Development and Validation of a Sonication-Assisted Dispersive Liquid-Liquid Microextraction Procedure and an HPLC-PDA Method for Quantitative Determination of Zolpidem in Human Plasma and Its Application to Forensic Samples.

The use of z-drugs has increased worldwide since its introduction. Although the prescribing patterns of hypnotics differ among countries, zolpidem is the most widely used z-drug in the world. Zolpidem may be involved in poisoning and deaths. A simple and fast HPLC-PDA method was developed and validated. Zolpidem and the internal standard chloramphenicol were extracted from plasma using a sonication-assisted dispersive liquid-liquid microextraction procedure. The method was validated including selectivity, linearity, precision, accuracy, and recovery. The calibration range (0.15-0.6 µg/mL) covers therapeutic and toxic levels of zolpidem in plasma. The limit of quantification was set at 0.15 µg/mL. Intra- and interday accuracy and precision values were lower than 15% at the concentration levels studied. Excellent recovery results were obtained for all concentrations. The proposed method was successfully applied to ten real postmortem plasma samples. In our series, multiple substances (alcohol and/or other drugs) were detected in most cases of death involving zolpidem. Our analytical method is suitable for routine toxicological analysis.

Evaluation of Physiologically Based Pharmacokinetic Models to Predict the Absorption of BCS Class I Drugs in Different Pediatric Age Groups.

Age-related changes in many parameters affecting drug absorption remain poorly characterized. The objective of this study was to apply physiologically based pharmacokinetic (PBPK) models in pediatric patients to investigate the absorption and pharmacokinetics of 4 drugs belonging to the Biopharmaceutics Classification System (BCS) class I administered as oral liquid formulations. Pediatric PBPK models built with PK-Sim/MoBi were used to predict the pharmacokinetics of acetaminophen, emtricitabine, theophylline, and zolpidem in different pediatric populations. The model performance for predicting drug absorption and pharmacokinetics was assessed by comparing the predicted absorption profile with the deconvoluted dose fraction absorbed over time and predicted with observed plasma concentration-time profiles. Sensitivity analyses were performed to analyze the effects of changes in relevant input parameters on the model output. Overall, most pharmacokinetic parameters were predicted within a 2-fold error range. The absorption profiles were generally reasonably predicted, but relatively large differences were observed for acetaminophen. Sensitivity analyses showed that the predicted absorption profile was most sensitive to changes in the gastric emptying time (GET) and the specific intestinal permeability. The drug's solubility played only a minor role. These findings confirm that gastric emptying time, more than intestinal permeability or solubility, is a key factor affecting BCS class I drug absorption in children. As gastric emptying time is prolonged in the fed state, a better understanding of the interplay between food intake and gastric emptying time in children is needed, especially in the very young in whom the (semi)fed condition is the prevailing prandial state, and hence prolonged gastric emptying time seems more plausible than the fasting state.

Supramolecular solvent (SUPRASs) extraction method for detecting benzodiazepines and zolpidem in human urine and blood using gas chromatography tandem mass spectrometry.

OBJECTIVE: A high-throughput and sensitive method using supramolecular solvent (SUPRASs) for detecting 9 benzodiazepines and zolpidem in human urine and blood by gas chromatography-tandem mass spectrometry (GC-MS/MS) was newly established and applied to authentic human urine and blood samples in this study. METHODS: Urine and blood samples were subjected to liquid-liquid extractions with supramolecular solvent mixture which consists of tetrahydrofuran and 1-hexanol. The solvent layer was evaporated to dryness by stream of nitrogen. The residue was reconstituted with methanol, and subjected to analysis by GC-MS/MS in multiple reaction monitoring (MRM) mode; internal standard method was employed for quantifying of each targeted compound. RESULTS: The regression equation has a good linear relationship with correlation coefficients for all tested compounds were not lower than 0.9991. The lower limits of the quantification ranged from 0.20 to 5 ng/mL for tested compounds in urine; Meanwhile, the lower limits of the quantification in this method ranged from 1 to 50 ng/mL for tested compounds in blood. These results showed that excellent reproducibility and satisfactory extraction recovery rates could be obtained for the established analytical method for 10 drugs in both blood and urine samples. CONCLUSION: The established method in this study was high-throughput, simple and sufficiently sensitive for determining of benzodiazepinesand zolpidem in human urine and blood. Therefore, this newly established method could be of use for qualitative and quantitative determination of such drugs in urine and blood samples either for clinical poisoning monitoring or for forensic identification.

Development and Validation of an LC-MS-MS Method for the Detection of 40 Benzodiazepines and Three Z-Drugs in Blood and Urine by Solid-Phase Extraction.

An analytical method for the detection of 40 benzodiazepines, (±)-zopiclone, zaleplon and zolpidem in blood and urine by solid-phase extraction liquid chromatography-tandem mass spectrometry was developed and validated. Twenty-nine of 43 analytes were quantified in 0.5 mL whole blood for investigating postmortem, drug-facilitated sexual assault (DFSA) and driving under the influence of drugs cases (DUID). The four different dynamic ranges of the seven-point, linear, 1/x weighted calibration curves with lower limits of quantification of 2, 5, 10 and 20 µg/L across the analytes encompassed the majority of our casework encountered in postmortem, DFSA and DUID samples. Reference materials were available for all analytes except α-hydroxyflualprazolam, a hydroxylated metabolite of flualprazolam. The fragmentation of α-hydroxyflualprazolam was predicted from the fragmentation pattern of α-hydroxyalprazolam, and the appropriate transitions were added to the method to enable monitoring for this analyte. Urine samples were hydrolyzed at 55°C for 30 min with a genetically modified ß-glucuronidase enzyme, which resulted in >95% efficiency measured by oxazepam glucuronide. Extensive sample preparation included combining osmotic lysing and protein precipitation with methanol/acetonitrile mixture followed by freezing and centrifugation resulted in exceptionally high signal-to-noise ratios. Bias and between-and within-day imprecision for quality controls (QCs) were all within ±15%, except for clonazolam and etizolam that were within ±20%. All 29 of the 43 analytes tested for QC performance met quantitative reporting criteria within the dynamic ranges of the calibration curves, and 14 analytes, present only in the calibrator solution, were qualitatively reported. Twenty-five analytes met all quantitative reporting criteria including dilution integrity. The ability to analyze quantitative blood and qualitative urine samples in the same batch is one of the most useful elements of this procedure. This sensitive, specific and robust analytical method was routinely employed in the analysis of >300 samples in our laboratory over the last 6 months.

A machine learning approach for handling big data produced by high resolution mass spectrometry after data independent acquisition of small molecules - Proof of concept study using an artificial neural network for sample classification.

Liquid chromatography coupled to high-resolution mass spectrometry (HRMS) enables data independent acquisition (DIA) and untargeted screening. However, to avoid the handling of the resulting large dataset, most laboratories in that field still use targeted screening methods, which offer good sensitivity and specificity but are limited to known compounds. The promising field of machine learning offers new possibilities such as artificial neural networks that can be trained to classify large amounts of data. In this proof of concept study, we exemplify such a machine learning approach for raw HRMS-DIA data files. We evaluated a machine learning model using training, validation, and test sets of solvent and whole blood samples containing drugs (of abuse) common in forensic toxicology. For that purpose, different platforms were used. With a feedforward neural network model architecture, a category prediction (blank sample vs. drug containing sample) was aimed for. With the applied machine learning approaches, the sensitivity and specificity, of the validation and test set, for the prediction of sample classes were in a suitable range for an actual use in a (routine) laboratory (e.g. workplace drug testing). In conclusion, this proof of concept study clearly demonstrated the huge potential of machine learning in the analysis of HRMS-DIA data.

Comparative bioavailability of two zolpidem hemitartrate formulations in healthy human Brazilian volunteers using high-performance liquid chromatography coupled to tandem mass spectrometry.

To assess the bioequivalence of two zolpidem hemitartrate formulations in 30 healthy volunteers. Plasma samples were obtained over a 24 h period. Plasma concentrations of zolpidem were analyzed by liquid chromatography coupled to tandem mass spectrometry with positive ion electrospray ionization using multiple reaction monitoring. Values of peak concentration (Cmax ), area under curve (AUC), half-life, elimination constant, volume of distribution and clearance showed statistically significant differences when comparing women (604.34 ng h/ml, 127.36 ng/ml, 4.4 h, 0.18 1/h, 50.56 L and 8.55 L/h, respectively) and men (276.1 ng h/ml, 70.9 ng/ml, 3.3 h, 0.26 1/h, 91.42 L and 24.34 L/h, respectively), receiving the same dose (5 mg), respectively. The geometric means with corresponding 90% confidence interval for Test/Reference percentage ratios were 99.73% (CI 93.69-106.16) for Cmax, 97.44% (90% CI = 91.85-103.37%) for area under curve of plasma concentration until the last concentration observed (AUClast ) and 98.30% (90% CI = 92.48-104.49) for the area under curve between the first sample (pre-dosage) and infinity (AUC0-inf ). Since the 90% CI for AUClast , AUC0-inf and Cmax ratios were within the 80-125% interval proposed by the US Food and Drug Administration, it was concluded that zolpidem hemitartrate formulation (5 mg orodispersible tablet) is bioequivalent to the zolpidem hemitartrate formulation (Patz SL 5 mg sublingual tablet) with regard to both the rate and the extent of absorption. A new formulation of zolpidem 2.5 mg may be useful in women for the same clinical benefits as the 5 mg formulation in men.

Effects of steady-state clarithromycin on the pharmacokinetics of zolpidem in healthy subjects.

Zolpidem is extensively metabolized by CYP3A4, CYP2C9 and CYP1A2. Previous studies demonstrated that pharmacokinetics of zolpidem was affected by CYP inhibitors, but not by short-term treatment of clarithromycin. The objective of this study was to investigate the effects of steady-state clarithromycin on the pharmacokinetics of zolpidem in healthy subjects. In the control phase, 33 subjects received a single dose of zolpidem (5 mg). One week later, in the clarithromycin phase, the subjects received clarithromycin (500 mg) twice daily for 5 days to reach steady state concentrations, followed by zolpidem (5 mg) and clarithromycin (500 mg). In each phase, plasma concentrations of zolpidem were evaluated up to 12 h after drug administration by using liquid chromatography-tandem mass spectrometry method. In the clarithromycin phase, mean total area under the curve of zolpidem (AUCinf) was 1.62-fold higher and the time to reach peak plasma concentration of zolpidem (tmax) was prolonged by 1.95-fold compared to the control phase. In addition, elimination half-life (t1/2) of zolpidem was 1.40-fold longer during co-administration with clarithromycin and its apparent oral clearance (CL/F) was 36.2% lower with clarithromycin administration. The experimental data demonstrate the significant pharmacokinetic interaction between zolpidem and clarithromycin at steady-state.

Pharmacodynamic and pharmacokinetic profile of SM-1, a triple-drug combination to increase total sleep time.

OBJECTIVE: The primary objective was to characterize the pharmacokinetics and pharmacodynamics of SM-1 after administration of a single oral dose to healthy volunteers in a placebo-controlled double-blind trial of daytime sedation. Secondary objectives were to determine the onset, duration, and offset of the sedative effects using subjective and objective measures of sedation. Safety and tolerability of SM-1 were also investigated. METHODS: Males and females 18-45 years of age received SM-1, a combination drug product comprised of diphenhydramine, zolpidem (delayed release), and lorazepam (delayed release). The pharmacokinetic profile of each drug was determined from blood samples. Sedative effects were assessed by visual analog scale, digit symbol substitution test, memory test, and quantitative electroencephalography. RESULTS: Similar number and severity of adverse events were observed following administration of SM-1 and placebo. Onset of sedation, as determined by subjective, performance, and electroencephalography measures, occurred 0.5-1 hr postdose, lasting about 7-7.5 hr. Plasma concentration curves for the two delayed-release components were altered compared with published data for unmodified drugs. Exposure values obtained with the combination product were in good agreement with published values of the drugs given individually. CONCLUSIONS: SM-1 was well tolerated and has pharmacologic activity starting within an hour of ingestion, lasting approximately 7-8 hr. Sedative activity was seen with subjective, psychomotor, and electroencephalography assays.

Pharmacokinetics, Pharmacodynamics, Safety, and Tolerability of Mirogabalin When Coadministered With Lorazepam, Zolpidem, Tramadol, or Ethanol: Results From Drug-Drug Interaction Studies in Healthy Subjects.

Four randomized, double-blind, placebo-controlled, 4-period drug-drug interaction studies were conducted in healthy subjects to evaluate the pharmacokinetic and pharmacodynamic (PD) interactions between mirogabalin and commonly used central nervous system depressants. Mirogabalin or placebo was administered alone or with single-dose lorazepam, zolpidem, tramadol, ethanol, or interacting drug placebo. Safety was assessed and serial samples for pharmacokinetic parameters were collected for up to 48 hours postdose. PD assessments included body sway (except tramadol), digit symbol substitution test, vertigo symptom scale short form, brief ataxia rating scale, and the Bond and Lader visual analog scale. Coadministration of mirogabalin with any of the 4 drugs did not cause any clinically relevant pharmacokinetic interactions. Peak mirogabalin concentration decreased by 28% (least squares mean ratio, 0.72; 90% confidence interval, [CI] 0.67, 0.76) following tramadol coadministration, and increased by 20% (least squares mean ratio, 1.20; 90%CI, 1.12, 1.28) following ethanol coadministration. Mirogabalin alone had little to no effect on PD parameters, but coadministration of mirogabalin with either lorazepam or ethanol increased the PD effects in body sway and digit symbol substitution test assays. Mirogabalin/lorazepam and mirogabalin/zolpidem increased occurrence of somnolence. Increased incidence of nausea and headache was noted with mirogabalin/tramadol and mirogabalin/ethanol, respectively.