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Lantern Pharma Announces Establishing an A.I. Center of Excellence in India to Industrialize the RADR® Platform and Accelerate Global Development Opportunities with BioPharma Companies

LTRN
  • Lantern Pharma Inc. (NASDAQ: LTRN) announced the establishment of an A.I. Center of Excellence & Advanced Agentic Labs in Bengaluru, India.
  • The new center will focus on large-scale data engineering, refinement of ML-ready disease models, & integration with global biopharma partners.
  • This strategic initiative aims to transition Lantern from AI-enabled cancer discovery to industrializing capabilities for broader drug development at global scale.
  • The Bengaluru hub will serve as the global scale-up center providing expanded computational capacity, specialized talent, & follow-the-sun development cycles.
  • Lantern is initiating hiring for AI engineers, data scientists, & computational biologists, anticipating that expansion will be cash flow neutral to the Company.
  • The center will expand the proprietary RADR® AI platform which currently leverages hundreds of billions of oncology data points.
  • Lantern plans to accelerate development of specialized large language models (LLMs) & large quantitative models (LQMs) for molecular assessment & optimization.
  • Phase 1 of the deployment will industrialize AI-driven cancer drug development by scaling multi-agentic systems for oncology & rare cancers.
  • Phase 2 will expand RADR® applications into inflammation, immunology, & neurodegenerative diseases including lupus, rheumatoid arthritis, & Alzheimer's.
  • The company expects immediate tangible results while maintaining cash neutrality during Q1 2026.
  • Lantern will host an Investor & Analyst Day in New York City on January 22, 2026, at 4:00 PM ET to showcase the AI Center initiative & platform rollout.
  • The center will operate as a cloud-native environment with dedicated infrastructure for model training, validation, & rapid deployment.
  • Lantern aims to integrate under-represented patient populations & real-world clinical data to improve model generalizability across global therapeutic areas.