THE COMPLETE GUIDE TO MACHINE LEARNING AND DEEP LEARNING IN DRUG DISCOVERY

Artificial Intelligence is transforming how we discover, develop, and deliver medicines. Using Machine Learning in Drug Discovery and Development offers a powerful and practical roadmap for pharmaceutical and biotech professionals to navigate this transformation with confidence.

Authored by a globally recognized expert with over 25 years of experience in AI, machine learning, and drug development, this book blends scientific depth with real-world insight. It guides readers through every stage of the drug lifecycle — from molecular discovery and lead optimization to clinical trials, regulatory decision-making, and post-launch monitoring — showing how machine learning accelerates innovation while upholding scientific and ethical integrity.

Through clear explanations, relatable analogies, and thought-provoking examples, the book transforms complex algorithms into intuitive concepts. Each chapter bridges data science and pharmacology, preparing readers to apply AI techniques responsibly and effectively in real-world scenarios.

Perfect for scientists, data professionals, and life science leaders alike, this is more than a guide — it’s a blueprint for the intelligent, ethical, and collaborative future of pharmaceutical innovation.