Department of Pharmacology and Toxicology, University of Toronto, Toronto, Ontario, Canada.
Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada.
Clin Pharmacol Ther. 2024 May;115(5):1065-1074. doi: 10.1002/cpt.3162. Epub 2024 Jan 29.
In this study, we aimed to improve upon a published population pharmacokinetic (PK) model for venlafaxine (VEN) in the treatment of depression in older adults, then investigate whether CYP2D6 metabolizer status affected model-estimated PK parameters of VEN and its active metabolite O-desmethylvenlafaxine. The model included 325 participants from a clinical trial in which older adults with depression were treated with open-label VEN (maximum 300 mg/day) for 12 weeks and plasma levels of VEN and O-desmethylvenlafaxine were assessed at weeks 4 and 12. We fitted a nonlinear mixed-effect PK model using NONMEM to estimate PK parameters for VEN and O-desmethylvenlafaxine adjusted for CYP2D6 metabolizer status and age. At both lower doses (up to 150 mg/day) and higher doses (up to 300 mg/day), CYP2D6 metabolizers impacted PK model-estimated VEN clearance, VEN exposure, and active moiety (VEN + O-desmethylvenlafaxine) exposure. Specifically, compared with CYP2D6 normal metabolizers, (i) CYP2D6 ultra-rapid metabolizers had higher VEN clearance; (ii) CYP2D6 intermediate metabolizers had lower VEN clearance; (iii) CYP2D6 poor metabolizers had lower VEN clearance, higher VEN exposure, and higher active moiety exposure. Overall, our study showed that including a pharmacogenetic factor in a population PK model could increase model fit, and this improved model demonstrated how CYP2D6 metabolizer status affected VEN-related PK parameters, highlighting the importance of genetic factors in personalized medicine.
在这项研究中,我们旨在改进之前发表的文拉法辛(VEN)治疗老年抑郁症的群体药代动力学(PK)模型,然后研究细胞色素 P450 2D6(CYP2D6)代谢物状态是否影响 VEN 及其活性代谢物 O-去甲文拉法辛(O-desmethylvenlafaxine)的模型估算 PK 参数。该模型纳入了一项临床试验中的 325 名参与者,这些参与者患有抑郁症,接受开放标签文拉法辛(最高 300mg/天)治疗 12 周,在第 4 周和第 12 周评估了 VEN 和 O-去甲文拉法辛的血浆水平。我们使用 NONMEM 拟合非线性混合效应 PK 模型,以估计调整 CYP2D6 代谢物状态和年龄后的 VEN 和 O-去甲文拉法辛的 PK 参数。在较低剂量(最高 150mg/天)和较高剂量(最高 300mg/天)下,CYP2D6 代谢物均影响 PK 模型估算的 VEN 清除率、VEN 暴露量和活性部分(VEN+O-去甲文拉法辛)暴露量。具体而言,与 CYP2D6 正常代谢者相比,(i)CYP2D6 超快代谢者的 VEN 清除率较高;(ii)CYP2D6 中间代谢者的 VEN 清除率较低;(iii)CYP2D6 弱代谢者的 VEN 清除率较低,VEN 暴露量较高,活性部分暴露量较高。总体而言,我们的研究表明,在群体 PK 模型中纳入遗传因素可以提高模型拟合度,并且该改进后的模型表明了 CYP2D6 代谢物状态如何影响 VEN 相关的 PK 参数,突出了遗传因素在个性化医学中的重要性。