Innovative preclinical models for pulmonary drug delivery research.
Innovative preclinical models for pulmonary drug delivery research.
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DOI:
10.1080/17425247.2020.1730807
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发表时间:
2020-04
影响因子:
6.6
通讯作者:
Heuze-Vourc'h N
中科院分区:
文献类型:
--
作者:
Ehrmann S;Schmid O;Darquenne C;Rothen-Rutishauser B;Sznitman J;Yang L;Barosova H;Vecellio L;Mitchell J;Heuze-Vourc'h N
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. 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. No single pre-clinical 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. Pre-clinical 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 pre-clinical 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.
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DOI:
10.1089/089426804322994406
发表时间:
2004-03-01
期刊:
JOURNAL OF AEROSOL MEDICINE-DEPOSITION CLEARANCE AND EFFECTS IN THE LUNG
影响因子:
--
作者:
Esposito-Festen, JE;Ates, B;Tiddens, HAWM
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影响因子:
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通讯作者:
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影响因子:
3.8
作者:
Corley, Richard A.;Kabilan, Senthil;Einstein, Daniel R.
通讯作者:
Einstein, Daniel R.
影响因子:
3.3
作者:
DARQUENNE, C;PAIVA, M
通讯作者:
PAIVA, M
DOI:
10.1089/jamp.2017.1369
发表时间:
2018-02-01
影响因子:
3.4
作者:
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通讯作者:
Puccini, Paola