دانلود کتاب طراحی دارو با استفاده از یادگیری ماشینی

Traditionally, the design of new drugs has been a long process that requires an investment of billions of dollars. In the last decades, molecular modeling techniques have been used in the pharmaceutical industry and large laboratories to accelerate this process in order to reduce the amount of money that needs to be invested. More recently, machine learning approaches to drug discovery have aroused great interest in the scientific community. This has occurred, among other reasons, due to advances in high-performance computing and the availability of an abundance of biological and chemical information on thousands of compounds. Through machine learning and artificial intelligence approaches, this information can be filtered quickly and at a low cost. From this, algorithms can be trained to be used in the different stages of drug design. The objective of this book is to bring together several chapters that function as an overview of the use of machine learning and artificial intelligence applied to drug development. The initial chapters discuss drug-target interactions through machine learning for improving drug delivery, healthcare, and medical systems. Further chapters also provide topics on drug repurposing through machine learning, drug designing, and ultimately discuss drug combinations prescribed for patients with multiple or complex ailments. This book should be useful for information technology professionals, pharmaceutical industry workers, engineers, university students and faculty members, medical practitioners, researchers and laboratory workers who have a keen interest in the area of machine learning and artificial intelligence approaches applied to drug advancements. A chapter-by-chapter summary of the work reported in the 12 chapters of this book follows.