent now close to 40% of all non-small cell lung cancer cases, compared to about 15%-17% in the U.S. and Europe. The market opportunity here is substantial. Over $4 billion, we believe, annually in spend on people who are not smokers or never smokers and get non-small cell lung cancer. There are currently no therapies approved specifically for this patient population.

The phase II HARMONIC trial continued to advance through the fourth quarter and into early 2026, with ongoing patient enrollment and follow-up across clinical sites in the U.S., Japan, and Taiwan. Last year, we completed the targeted enrollment in Japan ahead of schedule across five clinical sites, including the National Cancer Center Hospital in Tokyo. During Q4, clinical investigators presented data at the 66th annual meeting of the Japan Lung Cancer Society from both Asian and U.S. cohorts. The trial has previously demonstrated an 86% clinical benefit rate and a 43% objective response rate in its initial safety lead-in cohort, including one patient with a durable complete response and survival continuing for nearly 2 years. Let's talk a little bit about our upcoming Type C meeting.

We're getting more involved with the FDA, and in March, we submitted a Type C meeting package to the FDA for LP-300, with the meeting scheduled now for mid-May 2026. We are seeking FDA feedback on three proposed protocol amendments that came out as a direct result of our observations from the trial. First, focusing future enrollment on patients with EGFR exon 21 L858R mutation, where our preliminary analysis suggests greater clinical benefit from the LP-300 regimen in combination with the chemo doublet for these 858R mutation patients. Second, increasing maximum LP-300 treatment cycles from six to eight based on established safety data and the mechanism. Third, converting to a phase II single-arm Simon's 2-stage design reflecting the evolving treatment landscape that has made continued randomization to the control arm increasingly challenging due to changed control protocols.

We're actively exploring collaboration and partnering opportunities globally to maximize LP-300's commercial potential. We're in discussions with several regional and global pharma companies around the future of this exciting treatment, and we expect additional clinical updates in the coming weeks, along with insights on the exon 21 L858R population of patients. Turning now to what I believe remains one of our most significant assets, in Q4 of 2025, we reported additional positive LP-184 phase I results showing durable disease control in heavily pretreated advanced cancer patients. The trial enrolled 63 patients, achieved all primary endpoints with a 48% clinical benefit rate at or above the therapeutic dose threshold. It's a unique and promising signal of activity in this patient population. The data validated our synthetic lethality hypothesis.

We saw marked tumor reductions that were observed in patients with DNA damage repair mutations, including CHEK2, ATM, BRCA1, STK11, and these were all alterations that were initially flagged or signaled through RADR-driven insights. We also established a recommended phase II dose of 0.39 mg/kg with a favorable safety profile and saw notable clinical benefits in some very difficult-to-treat cancers, including relapsed GBM, gastrointestinal stromal tumors, and thymic carcinoma. Many of these patients are now getting clinical benefit for over a year into their treatment cycles. These are typically tumors with sub six-month PFS and very poor OS as well. The phase I-B, phase II-A development plan are building on these results, and we're positioning these into multiple precision oncology trials. Let me walk you through those. First, triple-negative breast cancer, where over $4 billion are spent.

We have an FDA-reviewed protocol for a combination study with olaparib, and we hold Fast Track designation. Second, non-small cell lung cancer with patients that have KEAP1 or STK11 mutations. We believe about a $1.5 billion opportunity in patients who typically fail immunotherapy and are not good responders for chemotherapy. Third, an investigator-led bladder cancer study planned in Denmark targeting PTGR1 overexpressing tumors with DNA damage repair mutations. All three are precision oncology trials, where they're being driven by mechanistic insights, biomarkers, and very focused patient populations that we believe have been validated from the outcomes in our phase I and also in our extensive preclinical work. These trials are subject, of course, to additional funding, which we're actively pursuing, and whether it be through grants or other mechanisms. What distinguishes our synthetic lethality approach is its mechanistic precision.

Unlike conventional chemotherapies that indiscriminately target dividing cells, both our first-in-human drugs, LP-184 and LP-284, exploit specific genomic vulnerabilities in cancer cells, particularly those with deficiencies in DNA damage repair. The pharmacokinetic data from these trials suggest we're approaching concentration levels that correlate with the nanomolar potency that we've already observed in clinical models, a critical inflection point that we believe has shown a proof of mechanism in patients, and it may pave the way for future trials and, more importantly, pharma partnerships. During our collaboration last year with MD Anderson, it was also revealed that LP-184 had a very unique and remarkable ability to transform immunologically cold tumors, especially in TNBC, into hot tumors, a breakthrough with profound implications for expanding immunotherapy benefits to previously unresponsive patients. This isn't merely additive efficacy.

It represents a mechanistic synergy that addresses one of immunotherapy's most significant limitations, and it opens up additional co-development opportunities and new indication expansion where PD-1 and PD-L1 checkpoint inhibitors have stopped working. Let me move on to Starlight Therapeutics. At Starlight Therapeutics, we cleared an IND for a planned phase I pediatric CNS cancer trial. We announced this last week on Friday. This is an innovative trial design that we unveiled at the Society for Neuro-Oncology, and it features a unique combination of spironolactone, and it exemplifies the power of computational biology. We're approaching so we're exploiting the synthetic lethality of our drug in GBM through a mechanistically elegant interaction. Spironolactone degrades ERCC, a critical DNA repair protein that causes further vulnerability that then STAR-001 exploits with precision in these brain tumors.

The IND being cleared for this trial is a milestone that I'm particularly proud of, and I wanna spend some more time on it because Starlight Therapeutics, our CNS oncology franchise, is now well-positioned for that. In early 2026, the FDA cleared the IND for Starlight Therapeutics in not only recurrent CNS tumors, but an ATRT and other rare pediatric tumors. With this clearance, we now have INDs cleared for both our adult and our pediatric programs, positioning us to pursue clinical development across the full patient spectrum. This is a pivotal regulatory milestone for our wholly-owned CNS-focused subsidiary. STAR-001 has received both Rare Pediatric Disease Designation and Orphan Drug Designation from the FDA for ATRT, along with additional Rare Pediatric Disease Designations for hepatoblastoma, rhabdomyosarcoma, and malignant rhabdoid tumors. These designations provide pathways for FDA Priority Review Vouchers upon a potential approval.

PRVs have been sold or transferred for significant value historically, with recent transactions in the range of $150 million-$200 million, and our drug has four of these. Importantly, each of these rare pediatric disease designations independently qualifies upon potential FDA approval and meeting other program conditions for these PRVs. That's multiple shots on goals from a single molecule, representing a potentially meaningful source of non-dilutive value for Lantern and its shareholders, independent of the commercial potential of the underlying therapy. Now, the scientific rationale for combination with spironolactone is compelling, it's unique, and novel. Preclinical studies demonstrated a three- to six-fold increase in GBM cell sensitivity when combining with these agents, with most preclinical models showing complete tumor eradication and minimal recurrence.

This can be especially critical in the most sensitive patients, such as children, the elderly, or those that have undergone multiple prior lines of therapy. Even more interesting is that STAR-001 has shown antitumor activity in GBM regardless of the MGMT status. Let's talk a little bit about why this mechanism is distinctive and first in class. This is where our RADR AI platform and novel mechanistic biology really comes to life. The plan trial includes a dedicated combination cohort evaluating STAR-001 with spironolactone, and again, this was initially identified with our platform, and we believe that this combination creates unique synthetic lethality in these challenging brain tumors. Now, once our drug is activated, when PTGR1 is overexpressed, it induces DNA double-stranded breaks that are lethal to the cancer cell if left unrepaired. That's the critical insight.

The cancer cell has a repair escape route, and we found a way to basically shut it down. We identified that we can degrade ERCC3, excision repair cross-complementation group. That's a key helicase in the repair pathway. It's a central repair mechanism that's used in some of these very aggressive tumors. Now, we can shut it down by delivering spironolactone. Basically, this is how you block the cancer cells from trying to come back. That's where spironolactone enters the picture. It's brain penetrant, it can be orally administered, it has a long safety record in adults and also now in pediatric, and it degrades the ERCC3 protein through targeted proteasomal degradation. In our preclinical models, we saw ERCC3 protein levels reduced by at least 50%, and actually through some dosing optimization, we got even more reduction.

By reducing that ERCC3, we remove the ability for the repair to happen. This is a rationally designed, AI-identified, validated combination that's been validated in the clinic that creates enhanced synthetic lethality that amplifies the tumor-killing activity of STAR-001. I wanna underscore several things that make this combination strategy unique. The ERCC3 was identified and validated through our analysis, not through just traditional screening. The combination partner, spironolactone, is already well-characterized, and it de-risks the safety profile of this combination. The mechanism, precision bioactivation with targeted repair pathway inhibition, we believe represents a first-in-class and unique approach to how to treat these devastating brain cancers. Now that the IND is cleared, Starlight Therapeutics is positioned to move rapidly into the clinic, of course, subject to more funding.

Starlight, which is 100% owned by Lantern, will have the potential to be another very positive impact on our investors as we monetize this unique asset, monetize the patents, and potentially monetize the PRVs. This computational capability doesn't merely enhance our existing programs. It opens up entirely new therapeutic possibilities as well. We'll talk about that a little later. In Q1 of 2026, we also received FDA Orphan Drug Designation for soft tissue sarcoma, adding to the existing designations in mantle cell and high-grade B-cell lymphoma. We also had a patient in Q4 that we presented clinical data at the 25th Lymphoma, Leukemia & Myeloma Congress in New York, and we confirmed a complete metabolic response in a heavily pretreated diffuse large B-cell patient who has remained cancer-free since we initially reported this result.

LP-284 benefits from composition of matter patents through 2039 across major global markets, and also, of course, the Orphan Drug Designation marks a. We continue to explore LP-284 beyond lymphoma, including as a potential therapeutic for autoimmune disorders such as lupus and SLE, where our preclinical data have showed significant potency in reducing clonal B-cells, actually CD19 and CD20 positive B-cells. This work could dramatically expand the commercial opportunity for this asset. We're beginning active dialogue to look and seek partners for this unique drug on the back of the compelling phase I data that's being put together and the responses that we're beginning to see. Now, let me shift to what I believe is becoming an increasingly important value driver for us and one that's more commercial.

RADR AI platform and its commercial opportunities independent of our drug programs. RADR integrates 200 billion-300 billion-plus oncology-focused data points, hundreds of advanced machine learning algorithms, and prediction success validated in actual clinical trials, not only for ourselves, but also for our partners. In early 2026, we initiated a AI Center of Excellence in India to help us grow, industrialize, and focus more on the RADR platform and withZeta.ai, giving us the ability to develop capabilities and features around the clock. We're beginning to recruit world-class ML talent and also give us additional scalability to support additional biopharma partnerships and feature development. We also continue to lead with BBB. BBB, which holds five of the top eleven positions in the Therapeutics Data Commons, also has been enhanced significantly over the last month or two.

We also are beginning now to commercialize our LBx-AI, which is our liquid biopsy AI. We've highlighted in our results the amount of money we've put into all our programs. Last year, we spent about $1 million across our AI technologies and platforms, and we're also, at the same time, able to develop what we believe is another key aspect for the future of AI-driven drug development. We're at an inflection point with withZeta.ai because it's not only inflection point because the system has now been launched to multiple demo partners, but it's really how science itself will be conducted. Agentic AI systems that reason, collaborate, and act autonomously, these are poised to become the standard infrastructure for drug discovery and scientific R&D. This is not a question of if, but when.

Lantern, through withZeta, intends to be the standard-bearer for this kind of shift, especially in rare cancers. Now think about how most people use AI in drug development today. They ask a single model a question, they get an answer, they typically do it in concert with a series of engineers and computational biologists, and it's really almost a one-off event. They may ask it in parallel, they may ask it several times. They may develop tools to look at the same question. With withZeta, you're doing it in natural language, and you're getting the facility of doing it as an orchestra, a multi-agent-agentic architecture, where specialized tools trained on literature synthesis, pathway analysis, clinical trial design, biomarker identification, molecular feature assessment, novel chemistry generation, collaborate, challenge assumptions, and cross-validate findings, all in real time before delivering hardened insights.

Many of you have been able to see this in person and actually see how we've been able to go from ideas to insights to actually potentially powerful new medicinal concepts in under an hour. Now, the true power is not in any single agent, but in their intelligent orchestration, a true AI co-scientist, and we've built that for helping to conquer rare cancers. This approach fundamentally inverts the traditional drug development paradigm. Before a single experiment is run, withZeta can rigorously stress test hypotheses through computational analysis and recursive reasoning, interrogating literature, modeling pathways, analyzing historical trial data, feeding on your own private, unique insights and data, evaluating biomarker strategies, stress-testing medicinal concepts, looking at molecules against known patient populations, and then only advancing the most hardened of the ideas.

By reducing failed experiments by 80% or 90%, we can allocate precious R&D resources and time to the most promising opportunities and do it faster. We can test dozens of hypotheses in parallel while a lab team would still be designing the first experiment. This platform also creates something fundamentally new, a persistent interactive organizational memory. Every interaction, every insight, every hypothesis tested is stored and instantly queryable. You generate knowledge graphs. It's like having your own entire scientific advisory group of experts, your full research team, and comprehensive access to questions and answers available 24 hours a day, seven days a week for any question in your domain. This is the future of scientific R&D, and it's already arriving now.

Since late 2025, withZeta has been an active demo in beta testing with over 25 biotech companies, cancer research centers, biopharma consultants, and even some CROs and investment banks, where we're generating significant early engagement that validates both demand and differentiation. We've designed withZeta with a multi-tiered commercial architecture that serves the entire drug development ecosystem. At the foundation, we'll have an accessible academic tier that brings early career researchers and university teams into the platform, and also individual subscriptions, institutional licenses, and they'll continue to help validate the platform and create the network effect, which makes withZeta increasingly valuable.

We'll have a professional tier that serves emerging biotech and mid-size developers through usage-based licensing, and then we'll also have an enterprise level for large pharma, where they can deploy in their own private clouds and also add to their proprietary knowledge graphs and deepen their internal data integration, and perhaps even deploy customized ontologies and use it for unique configurations. This will be a multi-tiered commercial architecture, and we believe it can also be used over time in multiple other disease areas beyond cancer. The beauty of this model is the natural progression researchers discover with Zeta in an academic setting, and they'll carry that experience as they continue deployment.

At every level, the platform gets smarter as more users and data flow through the system, and we believe that this global rare disease and rare cancers therapeutic market is projected to exceed about $300 billion by 2028. The broader AI-enabled drug discovery market represents, we believe, an additional $20 billion-$50 billion long-term opportunity for withZeta and our multi-agentic AI architecture. Our longer-term plan is to scale withZeta beyond rare cancers and into other complex therapeutic categories, each presenting the same fundamental problems of fragmented knowledge, slow experimental cycles, expensive failures. We believe this represents a potential near-term market opportunity of $20 billion-$50 billion, and that withZeta.ai is our first agentic commercial product designed to capture a meaningful share of that.

When you connect the dots, clinically validated RADR, commercially ready AI modules, and a multi-tiered revenue model, you see a business model that extends well beyond our pipeline. We believe our AI tools and services represent several hundred million dollars in standalone market potential, and that's a powerful complement to our drug development strategy. Now I'll turn the call over to David Margrave to discuss our financials and our other key metrics. David?

Thank you, Panna, and good afternoon, everyone. I'll now share some financial highlights from our fourth quarter and full year ended December 31, 2025. I'll start with a review of the fourth quarter. Our general and administrative expenses were approximately $1.5 million for the fourth quarter of 2025, compared to approximately $1.6 million in the prior year period. R&D expenses were approximately $2.7 million for the fourth quarter of 2025, compared to approximately $4.3 million in the fourth quarter of 2024. We recorded a net loss of approximately $4.1 million for the fourth quarter of 2025, or $0.36 per share, compared to a net loss of approximately $5.9 million or $0.54 per share for the fourth quarter of 2024.

For the full year of 2025, our R&D expenses were approximately $11.5 million, down from approximately $16.1 million in 2024. This decrease was primarily attributable to an approximate $4 million reduction in research studies and materials relating to the conduct and support of our clinical trials. Also, in part due to a $0.6 million decrease in payroll and compensation expenses and an $81,000 decrease in consulting expenses. Our general and administrative expenses for the full year 2025 were approximately $6.5 million, up slightly from approximately $6.1 million for 2024.

The increase was primarily attributable to increases in business development and investor relations expenditures of approximately $436,000, increases in patent costs of approximately $55,000, and an increase in corporate insurance of approximately $51,000. Our R&D expenses continue to exceed our G&A expenses by a strong margin, reflecting our focus on advancing our product candidates and pipeline. Net loss for the full year 2025 was approximately $17.1 million, or $1.57 per share, compared to approximately $20.8 million or $1.93 per share for 2024. Our loss from operations in the 2025 calendar year was partially offset by interest income and other income net, totaling approximately $0.9 million.

Our cash position, which includes cash equivalents and marketable securities, was approximately $10.1 million as of December 31, 2025. Based on our currently anticipated expenditures and capital commitments, we believe that our existing cash equivalents, and marketable securities as of the date of this call will enable us to fund our anticipated operating expenses and capital expenditure requirements until at least approximately late July 2026 to mid-September 2026. We will need to raise substantial additional funding in the near future, and we are actively evaluating and pursuing potential funding alternatives. As of December 31, 2025, we had 11,254,697 shares of common stock outstanding. No outstanding warrants to purchase shares, and outstanding options to purchase 1,296,126 shares.

These options, combined with our outstanding shares of common stock, give us a total fully diluted shares outstanding of approximately 12.6 million shares as of December 31, 2025. I'll now turn the call back over to Panna for an update on some of our development programs. Panna?

Thanks, 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 molecules into clinical trials with teams, costs, and efficiency that are almost unheard of in oncology biotech. Even that, we're actually seeing massive year-over-year improvements in our spend and in the output that we're seeing. During 2025, we achieved our goal of integrating generative AI to transform our platform into a system of autonomous agentic co-scientists and put together a model that we believe can be the future for how scientists create value. Looking ahead, how do we expect to see value creation catalysts? We have a Type C meeting coming up with the FDA on focusing enrollment in the HARMONIC trial on EGFR exon 21 L858R patients.

These are patients that do very poorly, and we've seen some meaningful improvement as a result of being dosed with our drug in combination with the chemo doublet. We've also seen the same in extending LP-300 treatment cycles, and we believe the current environment, because of the changes in standard of care, really require converting the current design to a single-arm Simon's 2-stage design. We'll have some data around the L858R patient population in the near future. Our planned investigator-sponsored trial with LP-300 in combination with osimertinib in chemo in front line with specific driver mutations is also advancing. We also have planned initiation of an LP-184 trial in bladder cancer in Denmark, which is paid for by the Danish government and the Danish Cancer Society.

We expect to start that for PTGR1 overexpressing bladder cancers, the DNA damage repair mutations. We also have planned initiation, again, subject to funding, of our LP-184 phase I-B/II in TNBC and in CNS cancers as well. Additionally, we'll have a major launch of our withZeta platform at AACR coming up, next month, and we'll be converting a lot of beta engagements to commercial partnerships and actually also launch the full multi-tiered subscription offering. We'll also be pursuing additional funding, including potential grant revenue, to fund planned operations and clinical advancement of our precision oncology trials. We're not just building better tools for ourselves. We're fundamentally reimagining what's possible in precision oncology and building tools that the entire community can actually use.

As we continue this journey, our agentic RADR 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 drug discovery forward through autonomous continuous learning and insights that can be tested in labs and deployed into the clinic and for patients. The golden age of AI in medicine isn't just beginning, it's accelerating exponentially. We've seen a lot of activity in the past four to six months. The intelligent always-on symphony is actually here. Cancer patients, especially rare cancer patients, can't wait another 50 years for the typical 50 years of progress we've seen. We believe that this next 50 years of progress can happen in the next 5 years.

This is something we believe very strongly, that AI is going to accelerate the development and the use of knowledge in a way that we haven't seen in medicine. As we advance into 2026, we're laser-focused on executing our dual engine strategy, advancing our clinical assets through key inflection points, and then out-licensing or partnering them while simultaneously scaling our AI platform for commercial deployment. Each clinical milestone validates our AI platform's predictive power while every platform enhancement accelerates our pipeline and creates new partnership opportunities. Also, now withZeta.ai, we believe we're setting the standard for how multi-agentic tools and AI systems can be used in drug development, and we're bringing that into the commercial setting, and we see multiple paths to create value using that platform. We're not just building better tools.

We believe we're fundamentally reimagining what's possible in the timeline and capabilities of precision oncology, and we're building it to be the standard that hopefully the rest of the industry also follows. I wanna thank our exceptional team, our partners, and our shareholders for your continued support, and also our team internally for helping put today's call together. Thank you, and I hope that we can continue improving outcomes for cancer patients while also transforming the economics of drug development. If you'd like to ask any questions, you can do so in one of two ways. You can type your question using the QA tool, and we'll get back to you shortly. Or you can send us an email to investor@lanternpharma, and we'll get back to you with any questions that you might have. Thank you, everyone, for your time this afternoon.

Thank you very much.

Good morning, and welcome to our third quarter 2025 earnings call. As a reminder, this call is being recorded. A webcast replay of today's conference call will be available on our website at lanternpharma.com shortly after the call. We issued a press release before the market opened today, summarizing our financial results and progress across the company for the third quarter ended September 30, 2025. A copy of this release is available through our website at lanternpharma.com, where you will also find a link to the slides management will be referencing on today's call. We would like to remind everyone that remarks about future expectations, performance, estimates and prospects constitute forward-looking statements for purposes of safe harbor provisions under the Private Securities Litigation Reform Act of 1995. Lantern Pharma cautions that these forward-looking statements are subject to risks and uncertainties that may cause actual results to differ materially from those anticipated. A number of factors could cause actual results to differ materially from those indicated by forward-looking statements, including results of clinical trials and the impact of competition. Additional information concerning factors that could cause actual results to differ materially from those in the forward-looking statements can be found in our annual report on Form 10-K for the year ended December 31, 2024, which is on file with the SEC and available on our website. Forward-looking statements made on this conference call are as of today, November 13, 2025, and Lantern Pharma does not intend to update any of these forward-looking statements to reflect events 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's CEO, Panna Sharma; and CFO, David Margrave. Panna will start things off with introductions and an overview of Lantern's strategy and business model and highlight recent achievements in our operations, after which David will discuss our financial results. This will be followed by some concluding comments from Panna, and then we'll open the call for Q&A. I'd now like to turn the call over to Panna Sharma, President and CEO of Lantern Pharma. Panna, please go ahead.

Good morning, everyone, and thank thank you for joining us to hear about our third quarter 2025 results and corporate progress. As many of you have heard me say in the past, computational and AI-driven approaches are increasing their presence and usage at both large and emerging pharma companies for all facets of drug discovery and development. Lantern's leadership in the innovative, efficient and pragmatic use of AI and machine learning to transform the process of developing precision oncology therapies should yield significant returns for investors and for patients as our industry matures and adopts an AI-centric data-first approach to drug development. This past quarter has been transformative in many respects for Lantern Pharma, a quarter where we have met many clinical, regulatory and validation milestones. And we have also significantly advanced the commercial availability and launch of our AI modules. The third quarter of 2025 represents a pivotal inflection point for Lantern Pharma. We've made significant advancements across our clinical stage portfolio, while simultaneously expanding the capabilities of our proprietary AI platform, RADR. And we've also set up the future of our CNS-focused subsidiary, Starlight Therapeutics. These achievements position us well for multiple value-creating catalysts in the coming quarters and years. Let me share with you some of the more notable achievements this past quarter. Let me start with what I believe is our most significant milestone to date clinically. Our LP-184 Phase Ia clinical trial successfully achieved all primary endpoints, demonstrating a 48% clinical benefit rate in evaluable cancer patients who received doses at or above the therapeutic threshold. What's particularly exciting is that we observed marked tumor reductions in patients harboring DNA damage repair mutations, specifically in CHK2, ATM, and STK11/KEAP1 genes. This validates our AI-driven precision medicine approach and the hypothesis of synthetic lethality and DNA damage repair that guided this program from the start. On the regulatory front, we completed a productive FDA Type C meeting for our subsidiary, Starlight Therapeutics, a company is focused entirely on CNS cancers. The agency provided clear guidance and pathway clarity for our planned pediatric CNS cancer trial targeting an ultra-rare brain cancer, ATRT. Importantly, the FDA confirmed our strategy to combine LP-184, which we will call STAR-001 in this indication with spironolactone based on our preclinical synergy data. We also made important progress across our broader pipeline. Preliminary Phase II data from our LP-300 HARMONIC trial were presented at the 66th Annual Meeting of the Japan Lung Cancer Society. We're planning a more comprehensive data update via webinar this December. For LP-284, our non-Hodgkin's lymphoma program, we showcased clinical data at the 25th Annual Lymphoma, Leukemia and Myeloma Congress. The presentation generated interest from both biopharma companies and clinical investigators, and we've initiated several discussions around combination therapy opportunities. Building on the Phase Ia results from LP-184, we're now positioned to advance LP-184 into multiple targeted Phase Ib, Phase II trials. Our precision biomarker-driven strategy will focus on 4 high-value indications, triple-negative breast cancer, non-small cell lung cancer with KEAP1 or STK mutations, bladder cancer with DNA repair deficiencies and first recurrent GBM. Collectively, these indications represent a combined annual market potential exceeding $7 billion. To provide additional insight into the LP-184 data and our development plans, we're hosting a KOL-led scientific webinar on November 20 at 4:30 Eastern. Dr. Igor Astsaturov from Fox Chase Cancer Center will join us to discuss the clinical results and what they mean for the future of this program. Beyond our clinical programs, we demonstrated the commercial readiness of our RADR AI platform at the inaugural AI for Biology and Medicine Symposium. We showcased several platform modules as deployable, highly scalable web accessible AI tools that can be licensed to biopharma partners and research centers. It's an important step in our strategy to monetize the technology that powers our drug discovery efforts. Finally, I want to emphasize our continued commitment to disciplined capital management. As of September 30, we had approximately $12.4 million in cash, cash equivalents and marketable securities. Based on our current operating plans, we expect this provides runway into approximately the third quarter of 2026. Before we turn to the financials, let me provide some color and details around our programs, both our drug programs and our growing program of AI modules, which we believe have the market potential of several hundred million on their own as AI tools and services. First, some context on the Phase Ia trial. This is a first-in-human study that enrolled 63 patients, a fairly large number given that we started at a very low dose and escalated upwards. This was in advanced solid tumors who had exhausted all standard treatment options, which is fairly normal for Phase I studies. These are heavily pretreated cancers, oftentimes in very difficult to treat tumors. The trial, which you can find on clinicaltrials.gov as NCT05933265, successfully met all of its primary endpoints. The headline number that I want you to focus on is this. We observed clinical benefit with 48% of evaluable patients who were treated at or above the therapeutic dose threshold. In a Phase Ia trial in heavily pretreated patients with advanced disease, that's a unique and promising signal of activity. But what's even more compelling is where we saw that activity. The data validated our core hypothesis about synthetic lethality. Patients whose tumors harbor specific DNA damage repair mutations, particularly in CHEK2, ATM and also STK/KEAP1 and actually also BRCA showed marked tumor reductions. This is what exactly what our RADR platform predicted well before starting this trial. And seeing it play out in actual patients is tremendously validating, but also very uplifting for our team where we can see how AI is being used for good and having a real-world impact on improving and changing outcomes. For us, this also gives us a very clear safety standpoint. LP-184 demonstrated a favorable profile with minimal dose-limiting toxicities. This is critical because it gives us flexibility. We can now pursue both monotherapy approaches and combinations with agents that we have identified as synergistic such as PARP inhibitors and immunotherapy, also spironolactone. Both -- these all have been predicted through our AI platform, again, as I note, before the trials even began. Let me give you a few clinical examples that really illustrate the potential here. In recurrent GBM, one of the most aggressive in treatment-resistant cancers, 2 out of 16 patients showed disease stabilization despite prior exposure to multiple therapies such as TMZ, lomustine and radiation. In GBM, as you will learn during our webinar on the 20th, we have the flexibility to modulate and enhance the efficacy of LP-184 by a factor of 3 to 6x, a potentially game-changing improvement. Even more encouraging, 2 patients at a dose level 10 have now maintained disease control for over 8 months and remain on treatment today. This is much more durable than has been expected for most Phase I studies. We also saw durable clinical benefit in other notoriously difficult tumor types, gastrointestinal stromal tumors and thymic carcinoma. These aren't common cancers, but they're devastating when they occur and options are extremely limited. Our work in these rare cancers has also encouraged us to double down on our desire to transform the world of rare cancers and develop an open access tool for rare cancer drug development, codenamed withZeta, which I'll talk about a little later this morning. Transitioning to clinical expansion. So the obvious question is this, what do we do with these results? And this is where our AI-driven development strategy really shines and demonstrates its value. Rather than pursuing a traditional broad Phase II basket type trial, we're taking a precision medicine approach. We're positioning to launch in 4 targeted Phase Ib, Phase II trials. Each one focused on a specific biomarker-defined patient population, where LP-184 has the highest probability of success and the best synergy agent for that particular tumor indication. One of these trials in Denmark in recurrent advanced bladder cancer is an investigator-led study. We have made this molecule into a portfolio of opportunities using data and precision oncology approaches. So let me walk through these quickly. The first one is in triple-negative breast cancer. It's our largest market opportunity, almost $4 billion. We're pursuing 2 parallel approaches, one in monotherapy with DNA repair gene mutations and a combination study with a PARP inhibitor, olaparib, specifically in BRCA-mutated patients. We've already received FDA Fast Track designation, which will expedite our development time line. We expect to enroll approximately 60 patients across both arms upon full enrollment. Second, non-small cell lung cancer with KEAP1 or STK11 mutations. This is a genetically defined subset of lung cancer who typically have very poor responses to immunotherapy. We're combining LP-184 with nivolumab and ipilimumab, 2 checkpoint inhibitors in patients with low PD-L1 expression. This represents, we believe, just in the U.S., close to $2 billion and probably closer to $3-plus billion globally. Again, we have an FDA Fast Track designation submission in process, and this trial will enroll approximately 34 patients. Third, an investigator-led trial in bladder cancer, recurrent advanced bladder cancer. This is being led by Dr. Pappot at Rigshospitalet in Denmark. It's focused on patients with advanced urothelial carcinoma who have specific markers indicating DNA repair deficiency. This represents, we believe, about a $500 million-plus global market opportunity, and we expect to enroll about 39 patients. Finally, first recurrent GBM, which we're pursuing through Starlight Therapeutics. Here, we're combining LP-184, which we will call STAR-001 and CNS indications with spironolactone. This combination showed synergistic activity in our preclinical models. We have both FDA Fast Track and Orphan Drug Designation for this indication. This trial will use a Simon 2-stage design with 2 separate arms based on IDH mutation status. We expect to enroll about 38 to 40 patients and represents what we believe is about $1 billion in U.S. market and probably closer to $2 billion globally. When you add up these indications, they represent a combined market opportunity exceeding $7 billion. And critically, each trial is designed with biomarker-driven enrollment criteria that increase our probability of success. In fact, as you've probably heard me say in the past, biomarker-driven cancer trials increased the success by 4 to 12x. Now rather than pursuing broad basket-like development, we're taking a very directed approach investing our resources exclusively in patient populations where the Phase I data and our AI-driven RADR insights predict meaningful clinical benefit and where there is real commercial opportunity and patient need. This is precision oncology at its best, using AI to identify the right patients in the right indications with the right combination drugs. And it all flows directly from what we learned in the Phase Ia trial, which was also heavily supported and predicted by the in silico AI work of our team and with multiple publications prior to that. Now let me turn to our LP-300 program and the HARMONIC trial, which addresses a significant growing need in lung cancer, lung cancer and never smokers that have progressed after treatment with TKIs. This is an important distinction. In Asia, never smokers represent 33% to 40% of all cases compared to only about 15% to 16% in the U.S. and Europe. This demographic reason is one of the reasons why we expanded this trial into Japan and Taiwan. It gives us access to the patient population, and it gives access to pharmas who want to develop therapies for this population. The market opportunity here is substantial globally, approaching $4 billion annually, and there are no current therapies approved for this patient population. But it is a space that more companies are interested in and are developing interested -- and are developing interest and are trying to approach it with various targeted combination opportunities. There's a real white space here that we're going after and the potential even to get to an earlier line of treatment. We completed enrollment in Japan this past quarter at 5 clinical sites, and we presented data at the 66th Annual Meeting in the Japan Lung Cancer Society, which was presented by Dr. Jonathan Dowell from UT Southwest. Now the preliminary data from this trial, which we've already shared publicly, showed 86% clinical benefit rate, which is very encouraging. And we have one patient who has demonstrated a durable complete response with survival continuing for nearly 2 years, a remarkable outcome. I think we have another patient, which is now approaching a year. Now we're planning a more comprehensive webinar in December before the year closes where we'll present additional patient follow-up data and clinical readouts from both the Asian and U.S. cohort. This will give us an opportunity to discuss the data in much greater depth and provide regulatory strategy insight and positioning moving forward. I should also mention that during the third quarter, we made a strategic change in our clinical operations in Asia. We transitioned our CRO services in Taiwan with a specific focus on cost reduction and operational efficiency. In Japan, we supplemented our team by bringing more activity in-house. This is part of a broader commitment to disciplined capital management and efficiency while maintaining the quality and integrity of the trial. The strategic positioning of Harmonic also opens doors for potential regional partnerships in Asia and co-development opportunities where the never smoker population is most prevalent. Now let me turn to LP-284, a program targeting recurrent non-Hodgkin's lymphoma, which has generated interest from clinical communities and also from biopharma to approach combination approaches. This is our first in-human trial for LP-284, which we expect to enroll about 30 to 35 patients with aggressive recurrent non-Hodgkin's lymphoma, including mantle cell and high-grade B-cell, where we have orphan indications for both. This represents a global market opportunity of about $3 billion and with patients who have failed multiple prior lines of therapy and have very limited options. In fact, in October, we presented clinical data from this ongoing trial at the 25th Annual Lymphoma Leukemia Myeloma Congress in New York City. The cornerstone of that presentation was a heavily pretreated patient with aggressive grade 3 B-cell lymphoma, specifically DLBCL, who had exhausted standard therapies, and we saw a complete metabolic response with LP-284 as monotherapy after 2 doses, 2 cycles. This is exactly the kind of signal we're hoping to see and validates many of our preclinical hypothesis for this drug. It also validates the mechanistic insight, and we saw complete metabolic response and the lesions around the hips and spine completely went away. This patient has now remained cancer-free since we initially reported this result in July Q2 of this year. LP-284 has a novel mechanism of action. It demonstrates particular lethality in cells with DDR, a targetable vulnerability that's common in non-Hodgkin's lymphoma. This mechanistic differentiation is what's driving interest from partners. Now following this presentation, we've started discussions with investigators and companies around opportunities for combination therapy development with existing FDA-approved agents, post-immunotherapy treatment strategies and leveraging the 284 mechanism where current therapies are failing, especially in what's exciting indications beyond lymphoma. Based on preclinical data, we're evaluating 284 and rituximab as a potential alternative to cyclophosphamide and methotrexate in lupus, systemic lupus SLE. Our preclinical models showed that 284 reduced urinary microalbumin and kidney damage -- which is a key marker of kidney damage in lupus by approximately tenfold and depleted B cells by fourfold when combined with rituximab. We saw even greater B-cell depletion when both agents were used together. This suggests LP-284 could become a next-generation B-cell depleting therapy in a number of autoimmune diseases, which would dramatically expand the commercial opportunity for this asset. LP-284 also benefits from strong intellectual property protection. We have composition of matter patents granted in U.S., Europe, Japan, India and Mexico, providing exclusivity through at least 2039. The molecule, as I mentioned, also has Orphan Drug Designation in mantle cell and high-grade B-cell lymphomas. We're now focused on recruiting additional sites with a focus on non-Hodgkin's lymphoma and high-grade B-cell lymphomas. The momentum we're seeing with LP-284, both clinically and in terms of partner interest reinforces our view that this asset has significant opportunity, both stand-alone as a wholly owned program or as part of a strategic collaboration. And we're very open to those discussions, both again in combination in non-Hodgkin's or in other autoimmune categories. Now transitioning to our AI platform discussion. As I mentioned earlier, I want to shift gears and talk about what I believe is an increasingly important value driver for Lantern, our RADR AI platform and the commercial opportunities it represents independent of our drug development programs. For those less familiar with RADR, it's our proprietary AI and machine learning platform. And it's not just a tool we use internally. It's now a commercial asset with its own revenue potential, which is growing. The platform has demonstrated over 80% prediction success across multiple use cases, and now it's been validated in natural clinical trials through programs like LP-184, LP-284 and also with Actuate Therapeutics. In all cases, it's correctly predicted biomarker responses and in many cases, combination synergies before we've even actually enrolled a patient. We've developed 8 distinct AI-powered modules that address critical pain points in oncology drug development. And we've developed cases for these pain points, which we're now developing into modules for the broader drug development community. In October, we showcased the commercial readiness of 2 RADR modules at the inaugural AI Biology and Medicine Symposium. We demonstrated that our AI platform, PredictBBB achieves a 94% accuracy for BBB permeability prediction and can screen 200,000 molecular candidates in under a week. To put that in context, our algorithms currently hold 5 of the top 11 positions on the therapeutic data comments, and that's a best-in-class performance. We also presented our LBx-AI liquid biopsy platform, which has achieved 86% to 90% accuracy in predicting treatment response initially in non-small cell lung cancer, which will be very useful for us. And now we're extending it through collaborations with research centers into other indications as well. Both of these opportunities, we believe, are significant. Blood-brain barrier technology market alone is predicted to be close to $1 billion. And when you consider a very few percentage, 2% to 6% of the molecules actually cross the BBB, there is a need for better predictive tools, one that don't take weeks or months and end up destroying animals. So the need there is obvious and urgent. The interesting thing, PredictBBB is it also gives us access to a lot of other molecular characteristics of that compound, and we can predict a lot of other drug-like features that are important, both for drug manufacturing and also predicting potential drug activity once delivered internally. Now let me introduce Zeta. It's our multi-agentic AI platform for rare cancers. Very excited about this and what connects directly to our experience with both LP-184 and 284 in rare tumors like gastrointestinal and thymic carcinoma. It's our newest initiative. We're calling it withZeta. It's a multi-agentic co-scientist. Now here's the fundamental challenge. In rare cancer research and drug development, which often comes after molecule developed that often comes much later, the critical insights in rare cancers are scattered across disconnected data sources. A researcher or a clinician trying to understand treatment options for a patient with a rare sarcoma or a rare pediatric brain tumor has to manually search through clinical trial databases, PubMed genomic databases, drug interaction databases, molecular feature databases. It's fragmented, time-consuming and inevitably incomplete. For drug developers, this fragmentation slows discovery, increases cost and often means that promising connections between existing molecules or indications and rare cancer vulnerabilities are [Audio Gap]. What Zeta does is a multi-agentic AI system. Think of it as a co-scientist that addresses this problem head on or actually a series of co-scientists. We've integrated curated rare cancer databases and ontologies across over 500,000 clinical trials, 250,000 publications with over 1.2 million knowledge objects into an agentic large language model architecture that uses recursive reasoning loops to transform fragmented biomedical knowledge and insights into an interconnected investigational platform. And it interacts with you in plain English. So -- and it's an AI system that thinks like a scientist, connects dots across disparate data sources and can answer complex questions in minutes about rare cancers. These are things that would otherwise take researchers weeks or months to investigate manually. We'll dig into more of the details about Zeta in the coming days, and we'll have more information as -- but the key is that it will help you design and improve and optimize molecules that can target vulnerabilities or mechanisms across these hundreds of rare cancers. So you can ask questions to Zeta like what existing molecules with blood-brain barrier penetration have shown activity against mutations commonly found in a specific pediatric brain tumor and will search, reason and provide evidence-based answers with citations, and you'll be able to have it quickly pick potential combination regimens as well for that rare cancer benchmarked against successful and not successful trials across drug classes that you can help Zeta understand. And it can actually also predict potential efficacy in subtypes of that rare cancer and give you considerations that can then be taken to the lab. From an industry and business value perspective, withZeta delivers several things: Speed, smarter decision-making, novel discovery and potential for improved patient outcomes faster and most importantly, massive cost and time savings across the rare cancer drug development cycle. I'd like to think about withZeta strategically is that we're positioning Lantern as a unified team of AI co-scientists, always available, always updated for rare cancer research and drug development, a unified AI interface for complex scattered data and models that accelerates and improves novel therapy discovery and trial design. This is a tool that can shorten development timelines by months and years, particularly in rare cancers where that data is sparse and every delay means challenges and time and lives lost. By making Zeta available to researchers and clinicians over the next month, we'll establish Lantern as a central hub for rare cancer drug development and insights. This creates network effects, brings more users and data into our ecosystem and positions us as a trusted partner when those researchers need to take the next step, whether it's preclinical development, biomarker validation, clinical trial design or co-development. Now we believe our AI tools and services in the future can represent several hundred million dollars in stand-alone market potential and will attract a lot of interest in the broader big tech community, and but most importantly, lower the risks and costs associated with creating cancer drugs. And that's a very powerful complement to our drug development strategy. Now I'll turn over the call to our CFO, David Margrave, who will provide details on our financial results for the quarter.

Thank you, Panna, and good morning, everyone. I'll now share some financial highlights from our third quarter ended September 30, 2025. Our R&D expenses were approximately $2.4 million for the third quarter of '25, down from approximately $3.7 million for the third quarter of 2024. The decrease was primarily due to decreases in research study and materials expenses relating to the conduct and support of clinical trials as well as decreases in consulting expenses and in payroll and compensation expenses. Our general and administrative expenses were approximately $1.9 million for the third quarter of 2025 compared to approximately $1.5 million in the prior year period. The increase was primarily attributable to increases in business development and investor relations expenditures as well as increases in other professional fees and increases in patent costs. We recorded a net loss of approximately $4.2 million for the third quarter of 2025 or $0.39 per share compared to a net loss of approximately $4.5 million or $0.42 per share for the third quarter of 2024. Our cash position, which includes cash equivalents and marketable securities was approximately $12.4 million as of September 30, 2025. We believe our cash, cash equivalents and marketable securities on hand as of the date of this earnings call will enable us to fund our anticipated operating expenses and capital expenditure requirements into approximately Q3 2026. We will need substantial additional funding in the near future, and one of our key objectives is to pursue additional funding opportunities. In July of this year, we entered into an ATM sales agreement with ThinkEquity as sales agent, pursuant to which Lantern may offer and sell up to $15.53 million of its common stock from time to time in at-the-market offerings to or through our sales agent. During the quarter ended September 30, 2025, we sold 212,444 shares of common stock under the ATM for gross proceeds of approximately $989,000. Between October 1, 2025, and the date of this earnings call, we've sold an additional 144,204 shares of common stock under the ATM for gross proceeds of approximately $634,000. As of September 30, 2025, we had 11,040,219 shares of common stock outstanding with outstanding options to purchase 1,218,828 shares and no warrants outstanding. These outstanding options, combined with our outstanding shares of common stock, give us total fully diluted shares outstanding of approximately 12.26 million shares as of September 30. And I'll now cover some near-term milestones that we think will accelerate value for investors. And these are several value-creating catalysts that we see in the near future. In the immediate near term, in this November, and Panna talked about this earlier, and we're very excited about this discussion. Next week, November 20, at 4:30 p.m. Eastern, we're going to have a KOL-hosted scientific webinar on LP-184 Phase Ia details from the clinical study and clinical development strategy. And in December of this year, we'll be giving for LP-300, an interim patient follow-up and additional clinical data. And then also in this upcoming quarter, we'll be discussing continued commercial developments for the AI platform modules, including the multi-agentic system that Panna discussed about withZeta for rare cancer development. And I'll now turn things back to Panna for some closing remarks.

Thanks, David. As you know, we've had a number of catalysts and objectives that continue to '26, which you can see on the slide, but we'll be talking about those in follow-up meetings with investors as well. But as you can see, by integrating our capabilities in AI and bringing them to the public, we're not just building better tools. We're actually fundamentally reimagining what's possible in precision oncology, an era that I call the golden age of AI in medicine. As we advance into 2026, we're laser-focused on executing our dual engine strategy. We got really 2 powerful engines of the company. One is the ability to generate new molecules that are very precise and focused on very unique cancers. And the second engine is the engine of our AI platform that we're now ready to commercialize and make available. So we're advancing our clinical assets while simultaneously scaling our platform for commercial deployment. So I want to thank our exceptional team, our partners, our shareholders for their continued support. Together, we're lighting the way toward precision oncology solutions, solutions that can improve outcomes for cancer patients while very importantly, transforming the economics of drug development. With that, I'd like to open the call to questions and also thank our team for helping to prepare us for these calls and preparing the content.

So we've a question in about tracking toward an interim event analysis for LP-300 trial. At the December webinar, we do not believe we'll be at the 31 events, which is good news because that means that patients are coming off of the trial. So the positive news is that patients are on the trial longer, but we will report out data, clinical data and insights that have resulted. We expect 31 events right now, we're tracking to be sometime in early '26, which we think is actually a very positive news. We do expect to see the Denmark trial. There's a question for the Denmark trial. That has now been approved. IRBs are set. project manager has been assigned. We expect that to start sometime either in late December or early January at one site, which is investigator-led in Denmark. Another question is that we've guided for an IND submission for the pediatric CNS program. Yes, now that the FDA is kind of back in business and looking and renewing new INDs, we're already prepared to submit that, and I expect that submission to happen here in the next few weeks. In terms of when we anticipate initial patient dosing, hard to say. We're already beginning discussions with sites, but I expect that to be sometime in early '26. There's a question about the withZeta portion of our AI platform. We will have additional news next week on withZeta, which is very exciting. Like most software, we expect the early rollout to be interesting and bumpy. We'll learn a lot from it. We've already begun using it internally. And in fact, we'll talk about this next week, but we've got a number of really exciting programs that have already been designed and are now being tested as a result of withZeta. But it will be available as select demo to collaborators and select partners. And so December will be a lot of demo and learning and broader rollout throughout January and February and Q1. Next question is for 184. Yes, for the indications, we do plan on figuring out what is the best of those indications where we're getting the biggest impact and move that into larger scale trials ideally with partners. As I mentioned, [ Boris ], all those indications are very exciting indications, and we've had interest from pharma companies. Of course, they want to see some of the early Phase Ib, Phase II data, but all of those are potentially partnerable. Next question is Zeta. Yes, Zeta was initially developed as a culmination of our internal efforts to develop drugs initially 184 and 284 for rare cancers. We wanted to go after categories where there was no therapy approved, categories there was high need, categories where we thought the mechanism would work and could be exploited. As we did that and we gathered information about some of these cancers, we said, well, we can do it for all rare cancers. There's no tool out there. In fact, when we talk to other rare cancer experts, many of the cancers we're pursuing, it was scattered. Papers were hard to get, hard to get in front of experts, hard to get data. Trials were oftentimes took way too long and standards of care often changed or the best drug often changed. And we said, this is part of the frustration in these cancers, and that's why they take time or too much money. What if you could actually have one source and then train that source to think in the way that a drug developer thinks. So yes, it was an internal effort, and now it's going to be a front-facing natural language interface tool. And I'm happy to give you [ Boris ], if you'd like peek at it and even early demo, happy to provide that to you. Another great question on STAR-001 trial design for pediatric brain tumors. Yes, I do believe that the trial design allows for inclusion of other pediatric high-grade gliomas. Yes, we designed it to allow for that, including specifically diffuse midline gliomas. Okay. If there are no further questions. I want to thank everyone for joining and very importantly, for listening in this morning. We know it's a little past the market open. So I appreciate all of you staying online. Thank you very much for your time, and I appreciate everyone's effort and also more importantly, your support as Lantern Pharma continues to transform drug development in oncology.

Thanks a lot.