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.
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