Simon Florian, Gautier-Veyret Elodie, Truffot Aurélie, Chenel Marylore, Payen Léa, Stanke-Labesque Françoise, Tod Michel
EA3738, Faculté de médecine de Lyon-Sud, Université de Lyon 1, 69921, Université de Lyon 1, Oullins cedex, France.
Laboratoire de biochimie-toxicologie, Centre hospitalier Lyon-Sud, Hospices civils de Lyon, Pierre Bénite, Lyon, France.
Pharm Res. 2021 Mar;38(3):415-428. doi: 10.1007/s11095-021-03019-7. Epub 2021 Mar 8.
For decades, inflammation has been considered a cause of pharmacokinetic variability, mainly in relation to the inhibitory effect of pro-inflammatory cytokines on the expression level and activity of cytochrome P450 (CYP). In vitro and clinical studies have shown that two major CYPs, CYP2C19 and CYP3A4, are both impaired. The objective of the present study was to quantify the impact of the inflammatory response on the activity of both CYPs in order to predict the pharmacokinetic profile of their substrates according to systemic C-reactive protein (CRP).
The relationships between CRP concentration and both CYPs activities were estimated and validated using clinical data first on midazolam then on voriconazole. Finally, clinical data on omeprazole were used to validate the findings. For each substrate, a physiologically based pharmacokinetics model was built using a bottom-up approach, and the relationships between CRP level and CYP activities were estimated by a top-down approach. After incorporating the respective relationships, we compared the predictions and observed drug concentrations.
Changes in pharmacokinetic profiles and parameters induced by inflammation seem to be captured accurately by the models.
These findings suggest that the pharmacokinetics of CYP2C19 and CYP3A4 substrates can be predicted depending on the CRP concentration.
几十年来,炎症一直被认为是药代动力学变异性的一个原因,主要与促炎细胞因子对细胞色素P450(CYP)表达水平和活性的抑制作用有关。体外和临床研究表明,两种主要的细胞色素P450酶,即CYP2C19和CYP3A4,都会受到影响。本研究的目的是量化炎症反应对这两种细胞色素P450酶活性的影响,以便根据全身C反应蛋白(CRP)预测其底物的药代动力学特征。
首先使用咪达唑仑的临床数据,然后使用伏立康唑的临床数据,估计并验证CRP浓度与两种细胞色素P450酶活性之间的关系。最后,使用奥美拉唑的临床数据来验证研究结果。对于每种底物,采用自下而上的方法建立基于生理学的药代动力学模型,并通过自上而下的方法估计CRP水平与细胞色素P450酶活性之间的关系。纳入各自的关系后,我们比较了预测值和观察到的药物浓度。
炎症引起的药代动力学特征和参数变化似乎能被模型准确捕捉。
这些发现表明,可根据CRP浓度预测CYP2C19和CYP3A4底物的药代动力学。