DATA SCIENCE IN PHARMACEUTICAL DEVELOPMENT (HB 2025). Este artículo no está disponible.DATA SCIENCE IN PHARMACEUTICAL DEVELOPMENT (HB 2025)

This book is an indispensable guide for anyone looking to understand how AI, machine learning, and data science are revolutionizing drug discovery, development, and delivery, offering practical insights and addressing crucial real-world applications and considerations.

Data Science in Pharmaceutical Development offers a comprehensive and forward-looking exploration of how artificial intelligence, machine learning, and data science are reshaping the pharmaceutical landscape. From the earliest stages of drug discovery to advanced delivery systems and post-market surveillance, this volume bridges the gap between innovation and real-world application. Practical examples and case studies bring to life the transformative potential of AI-powered tools in accelerating research, enhancing patient outcomes, and improving efficiency throughout the pharmaceutical product lifecycle.

Designed for researchers, industry professionals, and students alike, this book not only showcases cutting-edge technologies but also addresses the ethical, legal, and regulatory considerations critical to their implementation. Whether you’re navigating the complexities of clinical trials, optimizing supply chains, or seeking to understand the implications of smart drug delivery systems, this book is an indispensable guide to the future of medicine and healthcare innovation.

Readers will find the book:

• Explores the role of AI, machine learning, and data science across the entire pharmaceutical pipeline―from drug discovery and clinical trials to smart drug delivery systems;
• Rich with real-world case studies and practical examples, connecting theory to implementation in modern pharmaceutical research and development;
• Introduces advanced topics like predictive modeling, personalized medicine, IoT, pharmacovigilance, and nanotechnology-enabled drug delivery;
• Highlights emerging trends, ethical considerations, and the regulatory framework surrounding AI in healthcare.

Audience

Research scholars, pharmacy students, pharmaceutical process engineers, and pharmacy professionals in the pharmaceutical and biopharmaceutical industry who are working in drug discovery, chemical biology, computational chemistry, medicinal chemistry, and bioinformatics.

Vivek P. Chavda, PhD is an assistant professor in the Department of Pharmaceutics and Pharmaceutical Technology, Lallubhai Motilal College of Pharmacy, Ahmedabad, India. He has over 100 national and international publications, 30 book chapters, ten books, and two patents to his credit. His research interests include the development of biologics processes and formulations, medical device development, nanodiagnostics and non-carrier formulations, long-acting parenteral formulations, and nano-vaccines.

Usha Desai, PhD is a professor and the Dean of Research and Development at the South East Asia College of Engineering and Technology, Bangalore, India. She authored over 50 research articles, five books, and six patents, and has presented technical research papers in numerous international conferences. Her research interests include biomedical signal processing, machine learning, and brain-computer interface.