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通过基于生理的药代动力学模型预测糖尿病患者的药物处置情况。

Prediction of drug disposition in diabetic patients by means of a physiologically based pharmacokinetic model.

作者信息

Li Jia, Guo Hai-Fang, Liu Can, Zhong Zeyu, Liu Li, Liu Xiao-Dong

机构信息

Center of Drug Metabolism and Pharmacokinetics, China Pharmaceutical University, Nanjing, 210009, China.

出版信息

Clin Pharmacokinet. 2015 Feb;54(2):179-93. doi: 10.1007/s40262-014-0192-8.

Abstract

BACKGROUND AND OBJECTIVE

Accumulating evidence has shown that diabetes mellitus may affect the pharmacokinetics of some drugs, leading to alteration of pharmacodynamics and/or toxic effects. The aim of this study was to develop a novel physiologically based pharmacokinetic (PBPK) model for predicting drug pharmacokinetics in patients with type 2 diabetes mellitus quantitatively.

METHODS

Contributions of diabetes-induced alteration of physiological parameters including gastric emptying rates, intestinal transit time, drug metabolism in liver and kidney functions were incorporated into the model. Plasma concentration-time profiles and pharmacokinetic parameters of seven drugs (antipyrine, nisoldipine, repaglinide, glibenclamide, glimepiride, chlorzoxazone, and metformin) in non-diabetic and diabetic patients were predicted using the developed model. The PBPK model coupled with a Monte-Carlo simulation was also used to predict the means and variability of pharmacokinetic parameters.

RESULTS

The predicted area under the plasma concentration-time curve (AUC) and maximum (peak) concentration (C max) were reasonably consistent (<2-fold errors) with the reported values. Sensitivity analysis showed that gut transit time, hepatic enzyme activity, and renal function affected the pharmacokinetic characteristics of these drugs. Shortened gut transit time only decreased the AUC of controlled-released drugs and drugs with low absorption rates. Impairment of renal function markedly altered pharmacokinetics of drugs mainly eliminated via the kidneys.

CONCLUSION

All of these results indicate that the developed PBPK model can quantitatively predict pharmacokinetic alterations induced by diabetes.

摘要

背景与目的

越来越多的证据表明,糖尿病可能会影响某些药物的药代动力学,导致药效学改变和/或毒性作用。本研究的目的是建立一种新型的基于生理的药代动力学(PBPK)模型,用于定量预测2型糖尿病患者的药物药代动力学。

方法

将糖尿病引起的生理参数改变,包括胃排空率、肠道转运时间、肝脏药物代谢和肾功能,纳入模型。使用所建立的模型预测了非糖尿病患者和糖尿病患者中7种药物(安替比林、尼索地平、瑞格列奈、格列本脲、格列美脲、氯唑沙宗和二甲双胍)的血浆浓度-时间曲线和药代动力学参数。还使用结合蒙特卡洛模拟的PBPK模型来预测药代动力学参数的均值和变异性。

结果

预测的血浆浓度-时间曲线下面积(AUC)和最大(峰)浓度(Cmax)与报道值合理一致(误差<2倍)。敏感性分析表明,肠道转运时间、肝酶活性和肾功能影响这些药物的药代动力学特征。缩短肠道转运时间仅降低控释药物和低吸收率药物的AUC。肾功能损害显著改变主要经肾脏消除药物的药代动力学。

结论

所有这些结果表明,所建立的PBPK模型能够定量预测糖尿病引起的药代动力学改变。

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