Predicting Metabolism-Related Drug-Drug Interactions Using a Microphysiological Multitissue System.

Autor: Lohasz C; Department of Biosystems Science and Engineering, ETH Zurich, Basel, 4058, Switzerland., Bonanini F; Department of Biosystems Science and Engineering, ETH Zurich, Basel, 4058, Switzerland., Hoelting L; InSphero AG, Schlieren, 8952, Switzerland., Renggli K; Department of Biosystems Science and Engineering, ETH Zurich, Basel, 4058, Switzerland., Frey O; InSphero AG, Schlieren, 8952, Switzerland., Hierlemann A; Department of Biosystems Science and Engineering, ETH Zurich, Basel, 4058, Switzerland.
Jazyk: angličtina
Zdroj: Advanced biosystems [Adv Biosyst] 2020 Nov; Vol. 4 (11), pp. e2000079. Date of Electronic Publication: 2020 Oct 19.
DOI: 10.1002/adbi.202000079
Abstrakt: Drug-drug interactions (DDIs) occur when the pharmacological activity of one drug is altered by a second drug. As multimorbidity and polypharmacotherapy are becoming more common due to the increasing age of the population, the risk of DDIs is massively increasing. Therefore, in vitro testing methods are needed to capture such multiorgan events. Here, a scalable, gravity-driven microfluidic system featuring 3D microtissues (MTs) that represent different organs for the prediction of drug-drug interactions is used. Human liver microtissues (hLiMTs) are combined with tumor microtissues (TuMTs) and treated with drug combinations that are known to cause DDIs in vivo. The testing system is able to capture and quantify DDIs upon co-administration of the anticancer prodrugs cyclophosphamide or ifosfamide with the antiretroviral drug ritonavir. Dosage of ritonavir inhibits hepatic metabolization of the two prodrugs to different extents and decreases their efficacy in acting on TuMTs. The flexible MT compartment design of the system, the use of polystyrene as chip material, and the assembly of several chips in stackable plates offer the potential to significantly advance preclinical substance testing. The possibility of testing a broad variety of drug combinations to identify possible DDIs will improve the drug development process and increase patient safety.
(© 2020 Wiley-VCH GmbH.)
Databáze: MEDLINE
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