Advanced Applications of Bioinformatics in Precision Drug Design: Volume 2: Advanced Applications explores the transformative role of AI in modern drug discovery and development. This volume presents cutting-edge research and methodologies that integrate machine learning, network pharmacology, and computational modeling to accelerate therapeutic innovation. The book covers a wide range of applications, including AI-driven drug repurposing, combination therapies, cancer immunotherapy, neuroscience, vaccine development, and molecular dynamics. It also delves into emerging technologies such as quantum computing, large language models, and graph neural networks, offering a comprehensive view of how AI reshapes biomedical research. Designed for an academic audience, this volume provides researchers, clinicians, and graduate students with a rich resource to understand the latest AI methodologies in precision medicine. It supports evidence-based innovation, fosters interdisciplinary collaboration, and equips readers with insights to advance personalized healthcare solutions.
1. AI-Driven Drug Repurposing and Combination Therapies: Revolutionizing
Treatment Strategies and Overcoming Complex Challenges
2. AI-Driven Drug Repurposing in Precision Medicine: Transforming Existing
Therapies into Targeted Solutions
3. AI-Driven Network Pharmacology for Drug Repurposing
4. AI-Driven Network-Based Drug Repurposing: A Roadmap for Precision Medicine
in Kyrgyzstans and LMICs Resource-Limited Healthcare System
5. AI in Cancer Drug Development and Immunotherapy
6. AI-Driven Innovations in Neuroscience: Rewiring Precision Drug Design for
Neurological Disorders
7. Harnessing Artificial Intelligence for Accelerated Vaccine Development:
Innovations, Applications, and Case Studies
8. AI-Driven Advancements in Vaccine Development: From Discovery to Global
Deployment
9. The Role of Artificial Intelligence in Overcoming Challenges in Vaccine
Development
10. Towards Smart Drug Discovery: CogMol-VAE for Alzheimers Therapy
Optimization
11. Patient Stratification and Precision Medicine ApproachesKey to
Identifying Patient Subgroups for Personalized Treatment
12. Large Language Models for Automated Drug Target Discovery and Literature
Mining
13. Predictive Modeling of Drug Suitability Using Electronic Health Records
and Machine Learning
14. AI-Powered Medical Imaging for Precision Drug Design: Applications in
Therapeutic Targeting and Optimization
15. Revolutionizing Drug Design: The Convergence of AI and Quantum Computing
- A Systematic Review
16. AI for Antiviral and Antibacterial Drug Discovery
17. AI for Monitoring Clinical Outcomes and Adverse Events
18. Revolutionizing the Power of AI's Role in Precision Medicine:
Transforming Biologics, Cell, and Gene Therapy
19. Artificial Intelligence in Fragment-Based and Scaffold-Hopping Approaches
for Drug Discovery
20. AI-Driven DrugDrug Interaction Modeling with Graph Neural Networks: A
New Era in Safer Drug Development
21. Explainable AI for Structure-Based Drug Design: Concepts and Case Studies
Dr. Khalid Raza is an Associate Professor at the Department of Computer Science, Jamia Millia Islamia, New Delhi, India, and an Adjunct Professor at UCSI University, Malaysia. He has over 14 years of teaching and research experience and previously served as an ICCR Chair Visiting Professor at Ain Shams University, Egypt. Dr. Raza has published more than 160 peer-reviewed papers and authored/edited over 15 books with Springer, Elsevier, and CRC Press. He serves as Academic Editor of PLoS ONE, BMC Artificial Intelligence, and Guest Editor of npj Precision Oncology, JoVE, and several other journals. Recipient of Clarivates (Web of Science) India Excellence Research Citation Award 2025, Dr. Raza is consistently featured in the Worlds Top 2% Scientists list (20222025). His research focuses on AI, bioinformatics, and health informatics
