How can life sciences organizations connect AI, data, computational biology and laboratory science to make preclinical research faster, smarter and more confidence-driven?

Preclinical research is entering a new era. Advances in bioinformatics, computational biology and AI can help identify stronger targets, reduce unnecessary experiments, anticipate safety risks earlier and enable better-informed go/no-go decisions. Yet the real opportunity lies not in individual technologies, but in connecting them into a trusted scientific ecosystem.

Drawing on Capgemini’s life sciences experience and insights from the Capgemini Research Institute’s 2026 global survey of 500 senior biopharma executives, this point of view explores how scientific data, AI and agentic intelligence, computational models and connected laboratories can create an integrated preclinical research engine. It examines how autonomous scientific workflows can support researchers while keeping scientists in control, and how modular platforms and federated operating models can enable scalable adoption.