MSACL 2023 Abstract

INTRODUCTION

Venlafaxine (VEN) and its O-demethylated metabolite, O-desmethylvenlafaxine (ODV), are commonly prescribed serotonin-norepinephrine reuptake inhibitors, approved for the treatment of depression and anxiety. Both VEN and ODV have similar antidepressant activity and their three metabolites formed by further demethylation (N-desmethylvenlafaxine (NDV), N,O-didesmethylvenlafaxine (NODDV), and N,N-didesmethylvenlafaxine (NNDDV)) are inactive. This metabolism is accomplished by CYP450 enzymes, namely CYP2D6, CYP3A4, and CYP2C19, all of which are polymorphic and can be inhibited or activated by foods and other drugs. At standard dosing levels, approximately 40% of patients have VEN and ODV concentrations outside the therapeutic range, demonstrating the potential clinical value of quantifying these drugs.

OBJECTIVES

The objectives of this study were to develop and validate a quantitative tandem mass spectrometry method for venlafaxine, desvenlafaxine, and their three inactive metabolites. A secondary objective was to quantify these molecules in remnant patient plasma and observe the relationship between administered drug and metabolites.

METHODS

K2EDTA plasma was spiked with VEN, ODV, NDV, NODDV, and NNDDV. Remnant whole blood from patients prescribed venlafaxine was obtained and plasma was obtained by centrifugation. Collection of remnant whole blood was approved by the IRB. Following the addition of isotopically-labeled internal standards (VEN-d6 and ODV-d6) to plasma and sample extraction via protein precipitation, samples were subjected to analysis by liquid chromatography-tandem mass spectrometry. Chromatographic separation was performed using a ZORBAX Eclipse Plus C18 column and detected on a SCIEX API 4500 mass analyzer operated in positive ionization mode.

RESULTS

The analytical measuring range for VEN and all four metabolites was 5 – 800 ng/mL. Standard curves were generated via weighted quadratic (NNDDV) or linear (VEN, ODV, NDV, NODDV) regression of calibrators. Inter-assay imprecision was less than 10% for all levels of all analytes. No carryover was observed after repeated injections of sample at upper limit of measuring range and no cross-talk was observed between any analyte or internal standard. Only minor matrix effects were observed and both recovery efficiency and process efficiency were >96% for all analytes. Twenty-one remnant plasma specimens were obtained from patients with current venlafaxine prescriptions (prescribed doses of 37.5 – 450 mg/day) and analyzed with this method. VEN and ODV were quantified in all samples, with concentrations ranging from 7-1200 ng/mL. NODDV was quantified in all but one sample and ranged from 10.2 to 430 ng/mL. NDV and NNDDV were quantified in 14 and 6 samples, respectively, at concentrations up to 1060 and 168 ng/mL, respectively. The ratio of total active to total inactive analytes ranged from 0.74 to 14.5, with a median of 6.39.

CONCLUSION

While previous studies have focused on quantifying VEN and ODV, fewer studies have evaluated the contribution of metabolism to the inactive metabolites to the overall pharmacokinetics of these antidepressants. This effort developed an efficient and accurate method for the quantification of VEN, ODV, and all three inactive metabolites in human plasma and demonstrated this capacity in remnant human samples. This method’s performance fulfills the criteria for an FDA Bioanalytical Method and may be used to study the pharmacokinetics of these drugs and metabolites. Additionally, these validation studies demonstrate that this method is suitable for analysis of patient samples. Although the time of dosing relative to the blood collection was not captured, all patients had been prescribed daily doses of venlafaxine for more than 10 days, during which time a daily dose would reach a steady state concentration. In agreement with published reports, ODV was the major metabolite present in most samples (18 of 21). Evaluation of the ratios of active analytes VEN and ODV to the inactive metabolites demonstrates wide inter-individual variation in metabolism. Importantly, this method enables further studies combining drug and metabolite quantification with pharmacogenetic evaluation of metabolizing genes. Future clinical studies can be performed to probe the impact of utilizing VEN and metabolite monitoring on therapeutic efficacy.