Pharmaceuticals in the AI Age

Artificial intelligence is transforming drug discovery by addressing key challenges in cost, speed, and success rates. This chapter examines the application of artificial intelligence technologies, including machine learning, deep learning, and generative models, across the drug development pipeline, from target identification and hit discovery to lead optimization and clinical trials. Use cases include virtual screening, de novo molecule generation, ADMET prediction, and patient stratification. Despite rapid progress, challenges persist in data quality, model interpretability, regulation, and ethical concerns such as dual-use risks. Future directions, including hybrid artificial intelligence-quantum systems, federated learning, and digital twins, promise to further personalize and optimize drug development. The chapter highlights the potential of artificial intelligence to drive innovation while emphasizing responsible implementation.