Artificial Intelligence for Drug Product Lifecycle Applications 1st Edition

Artificial Intelligence for Drug Product Lifecycle Applications, 1st Edition by Alberto Pais, Carla Vitorino, Sandra Nunes and Tânia Cova offers a clear, practical gateway to applying AI across the pharmaceutical product lifecycle. Whether you manage R&D, manufacturing, regulatory affairs or quality systems, this book immediately captures attention with real-world relevance and expert authorship.

Dive into thoughtfully structured chapters that translate machine learning, predictive analytics and digital-twin concepts into actionable strategies for formulation, process development, stability prediction, packaging and post-marketing surveillance. The authors bridge theory and practice, showing how AI can improve risk-based decision making, accelerate time-to-market and strengthen compliance with global regulatory frameworks such as FDA and EMA.

Readers will find compelling case studies, workflow examples and implementation roadmaps that make complex technologies accessible without sacrificing scientific rigor. Practical guidance on data governance, model validation and integration with Quality-by-Design (QbD) and Process Analytical Technology (PAT) initiatives helps multidisciplinary teams move from pilots to robust production deployments.

Ideal for pharmaceutical scientists, data scientists, quality managers and regulatory professionals, this volume equips you to lead AI-driven transformation in your organization. Clear language, industry-focused examples and forward-looking perspectives make it a valuable reference for global teams aiming to improve efficiency, reliability and patient safety.

Add this authoritative resource to your professional library to stay ahead in the rapidly evolving intersection of AI and pharmaceuticals—an essential read for anyone shaping the future of drug product development and lifecycle management.

Note: eBooks do not include supplementary materials such as CDs, access codes, etc.