Artificial Intelligence in Precision Drug Design, Volume 2
Advanced Applications
- 1st Edition - May 1, 2026
- Latest edition
- Editor: Khalid Raza
- Language: English
Artificial Intelligence in Precision Drug Design, Volume 2: Advanced Applications explores the transformative role of AI in modern drug discovery and development, presenting cuttin… Read more
Artificial Intelligence in Precision Drug Design, Volume 2: Advanced Applications explores the transformative role of AI in modern drug discovery and development, presenting cutting-edge research and methodologies that integrate machine learning, network pharmacology, and computational modeling to accelerate therapeutic innovation. It covers a wide range of applications, including AI-driven drug repurposing, combination therapies, cancer immunotherapy, neuroscience, vaccine development, and molecular dynamics, but also delves into emerging technologies such as quantum computing, large language models, and graph neural networks. Designed for academics, this volume provides researchers, clinicians, and graduate students with a resource on the latest AI methodologies in precision medicine.
Users will find this to be a great resource that supports evidence-based innovation, fosters interdisciplinary collaboration, and equips them with insights to advance personalized healthcare solutions.
Users will find this to be a great resource that supports evidence-based innovation, fosters interdisciplinary collaboration, and equips them with insights to advance personalized healthcare solutions.
- Presents state-of-the-art research on AI-driven drug repurposing, combination therapies, vaccine development, and molecular modeling, offering a comprehensive view of current innovations
- Covers cutting-edge AI applications across drug discovery
- Combines machine learning, network pharmacology, quantum computing, and large language models to address complex biomedical challenges with precision and scalability
- Equips scholars, clinicians, and graduate students with practical insights and frameworks to accelerate personalized medicine and foster interdisciplinary collaboration
Researchers in interdisciplinary research at the intersection of artificial intelligence, life sciences, and clinical innovation
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 Kyrgyzstan’s 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 Alzheimer’s Therapy Optimization
11. Patient Stratification and Precision Medicine Approaches—Key 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 Drug–Drug 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
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 Kyrgyzstan’s 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 Alzheimer’s Therapy Optimization
11. Patient Stratification and Precision Medicine Approaches—Key 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 Drug–Drug 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
- Edition: 1
- Latest edition
- Published: May 1, 2026
- Language: English
KR
Khalid Raza
Dr. Khalid Raza is working as an Associate Professor at the Department of Computer Science, Jamia Millia Islamia, New Delhi. Earlier he worked as an “ICCR Chair Professor” at Ain Shams University, Cairo, Egypt. He has many years of teaching & research experiments in the field of Translational Bioinformatics and Computational Intelligence. He has contributed over 120 research articles in reputed Journals and Edited Books. Dr. Raza has authored/edited dozens of books published by reputed publishers. Dr. Raza is an Academic Editor of PeerJ Computer Science International Journal, and Guest Editor of the Journal Natural Product Communications. He has an active collaboration with the scientists from leading institutions of India and abroad. Recently, Dr. Raza has been featured in the list of Top 2% Scientists released by Stanford University (USA) in collaboration with Elsevier. His research interest lies in Machine Learning and its applications in Bioinformatics and Health-informatics.
Affiliations and expertise
Department of Computer Science, Jamia Millia Islamia (Central University), Jamia Nagar, New Delhi, India