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用于预测被动肾小管重吸收和肾排泄清除率的新型最小生理模型。

Novel minimal physiologically-based model for the prediction of passive tubular reabsorption and renal excretion clearance.

作者信息

Scotcher Daniel, Jones Christopher, Rostami-Hodjegan Amin, Galetin Aleksandra

机构信息

Centre for Applied Pharmacokinetic Research, Manchester Pharmacy School, University of Manchester, Manchester, United Kingdom.

Oncology iMed, AstraZeneca, Alderley Park, United Kingdom.

出版信息

Eur J Pharm Sci. 2016 Oct 30;94:59-71. doi: 10.1016/j.ejps.2016.03.018. Epub 2016 Mar 28.

Abstract

PURPOSE

Develop a minimal mechanistic model based on in vitro-in vivo extrapolation (IVIVE) principles to predict extent of passive tubular reabsorption. Assess the ability of the model developed to predict extent of passive tubular reabsorption (F) and renal excretion clearance (CL) from in vitro permeability data and tubular physiological parameters.

METHODS

Model system parameters were informed by physiological data collated following extensive literature analysis. A database of clinical CL was collated for 157 drugs. A subset of 45 drugs was selected for model validation; for those, Caco-2 permeability (P) data were measured under pH6.5-7.4 gradient conditions and used to predict F and subsequently CL. An empirical calibration approach was proposed to account for the effect of inter-assay/laboratory variation in P on the IVIVE of F.

RESULTS

The 5-compartmental model accounted for regional differences in tubular surface area and flow rates and successfully predicted the extent of tubular reabsorption of 45 drugs for which filtration and reabsorption were contributing to renal excretion. Subsequently, predicted CL was within 3-fold of the observed values for 87% of drugs in this dataset, with an overall gmfe of 1.96. Consideration of the empirical calibration method improved overall prediction of CL (gmfe=1.73 for 34 drugs in the internal validation dataset), in particular for basic drugs and drugs with low extent of tubular reabsorption.

CONCLUSIONS

The novel 5-compartment model represents an important addition to the IVIVE toolbox for physiologically-based prediction of renal tubular reabsorption and CL. Physiological basis of the model proposed allows its application in future mechanistic kidney models in preclinical species and human.

摘要

目的

基于体外-体内外推(IVIVE)原理开发一个最小化机制模型,以预测被动肾小管重吸收的程度。评估所开发模型根据体外通透性数据和肾小管生理参数预测被动肾小管重吸收程度(F)和肾排泄清除率(CL)的能力。

方法

通过广泛文献分析整理的生理数据为模型系统参数提供依据。整理了157种药物的临床CL数据库。选择45种药物的子集进行模型验证;对于这些药物,在pH6.5 - 7.4梯度条件下测量Caco - 2通透性(P)数据,并用于预测F,进而预测CL。提出了一种经验校准方法,以考虑P的测定间/实验室差异对F的IVIVE的影响。

结果

五室模型考虑了肾小管表面积和流速的区域差异,并成功预测了45种药物的肾小管重吸收程度,这些药物的滤过和重吸收对肾排泄有贡献。随后,该数据集中87%的药物预测CL在观测值的3倍以内,总体几何平均倍数误差(gmfe)为1.96。考虑经验校准方法改善了CL的总体预测(内部验证数据集中34种药物的gmfe = 1.73),特别是对于碱性药物和肾小管重吸收程度低的药物。

结论

新型五室模型是IVIVE工具箱中基于生理学预测肾小管重吸收和CL的重要补充。所提出模型的生理学基础使其可应用于未来临床前物种和人类的机制性肾脏模型。

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