The Potential of Generative AI in Drug Development
Deepak Gupta, R. Sudhakar, Sofiya S. Mujawar, Rita Kadam, Vivek Patil, Anurag Kumar, Prashant Ahire, Kapil Gupta · 2025
Drug development is a complex, time-consuming, and expensive process with high failure rates. Traditional approaches face significant challenges, including lengthy timelines (10-15 years), astronomical costs (exceeding $2.5 billion per successful drug), and high attrition rates (>90%). Generative artificial intelligence (AI) represents a paradigm shift in this field, offering novel approaches to address these longstanding challenges. This chapter explores the transformative potential of generative AI across the drug development pipeline, from target identification to clinical trial design. Various AI architectures and their pharmaceutical applications are examined, breakthrough case studies are analyzed, current challenges are addressed, and future directions are discussed that may revolutionize pharmaceutical research and development, providing stakeholders with the knowledge necessary to navigate the rapidly evolving landscape of AI-driven drug development.