SupplyLogic

Generative AI Use Cases in research-based biopharma are moving beyond isolated copilots and into the scientific and quality systems that govern how molecules become medicines. Over the next three to five years, the important change will not be a single dramatic breakthrough. It will be the gradual connection of target biology, medicinal chemistry, clinical evidence, safety surveillance, regulatory documentation, and manufacturing knowledge through models that can propose, summarize, simulate, and explain. For companies operating at the scale of Pfizer, Roche, or Novartis, that shift could compress decision cycles while preserving the traceability expected in GxP environments. The most consequential Generative AI Use Cases will therefore be judged by more than model fluency. They must improve a defined scientific or operational decision, remain grounded in controlled evidence, and fit established accountabilities. A generated protocol synopsis, for example, is useful only when clinical...