Английски език
The subject of this book is drug design using artificial intelligence (AI). It mainly covers the area of machine learning, deep learning and their applications in drug development, target identification and structure prediction. As the rapid development of AI technologies and continuous accumulation of biomedical data, AI has been widely employed in the pharmaceutical field, dramatically accelerating the process of drug discovery. AI can rapidly mine high information density data from huge amounts of raw data, providing more new insights by integrating and analysing these data. With numerous research teams and major pharmaceutical companies actively strategizing their drug development plans based on artificial intelligence, there is promising potential for breakthroughs in the progress of 'First-in-Class' novel drug research and development in China.
This book systematically introduces the professional knowledge of artificial intelligence and its applications in various aspects of the pharmaceutical field. The overall structure of the book is progressive, starting from the basics and gradually delving into more advanced topics. The content is layered and progressive, with strong logical and systematic connections between chapters. Each chapter not only provides detailed explanations of the principles, algorithms, and models of artificial intelligence but also closely relates them to practical cases in the pharmaceutical field and drug development. This approach caters to the knowledge needs of readers with different professional backgrounds. In summary, this book not only focuses on the present but also provides readers with foundational knowledge in the field of artificial intelligence in pharmacy, helping them smoothly enter this rapidly advancing frontier of science
