Abstract
Pulmonary drug delivery (PDD) involves flow and deposition of aerosol particles acting as carriers of drugs delivered onto the surface of the airways. As a direct consequence, optimal PDD requires controlling of drug aerosolization processes and deep understanding of multiphase flows in complex geometry of the airways including aerosol particle dynamics during the transient inhalation cycles. A chemical engineering-based approache can be effectively used to analyze these processes and help in designing optimized drug formulations and more effective drug delivery devices (inhalers). One of prerequisites of improved PDD is the knowledge of in vivo–in vitro correlation (IVIVC) for inhaled drugs that would allow establishment of the relationships between aerosol quality determined using ex vivo methods (such as determination of particle size, deposition in reconstructed anatomical structures, pharmacokinetics/pharmacodynamics using in vitro cellular systems, or in silico modeling of aerosol dynamics) in connection to the clinical effects. This manuscript discusses the challenges of the IVIVC analyses for aerosol delivery systems. The primary focus is given to the physical and physicochemical constraints in the PDD that can be effectively described and investigated using engineering approaches.
Funding source: Collaboration Initiative Program between Warsaw Medical University and Warsaw University of Technology (Poland)
Award Identifier / Grant number: WUM_PW Integra
Acknowledgments
The authors would like to thank the editor David Bogle for his guidance and review of this article before its publication. The work has been done under umbrella of the scientific section “Chemical Engineering as Applied to Medicine” (ChemE-Med) of the European Federation of Chemical Engineering (EFCE).
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Research ethics: Not applicable.
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Informed consent: Not applicable.
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Author contributions: Both authors have accepted responsibility for the entire content of this manuscript and approved its submission.
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Use of Large Language Models, AI and Machine Learning Tools: None declared.
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Conflict of interest: The authors state no conflict of interest.
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Research funding: T.R.S’s contribution was partially supported by WUM_PW Integra project under the Collaboration Initiative Program between Warsaw Medical University and Warsaw University of Technology.
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Data availability: Not applicable.
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© 2025 Walter de Gruyter GmbH, Berlin/Boston
Articles in the same Issue
- Frontmatter
- Reviews
- Inhaled aerosols as carriers of pulmonary medicines and the limitations of in vitro–in vivo correlation (IVIVC) methods
- Analysis of an automated solar panel cleaning robot on photovoltaics (PV) module frames with composites materials
- Mechanical and thermal properties of graphene reinforced poly (lactic acid) composites for battery casing in electric vehicles
- Precision medicine in hypothyroidism: an engineering approach to individualized levothyroxine dosing
- Advancements in composite materials for energy harvesting
- Model-based dose selection for gene therapy for haemophilia B
Articles in the same Issue
- Frontmatter
- Reviews
- Inhaled aerosols as carriers of pulmonary medicines and the limitations of in vitro–in vivo correlation (IVIVC) methods
- Analysis of an automated solar panel cleaning robot on photovoltaics (PV) module frames with composites materials
- Mechanical and thermal properties of graphene reinforced poly (lactic acid) composites for battery casing in electric vehicles
- Precision medicine in hypothyroidism: an engineering approach to individualized levothyroxine dosing
- Advancements in composite materials for energy harvesting
- Model-based dose selection for gene therapy for haemophilia B