Micropatterned Co-Cultures of Human Hepatocytes and Stromal Cells for the Assessment of Drug Clearance and Drug-Drug Interactions

Christine Lin, Salman R Khetani
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引用次数: 13

Abstract

Drug clearance rates from the body can determine drug exposure that can affect efficacy or toxicity. Thus, accurate prediction of drug clearance during preclinical development can help guide dose selection in humans, but animal testing is not always predictive of human outcomes. Because hepatic drug metabolism is a rate-limiting step in the overall clearance of many drugs, primary human hepatocytes (PHHs) in suspension cultures or monolayers are used for drug clearance predictions. Yet, the precipitous decline in drug metabolism capacity can lead to significant underestimation of clearance rates, particularly for low turnover compounds that have desirable one-pill-a-day dosing regimens. In contrast, micropatterned co-cultures (MPCCs) of PHHs and fibroblasts display phenotypic stability for several weeks and can help mitigate the limitations of conventional cultures. Here, we describe protocols to create and use MPCCs for drug clearance predictions, and for modeling clinically-relevant drug-drug interactions that can affect drug clearance. © 2017 by John Wiley & Sons, Inc.

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人肝细胞和基质细胞微模式共培养用于评估药物清除和药物-药物相互作用
药物从体内的清除率可以决定影响药效或毒性的药物暴露。因此,在临床前开发过程中对药物清除率的准确预测可以帮助指导人类的剂量选择,但动物试验并不总是能预测人类的结果。由于肝脏药物代谢是许多药物整体清除的限速步骤,因此悬浮培养或单层的原代人肝细胞(phh)用于药物清除预测。然而,药物代谢能力的急剧下降可能导致对清除率的严重低估,特别是对于具有理想的每天一粒给药方案的低周转率化合物。相比之下,phh和成纤维细胞的微模式共培养(mpcc)在数周内表现出表型稳定性,有助于减轻传统培养的局限性。在这里,我们描述了创建和使用mpcc进行药物清除预测的方案,以及对可能影响药物清除的临床相关药物-药物相互作用进行建模的方案。©2017 by John Wiley &儿子,Inc。
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