Artificial Intelligence in Precision Pharmacotherapy: Clinical Applications, Opportunities, and Challenges
Abstract
Abstract: Artificial intelligence is emerging as a key enabler of precision pharmacotherapy by improving individualized drug selection,therapeutic monitoring, and dose optimization. Machine learning models integrate clinical, molecular, pharmacokinetic, and longitudinal data to characterize interpatient variability and anticipate therapeutic response. Clinical applications include prediction of benefit and toxicity, pharmacogenomic interpretation, therapeutic drug monitoring, and adaptive dosing. These opportunities align with priorities to reduce adverse events, enhance treatment efficiency, and personalize therapeutic trajectories. However, challenges remain in validation,generalizability, interpretability, regulation, and workflow integration. Translational progress will depend on hybrid approaches that combine pharmacological knowledge with data-driven inference, interpretable decision support, and uncertainty-aware prediction. Future development may expand closed-loop exposure control, multi omics integration, virtual physiological models, and model informed trial design. Artificial intelligence has potential to reshape individualized therapy by making response more predictable, dosing more adaptive, and clinical reasoning more anticipatory.
References
[2] Hall NM et al. Model-informed precision dosing improves outcomes in patients receiving vancomycin. Open Forum Infect Dis. 2024;11(1):ofae002.
[3] Taherdoost H. AI’s role in revolutionizing personalized medicine by transforming pharmacogenomics. Intelligent Pharmacology. 2024;2(1):1–18.
[4] Polasek TM. Virtual twin for healthcare management and individualized therapy. Front Digit Health. 2023;5:1246659.
[5] Mitchell J et al. Digital health and precision therapeutics: Opportunities and regulatory considerations. Nat Med. 2023;29(7):1590–1601.
Yibo Research & Academic Press is committed to safeguarding authors' copyrights and all related information, ensuring these rights are fully protected by law. Whether you choose to publish your articles with our press or not, we require every employee to adhere to the highest ethical standards in the industry, assume responsibilities, and fulfill legal obligations.
To further protect authors' rights, we provide detailed information on copyright agreements on our official website for your reference. Regarding the reuse rights of articles, Yibo Research & Academic Press maintains an open attitude and strictly complies with the CC BY-NC 4.0 publication guidelines. This guideline not only provides copyright protection for authors but also meets the standards for usage rights set by the Open Access Scholarly Publishing Association (OASPA).
For authors who wish to further protect their articles, we also offer the CC BY-NC guideline service. Based on the CC guideline selected by the author, the original copyright and reuse rights of the article will be clearly stated in the article. This approach not only respects the authors' intellectual property rights but also promotes the reasonable dissemination and use of academic achievements.
