Artificial Intelligence in Precision Drug Design, Volume 1

Foundations and Core Techniques

Khalid Raza

• Publisher: Academic Press
• Year: 2026
• eBook ISBN:
  9780443444166
• Topic: Medicine
• Subtopic: Pharmaceutical, Biotechnology & Healthcare Industry

Artificial Intelligence in Precision Drug Design: Advanced Applications showcases how artificial intelligence (AI) is revolutionizing modern drug discovery and development. Building upon the foundational principles established in Volume 1, this book dives into real-world applications where AI accelerates innovation, enhances predictive accuracy, and enables breakthrough therapeutics. Featuring contributions from leading global researchers and practitioners, the book explores machine learning, deep learning, and network-based approaches applied to complex biomedical challenges. Key areas include AI driven drug repurposing, combination therapies, immunotherapy, vaccine design, quantum computing, and the integration of large language models in drug discovery. Additional chapters highlight predictive modeling using electronic health records, AI-powered medical imaging, and explainable AI for structure-based drug design. What sets this volume apart is its emphasis on practical impact, demonstrating how data, computation, and interdisciplinary collaboration converge to advance precision medicine. Designed for scientists, clinicians, educators, and students, it serves as both a comprehensive reference and a source of inspiration for leveraging AI to transform healthcare.• Focuses on real-world AI applications in drug design and development provides comprehensive coverage of advanced techniques: deep learning, network-based models, and quantum computing.• Includes case studies on drug repurposing, combination therapies, immunotherapy, and vaccine development.• Provides insights into predictive modeling, AI-driven medical imaging, and explainable AI.• Highlights practical impact and interdisciplinary collaboration in precision medicine.

Table of contents

• Title of Book
• Chapter 1. AI in drug design: A historical and future perspective
• Chapter 2. Can machines truly know? Epistemological challenges in AI-driven drug discovery
• Chapter 3. Ethical implications of AI in precision drug design: A philosophical inquiry
• Chapter 4. Metaphors of medicine: a literary perspective of the involvement of AI in drug discovery, design, and target precision
• Chapter 5. Artificial intelligence in molecular screening: Advances, challenges, and future perspectives
• Chapter 6. AI for predicting pharmacokinetics and pharmacodynamics
• Chapter 7. Artificial Intelligence for predicting drug-likeness and bioavailability
• Chapter 8. AI-powered In silico ADMET modeling and optimization in drug design
• Chapter 9. Artificial Intelligence based toxicity prediction: Advancing drug safety and risk assessment
• Chapter 10. Leveraging AI for integrating genomics, transcriptomics, and proteomics
• Chapter 11. Artificial intelligence in multi-omics integration for precision drug design
• Chapter 12. AI and machine learning for disease pathway modeling [case study: malaria infection]
• Chapter 13. AI-powered genomic medicine: Technologies and challenges
• Chapter 14. PGP-miner: An AI and machine learning tool in cancer drug development and immunotherapy
• Chapter 15. Artificial intelligence for drug repurposing: Opportunities and challenges
• Chapter 16. Generative artificial intelligence for de novo drug design
• Chapter 17. Bias and transparency in AI and machine learning models for drug design
• Chapter 18. Blockchain and AI in drug development: Securing data integrity and transparency
• Chapter 19. Counterfactual explainability in AI-driven drug discovery: Enhancing transparency and decision-making
• Chapter 20. Integrating AI in pharmacovigilance and clinical trial monitoring: Enhancing drug safety and efficacy in Kyrgyzstan’s and LMIC’s evolving healthcare landscape
• Index