Innovative preclinical models for pulmonary drug delivery research

Autor: Lin Yang, Barbara Rothen-Rutishauser, Josué Sznitman, Stephan Ehrmann, Hana Barosova, Laurent Vecellio, Nathalie Heuzé-Vourc'h, Chantal Darquenne, Otmar Schmid, Jolyon P. Mitchell
Přispěvatelé: Service de Médecine Intensive Réanimation [Tours], Centre Hospitalier Régional Universitaire de Tours (CHRU Tours), Centre d’Etude des Pathologies Respiratoires (CEPR), UMR 1100 (CEPR), Université de Tours (UT)-Institut National de la Santé et de la Recherche Médicale (INSERM), Université de Tours (UT)
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Zdroj: Expert Opin Drug Deliv
Expert Opin. Drug Deliv. 17, 463-478 (2020)
Expert Opinion on Drug Delivery
Expert Opinion on Drug Delivery, Taylor & Francis, 2020, 17 (4), pp.463-478. ⟨10.1080/17425247.2020.1730807⟩
ISSN: 1742-5247
1744-7593
Popis: 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.
Databáze: OpenAIRE