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<p class="MsoBodyText"><span data-olk-copy-source="MessageBody">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&amp;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&amp;D.</span></p>

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Artificial Intelligence for Drug Design

  • 工具书

  • 发表日期：

    2026年

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摘要

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.