Artificial Intelligence in Precision Drug Design, Volume 1

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

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• Indústria farmacêutica
• Farmacologia

Machine learning in drug discovery; Deep learning; Pharmacokinetics modeling; ADMET prediction; Bioinformatics