Lantern Pharma (NASDAQ: LTRN), an AI-native precision oncology company, announced that the European Medicines Agency (EMA) has cleared an investigator-initiated Phase 1b/2 clinical trial evaluating its lead drug candidate LP-184 (zirdafulven) in patients with advanced or metastatic bladder cancer. The study, to be conducted at Rigshospitalet in Copenhagen, Denmark, will enroll up to 39 patients and prospectively select participants based on PTGR1 overexpression and DNA-damage-repair deficiency.
The trial will evaluate LP-184 in patients who have progressed on or are ineligible for current standard-of-care therapies. This development further advances Lantern's AI-driven precision oncology strategy through its proprietary RADR® platform. LP-184 is an acylfulvene compound that targets tumors with specific genetic vulnerabilities, and the biomarker-guided approach aims to identify patients most likely to benefit.
Bladder cancer remains a significant unmet medical need, with limited options for patients who fail first-line therapies. The EMA clearance allows Lantern to expand its clinical program into Europe, potentially accelerating patient recruitment and regulatory pathways. The trial's design, leveraging Lantern's AI capabilities, underscores the company's commitment to precision oncology.
Lantern's pipeline also includes LP-284, targeting hematologic and solid tumors, and LP-300, being evaluated in the HARMONIC Phase 2 trial for never-smoker lung adenocarcinoma. Additionally, LP-184 is being developed for pediatric CNS cancers through Starlight Therapeutics, Lantern's wholly owned CNS-focused subsidiary. The company's withZeta.ai platform, a multi-agentic AI co-scientist, is now commercially available, representing a new revenue stream.
This announcement is important as it validates Lantern's AI-driven approach to oncology drug development and expands the clinical evaluation of LP-184 into Europe. The biomarker-guided trial design could lead to more effective treatments for bladder cancer patients with limited options, and the use of AI for patient selection may serve as a model for future precision oncology trials.
