Revolutionizing Drug Development

Harnessing AI and Computational Biology

Jen-Tsung Chen

• Publisher: Academic Press
• Year: 2026
• Topic: Biological Sciences
• eBook ISBN:
  9780443340604
• Subtopic: Biology
• Index: Biological Sciences

Revolutionizing Drug Development: Harnessing AI and Computational Biology presents cutting-edge artificial intelligence (AI) tools, such as machine- and deep-learning models and generative AI, to assist structure-based drug design and clinical trial design and integrate with drug development programs. This book summarizes technical advancements of AI-based technologies and computational biology approaches, highlighting their applications in developing new drugs through discovery, repurposing, and designing, for advancing R&D in the pharmaceutical industry and benefiting precision medicine. This book serves as an ideal reference for students, teachers, professors, and researchers in biological and biomedical sciences, particularly the topics related to bioinformatics, systems biology, pharmacology, and drug development. The readers can efficiently and precisely overview this burning field, which might inspire their future directions of research in drug development and AI-based digital biology. - Provides cutting-edge AI technologies in drug development - Presents ways to utilize AI models for drug discovery, repurposing, and design - Summarizes current achievements of AI models for accelerating drug development programs

Table of contents

• Front Cover
• Revolutionizing Drug Development
• Copyright
• Contents
• List of contributors
• Preface
• 1 Artificial intelligence and accelerated computing in drug discovery: an updated overview
• 2 AI strategies for drug discovery and bioactivity prediction: opportunities and challenges
• 3 AI technologies for drug repurposing: methods and applications
• 4 Data science and databases in drug discovery: technical development and applications
• 5 Graph neural networks for drug discovery: protocols and applications
• 6 Deep learning and generative models for drug discovery: techniques and current achievements
• 7 Artificial intelligence-enabled personalized medicine: strategies and challenges
• 8 Artificial intelligence-based technologies for advancing research and development in the pharmaceutical industry: current developments and challenges
• 9 Artificial intelligence powered drug response prediction against cancer
• 10 Artificial intelligence in  drug discovery for neurological disorders: progress, challenges, and future directions
• 11 AI applications in drug discovery for promoting longevity
• 12 Transforming drug development with AI„-„driven models
• 13 AI technologies for precision and personalized medicine
• 14 AI technologies for smart pharmacology
• 15 AI-powered immunopharmacological strategies to combat inflammatory diseases
• 16 AI and nanotechnology for advancing drug development
• 17 Integration of artificial intelligence and machine learning technologies in antiviral drug discovery: strategies and challenges
• 18 Artificial intelligence in the discovery of new antibiotics
• 19 AI-designed drugs: clinical development and future directions
• Index
• Back Cover