This book covers the principles, methodology, and applications of network pharmacology in drug formulations, repurposing, formation and discovery, pharmacovigilance, and precision medicine, and presents the role of machine learning and AI in network pharmacology. It caters to professionals and advanced students of pharmaceutical sciences.
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
1) Presents principles, methodologies, and applications of network pharmacology.
2) Explores the intersection of network pharmacology with quantitative systems pharmacology.
3) Highlights the role of machine learning and artificial intelligence in network pharmacology.
4) Reviews the role of network pharmacology in different stages of drug discovery and repurposing.
5) Examines the pivotal role of network pharmacology in precision medicine
Introduction to Network Pharmacology.
2. Principles and Processes
involved in Network Pharmacology.
3. Quantitative Systems Pharmacology.
4.
Network Pharmacology Databases and Softwares.
5. Application of machine
learning and artificial intelligence-based tools in network pharmacology.
6.
Role of system biology in drug discovery and repurposing.
7. Role of network
pharmacology in herbal drug discovery and development.
8. Case Study of
Network Pharmacology in Pharmacovigilance.
9. Network Pharmacology in
Pharmaceutical Formulations.
10. Role of Network Pharmacology in Precision
Medicine.
11. Unveiling Drug-Target Interactions and Disease Pathways:
Leveraging Cytoscape for Comprehensive Network Pharmacology and Addressing
Challenges.
12. Cherylline, a phytoconstituent of Crinum moorei, targets
MAO-A in Alzheimer's disease: Network pharmacology integrated with molecular
docking and dynamics studies.
13. Case Studies on Network Pharmacology In
Predicting The Mechanism Of Herbal Drugs.
14. Ethics in Network Pharmacology:
Challenges and Opportunities.
15. Applications, Current Challenges, and
Future Perspectives of Network Pharmacology.
16. Network pharmacology:
illuminating the path towards exploring the herbal formulations of the Indian
Traditional Ayurvedic System.
17. Role of Network Pharmacology in Medicinal
Chemistry.
18. Role of Network Pharmacology in Homoepathy.
19. Role of
Network Pharmacology in Traditional Chinese Medicine (TCM) System.
Anoop Kumar currently working as an Assistant Professor in the Department of Pharmacology, Delhi Institute of Pharmaceutical Education and Research (DIPSAR), Delhi Pharmaceutical Sciences & Research University (DPSRU), Govt of NCT of Delhi. He has more than 10 years of teaching and research experience in reputed organizations like Cipla Pharmaceutical Limited Baddi, Shanti Niketan College of Pharmacy, Mandi, Sun Pharmaceutical Industries Limited, Gurugram, Translational Health Science Institute (THSTI), Faridabad, ISF College of Pharmacy, Moga, Punjab and National Institute of Pharmaceutical Education and Research (NIPER), Raebareli. Recently, he has also been included in top 2% list of scientists released by Stanford. His current h-index is 28, and i10-index 70 with citations of 3016 with more than 100 research and review articles. His lab gets funding from various government bodies like DST SERB, ICMR, NIF, and IIT-Delhi.
Chandragouda R. Patil is serving as a Professor of Pharmacology at R.C. Patel Institute of Pharmaceutical Education and Research, Shirpur, India. He has total 25 years of teaching experience in the subject of Pharmacology, Pathophysiology and Clinical Pharmacology. Dr. Patil is a recipient of prestigious National Teachers Award-2023 (Ministry of Education, Govt. of India), Innovator Teacher award-2016 (Ministry of Human Resources, Govt. of India), Young Scientist Award-2016 (Ministry of AYUSH, Govt. of India). He has more than 100 research and review publications to his credit with the h-index 36 and i-10 index 71. His educational software 'Xcology Pro' and CALpharm have supported the teaching and learning of experimental pharmacology at undergraduate and postgraduate learning.
