Division of Clinical Pharmacology and Toxicology, Geneva University Hospitals, Geneva, Switzerland.
Geneva-Lausanne School of Pharmacy, Geneva University, Geneva, Switzerland.
CPT Pharmacometrics Syst Pharmacol. 2019 Aug;8(8):567-576. doi: 10.1002/psp4.12411. Epub 2019 Jul 3.
The aim of this work was to predict the extent of Cytochrome P450 2D6 (CYP2D6)-mediated drug-drug interactions (DDIs) in different CYP2D6 genotypes using physiologically-based pharmacokinetic (PBPK) modeling. Following the development of a new duloxetine model and optimization of a paroxetine model, the effect of genetic polymorphisms on CYP2D6-mediated intrinsic clearances of dextromethorphan, duloxetine, and paroxetine was estimated from rich pharmacokinetic profiles in activity score (AS)1 and AS2 subjects. We obtained good predictions for the dextromethorphan-duloxetine interaction (Ratio of predicted over observed area under the curve (AUC) ratio (R ) 1.38-1.43). Similarly, the effect of genotype was well predicted, with an increase of area under the curve ratio of 28% in AS2 subjects when compared with AS1 (observed, 33%). Despite an approximately twofold underprediction of the dextromethorphan-paroxetine interaction, an R of 0.71 was obtained for the effect of genotype on the area under the curve ratio. Therefore, PBPK modeling can be successfully used to predict gene-drug-drug interactions (GDDIs). Based on these promising results, a workflow is suggested for the generic evaluation of GDDIs and DDIs that can be applied in other situations.
本研究旨在通过基于生理的药代动力学（PBPK）模型预测不同 CYP2D6 基因型中细胞色素 P450 2D6（CYP2D6）介导的药物-药物相互作用（DDI）的程度。在开发新的度洛西汀模型和优化帕罗西汀模型之后，从活性评分（AS）1 和 AS2 受试者的丰富药代动力学特征中估算了遗传多态性对去甲右美沙芬、度洛西汀和帕罗西汀 CYP2D6 介导的内在清除率的影响。我们对去甲右美沙芬-度洛西汀相互作用（预测与观察的 AUC 比值的比值（R）1.38-1.43）进行了良好的预测。同样，基因型的影响也得到了很好的预测，与 AS1 相比，AS2 受试者的 AUC 比值增加了 28%（观察值为 33%）。尽管去甲右美沙芬-帕罗西汀相互作用的预测值约低两倍，但基因型对 AUC 比值的影响的 R 为 0.71。因此，PBPK 模型可成功用于预测基因-药物-药物相互作用（GDDI）。基于这些有希望的结果，提出了一种用于一般评估 GDDI 和 DDI 的工作流程，可应用于其他情况。
