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.

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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
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article

A Mini-Review on Machine Learning Framework for Drug Delivery Applications

Farid Naeimi, Mahdie Saheban SHahreza
Journal of advanced materials and processing
Computational Drug Discovery Methods
article

A Mini-Review on Machine Learning Framework for Drug Delivery Applications

Farid Naeimi, Mahdie Saheban SHahreza
article en

Abstract

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.

Journal of advanced materials and processing
Islamic Azad University of Najafabad (IR)
Openalex Percentile: Top 44%
Computational Drug Discovery Methods
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