文
CYP2D6型
药代动力学
医学
药理学
非金属
人口
药物遗传学
活性代谢物
内科学
化学
细胞色素P450
基因型
新陈代谢
环境卫生
基因
生物化学
计算机科学
计算机安全
作者
Xiaoyu Men,Zachary L. Taylor,Victoria Marshe,Daniel M. Blumberger,Jordan F. Karp,James L. Kennedy,Eric J. Lenze,Charles F. Reynolds,Cristiana Stefan,Benoit H. Mulsant,Laura B. Ramsey,Daniel J. Müller
摘要
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.
科研通智能强力驱动
Strongly Powered by AbleSci AI