Korzekwa Ken, Nagar Swati
Pharm Res. 2014 Feb;31(2):335-46. doi: 10.1007/s11095-013-1163-8.
The impact of efflux transporters in intracellular concentrations of a drug can be predicted with modeling techniques. In Part 1, several compartmental models were developed and evaluated. The goal of Part 2 was to apply these models to the characterization and interpretation of saturation kinetic data.
The compartmental models from Part 1 were used to evaluate a previously published dataset from cell lines expressing varying levels of P-glycoprotein. Kinetic parameters for the transporter were estimated and compared across models.
Fits and errors for all compartmental models were identical. All compartmental models predicted more consistent parameters than the Michaelis-Menten model. The 5-compartment model with efflux out of the membrane predicted differential impact of P-gp upon apical versus basolateral drug exposure. Finally, the saturable kinetics of active efflux along with a permeability barrier was modeled to delineate a relationship between intracellular concentration with or without active efflux versus donor concentration. This relationship was not a rectangular hyperbola, but instead was shown to be a quadratic function.
One approach to estimate an in vivo transporter effect is to first model an intracellular Km value from in vitro data, and use this value along with the appropriate tissue transporter expression levels and relative surface area to calculate the relevant apparent Km (or Ki) values. Together with the results from Part 1, these studies suggest that compartmental models can provide a path forward to better utilize in vitro transporter data for in vivo predictions such as physiologically based pharmacokinetic modeling.
可以使用建模技术预测外排转运蛋白对药物细胞内浓度的影响。在第1部分中,开发并评估了几种房室模型。第2部分的目标是将这些模型应用于饱和动力学数据的表征和解释。
使用第1部分中的房室模型评估先前发表的来自表达不同水平P-糖蛋白的细胞系的数据集。估计转运蛋白的动力学参数并在各模型之间进行比较。
所有房室模型的拟合度和误差均相同。所有房室模型预测的参数比米氏模型更一致。具有膜外排的五房室模型预测了P-糖蛋白对顶端与基底外侧药物暴露的不同影响。最后,对主动外排的饱和动力学以及通透性屏障进行建模,以描绘有或无主动外排时细胞内浓度与供体浓度之间的关系。这种关系不是矩形双曲线,而是显示为二次函数。
估计体内转运蛋白效应的一种方法是首先根据体外数据对细胞内Km值进行建模,并使用该值以及适当的组织转运蛋白表达水平和相对表面积来计算相关的表观Km(或Ki)值。与第1部分的结果一起,这些研究表明房室模型可以为更好地利用体外转运蛋白数据进行体内预测(如基于生理学的药代动力学建模)提供一条前进的道路。