Overview
- AIFA reports 62% of pharma firms already deploy AI in R&D, with adoption projected to rise about 45% over five years and the market growing at over 40% annually to 2030.
- Deep-learning systems scan vast chemical, genetic and clinical datasets to identify targets and generate candidate molecules in hours; several AI-assisted drugs have reached advanced human trials, including rentosertib and Rec-994.
- Trial operations are being streamlined through tools such as TrialGPT for rapid patient matching and through virtual patient cohorts that simulate therapeutic scenarios to cut cost and failure risk.
- Efficiency gains cited by Capgemini include up to a 30% faster time-to-market, roughly 40% higher research productivity and about 25% lower engineering costs.
- Regulators are adjusting processes, with EMA launching an AI program, FDA testing algorithmic tools and AIFA piloting predictive analytics, even as concerns persist over black-box explainability, liability and data protection raised by AIFA president Robert Nisticò.