Objective

The objective of this study was to compare the predictive performances of a glomerular filtration rate (GFR) model with a physiologically based pharmacokinetic (PBPK) model to predict total or renal clearance or area under the curve of renally excreted drugs in subjects with varying degrees of renal impairment.

Methods

From the literature, 11 studies were randomly selected in which total or renal clearance or area under the curve of drugs in subjects with different degrees of renal impairment were predicted by PBPK models. In these published studies, drugs were given to subjects intravenously or orally. The PBPK model was generally a whole-body model whereas the GFR model was as follows: Predicted total clearance (CL_T) = CL_T in healthy subjects × (GFR in RI/GFR in H), Predicted AUC = AUC in healthy subjects × (GFR in H/GFR in RI), where H is the healthy subjects and RI is renal impairment. The predicted clearance or area under the curve values using PBPK and GFR models were compared with the observed (experimental pharmacokinetic) values. The acceptable prediction error was within the 0.5- to 2-fold or 0.5- to 1.5-fold prediction error.

Results

There were 33 drugs with a total number of 101 observations (area under the curve, total and renal clearance in subjects with mild, moderate, and severe renal impairment). From PBPK and GFR models, out of 101 observations, 94 (93.1%) and 96 (95.0%) observations were within the 0.5- to 2-fold prediction error, respectively.

Conclusions

This study indicates that the predictive power of a simple GFR model is similar to a PBPK model for the prediction of clearance or area under the curve in subjects with renal impairment. The GFR method is simple, robust, and reliable and can replace complex empirical PBPK models.

中文翻译：

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一种基于 GFR 的方法来预测肾功能损害对肾排泄药物暴露或清除的影响：简单 GFR 方法与基于生理学的药代动力学模型之间的比较研究

客观的

本研究的目的是比较肾小球滤过率 (GFR) 模型与基于生理学的药代动力学 (PBPK) 模型的预测性能，以预测具有不同程度肾功能不全的受试者的总或肾脏清除率或肾脏排泄药物的曲线下面积。肾功能不全。

方法

从文献中随机选取了11项研究，其中通过PBPK模型预测了不同程度肾功能损害受试者的总或肾清除率或药物曲线下面积。在这些已发表的研究中，药物是通过静脉注射或口服给药的。PBPK模型一般是全身模型，而GFR模型如下：预测总清除率（CL _T）=健康受试者的CL _T ×（RI的GFR/H的GFR），预测的AUC =健康受试者的AUC × （H 中的 GFR/RI 中的 GFR），其中H是健康受试者，RI是肾功能不全。将使用 PBPK 和 GFR 模型的预测清除率或曲线下面积值与观察到的（实验药代动力学）值进行比较。可接受的预测误差在 0.5 至 2 倍或 0.5 至 1.5 倍的预测误差内。

结果

共有 33 种药物，总共有 101 个观察值（曲线下面积、轻度、中度和重度肾功能不全受试者的总清除率和肾清除率）。从 PBPK 和 GFR 模型中，在 101 个观察中，分别有 94 个（93.1%）和 96 个（95.0%）在 0.5 到 2 倍的预测误差范围内。

结论

该研究表明，简单 GFR 模型的预测能力类似于 PBPK 模型，用于预测肾功能不全受试者的清除率或曲线下面积。GFR 方法简单、稳健且可靠，可以替代复杂的经验 PBPK 模型。