Metabolism enzyme induction-mediated drug-drug interactions need to be carefully characterized in vitro for drug candidates to predict in vivo safety risk and therapeutic efficiency. Currently, both the Food and Drug Administration and European Medicines Agency recommend using primary human hepatocytes as the gold standard in vitro test system for studying the induction potential of candidate drugs on cytochrome P450 (CYP), CYP3A4, CYP1A2, and CYP2B6. However, primary human hepatocytes are known to bear inherent limitations such as limited supply and large lot-to-lot variations, which result in an experimental burden to qualify new lots. To overcome these shortcomings, a renewable source of human hepatocytes (i.e., Corning HepatoCells) was developed from primary human hepatocytes and was evaluated for in vitro CYP3A4 induction using methods well established by the pharmaceutical industry. HepatoCells have shown mature hepatocyte-like morphology and demonstrated primary hepatocyte-like response to prototypical inducers of all three CYP enzymes with excellent consistency. Importantly, HepatoCells retain a phenobarbital-responsive nuclear translocation of human constitutive androstane receptor from the cytoplasm, characteristic to primary hepatocytes. To validate HepatoCells as a useful tool to predict potential clinical relevant CYP3A4 induction, we tested three different lots of HepatoCells with a group of clinical strong, moderate/weak CYP3A4 inducers, and noninducers. A relative induction score calibration curve-based approach was used for prediction. HepatoCells showed accurate prediction comparable to primary human hepatocytes. Together, these results demonstrate that Corning HepatoCells is a reliable in vitro model for drug-drug interaction studies during the early phase of drug testing.
Evaluation of a Novel Renewable Hepatic Cell Model for Prediction of Clinical CYP3A4 Induction Using a Correlation-Based Relative Induction Score Approach.
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作者:Zuo Rongjun, Li Feng, Parikh Sweta, Cao Li, Cooper Kirsten L, Hong Yulong, Liu Jin, Faris Ronald A, Li Daochuan, Wang Hongbing
| 期刊: | Drug Metabolism and Disposition | 影响因子: | 4.000 |
| 时间: | 2017 | 起止号: | 2017 Feb;45(2):198-207 |
| doi: | 10.1124/dmd.116.072124 | ||
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