PII-167 - DEVELOPMENT OF A PHYSIOLOGICALLY-BASED PHARMACOKINETIC MODEL FOR VENLAFAXINE AND O-DESMETHYLVENLAFAXINE: ASSESSING THE IMPACT OF CYP2D6, CYP2C9 AND CYP2C19 GENETIC POLYMORPHISMS

X. Pan, K. Yeo; Certara UK Ltd, Simcyp Division.

Background: Venlafaxine is a potent and selective neuronal serotonin-norepinephrine reuptake inhibitor indicated for treating major depressive disorder. Both venlafaxine and its metabolite O-desmethylvenlafaxine (ODV) demonstrate similar antidepressant efficacy; evaluating the total concentration of active compounds (venlafaxine plus ODV) is crucial. Venlafaxine is primarily metabolised via CYP2D6, with minor contributions from CYP2C9 and CYP2C19, leading to the formation of ODV. Subsequently, ODV undergoes CYP3A4-mediated metabolism and renal excretion. Genetic polymorphisms in CYP2D6, CYP2C9, and CYP2C19 can influence venlafaxine metabolism and ODV formation. The primary objective of this research was to develop and validate physiologically-based pharmacokinetic (PBPK) models for venlafaxine and ODV, followed by subsequent assessment of the impact of genetic polymorphisms of CYP2D6, CYP2C9, and CYP2C19.

Methods: Using prior in vitro and in vivo data from the literature, we developed PBPK models for venlafaxine for both immediate-release and extended-release formulations, as well as for ODV.

Results: Our models were verified against the clinical PK studies following single and multiple oral doses, complemented by pharmacogenomic data involving CYP2D6 extensive metabolisers (EMs) and poor metabolisers (PMs). Despite the elevated venlafaxine and reduced ODV exposure observed in CYP2D6 PMs, the total concentration of active compounds remained consistent between CYP2D6 PMs and EMs which was successfully captured by our PBPK models. Clinical drug-drug interaction (DDI) studies with quinidine in CYP2D6 EMs and PMs, cimetidine, ketoconazole in CYP2D6 EMs and PMs, and voriconazole were applied to verify each CYP component within the model. The simulated AUC, Cmax and CL ratios were all within 1.5-fold of the observed data. Collectively, 14 out of 16 predictions fell within 0.8- to 1.25-fold of the observed data. Simulated total active compound AUC values were 1.27-, 1.51-, 1.44-, and 1.82-fold higher in CYP2D6 PMs, CYP2D6/2C9 PMs, CYP2D6/2C19 PMs, and CYP2D6/2C9/2C19 PMs, respectively, compared to all EMs.

Conclusion: In conclusion, our validated PBPK models enable informed dosing decisions and personalised treatment strategies for major depressive disorder, considering genetic polymorphisms.