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具有一级吸收的单室模型是一种有用的近似模型吗?

Is the One-Compartment Model with First Order Absorption a Useful Approximation?

作者信息

Weiss Michael

机构信息

Department of Pharmacology, Martin Luther University Halle-Wittenberg, Halle, Germany.

出版信息

Pharm Res. 2023 Sep;40(9):2147-2153. doi: 10.1007/s11095-023-03582-1. Epub 2023 Aug 18.

Abstract

PURPOSE

The one-compartment model with first order absorption (ka1C) has been extensively used to fit oral data. But when the disposition parameters of the drug are not available, the bias in the parameter estimates remains unclear. In this paper, the effect of potential misspecification of the area under the curve (AUC) and the mean absorption time (MAT) was evaluated for three relatively slowly absorbed drugs/formulations.

METHODS

Assuming a three-compartment disposition model with an input (absorption) rate described as a sum of two inverse Gaussian functions (2IG3C) as the true model, the deviations of AUC and MAT estimated with simpler models were analyzed. Simpler models, as the ka1C model (Bateman function), the one-compartment model with IG input function (IG1C) and the gamma density function were fitted to the oral data alone, and compared to the fits obtained with the 2IG3C model which also uses the 3C disposition parameters of the drug. Data from pharmacokinetic studies of trospium, propiverine and ketamine in healthy volunteers were analyzed using a population approach.

RESULTS

The Bateman function (ka1C) allowed a robust estimation of the population mean AUC, but the individual estimates were highly biased. It failed in evaluating MAT. The simple alternative models did not improve the situation.

CONCLUSIONS

The Bateman function appears to be useful for estimating the population mean value of AUC after oral administration. The results reemphasize the fact that insight into the absorption process can be only gained when also intravenous reference data are available.

摘要

目的

具有一级吸收的单室模型(ka1C)已被广泛用于拟合口服数据。但是,当药物的处置参数不可用时,参数估计中的偏差仍不明确。本文评估了三种吸收相对缓慢的药物/制剂在曲线下面积(AUC)和平均吸收时间(MAT)潜在错误指定的影响。

方法

假设以两个逆高斯函数之和(2IG3C)描述输入(吸收)速率的三室处置模型为真实模型,分析用更简单模型估计的AUC和MAT的偏差。更简单的模型,如ka1C模型(贝特曼函数)、具有IG输入函数的单室模型(IG1C)和伽马密度函数,单独拟合口服数据,并与使用药物的3C处置参数的2IG3C模型得到的拟合结果进行比较。采用群体方法分析了健康志愿者中曲司氯铵、丙哌维林和氯胺酮的药代动力学研究数据。

结果

贝特曼函数(ka1C)能够可靠地估计群体平均AUC,但个体估计存在高度偏差。它在评估MAT方面失败了。简单的替代模型并没有改善这种情况。

结论

贝特曼函数似乎可用于估计口服给药后AUC的群体平均值。结果再次强调了只有当也有静脉参考数据时才能深入了解吸收过程这一事实。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c811/10547630/3ffc0eae17b1/11095_2023_3582_Fig1_HTML.jpg

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