PharmaMar, a Madrid-based company focused on marine-derived oncology therapeutics, and Globant, a Buenos Aires-founded digital and AI services firm listed on the NYSE, announced a collaboration to deploy a multi-agent artificial intelligence framework across PharmaMar's research operations (announcement). The deal is structured as a technology services partnership rather than a traditional drug licensing agreement. No specific molecule is being licensed or co-developed. Globant is providing its Enterprise AI platform to help PharmaMar prioritize compound-indication combinations from its marine-derived compound portfolio in oncology.
Financial terms of the collaboration were not disclosed. The announcement contains no mention of upfront payments, milestone structures, royalty rates, equity components, or total deal value. The absence of such terms is consistent with the nature of the arrangement, which resembles a technology services engagement rather than a structured biopharma transaction with defined financial triggers tied to development or commercial events.
Deal context
The collaboration centers on Globant Enterprise AI, configured as a multi-agent AI system in which more than 20 specialized digital agents operate across preclinical, clinical, regulatory, and commercial functions within PharmaMar's research ecosystem. The system is designed to ingest and analyze large volumes of scientific literature, regulatory documents, and clinical data. In a pilot phase, the platform processed over 4,500 research documents to identify and rank the 10 most viable treatment-indication combinations from more than 8,000 possibilities. PharmaMar reported that the system reduced the time required for this analysis from weeks to hours and achieved over 90% accuracy in data retrieval tasks.
No specific drug candidate has been named as an output of the platform. PharmaMar's existing portfolio includes lurbinectedin, marketed as Zepzelca for small cell lung cancer, and other marine-derived compounds at various development stages. The AI system is intended to evaluate this portfolio broadly rather than advance a single asset. Future phases are expected to add autonomous hypothesis generation, real-time regulatory compliance checks, and automated scientific reporting.