A Mini-Review on Machine Learning Framework for Drug Delivery Applications
Artificial intelligence (AI) represents a transformative technology that is reshaping the healthcare and pharmaceutical industries. This review provides an analysis of the current and prospective applications of machine learning in pharmaceutical science, emphasizing its role in drug delivery and development. By leveraging advanced machine learning algorithms and data analytics, AI facilitates the identification of novel therapeutic targets, streamlines drug formulation processes, and enhances predictive modeling for pharmacokinetics and toxicity. The integration of AI into pharmaceutical workflows promises to accelerate drug discovery timelines, reduce development costs, and improve precision medicine approaches, ultimately leading to more effective treatments and optimized patient outcomes.
Authors
- Farid Naeimi
- Mahdie Saheban SHahreza
Institutions
- Islamic Azad University of Najafabad (IR)
Publication Details
- Journal
- Journal of advanced materials and processing
- Published
- 2026-02-02
- DOI
- https://doi.org/10.71670/jmatpro.2024.1232710
- Primary Topic
- Computational Drug Discovery Methods
- Type
- article
- Field-Weighted Citation Impact
- 0.00