Clinical drug-drug interactions: focus on venlafaxine

Glutathione conjugation and protein modification resulting from metabolic activation of venlafaxine in vitro and in vivo

Venlafaxine (VLF), an antidepressant agent, is widely used to combat major depressive disorders, particularly for the treatment of selective serotonin reuptake inhibitor-resistant depression. VLF has been shown to cause liver injury. The present study aimed to investigate the metabolic activation of VLF and explore the mechanisms of hepatotoxicity induced by VLF.One glutathione (GSH) conjugate and one cysteine conjugate were both detected in mouse and human liver microsomal incubations containing VLF and GSH or cysteine. The two conjugates were also detected in cultured mouse primary hepatocytes and bile of rats after exposure to VLF. The in vitro and in vivo studies demonstrated that VLF was metabolized to a quinone methide intermediate reactive to GSH and cysteine residues of hepatic protein. The observed protein covalent binding revealed dose-dependency. The metabolic activation of VLF was P450-dependent, and CYP3A4 was found as the predominant enzyme involved in the bioactivation process.These findings facilitate better understanding of the metabolic activation-hepatotoxicity relationship of VLF and provide chemists with information about new potential structural alerts during drug design process.

Venlafaxine Improves the Cognitive Impairment and Depression-Like Behaviors in a Cuprizone Mouse Model by Alleviating Demyelination and Neuroinflammation in the Brain

Growing evidence has implicated that myelin deficits and neuroinflammation are the coexisted pathological features that contribute to the mood swing and cognitive decline in major depressive disorder (MDD) and multiple sclerosis (MS). Therefore, attenuation of neuroinflammation and reduction of demyelination became newly emerging treatment strategies for the mood and cognitive symptoms. Antidepressant venlafaxine has been used in depression and anxiety through its multiple neuroprotective effects. However, it is unclear whether venlafaxine can improve myelin integrity and alter inflammation status in the brain. By using a well-established cuprizone-induced acute mouse model of demyelination, we investigated the protective effects of venlafaxine on these facets. The cuprizone-fed animals exhibited cognitive impairment and mood disturbances together with myelin loss and prominent neuroinflammation in the brain. Our present study showed that a high dose of venlafaxine alleviated the loss of myelin and oligodendrocytes (OLs), mitigated depression-like behaviors, and improved cognitive function in cuprizone-fed animals. Data from the present study also showed that venlafaxine reduced microglia-mediated inflammation in the brains of cuprizone-fed animals. These findings suggest that venlafaxine may exert its therapeutic effects via facilitating myelin integrity and controlling neuroinflammation, which may provide extra benefits to MS patients with depression and anxiety beyond the symptom management.

Reduced clearance of venlafaxine in a combined treatment with quetiapine

Venlafaxine and the atypical antipsychotic quetiapine are often administered concomitantly. Both drugs share several metabolic hepatic pathways. However, pharmacokinetic interactions between venlafaxine and quetiapine have not been studied yet. A therapeutic drug monitoring database containing serum concentrations of venlafaxine (VEN) and its active metabolite O-desmethylvenlafaxine (ODVEN) was analyzed. Two groups of patients were compared: venlafaxine monotherapy V₀ (n = 153) and co-medication with quetiapine, V_QUE (n = 71). Serum concentrations of VEN, ODVEN, and active moiety, AM (VEN + ODVEN), metabolite to parent compound ratio (ODVEN/VEN) and dose adjusted serum concentrations were compared using non-parametrical tests without information on CYP2D6 genotype. The two groups did not differ in terms of the daily dosage of venlafaxine, age, or sex. Median serum concentrations in the quetiapine group showed significantly, 15.8% and 29.3% higher values for AM and ODVEN (p = 0.002, Cohen's d = 0,41; p = 0.003, d = 0,44), respectively. Dose adjusted serum concentrations of active moiety and ODVEN revealed comparable differences (p = 0.038, d = 0,32; p = 0.015, d = 0,28) with significantly higher values in the co-medicated group. Significantly higher values for ODVEN and AM suggest a reduced clearance of ODVEN and active moiety when quetiapine is co-administered. This may be a consequence of a reduced metabolism of venlafaxine to the inactive metabolite N-desmethylvenlafaxine via CYP3A4, the main metabolizing enzyme for quetiapine, and a shift towards a higher proportion of the active metabolite ODVEN. Therapeutic drug monitoring is recommended in the case of co-medication to ensure clinical efficacy and patient safety. Although the increase of AM is moderate, we consider it relevant for clinicians given the prevalence of concomitant medication of quetiapine and venlafaxine.

Prediction of Drug-Drug Interactions with Bupropion and Its Metabolites as CYP2D6 Inhibitors Using a Physiologically-Based Pharmacokinetic Model

The potential of inhibitory metabolites of perpetrator drugs to contribute to drug-drug interactions (DDIs) is uncommon and underestimated. However, the occurrence of unexpected DDI suggests the potential contribution of metabolites to the observed DDI. The aim of this study was to develop a physiologically-based pharmacokinetic (PBPK) model for bupropion and its three primary metabolites—hydroxybupropion, threohydrobupropion and erythrohydrobupropion—based on a mixed “bottom-up” and “top-down” approach and to contribute to the understanding of the involvement and impact of inhibitory metabolites for DDIs observed in the clinic. PK profiles from clinical researches of different dosages were used to verify the bupropion model. Reasonable PK profiles of bupropion and its metabolites were captured in the PBPK model. Confidence in the DDI prediction involving bupropion and co-administered CYP2D6 substrates could be maximized. The predicted maximum concentration (C_max) area under the concentration-time curve (AUC) values and C_max and AUC ratios were consistent with clinically observed data. The addition of the inhibitory metabolites into the PBPK model resulted in a more accurate prediction of DDIs (AUC and C_max ratio) than that which only considered parent drug (bupropion) P450 inhibition. The simulation suggests that bupropion and its metabolites contribute to the DDI between bupropion and CYP2D6 substrates. The inhibitory potency from strong to weak is hydroxybupropion, threohydrobupropion, erythrohydrobupropion, and bupropion, respectively. The present bupropion PBPK model can be useful for predicting inhibition from bupropion in other clinical studies. This study highlights the need for caution and dosage adjustment when combining bupropion with medications metabolized by CYP2D6. It also demonstrates the feasibility of applying the PBPK approach to predict the DDI potential of drugs undergoing complex metabolism, especially in the DDI involving inhibitory metabolites.

Therapeutic Drug Monitoring of Fluoxetine, Norfluoxetine and Paroxetine: A New Tool Based on Microextraction by Packed Sorbent Coupled to Liquid Chromatography

The present article reports the first liquid chromatography (LC) assay for the simultaneous quantification of fluoxetine (FLU), its metabolite norfluoxetine (NFLU) and paroxetine (PAR) in human plasma, applying the microextraction by packed sorbent (MEPS) technology in sample preparation. Chromatographic analysis of FLU, NFLU and PAR was achieved in <13 min on a reverse-phase C18 column using isocratic elution and fluorescence detection (FLD). The mobile phase was composed by an aqueous solution of 25 mM sodium phosphate monobasic anhydrous and 7.5 mM di-potassium hydrogen phosphate anhydrous (pH 3.0)/acetonitrile/methanol (70:23:7, v/v/v). The detector was set at 240/312 nm for FLU, NFLU and IS and at 295/350 nm for PAR. The method showed linearity in the ranges of 20-750 ng mL-1 for FLU and NFLU, and 5-750 ng mL-1 for PAR (r2 ≥ 0.9919). The overall intra- and interday precision did not exceed 13.6% and the corresponding accuracy (bias) ranged from 0.02 to 16.7%. The method was successfully applied in the analysis of authentic plasma samples. Hence, this new MEPS/LC-FLD assay ensures robust and low-cost analyses representing, therefore, a good alternative to support therapeutic drug monitoring and clinical studies involving these antidepressant drugs.