Qiao Juan

Artificial Intelligence (AI) is transforming the pharmaceutical lifecycle —from discovery to manufacturing and safety oversight. In discovery, AI accelerates target identification, molecular design, and repurposing (e.g., baricitinib; rentosertib), while the DSP-1181 experience highlights the risk of structural conservatism. In clinical development, AI supports patient stratification, digital-twin-informed design, and automated analysis, improving statistical power and operational speed. In manufacturing, predictive analytics, computer vision, and knowledge-graph-assisted documentation enhance quality and throughput. Pharmacovigilance benefits from natural language processing (NLP) — enabled signal detection and workflow automation. Emerging uses in antibody engineering and personalized therapy broaden its scope, but real-world benefit hinges on data quality, rigorous validation, transparency, and regulatory alignment (including real-world evidence).