Enantioselective pharmacokinetics of tramadol and its three main metabolites; impact of CYP2D6, CYP2B6, and CYP3A4 genotype

Tramadol is a complex drug, being metabolized by polymorphic enzymes and administered as a racemate with the (+)- and (−)-enantiomers of the parent compound and metabolites showing different pharmacological effects. The study aimed to simultaneously determine the enantiomer concentrations of tramadol, O-desmethyltramadol, N-desmethyltramadol, and N,O-didesmethyltramadol following a single dose, and elucidate if enantioselective pharmacokinetics is associated with the time following drug intake and if interindividual differences may be genetically explained. Nineteen healthy volunteers were orally administered either 50 or 100 mg tramadol, whereupon blood samples were drawn at 17 occasions. Enantiomer concentrations in whole blood were measured by LC-MS/MS and the CYP2D6, CYP2B6 and CYP3A4 genotype were determined, using the xTAG CYP2D6 Kit, pyrosequencing and real-time PCR, respectively. A positive correlation between the (+)/(−)-enantiomer ratio and time following drug administration was shown for all four enantiomer pairs. The largest increase in enantiomer ratio was observed for N-desmethyltramadol in CYP2D6 extensive and intermediate metabolizers, rising from about two to almost seven during 24 hours following drug intake. CYP2D6 poor metabolizers showed metabolic profiles markedly different from the ones of intermediate and extensive metabolizers, with large area under the concentration curves (AUCs) of the N-desmethyltramadol enantiomers and low corresponding values of the O-desmethyltramadol and N,O-didesmethyltramadol enantiomers, especially of the (+)-enantiomers. Homozygosity of CYP2B6 *5 and *6 indicated a reduced enzyme function, although further studies are required to confirm it. In conclusion, the increase in enantiomer ratios over time might possibly be used to distinguish a recent tramadol intake from a past one. It also implies that, even though (+)-O-desmethyltramadol is regarded the enantiomer most potent in causing adverse effects, one should not investigate the (+)/(−)-enantiomer ratio of O-desmethyltramadol in relation to side effects without consideration for the time that has passed since drug intake

Smoking as a product of gene–environment interaction

A strong hereditary influence on smoking has been demonstrated. As one of the candidate genes in relation to smoking, the serotonin transporter gene (5-HTTLPR) has been suggested, however with conflicting results. In recent studies, it has been shown that genotypic and environmental (G*E) factors interact in the shaping of a variety of phenotypic expressions. The objective of the present study was to investigate the interaction between a variation in the 5-HTTLPR and family environment in relation to smoking habits, nicotine dependence, and nicotine and cotinine levels in hair samples

Separation of Sympathomimetic Amines of Abuse and Related Compounds by Micellar Electrokinetic Chromatography

Separation of twelve sympathomimetic amines and related compounds by micellar electrokinetic chromatography (MEKC) with UV absorbance detection is described. These amines were well separated within 25 min using 50 mM sodium tetraborate solution containing 15 mM sodium dodecylsulfate (SDS) of pH 9.3 as a running solution and detected at 210 nm. MEKC was performed with an applied voltage of 13 kV at 25 °C using a fused-silica capillary (50 cm×75 mm i.d.) with effective length of 37.5 cm. The detection limits of these compounds were in the range from 4 to 97 fmol/injection at a signal-to-noise ratio (S/N) of 3. The reproducibility of the method expressed as relative standard deviation (RSD) for within-day (n=6) and between-day (n=5) assays was less than 4.8 and 8.8%, respectively. The proposed method could be applied to the determination of an anorectic drug, phentermine, in Chinese tea with a detection limit of 99 μg/g (105 fmol/injection, S/N=3)

A review of bioanalytical techniques for evaluation of cannabis (Marijuana, weed, Hashish) in human hair

Cannabis products (marijuana, weed, hashish) are among the most widely abused psychoactive drugs in the world, due to their euphorigenic and anxiolytic properties. Recently, hair analysis is of great interest in analytical, clinical, and forensic sciences due to its non-invasiveness, negligible risk of infection and tampering, facile storage, and a wider window of detection. Hair analysis is now widely accepted as evidence in courts around the world. Hair analysis is very feasible to complement saliva, blood tests, and urinalysis. In this review, we have focused on state of the art in hair analysis of cannabis with particular attention to hair sample preparation for cannabis analysis involving pulverization, extraction and screening techniques followed by confirmatory tests (e.g., GC–MS and LC–MS/MS). We have reviewed the literature for the past 10 years’ period with special emphasis on cannabis quantification using mass spectrometry. The pros and cons of all the published methods have also been discussed along with the prospective future of cannabis analysis

Current status of accreditation for drug testing in hair

At the annual meeting of the Society of Hair Testing in Vadstena, Sweden in 2006, a committee was appointed to address the issue of guidelines for hair testing and to assess the current status of accreditation amongst laboratories offering drug testing in hair. A short questionnaire was circulated amongst the membership and interested parties. Fifty-two responses were received from hair testing laboratories providing details on the amount and type of hair tests they offered and the status of accreditation within their facilities. Although the vast majority of laboratories follow current guidelines (83%), only nine laboratories were accredited to ISO/IEC 17025 for hair testing. A significant number of laboratories reporting that they were in the process of developing quality systems with a view to accrediting their methods within 2–3 years. This study provides an insight into the status of accreditation in hair testing laboratories and supports the need for guidelines to encourage best practice

In Vitro and In Vivo Metabolite Identification Studies for the New Synthetic Opioids Acetylfentanyl, Acrylfentanyl, Furanylfentanyl, and 4-Fluoro-Isobutyrylfentanyl

© 2017, American Association of Pharmaceutical Scientists. New fentanyl analogs have recently emerged as new psychoactive substances and have caused numerous fatalities worldwide. To determine if the new analogs follow the same metabolic pathways elucidated for fentanyl and known fentanyl analogs, we performed in vitro and in vivo metabolite identification studies for acetylfentanyl, acrylfentanyl, 4-fluoro-isobutyrylfentanyl, and furanylfentanyl. All compounds were incubated at 10 μM with pooled human hepatocytes for up to 5 h. For each compound, four or five authentic human urine samples from autopsy cases with and without enzymatic hydrolysis were analyzed. Data acquisition was performed in data-dependent acquisition mode during liquid chromatography high-resolution mass spectrometry analyses. Data was analyzed (1) manually based on predicted biotransformations and (2) with MetaSense software using data-driven search algorithms. Acetylfentanyl, acrylfentanyl, and 4-fluoro-isobutyrylfentanyl were predominantly metabolized by N-dealkylation, cleaving off the phenethyl moiety, monohydroxylation at the ethyl linker and piperidine ring, as well as hydroxylation/methoxylation at the phenyl ring. In contrast, furanylfentanyl’s major metabolites were generated by amide hydrolysis and dihydrodiol formation, while the nor-metabolite was minor or not detected in case samples at all. In general, in vitro results matched the in vivo findings well, showing identical biotransformations in each system. Phase II conjugation was observed, particularly for acetylfentanyl. Based on our results, we suggest the following specific and abundant metabolites as analytical targets in urine: a hydroxymethoxy and monohydroxylated metabolite for acetylfentanyl, a monohydroxy and dihydroxy metabolite for acrylfentanyl, two monohydroxy metabolites and a hydroxymethoxy metabolite for 4-fluoro-isobutyrylfentanyl, and a dihydrodiol metabolite and the amide hydrolysis metabolite for furanylfentanyl