Applications of AI/ML in accelerating the development of pulmonary drug delivery system

Artificial intelligence (AI) is a transformative technique for drug development, and it has been widely applied in pharmaceutical industry and academia. Pulmonary drug delivery systems (PDDS) are preferred for treating respiratory diseases due to their ability to provide localized and rapid action with fewer side effects. The integration of AI and Machine Learning (ML) has significantly accelerated the development of PDDS by enhancing both respiratory disease detection, and different stages during PDDS development. This paper provides an overview of the present landscape by literature analysis of the key areas of research. This review first introduces the fundamental principles of AI/ML and how they are applied in respiratory disease detection and diagnostics, highlighting FDA-approved software used in this field. Furthermore, we examine the role of AI in different stages during the development of PDDS, from identifying novel drug candidates to optimizing formulations and drug delivery mechanisms. The review also discusses regulatory and ethical considerations, along with existing challenges during AI-driven PDDS development. By addressing these key aspects, we provide insights into the revolutionary potential of AI/ML in advancing pulmonary drug delivery and improving therapeutic outcomes.

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Publication Details

Journal
Acta Pharmaceutica Sinica B
Published
2025-11-29
DOI
https://doi.org/10.1016/j.apsb.2025.11.028
Primary Topic
Inhalation and Respiratory Drug Delivery
Type
article
Field-Weighted Citation Impact
0.00
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article

Applications of AI/ML in accelerating the development of pulmonary drug delivery system

Junhuang Jiang, Zhengwei Huang, Tingting Peng, Chuanbin Wu et al.
Acta Pharmaceutica Sinica B
Inhalation and Respiratory Drug Delivery
article

Applications of AI/ML in accelerating the development of pulmonary drug delivery system

Junhuang Jiang, Zhengwei Huang, Tingting Peng, Chuanbin Wu, Xin Pan, Ziling Zhou
article en

Abstract

Artificial intelligence (AI) is a transformative technique for drug development, and it has been widely applied in pharmaceutical industry and academia. Pulmonary drug delivery systems (PDDS) are preferred for treating respiratory diseases due to their ability to provide localized and rapid action with fewer side effects. The integration of AI and Machine Learning (ML) has significantly accelerated the development of PDDS by enhancing both respiratory disease detection, and different stages during PDDS development. This paper provides an overview of the present landscape by literature analysis of the key areas of research. This review first introduces the fundamental principles of AI/ML and how they are applied in respiratory disease detection and diagnostics, highlighting FDA-approved software used in this field. Furthermore, we examine the role of AI in different stages during the development of PDDS, from identifying novel drug candidates to optimizing formulations and drug delivery mechanisms. The review also discusses regulatory and ethical considerations, along with existing challenges during AI-driven PDDS development. By addressing these key aspects, we provide insights into the revolutionary potential of AI/ML in advancing pulmonary drug delivery and improving therapeutic outcomes.

Acta Pharmaceutica Sinica BVol. 16(2)
Sun Yat-sen University (CN), Laboratoire de Chémo-biologie synthétique et thérapeutique (FR), Jiangmen Wuyi Traditional Chinese Medicine Hospital (CN)
Openalex Percentile: Top 44%
Inhalation and Respiratory Drug Delivery
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