Previously submitted to: JMIR Bioinformatics and Biotechnology (no longer under consideration since Apr 20, 2026)
Date Submitted: Jun 14, 2025
Open Peer Review Period: Jul 21, 2025 - Sep 15, 2025
(closed for review but you can still tweet)
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Challenges and Ethical Considerations in AI-Driven Drug Delivery: Implications for Clinical Translation
ABSTRACT
Background:
The integration of artificial intelligence (AI) into personalized medicine is revolutionizing drug delivery by transitioning from the traditional “one-size-fits-all” approach to patient-specific therapeutic strategies.
Objective:
This review aims to explore the transformative role of artificial intelligence (AI) in personalizing drug delivery systems by leveraging genomic, proteomic, and metabolic data.
Methods:
A comprehensive literature review was conducted using electronic databases such as PubMed, Scopus, and Web of Science to examine studies related to AI in pharmacogenomics, smart drug delivery, biosensing technologies, and drug repurposing. Inclusion and exclusion criteria were applied, and findings were thematically synthesized.
Results:
AI facilitates real-time data interpretation and personalized therapy through smart nanoformulations, biosensor-enabled monitoring, and deep learning-based pharmacogenomic modeling. Applications in oncology, diabetes, and neurodegenerative disorders show improved treatment outcomes. However, challenges include data security, regulatory constraints, and interpretability of AI models.
Conclusions:
AI bridges genomics and pharmaceutics, driving precision medicine. Innovations like AI-driven 3D printing and federated learning promise a new era in personalized healthcare.
Citation
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Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.