Artificial Intelligence for Drug Delivery

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Authors: Xinmin Yu, Xinyun Jiang, Tao Sheng, Phylisse Nichelle Tiong, Jicheng Yu, Feng Zhu, Defang Ouyang, Marı́a José Alonso, Jianqing Gao, Zhen Gu, Yuqi Zhang
Cited by: 1
References: 175

Abstract

Drug delivery, serving as a pivotal link between pharmaceutical innovation and clinical implementation, faces numerous challenges in achieving optimal therapeutic outcomes. With the advancement of computational methodologies and technological tools, artificial intelligence (AI) has been increasingly applied in pharmaceutical sciences, ranging from target discovery to product management. In recent years, AI has been extensively used in drug delivery to tailor formulation design, enhance therapeutic efficacy, and reduce side effects. However, limitations in data quality and model interpretability frequently restrict AI's predictive performance and hinder its clinical applicability. This overview highlights the applications of AI in drug delivery, focusing on AI-designed drug formulations, AI-driven prediction of ADMET properties, and AI-assisted drug delivery devices, which support the development of precision medicine. Additionally, the translation challenges and future perspectives in this field are discussed.

Fields of Study & Subjects

Computational Drug Discovery Methods Inhalation and Respiratory Drug Delivery Drug Solubulity and Delivery Systems

Publication details

Journal / source
ACS Nano
Publisher
American Chemical Society (ACS)
Volume
20
Issue
32
Pages
22247–22264
Publication date
4 August 2026
Language
EN