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用于预测药物肝代谢清除率的体外-体内外推方法的比较评估。

Comparative assessment of In Vitro-In Vivo extrapolation methods used for predicting hepatic metabolic clearance of drugs.

机构信息

Consultant, 4009 Sylvia Daoust, Québec City, Québec G1X 0A6, Canada.

出版信息

J Pharm Sci. 2012 Nov;101(11):4308-26. doi: 10.1002/jps.23288. Epub 2012 Aug 13.

Abstract

The purpose of this study was to perform a comparative analysis of various in vitro--in vivo extrapolation (IVIVE) methods used for predicting hepatic metabolic clearance (CL) of drugs on the basis of intrinsic CL data determined in microsomes. Five IVIVE methods were evaluated: the "conventional and conventional bias-corrected methods" using the unbound fraction in plasma (fu(p) ), the "Berezhkovskiy method" in which the fu(p) is adjusted for drug ionization, the "Poulin et al. method" using the unbound fraction in liver (fu(liver) ), and the "direct scaling method," which does not consider any binding corrections. We investigated the effects of the following scenarios on the prediction of CL: the use of preclinical or human datasets, the extent of plasma protein binding, the magnitude of CL in vivo, and the extent of drug disposition based on biopharmaceutics drug disposition classification system (BDDCS) categorization. A large and diverse dataset of 139 compounds was collected, including those from the literature and in house from Genentech. The results of this study confirm that the Poulin et al. method is robust and showed the greatest accuracy as compared with the other IVIVE methods in the majority of prediction scenarios studied here. The difference across the prediction methods is most pronounced for (a) albumin-bound drugs, (b) highly bound drugs, and (c) low CL drugs. Predictions of CL showed relevant interspecies differences for BDDCS class 2 compounds; the direct scaling method showed the greatest predictivity for these compounds, particularly for a reduced dataset in rat that have unexpectedly high CL in vivo. This result is a reflection of the direct scaling method's natural tendency to overpredict the true metabolic CL. Overall, this study should facilitate the use of IVIVE correlation methods in physiologically based pharmacokinetics (PBPK) model.

摘要

本研究的目的是基于在微粒体中测定的内在 CL 数据,对用于预测药物肝代谢清除率 (CL) 的各种体外-体内外推 (IVIVE) 方法进行比较分析。评估了五种 IVIVE 方法:使用血浆中未结合分数 (fu(p)) 的“常规和常规偏倚校正方法”、调整药物离解的 fu(p) 的 Berezhkovskiy 方法、使用肝中未结合分数 (fu(liver)) 的 Poulin 等人方法,以及不考虑任何结合校正的“直接缩放方法”。我们研究了以下情况对 CL 预测的影响:使用临床前或人体数据集、血浆蛋白结合程度、体内 CL 的幅度以及基于生物药剂学药物处置分类系统 (BDDCS) 分类的药物处置程度。收集了一个包含 139 种化合物的大型和多样化数据集,包括文献中的化合物和来自 Genentech 的化合物。本研究的结果证实,Poulin 等人方法具有稳健性,并且在大多数研究的预测情况下,与其他 IVIVE 方法相比,表现出最高的准确性。预测方法之间的差异在以下方面最为明显:(a) 白蛋白结合药物、(b) 高度结合药物和 (c) CL 低的药物。BDDCS 类别 2 化合物的 CL 预测显示出相关的种间差异;直接缩放方法对这些化合物表现出最大的预测能力,尤其是对于在大鼠中具有出乎意料的高体内 CL 的减少数据集。这一结果反映了直接缩放方法自然倾向于过高预测真实代谢 CL。总体而言,本研究应有助于 IVIVE 相关方法在生理相关药代动力学 (PBPK) 模型中的应用。

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