Industrialization of Drug Discovery: From Target Selection Through Lead Optimization

Harnessing the Power of Artificial Intelligence in Drug Discovery

This volume delivers up-to-date information on the identification of newer uses, molecular mechanisms, and novel targets of existing drug candidates through the application of various experimental, biophysical, and computational approaches and techniques. The book discusses recent advances in drug repurposing strategies that are currently being used in the discovery and development of drugs against difficult-to-treat, rare, and life-threatening diseases, including microbial infections, COVID-19, parasitic diseases, cardiovascular diseases, neurological disorders, and cancer. The book also discusses the modern experimental assays (HTS) and computational techniques including informatics and databases, molecular docking and dynamics, artificial intelligence and machine learning, virtual screening and pharmacophore modeling, proteomics and metabolomics, and network pharmacology and systems biology approaches.

The Science and Business of Drug Discovery is written for those who want to learn about the biopharmaceutical industry and its products whatever their level of technical knowledge. Its aim is to demystify the jargon used in drug development, but in a way that avoids over simplification and the resulting loss of key information.

This book, authors discusses the development of techniques in machine learning for improving the efficiency of oncology drug development and delivering cost-effective precision treatment. Authors consider how to structure data for drug repurposing and target identification, how to improve clinical trials and how patients may view artificial intelligence.