Tsamandouras N, Kostrzewski T, Stokes C L, Griffith L G, Hughes D J, Cirit M
Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts (N.T., L.G.G., M.C.); CN Bio Innovations, Hertfordshire, United Kingdom (T.K., D.J.H.); and Stokes Consulting, Redwood City, California (C.L.S.).
Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts (N.T., L.G.G., M.C.); CN Bio Innovations, Hertfordshire, United Kingdom (T.K., D.J.H.); and Stokes Consulting, Redwood City, California (C.L.S.)
J Pharmacol Exp Ther. 2017 Jan;360(1):95-105. doi: 10.1124/jpet.116.237495. Epub 2016 Oct 19.
In this work, we first describe the population variability in hepatic drug metabolism using cryopreserved hepatocytes from five different donors cultured in a perfused three-dimensional 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 six 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 [lactate dehydrogenase (LDH) release, albumin, and urea production]. Drug depletion data were analyzed with mixed-effects modeling. Substantial interdonor variability was observed with respect to gene expression levels, drug metabolism, and other measured hepatocyte functions. Specifically, interdonor 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 cytochrome P450 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 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.
在本研究中,我们首先利用在灌注式三维人肝微生理系统中培养的来自五个不同供体的冷冻保存肝细胞,描述肝脏药物代谢中的群体变异性,然后展示如何将所得数据与建模和模拟框架相结合以实现体外-体内转化。对于每个供体,测量了六种化合物(非那西丁、双氯芬酸、利多卡因、布洛芬、普萘洛尔和泼尼松龙)的代谢消耗曲线,以及代谢物形成、90个与代谢相关基因的mRNA水平和功能活力标志物[乳酸脱氢酶(LDH)释放、白蛋白和尿素生成]。药物消耗数据采用混合效应模型进行分析。在基因表达水平、药物代谢和其他测量的肝细胞功能方面观察到了显著的供体间变异性。具体而言,内在代谢清除率的供体间变异性范围为非那西丁的24.1%至普萘洛尔的66.8%(以变异系数表示)。白蛋白、尿素、LDH和细胞色素P450的mRNA水平被确定为体外代谢清除率的显著预测因子。肝脏微生理系统预测的清除值与观察到的体内值相关。为利多卡因建立了群体生理药代动力学模型,以说明体外输出向观察到的体内药代动力学变异性的转化。使用该模型的随机模拟成功预测了观察到的临床浓度-时间曲线和相关的群体变异性。这是在微生理系统背景下对药物代谢群体变异性的首次研究,对这些系统在药物开发过程中的应用具有重要意义。