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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.