Beschreibung
This book focuses on the application of artificial intelligence in drug research and development, particularly its growing role in evaluating interactions between biological targets and drug molecules and optimizing drug design pathways. It offers a comprehensive structure divided into four parts: fundamentals of AI algorithms, data foundations and representations, AI driven drug design, and program code. The book systematically introduces key AI methodologies, highlights essential biomedical data resources, and presents data mining approaches based on artificial intelligence. Following the workflow of drug R&D, each chapter explains the basic principles and challenges of specific drug design steps and then reviews the corresponding advances in AI algorithms, supplemented by cross-disciplinary application examples. Readers will gain a clear understanding of how AI integrates into and accelerates the drug development process while reducing associated risks and costs, making the book particularly valuable for researchers and technical professionals engaged in life sciences and pharmaceutical R&D.
Autorenporträt
Honglin Li Dean of the School of Pharmacy at East China Normal University and Director of the Innovation Center for AI and Drug Discovery. His research focuses on the development and application of computational methodologies for drug discovery and target identification, integrating artificial intelligence with experimental and theoretical approaches. Mingyue Zheng Professor and Principal Investigator at the Shanghai Institute of Materia Medica, Chinese Academy of Sciences. His work focuses on the development of artificial intelligence and big data-driven drug design technologies, including methods for biomedical big data mining, AI-powered precision drug design, and the discovery of novel targets and drug candidates. Feng Zhu Professor at the College of Pharmaceutical Science, Zhejiang University. His research focuses on identifying the druggability of therapeutic drug targets by leveraging AI and OMICs, developing innovative computational methods and online tools for drug target discovery, and investigating the mechanisms between drugs and key biological targets. Fang Bai Associate Professor jointly appointed in the School of Life Science and Technology and the Shanghai Institute for Advanced Immunochemical Studies at ShanghaiTech University. Her research focuses on developing advanced computational methods for drug design that integrate artificial intelligence with physical modeling. Recently, her work has addressed challenging drug targetssuch as protein-protein interactionsby designing innovative therapeutic strategies, including molecular glues and PROTACs (proteolysis-targeting chimeras).
Herstellerkennzeichnung:
Springer Verlag GmbH
Tiergartenstr. 17
69121 Heidelberg
DE
E-Mail: juergen.hartmann@springer.com
