Talk Bio

Owkin CEO Thomas Clozel highlights five key areas where AI can address core challenges in drug R&D, focusing on medicine discovery and development. 6 AI accelerates clinical development more than discovery due to better data availability in later stages, with tools like AlphaFold3 aiding structure determination and experimental science. 1 Traditional drug development costs $2.6 billion with 90% failure rate; AI improves target identification, molecule design, clinical trial recruitment (30-50% faster), and extends to manufacturing and regulatory processes. 2 AI enhances preclinical research via protein structure prediction and virtual compound screening, while revolutionizing patient recruitment using NLP on health records. 3 AI market in pharma projected to grow from $4B to $25.7B by 2030, aiding formulation challenges like solubility and bioavailability with data-driven insights. 4 Dozens of AI-driven drug candidates have entered trials after $18–30B investment by 2024,...