C.R. Patil – författare

This book comprehensively covers the principles, methodology, and applications of network pharmacology in drug discovery, pharmacovigilance, and precision medicine. The initial chapters guide readers through the principles and processes, detailing step-by-step procedures such as creating networks for compounds and disease targets. The intersection of network pharmacology with quantitative systems pharmacology is explored, along with an examination of various databases and essential software tools for conducting network pharmacological studies. It discusses the role of machine learning and AI in network pharmacology, delves into the application of systems biology for understanding complex diseases' pathogenesis, and highlights its contribution to drug discovery and repurposing. The book reviews the role of network pharmacology in different stages of drug discovery and repurposing, emphasizing its application in shaping drug formulations for enhanced efficacy and reduced side effects. Towards the end, it addresses translatability issues in drug discovery and repositioning predictions in clinical practice. This book caters to professionals, researchers, and advanced students in the pharmaceutical sciences. Key Features:Presents principles, methodologies, and applications of network pharmacologyExplores the intersection of network pharmacology with quantitative systems pharmacologyHighlights the role of machine learning and artificial intelligence in network pharmacologyReviews the role of network pharmacology in different stages of drug discovery and repurposingExamines the pivotal role of network pharmacology in precision medicine

This book comprehensively covers the principles, methodology, and applications of network pharmacology in drug discovery, pharmacovigilance, and precision medicine. The initial chapters guide readers through the principles and processes, detailing step-by-step procedures such as creating networks for compounds and disease targets. The intersection of network pharmacology with quantitative systems pharmacology is explored, along with an examination of various databases and essential software tools for conducting network pharmacological studies. It discusses the role of machine learning and AI in network pharmacology, delves into the application of systems biology for understanding complex diseases' pathogenesis, and highlights its contribution to drug discovery and repurposing. The book reviews the role of network pharmacology in different stages of drug discovery and repurposing, emphasizing its application in shaping drug formulations for enhanced efficacy and reduced side effects. Towards the end, it addresses translatability issues in drug discovery and repositioning predictions in clinical practice. This book caters to professionals, researchers, and advanced students in the pharmaceutical sciences. Key Features: Presents principles, methodologies, and applications of network pharmacology Explores the intersection of network pharmacology with quantitative systems pharmacology Highlights the role of machine learning and artificial intelligence in network pharmacology Reviews the role of network pharmacology in different stages of drug discovery and repurposing Examines the pivotal role of network pharmacology in precision medicine