1. AI in Drug Design: A Historical and Future Perspective 2. Can Machines Truly Know? Epistemological Challenges in AI-Driven Drug Discovery 3. Ethical Implications of AI in Precision Drug Design: A Philosophical Inquiry 4. Metaphors of Medicine: A Literary Perspective on AI in Drug Discovery, Design and Target Precision 5. Artificial Intelligence in Molecular Screening: Advances, Challenges, and Future Perspectives 6. AI for Predicting Pharmacokinetics and Pharmacodynamics 7. AI for Predicting Drug-Likeness and Bioavailability 8.

AI-Powered In Silico ADMET Modeling and Optimization in Drug Design 9. AI-Based Toxicity Prediction: Advancing Drug Safety and Risk Assessment 10. Leveraging AI for Integrating Genomics, Transcriptomics, and Proteomics 11. Artificial Intelligence in Multi-Omics Integration for Precision Drug Design 12. AI and Machine Learning for Disease Pathway Modelling 13. AI-Powered Genomic Medicine: Technologies and Challenges 14. PGP-Miner: An AI and Machine Learning Tool in Cancer Drug Development and Immunotherapy 15. Artificial Intelligence for Drug Repurposing: Opportunities and Challenges 16.

Generative Artificial Intelligence for De-novo Drug Design 17. Bias and Transparency in AI and Machine Learning Models for Drug Design 18. Blockchain and AI in Drug Development: Securing Data Integrity and Transparency 19. Counterfactual Explainability in AI-Driven Drug Discovery: Enhancing Transparency and Decision-Making 20. Integrating AI in Pharmacovigilance and Clinical Trial Monitoring: Enhancing Drug Safety and Efficacy in Kyrgyzstan's and LMIC's Evolving Healthcare Landscape.