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.
Authors
- Junhuang Jiang (ORCID: https://orcid.org/0000-0002-1772-8482)
- Zhengwei Huang (ORCID: https://orcid.org/0000-0001-9861-514X)
- Tingting Peng (ORCID: https://orcid.org/0000-0003-4399-4757)
- Chuanbin Wu (ORCID: https://orcid.org/0000-0003-1661-0201)
- Xin Pan (ORCID: https://orcid.org/0000-0003-1437-2780)
- Ziling Zhou
Institutions
- Sun Yat-sen University (CN)
- Laboratoire de Chémo-biologie synthétique et thérapeutique (FR)
- Jiangmen Wuyi Traditional Chinese Medicine Hospital (CN)
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