Innovative preclinical models for pulmonary drug delivery research. (2nd April 2020)

• Record Type: Journal Article
• Authors: Ehrmann, Stephan; Schmid, Otmar; Darquenne, Chantal; Rothen-Rutishauser, Barbara; Sznitman, Josue; Yang, Lin; Barosova, Hana; Vecellio, Laurent; Mitchell, Jolyon; Heuze-Vourc'h, Nathalie
• Is Part Of: Expert opinion on drug delivery. Volume 17:Number 4(2020)
• Page Start: 463
• Page End: 478
• Publication Date: 2020-04-02
• Subjects: Nebulization -- aerosolization -- inhalation -- theoretical modeling -- cell culture techniques -- animal models; Drug delivery devices -- Periodicals; Drug delivery systems -- Periodicals; 615.605
• DOI: 10.1080/17425247.2020.1730807
• Languages: English
• ISSNs: 1742-5247

Abstract

ABSTRACT: Introduction : Pulmonary drug delivery is a complex field of research combining physics which drive aerosol transport and deposition and biology which underpins efficacy and toxicity of inhaled drugs. A myriad of preclinical methods, ranging from in-silico to in-vitro, ex–vivo and in-vivo, can be implemented. Areas covered : The present review covers in-silico mathematical and computational fluid dynamics modelization of aerosol deposition, cascade impactor technology to estimated drug delivery and deposition, advanced in-vitro cell culture methods and associated aerosol exposure, lung-on-chip technology, ex–vivo modeling, in-vivo inhaled drug delivery, lung imaging, and longitudinal pharmacokinetic analysis. Expert opinion : No single preclinical model can be advocated; all methods are fundamentally complementary and should be implemented based on benefits and drawbacks to answer specific scientific questions. The overall best scientific strategy depends, among others, on the product under investigations, inhalation device design, disease of interest, clinical patient population, previous knowledge. Preclinical testing is not to be separated from clinical evaluation, as small proof-of-concept clinical studies or conversely large-scale clinical big data may inform preclinical testing. The extend of expertise required for such translational research is unlikely to be found in one single laboratory calling for the setup of multinational large-scale research consortiums.