Revolutionizing Drug Development: Harnessing AI and Computational Biology
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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.
Chen, Jen-Tsung: - Jen-Tsung Chen is a Professor of Cell Biology at the National University of Kaohsiung in Taiwan, where he teaches cell biology, genomics, proteomics, plant physiology, and plant biotechnology. His research spans bioactive compounds, chromatography techniques, plant molecular biology, bioinformatics, systems pharmacology, and broader themes in biotechnological plant disease management, plant biotic stress responses, nanotechnology for combating pests and pathogens, ethnopharmacology, and systems biology. An active scholar, Dr. Chen serves on the editorial boards of several international journals and has guest-edited numerous special issues. He has also authored and edited books with major international publishers on topics including drug discovery, herbal medicine, medicinal biotechnology, nanotechnology, bioengineering, plant functional genomics, plant speed breeding, CRISPR-based genome editing, and artificial intelligence. Recognized for his scientific impact and editorial leadership, Dr. Chen was listed among Elsevier and Stanford University's "World's Top 2% Scientists" in 2023 and 2024 and received the Springer Nature Editor of Distinction Award in 2025.
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