Purpose

More accurate prediction of the extent of drug brain exposure in early drug discovery and understanding potential species differences could help to guide medicinal chemistry and avoid unnecessary animal studies. Hence, the aim of the current study was to validate the use of a P-gp transfected LLC-PK1 model to predict the unbound brain-to-plasma concentration ratio (Kp_uu,brain) in rats and humans.

Methods

MOCK-, Mdr1a- and MDR1-transfected LLC-PK1 monolayers were applied in a transwell setup to quantify the bidirectional transport for 12 specific P-gp substrates, 48 UCB drug discovery compounds, 11 compounds with reported rat in situ brain perfusion data and 6 compounds with reported human Kp_uu,brain values. The in vitro transport data were introduced in a minimal PBPK model (SIVA®) to determine the transport parameters. These parameters were combined with the differences between in vitro and in vivo passive permeability as well as P-gp expression levels (as determined by LC-MS/MS), to predict the Kp_uu,brain.

Results

A 10-fold difference between in vitro and in vivo passive permeability was observed. Incorporation of the differences between in vitro and in vivo passive permeability and P-gp expression levels resulted in an improved prediction of rat (AAFE 2.17) and human Kp_uu,brain (AAFE 2.10).

Conclusions

We have succesfully validated a methodology to use a P-gp overexpressing LLC-PK1 cell line to predict both rat and human Kp_uu,brain by correcting for both passive permeability and P-gp expression levels.

中文翻译：

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P-gp转染的LLC-PK1模型中的体外被动通透性对大鼠和人类未绑定脑对血浆浓度比预测的影响。

目的

在早期药物发现中更准确地预测药物脑暴露的程度，并了解潜在的物种差异可能有助于指导药物化学反应并避免不必要的动物研究。因此，本研究的目的是验证使用P-gp转染的LLC-PK1模型预测大鼠和人类的未结合脑与血浆的浓度比（Kp _uu，brain）。

方法

将MOCK-，Mdr1a-和MDR1转染的LLC-PK1单层应用于Transwell装置中，以量化12种特定P-gp底物，48种UCB药物发现化合物，11种具有大鼠原位脑灌注数据的化合物的双向转运具有已报道的人Kp _uu，大脑值的化合物。将体外运输数据引入最小PBPK模型（SIVA®）中，以确定运输参数。将这些参数与体外和体内被动通透性之间的差异以及P-gp表达水平（通过LC-MS / MS确定）相结合，以预测Kp _uu，brain。

结果

观察到体外和体内被动渗透性之间的10倍差异。结合体外和体内被动渗透性和P-gp表达水平之间的差异，导致对大鼠（AAFE 2.17）和人Kp _uu，大脑（AAFE 2.10）的预测得到改善。

结论

我们已成功验证了一种方法，该方法可通过校正被动通透性和P-gp表达水平来使用过表达P-gp的LLC-PK1细胞系预测大鼠和人的Kp _uu，大脑。