Only trace amounts of parent benzodiazepines are present in urine following extensive metabolism and conjugation. Thus, hydrolysis of glucuronides is necessary for improved detection. Enzyme hydrolysis is preferred to retain identification specificity, but can be costly and time-consuming. The assessment of a novel recombinant β-glucuronidase for rapid hydrolysis in benzodiazepine urinalysis is presented. Glucuronide controls for oxazepam, lorazepam and temazepam were treated with IMCSzyme™ recombinant β-glucuronidase. Hydrolysis efficiency was assessed at 55°C and at room temperature (RT) using the recommended optimum pH. Hydrolysis efficiency for four other benzodiazepines was evaluated solely with positive patient samples. Maximum hydrolysis of glucuronide controls at 5 min at RT (mean analyte recovery ≥ 94% for oxazepam and lorazepam and ≥ 80% for temazepam) was observed. This was considerably faster than the optimized 30 min incubation time for the abalone β-glucuronidase at 65°C. Mean analyte recovery increased at longer incubation times at 55°C for temazepam only. Total analyte in patient samples compared well to targets from abalone hydrolysis after recombinant β-glucuronidase hydrolysis at RT with no incubation. Some matrix effect, differential reactivity, conjugation variability and transformation impacting total analyte recovery were indicated. The unique potential of the IMCSzyme™ recombinant β-glucuronidase was demonstrated with fast benzodiazepine hydrolysis at RT leading to decreased processing time without the need for heat activation.
Oral fluid testing to assist in the assessment of treatment adherence for chronic pain patients is attractive for a number of reasons. However, efforts focused on interpreting patient results have been modest when compared to urine drug testing. This work details a retrospective approach developed to transform and normalize oral fluid testing results to provide a historical picture of patient values in this important test fluid. Using this approach, a model was developed using data from 6,800 independent patients who were both prescribed hydrocodone and tested positive (with limitations: reporting cutoff < X < upper limit of quantitation) by liquid chromatography-mass spectrometry. Patient demographic data were used to calculate the relevant parameters (e.g., calculated blood volume (CBV)) used in the transformation and normalization of the oral fluid data. The crucial normalizing factor in oral fluids was found to be the CBV which parallels the use of creatinine to normalize drug concentration levels in urine and is consistent with the view that oral fluid samples reflect plasma concentrations of the respective drugs. The resulting near Gaussian distribution is dose independent and as such should be of value to physicians in quickly assessing whether their patient is consistent with this historical population in the broad terms of this model. While this comparison alone is not definitive for adherence with a treatment regimen, together with patient interviews, prescription history and other clinical criteria, it can add an idea of expected patient values from oral fluid testing.
The analytical assay produced by Ameritox, Ltd using Ultra Performance Liquid Chromatography-Tandem Mass Spectrometry can qualitatively detect antipsychotics in human urine specimens. The present study highlights the potential utility of the urine assay to help monitor adherence to antipsychotic medications.
Treatment adherence is often an issue with mental health patients. For those prescribed quetiapine (Seroquel), the low levels of parent drug and plasma metabolite(s) (e.g., 7-hydroxyquetiapine) typically used in urine drug monitoring can result in false negatives with concomitant unfavorable impacts on patient care. Literature review coupled with liquid chromatography/time-of-flight mass spectrometry analysis of patient positive urine samples indicated the presence of quetiapine carboxylic acid and quetiapine sulfoxide as significant urinary metabolites of quetiapine. Analysis of these two metabolites determined that they are abundant in the urine of quetiapine patients and can result in apparent adherence rates that are improved relative to those determined using only quetiapine and 7-hydroxyquetiapine. For example, analysis of a random set of 114 patients who were prescribed quetiapine exhibited an apparent adherence rate of 47% using the quetiapine carboxylic acid and quetiapine sulfoxide metabolites. Traditional metabolite testing with quetiapine and 7-hydroxyquetiapine yielded apparent adherence rates of ~31% while all four analytes resulted in apparent adherence of 48%. The prevalence of these metabolites suggests that quetiapine urine drug testing would be more consistent with prescriptions when they are included in the analysis.
ObjectiveThe aim of this study is to assess urine levels of aripiprazole and metabolites among patients receiving steady-state dosing of aripiprazole.MethodsOne hundred fifty adults, judged compliant with a stable aripiprazole regimen, had observed dosing for 5 consecutive days. Urine specimens, obtained on days 1, 4, and 5, were analyzed for pH, creatinine, specific gravity, and for aripiprazole, OPC3373, and dehydroaripiprazole. Linear regression was used to assess the association between unadjusted urine levels of each drug/metabolite and dose taken, and linear stepwise multiple regression was performed to identify variables that added to the explanation of the variance.ResultsOPC3373 was found in 97 % of urine samples, whereas unchanged aripiprazole and dehydroaripiprazole were found in only 58 and 39 % of samples, respectively. Variance in urine metabolite levels accounted for by medication dose was relatively low for each individual drug/metabolite, r2 only 0.13 to 0.23. However, when OPC3373 was adjusted for age, weight, sex, and urine creatinine values, the r2 improved to 0.63, and further improved to 0.70, when height, urine specific gravity, and the presence of dehydroaripiprazole were added in a stepwise multiple regression model.ConclusionsUnadjusted urine levels of aripiprazole and metabolites are not strongly related to aripiprazole dosing, however, accounting for key variables yields a strong relationship between measurable urine parameters and dose taken. By defining the expected range of adjusted urine levels for each dose, the potential exists for a clinical test to identify partially nonadherent individuals who would not have been identified by conventional “present vs. absent” urine drug testing.
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