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Artificial Intelligence in Precision Drug Design, Volume 2

Advanced Applications

  • 1st Edition - March 6, 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

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Description

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.

Key features

  • 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

Readership

Researchers in interdisciplinary research at the intersection of artificial intelligence, life sciences, and clinical innovation

Table of contents

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

Product details

  • Edition: 1
  • Latest edition
  • Published: March 11, 2026
  • Language: English

About the editor

KR

Khalid Raza

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 Clarivate’s (Web of Science) India Excellence Research Citation Award 2025, Dr. Raza is consistently featured in the World’s Top 2% Scientists list (2022–2025). His research focuses on AI, bioinformatics, and health informatics

Affiliations and expertise
Department of Computer Science, Jamia Millia Islamia (Central University), Jamia Nagar, New Delhi, India

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