The effects of airway disease on the deposition of inhaled drugs

The deposition of inhaled medications is the first step in the pulmonary pharmacokinetic process to produce a therapeutic response. Not only lung dose but more importantly the distribution of deposited drug in the different regions of the lung determines local bioavailability, efficacy, and clinical...

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Published inExpert opinion on drug delivery Vol. 21; no. 8; p. 1175
Main Authors Darquenne, Chantal, Corcoran, Timothy E, Lavorini, Federico, Sorano, Alessandra, Usmani, Omar S
Format Journal Article
LanguageEnglish
Published England 01.08.2024
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Summary:The deposition of inhaled medications is the first step in the pulmonary pharmacokinetic process to produce a therapeutic response. Not only lung dose but more importantly the distribution of deposited drug in the different regions of the lung determines local bioavailability, efficacy, and clinical safety. Assessing aerosol deposition patterns has been the focus of intense research that combines the fields of physics, radiology, physiology, and biology. The review covers the physics of aerosol transport in the lung, experimental, and in-silico modeling approaches to determine lung dose and aerosol deposition patterns, the effect of asthma, chronic obstructive pulmonary disease, and cystic fibrosis on aerosol deposition, and the clinical translation potential of determining aerosol deposition dose. Recent advances in in-silico modeling and lung imaging have enabled the development of realistic subject-specific aerosol deposition models, albeit mainly in health. Accurate modeling of lung disease still requires additional refinements in existing imaging and modeling approaches to better characterize disease heterogeneity in peripheral airways. Nevertheless, recent patient-centric innovation in inhaler device engineering and the incorporation of digital technology have led to more consistent lung deposition and improved targeting of the distal airways, which better serve the clinical needs of patients.
ISSN:1744-7593
DOI:10.1080/17425247.2024.2392790