Stringer R, Nicklin P L, Houston J B
Novartis Institutes for Biomedical Research, Horsham, UK.
Xenobiotica. 2008 Oct;38(10):1313-29. doi: 10.1080/00498250802446286.
A total of 110 drugs, selected to cover a range of physicochemical and pharmacokinetic properties, were used to explore standard approaches to the prediction of in vivo metabolic clearance using drug-depletion profiles from human liver microsomes (HLMs) and cyropreserved hepatocytes. A total of 41 drugs (37% of the compounds tested) showed measurable depletion rates using HLMs (depletion by 20% or more over the time course). The most reliable correlations in terms of bias (average fold error (AFE) = 2.32) and precision (root mean square error (RMSE) = 3501) were observed by comparing in vivo intrinsic clearance (CL(int)), calculated using the parallel-tube model and incorporating the fraction unbound in blood, with in vitro CL(int) adjusted for microsomal binding. For these reference drugs, 29% of predictions were within two-fold of the observed values and 66% were within five-fold. Compared with HLMs, clearance predictions with cryopreserved hepatocytes (57 drugs) were of similar precision (RMSE = 3608) but showed more bias (AFE = 5.21) with 18% of predictions within two-fold of the observed values and 46% within five-fold. However, with a broad complement of drug-metabolizing enzymes, hepatocytes catalysed measurable CL(int) values for a greater proportion (52%) of the reference compounds and were particularly proficient at defining metabolic rates for drugs with predominantly phase 2 metabolic routes.
共选用了110种药物,这些药物涵盖了一系列物理化学和药代动力学特性,用于探索利用人肝微粒体(HLM)和冷冻保存的肝细胞中的药物消耗曲线预测体内代谢清除率的标准方法。共有41种药物(占测试化合物的37%)在使用HLM时显示出可测量的消耗率(在整个时间过程中消耗20%或更多)。通过比较使用平行管模型并纳入血液中未结合分数计算的体内固有清除率(CL(int))与针对微粒体结合进行调整的体外CL(int),观察到在偏差(平均倍数误差(AFE)=2.32)和精密度(均方根误差(RMSE)=3501)方面最可靠的相关性。对于这些参考药物,29%的预测值在观察值的两倍以内,66%在五倍以内。与HLM相比,冷冻保存的肝细胞(57种药物)的清除率预测具有相似的精密度(RMSE=3608),但偏差更大(AFE=5.21),18%的预测值在观察值的两倍以内,46%在五倍以内。然而,由于肝细胞具有广泛的药物代谢酶,其催化了更大比例(52%)的参考化合物的可测量CL(int)值,并且在确定主要具有2期代谢途径的药物的代谢率方面特别熟练。