Quantitative assessment of population variability in hepatic drug metabolism using a perfused 3 D human liver microphysiological system

semanticscholar(2016)

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摘要
This article has not been copyedited and formatted. The final version may differ from this version. Abstract In this work, we first describe the population variability in hepatic drug metabolism using cryopreserved hepatocytes from 5 different donors cultured in a perfused 3D human liver microphysiological system and then show how the resulting data can be integrated with a modeling and simulation framework to accomplish in vitro-in vivo translation. For each donor, metabolic depletion profiles of 6 compounds (phenacetin, diclofenac, lidocaine, ibuprofen, propranolol and prednisolone) were measured, along with metabolite formation, mRNA levels of 90 metabolism-related genes, and markers of functional viability (LDH release, albumin and urea production). Drug depletion data were analyzed with mixed effects modeling. Substantial inter-donor variability was observed with respect to gene expression levels, drug metabolism and other measured hepatocyte functions. Specifically, inter-donor variability in intrinsic metabolic clearance ranged from 24.1% for phenacetin to 66.8% for propranolol (expressed as coefficient of variation). Albumin, urea, LDH and CYP mRNA levels were identified as significant predictors of in vitro metabolic clearance. Predicted clearance values from the liver microphysiological system were correlated with the observed in vivo values. A population physiologically-based pharmacokinetic (PBPK) model was developed for lidocaine to illustrate the translation of the in vitro output to the observed pharmacokinetic variability in vivo. Stochastic simulations with this model successfully predicted the observed clinical concentration-time profiles and the associated population variability. This is the first study of population variability in drug metabolism in the context of a microphysiological system and has important implications for the use of these systems during the drug development process. This article has not been copyedited and formatted. The final version may differ from this version.
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