The McKinsey Global Institute projects generative AI could create up to

in annual global value for the pharmaceutical industry

This fourth wave can be broken down into five core pillars:

1. AI-native research and drug discovery Key technologies: Foundation models, generative AI, multimodal AI, lab automation and digital biology.

Where the third wave saw AI applied to individual discovery tasks in isolation, it is now becoming embedded across the entire process, including target identification and molecule design to biomarker discovery and candidate optimisation. The key shift is companies pairing generative AI with laboratory automation to create autonomous or semi-autonomous discovery workflows, closing the loop between AI-generated hypotheses and physical experimentation.

2. Intelligent clinical development Key technologies: AI trial design, real-world evidence, digital biomarkers, remote monitoring and predictive analytics.

Clinical development has become genuinely data-driven rather than data-supported. AI now shapes protocol design, identifies suitable trial sites and participants, predicts recruitment challenges and analyses real-world evidence at scale.

80 September 2026