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Lantern Pharma (LTRN) investor relations material
Lantern Pharma Investor Update summary
Complete event summary combining all related documents: earnings call transcript, report, and slide presentation.
Business and operational overview
Focuses on AI-driven development of precision oncology medicines, with three clinical-stage small molecules and a robust preclinical pipeline, including antibody drug conjugates.
Maintains a disciplined fiscal profile with a quarterly burn rate of $4.5M, cash runway into 2026, no debt, and approximately 12M fully diluted shares.
Holds 11 FDA designations (5 orphan, 4 rare pediatric, 2 fast track) and about 140 issued and pending patents covering composition, methods, and AI platform innovations.
Business model centers on early innovation, rapid execution, and out-licensing assets to larger pharma partners.
Clinical pipeline and trial updates
LP-300 in Phase II targets never-smoker non-small cell lung cancer, a $4–5B global market, with strong early data and expansion into Japan and Taiwan.
LP-184 completed Phase I enrollment (65 patients) across multiple solid tumors; moving to Phase Ib/II in TNBC, STK11/KEAP1-mutated lung cancer, and bladder cancer.
LP-284, a sister drug to LP-184, is in trials for B-cell lymphomas, showing a complete metabolic response in a patient who failed multiple prior therapies.
Combination therapy strategies are a major focus, with promising preclinical synergy between LP-184 and PARP inhibitors in TNBC and checkpoint inhibitors in lung cancer.
AI platform and technology strategy
AI platform (RADAR) is central to drug discovery, enabling rapid, iterative modeling and prediction for molecule selection, trial design, and combination strategies.
Public release of PredictBBB.ai module allows users to predict blood-brain barrier penetrability with high accuracy, supporting both internal and external collaborations.
Future modules will expand predictive capabilities to additional molecular properties, aiming to disrupt traditional drug development timelines and costs.
AI platform is being commercialized via a freemium model, with free trials and paid tokens or collaborations for extended use.
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