3-CMC, 4-CMC, and 4-BMC Human Metabolic Profiling: New Major Pathways to Document Consumption of Methcathinone Analogues?

Synthetic cathinones represent one of the largest and most abused new psychoactive substance classes, and have been involved in numerous intoxications and fatalities worldwide. Methcathinone analogues like 3-methylmethcathinone (3-MMC), 3-chloromethcathinone (3-CMC), and 4-CMC currently constitute most of synthetic cathinone seizures in Europe. Documenting their consumption in clinical/forensic casework is therefore essential to tackle this trend. Targeting metabolite markers is a go-to to document consumption in analytical toxicology, and metabolite profiling is crucial to support investigations. We sought to identify 3-CMC, 4-CMC, and 4-bromomethcathinone (4-BMC) human metabolites. The substances were incubated with human hepatocytes; incubates were screened by liquid chromatography-high-resolution tandem mass spectrometry and data were mined with Compound Discoverer (Themo Scientific). 3-CMC-positive blood, urine, and oral fluid and 4-CMC-positive urine and saliva from clinical/forensic casework were analyzed. Analyses were supported by metabolite predictions with GLORYx freeware. Twelve, ten, and ten metabolites were identified for 3-CMC, 4-CMC, and 4-BMC, respectively, with similar transformations occurring for the three cathinones. Major reactions included ketoreduction and N-demethylation. Surprisingly, predominant metabolites were produced by combination of N-demethylation and ω-carboxylation (main metabolite in 3-CMC-positive urine), and combination of ß-ketoreduction, oxidative deamination, and O-glucuronidation (main metabolite in 4-CMC-positive urine). These latter metabolites were detected in negative-ionization mode only and their non-conjugated form was not detected after glucuronide hydrolysis; this metabolic pathway was never reported for any methcathinone analogue susceptible to undergo the same transformations. These results support the need for comprehensive screening strategies in metabolite identification studies, to avoid overlooking significant metabolites and major markers of consumption.

Human metabolism of four synthetic benzimidazole opioids: isotonitazene, metonitazene, etodesnitazene, and metodesnitazene.

Following isotonitazene scheduling in 2019, the availability of alternative 2-benzylbenzimidazole opioids (nitazenes) on the global drug market increased, resulting in many fatalities worldwide. Nitazenes are potent µ-opioid receptor agonists with strong narcotic/analgesic effects, and their concentrations in biological matrices are low, making the detection of metabolite biomarkers of consumption crucial to document use in clinical and forensic settings. However, there is little to no data on the metabolism of the most recently available nitazenes, especially desnitro-analogues. The aim of the research was to assess isotonitazene, metonitazene, etodesnitazene, and metodesnitazene human metabolism and identify specific metabolite biomarkers of consumption. The four analogues were incubated with 10-donor-pooled human hepatocytes, and the incubates were analyzed by liquid chromatography-high-resolution tandem mass spectrometry and data mining with Compound Discoverer (Thermo Scientific); the analysis was supported by in silico metabolite predictions with GLORYx open-access software. Metabolites were identified in postmortem blood and/or urine samples from two metonitazene-positive and three etodesnitazene-positive cases following the same workflow, with and without glucuronide hydrolysis in urine, to confirm in vitro results. Twelve, nine, twenty-two, and ten metabolites were identified for isotonitazene, metonitazene, etodesnitazene, and metodesnitazene, respectively. The main transformations were N-deethylation at the N,N-diethylethanamine side chain, O-dealkylation, and further O-glucuronidation. In vitro and autopsy results were consistent, demonstrating the efficacy of the 10-donor-pooled human hepatocyte model to predict human metabolism. We suggest the parent and the corresponding O-dealkyl- and N-deethyl-O-dealkyl metabolites as biomarkers of exposure in urine after glucuronide hydrolysis, and the corresponding N-deethyl metabolite as additional biomarker in blood.

In vitro, in vivo metabolism and quantification of the novel synthetic opioid N-piperidinyl etonitazene (etonitazepipne).

OBJECTIVES: N-piperidinyl etonitazene (etonitazepipne) is a newly synthesized opioid related to the 2-benzylbenzimidazole analog class. Etonitazepipne has been formally notified and placed under intensive monitoring in Europe in January 2022. Nitazenes have high affinity at µ-opioid receptor (MOR). Etonitazepipne, specifically shows a EC50 of 2.49 nM, suggesting about 50 times higher potency combined with higher efficacy compared to morphine. Antinociceptive potency l ('hot plate test' with rats) was 192-fold greater than that of morphine. METHODS: Here we report on a post-mortem case involving etonitazepipne and its quantification using a standard addition method (SAM) through liquid chromatography tandem mass spectrometry (LC-MS/MS). In addition, characterization and identification of phase I human metabolites using in vitro assay based on pooled human liver microsomes (pHLM) was performed along with the analysis of authentic urine samples by means of high-performance liquid chromatography high-resolution tandem mass spectrometry (LC-HRMS/MS). RESULTS: The concentration of etonitazepipne in post-mortem blood and urine was 8.3 and 11 ng/mL, respectively. SAM was validated by assessing the following parameters: intraday and interday repeatability, matrix effect and recovery rate in post-mortem blood. A total of 20 and 14 metabolites were identified after pHLM incubation and urine analysis, respectively. Most pronounced in vitro and in vivo transformations were O-deethylation, hydroxylation, ketone reduction, and combinations thereof. CONCLUSIONS: Considering small traces of the parent drug often found in real cases, the identification of metabolic biomarkers is crucial to identify exposure to this drug. O-deethylated, oxidated metabolites, and combination thereof are proposed as urinary biomarkers along with the parent compound.

Disposition of Hexahydrocannabinol Epimers and Their Metabolites in Biological Matrices following a Single Administration of Smoked Hexahydrocannabinol: A Preliminary Study.

In 2023, hexahydrocannabinol (HHC) attracted the attention of international agencies due to its rapid spread in the illegal market. Although it was discovered in 1940, less is known about the pharmacology of its two naturally occurring epimers, 9(R)-HHC and 9(S)-HHC. Thus, we aimed to investigate the disposition of hexahydrocannabinol epimers and their metabolites in whole blood, urine and oral fluid following a single controlled administration of a 50:50 mixture of 9(R)-HHC and 9(S)-HHC smoked with tobacco. To this end, six non-user volunteers smoked 25 mg of the HHC mixture in 500 mg of tobacco. Blood and oral fluid were sampled at different time points up to 3 h after the intake, while urine was collected between 0 and 2 h and between 2 and 6 h. The samples were analyzed with a validated HPLC-MS/MS method to quantify 9(R)-HHC, 9(S)-HHC and eight metabolites. 9(R)-HHC showed the highest Cmax and AUC0-3h in all the investigated matrices, with an average concentration 3-fold higher than that of 9(S)-HHC. In oral fluid, no metabolites were detected, while they were observed as glucuronides in urine and blood, but with different profiles. Indeed, 11nor-9(R)-HHC was the most abundant metabolite in blood, while 8(R)OH-9(R) HHC was the most prevalent in urine. Interestingly, 11nor 9(S) COOH HHC was detected only in blood, whereas 8(S)OH-9(S) HHC was detected only in urine.

In silico and in vitro human metabolism of IOX2, a performance-enhancing doping agent.

IOX2 is a potent inhibitor of prolyl hydroxylase 2, a key enzyme in the regulation of hypoxia-inducible factor (HIF) and oxygen homeostasis. As such, it can be used to enhance athletic performance and is currently banned by the World Anti-Doping Agency (WADA). Detection of metabolites is critical to demonstrate drug use in doping. However, there is currently little data on IOX2 human metabolism. Our aim was to identify relevant biomarkers of IOX2 use in humans. For this purpose, IOX2 was incubated with 10-donor-pooled human hepatocytes for 3 h, incubates were analyzed by liquid chromatography-high-resolution tandem mass spectrometry (LC-HRMS/MS), and LC-HRMS/MS data were screened with Compound Discoverer (Thermo Scientific) for a comprehensive identification of IOX2 metabolites. Additionally, IOX2 human metabolites were predicted with GLORYx open-access software (University of Hamburg, Germany) to assist in the LC-HRMS/MS analysis and data mining. Thirteen metabolites were identified, oxidation at the quinolinyl group, O-glucuronidation, and combinations being predominant biotransformations. The results were consistent with previous animal studies and a single case of oral microdose administration. We suggest hydroxyquinolinyl-IOX2 as major biomarker of IOX2 use in biological samples, glucuronide hydrolysis being critical to increase IOX2 and hydroxyquinolinyl-IOX2 detectability in urine.

Metabolism Study of Anamorelin, a GHSR1a Receptor Agonist Potentially Misused in Sport, with Human Hepatocytes and LC-HRMS/MS.

Anamorelin, developed for the treatment of cancer cachexia, is an orally active medication that improves appetite and food intake, thereby increasing body mass and physical functioning. It is classified as a growth hormone secretagogue and strictly monitored by the World Anti-Doping Agency (WADA), owing to its anabolic enhancing potential. Identifying anamorelin and/or metabolite biomarkers of consumption is critical in doping controls. However, there are currently no data available on anamorelin human metabolic fate. The aim of this study was to investigate and identify biomarkers characteristic of anamorelin intake using in silico metabolite predictions with GLORYx, in vitro incubation with 10-donor-pooled human hepatocytes, liquid chromatography-high-resolution tandem mass spectrometry (LC-HRMS/MS) analysis, and data processing with Thermo Scientific's Compound Discoverer. In silico prediction resulted in N-acetylation at the methylalanyl group as the main transformation (score, 88%). Others including hydroxylation at the indole substructure, and oxidation and N-demethylation at the trimethylhydrazino group were predicted (score, ≤36%). Hepatocyte incubations resulted in 14 phase I metabolites formed through N-demethylation at the trimethylhydrazino group, N-dealkylation at the piperidine ring, and oxidation at the indole and methylalanyl groups; and two phase II glucuronide conjugates occurring at the indole. We propose four metabolites detected as specific biomarkers for toxicological screening.

Development of an enantioselective high-performance liquid chromatography-tandem mass spectrometry method for the quantitative determination of methorphan and its O-demethylated metabolite in human blood and its application to post-mortem samples.

In the present work an isocratic enantioselective high-performance liquid chromatography-tandem mass spectrometry (LC-MS/MS) method was developed for the separation and quantitative determination of dextro - and levo -methorphan and their pharmacologically relevant metabolites, dextrorphan and levorphanol, respectively, in human blood samples. The separation of enantiomers of methorphan and metabolites was performed on the polysaccharide-based chiral column Lux AMP in combination with acetonitrile and 5 mM aqueous ammonium bicarbonate pH 11 in the ratio 50:50 (%, v/v) as mobile phase with the flow rate 1 mL/min. The mass spectrometer was operated in scheduled multiple reaction monitoring (MRM) mode, with four transitions for each dextromethorpan, levomethorphan, dextrorphan and dextromethorphan-d3 and two transitions for each levorphanol, levorphanol-d3 and dextrorphan-d3. Application of this method to human post-mortem blood samples confirmed cases of severe overdosing with dextromethorphan, levomethorphan, and less commonly with both.

Update on Cannabidiol Clinical Toxicity and Adverse Effects: A Systematic Review.

BACKGROUND: Compelling evidence from preclinical and clinical studies supports the therapeutic role of cannabidiol (CBD) in several medical disorders. We reviewed the scientific evidence on CBD-related toxicity and adverse events (AEs) in 2019, at the beginning of the spike in clinical studies involving CBD. However, CBD safety remained uncertain. OBJECTIVE: With the benefit of hindsight, we aimed to provide an update on CBD-related toxicity and AEs in humans. METHODS: A systematic literature search was conducted following PRISMA guidelines. PubMed, Cochrane, and Embase were accessed in October 2022 to identify clinical studies mentioning CBDrelated toxicity/AEs from February 2019 to September 2022. Study design, population characteristics, CBD doses, treatment duration, co-medications, and AEs were compiled. RESULTS: A total of 51 reports were included. Most studies investigated CBD efficacy and safety in neurological conditions, such as treatment-resistant epilepsies, although a growing number of studies are focusing on specific psychopathological conditions, such as substance use disorders, chronic psychosis, and anxiety. Most studies report mild or moderate severity of AEs. The most common AEs are diarrhea, somnolence, sedation, and upper respiratory disturbances. Few serious AEs have been reported, especially when CBD is co-administered with other classes of drugs, such as clobazam and valproate. CONCLUSION: Clinical data suggest that CBD is well tolerated and associated with few serious AEs at therapeutic doses both in children and adults. However, interactions with other medications should be monitored carefully. Additional data are needed to investigate CBD's long-term efficacy and safety, and CBD use in medical conditions other than epilepsy syndromes.

α-Methyltryptamine (α-MT) Metabolite Profiling in Human Hepatocyte Incubations and Postmortem Urine and Blood.

α-MT is a hallucinogenic and stimulant tryptamine that was involved in several overdose fatalities in the United States and Europe. Analytical toxicology, and particularly the identification of metabolite biomarkers in biological samples, often is the only way to prove tryptamine use in clinical and forensic caseworks. We aimed to identify optimal α-MT metabolite biomarkers of consumption in humans. We identified α-MT metabolites in 10-donor-pooled human hepatocyte incubations and postmortem urine and blood from an α-MT overdose case using in silico metabolite predictions, liquid chromatography high-resolution-tandem mass spectrometry (LC-HRMS/MS), and software-assisted data mining. Nine metabolites were identified in vitro and eight additional metabolites were found in urine; five metabolites were found in blood. Metabolic transformations were hydroxylation, O-sulfation, O-glucuronidation, N-glucuronidation, and N-acetylation, consistent with the metabolism of structural analogues. The findings in hepatocyte incubations and postmortem samples were consistent, proving the in vitro model suitability. We suggest α-MT, hydroxy-α-MT glucuronide, and two hydroxy-α-MT sulfates as biomarkers of α-MT use in non-hydrolyzed urine; we suggest α-MT, two hydroxy-α-MT sulfates and N-acetyl-α-MT as biomarkers of α-MT use in blood. Further studies on α-MT clinical and forensic caseworks with different doses and routes of administration are necessary to better explore α-MT metabolism.

ß'-Phenylfentanyl Metabolism in Primary Human Hepatocyte Incubations: Identification of Potential Biomarkers of Exposure in Clinical and Forensic Toxicology.

From 2014 onwards, illicit fentanyl and analogues have caused numerous intoxications and fatalities worldwide, impacting the demographics of opioid-related overdoses. The identification of cases involving fentanyl analogues is crucial in clinical and forensic settings to treat patients, elucidate intoxications, address drug use disorders and tackle drug trends. However, in analytical toxicology, the concentration of fentanyl analogues in biological matrices is low, making their detection challenging. Therefore, the identification of specific metabolite biomarkers is often required to document consumption. ß'-Phenylfentanyl (N-phenyl-N-[1-(2-phenylethyl)-4-piperidinyl]-benzenepropanamide) is a fentanyl analogue that was first detected in Sweden in 2017 and has recently reemerged onto the American illicit drug market. There is little data available on ß'-phenylfentanyl effects and toxicokinetics and its metabolism is yet to be studied. We aimed to investigate ß'-phenylfentanyl human metabolism to identify potential biomarkers of use. To assist in ß'-phenylfentanyl metabolite identification, a list of putative reactions was generated using in silico predictions with GLORYx freeware. ß'-phenylfentanyl was incubated with cryopreserved 10-donor-pooled human hepatocytes, analyses were performed by liquid chromatography-high-resolution tandem mass spectrometry (LC-HRMS-MS) and data were processed using a partially automated targeted/untargeted approach with Compound Discoverer. We identified 26 metabolites produced by N-dealkylation, oxidation, hydroxylation, O-glucuronidation, O-methylation and combinations thereof. We suggest ß'-phenylnorfentanyl (N-phenyl-N-4-piperidinyl-benzenepropanamide) and further metabolites 1-oxo-N-phenyl-N-4-piperidinyl-benzenepropanamide and 1-hydroxy-N-phenyl-N-4-piperidinyl-benzenepropanamide as major biomarkers of ß'-phenylfentanyl use. In silico predictions were mostly wrong, and ß'-phenylfentanyl metabolic fate substantially differed from that of a closely related analogue incubated in the same conditions, highlighting the value of the experimental assessment of new psychoactive substance human metabolism. In vivo data are necessary to confirm the present results. However, the present results may be necessary to help analytical toxicologists identify ß'-phenylfentanyl-positive cases to provide authentic samples.

UHPLC-MS-MS Determination of THC, CBD and Their Metabolites in Whole Blood of Light Cannabis Smokers.

"Light cannabis" is a product legally sold in Europe with Δ9-tetrahydrocannabinol (THC) concentration <0.2% and variable cannabidiol (CBD) content. In this study, we aimed to assess the time courses of THC and metabolites (11-nor-9-carboxy-THC and 11-hydroxy-THC) and CBD and metabolites (CBD-7-oic acid, 7-hydroxy-CBD, 6α-hydroxy-CBD and 6ß-hydroxy-CBD) in whole blood of 10 healthy participants after smoking one or four light cannabis cigarettes (0.16% THC and 5.8% CBD). Blood samples were collected 0.5-4 h after administration. Blood analysis was performed by reversed-phase ultra-performance liquid chromatography-tandem mass spectrometry in multiple reaction monitoring mode after glucuronide hydrolysis and liquid-liquid extraction in basic and acidic conditions. The method was validated following the most recent guidelines in toxicology: the method was linear, accurate, precise and sensitive (lower limits of quantification ranged from 0.005 to 0.01 ng/mL); carryover, matrix effect, recovery, process efficiency and dilution integrity were also assessed. As previously reported, the main metabolites of THC were THC-COOH and then 11-OH-THC, and the main metabolites of CBD were 7-OH-CBD and then 7-COOH-CBD. The time of the first collection, which likely occurred after the maximal concentration of most of the analytes, and the short monitoring time, up to 4 h after smoking, limited the evaluation of the pharmacokinetic parameters.

Quantification of Carbonic Anhydrase Inhibitors and Metabolites in Urine and Hair of Patients and Their Relatives.

Carbonic anhydrase inhibitors (CAIs) are prescription drugs also used in doping to dilute urine samples and tamper with urinalyses. Dorzolamide, brinzolamide, and acetazolamide are prohibited by the World Anti-Doping Agency. Detecting CAIs and their metabolites in biological samples is crucial to documenting misuse in doping. We quantified dorzolamide, brinzolamide, acetazolamide, and their metabolites in the urine and hair of 88 patients under treatment for ocular hypertension or glaucoma. Samples of the patients' relatives were analyzed to assess potential for accidental exposure. After washing, 25 mg hair was incubated with an acidic buffer at 100 °C for 1 h. After cooling and centrifugation, the supernatant was analyzed by ultra-high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS). Urine (100 µL) was diluted and centrifuged before UHPLC-MS/MS analysis. Run time was 8 min through a reverse-phase column with a mobile phase gradient. MS/MS analysis was performed in a multiple-reaction monitoring mode after positive electrospray ionization. Median urinary concentration was 245 ng/mL (IQR: 116.2-501 ng/mL) for dorzolamide, 81.1 ng/mL (IQR: 35.9-125.3 ng/mL) for N-deethyl-dorzolamide, 0.77 ng/mL (IQR: 0.64 ng/mL-0.84 ng/mL) for N-acetyl-dorzolamide, 38.9 ng/mL (IQR: 20.4-79.2 ng/mL) for brinzolamide, and 72.8 ng/mL (IQR: 20.7-437.3 ng/mL) for acetazolamide. Median hair concentration was 0.48 ng/mg (IQR: 0.1-0.98 ng/mg) for dorzolamide, 0.07 ng/mg (IQR: 0.06-0.08 ng/mg) for N-deethyl-dorzolamide, 0.40 ng/mL (IQR: 0.13-1.95 ng/mL) for brinzolamide. Acetazolamide was detected in only one hair sample. Dorzolamide and brinzolamide were detected in the urine of three and one relatives, respectively. Cutoff concentrations of urinary dorzolamide and brinzolamide are necessary to preclude false positives due to contamination or passive exposure. We reported the first concentrations of brinzolamide in hair.

Human Hepatocyte 4-Acetoxy-N,N-Diisopropyltryptamine Metabolite Profiling by Reversed-Phase Liquid Chromatography Coupled with High-Resolution Tandem Mass Spectrometry.

Tryptamine intoxications and fatalities are increasing, although these novel psychoactive substances (NPS) are not controlled in most countries. There are few data on the metabolic pathways and enzymes involved in tryptamine biotransformation. 4-acetoxy-N,N-diisopropyltryptamine (4-AcO-DiPT) is a synthetic tryptamine related to 4-hydroxy-N,N-diisopropyltryptamine (4-OH-DiPT), 4-acetyloxy-N,N-dipropyltryptamine (4-AcO-DPT), and 4-acetoxy-N,N-dimethyltryptamine (4-AcO-DMT). The aim of this study was to determine the best 4-AcO-DiPT metabolites to identify 4-AcO-DiPT consumption through human hepatocyte metabolism and high-resolution mass spectrometry. 4-AcO-DiPT metabolites were predicted in silico with GLORYx freeware to assist in metabolite identification. 4-AcO-DiPT was incubated with 10-donor-pooled human hepatocytes and sample analysis was performed with reversed-phase liquid chromatography coupled with high-resolution tandem mass spectrometry (LC-HRMS/MS) in positive- and negative-ion modes. Software-assisted LC-HRMS/MS raw data mining was performed. A total of 47 phase I and II metabolites were predicted, and six metabolites were identified after 3 h incubation following ester hydrolysis, O-glucuronidation, O-sulfation, N-oxidation, and N-dealkylation. All second-generation metabolites were derived from the only first-generation metabolite detected after ester hydrolysis (4-OH-DiPT). The metabolite with the second-most-intense signal was 4-OH-iPT-sulfate followed by 4-OH-DiPT-glucuronide, indicating that glucuronidation and sulfation are common in this tryptamine's metabolic pathway. 4-OH-DiPT, 4-OH-iPT, and 4-OH-DiPT-N-oxide are suggested as optimal biomarkers to identify 4-AcO-DiPT consumption.

In silico, in vitro, and in vivo human metabolism of acetazolamide, a carbonic anhydrase inhibitor and common "diuretic and masking agent" in doping.

Acetazolamide (ACZ) is a carbonic anhydrase inhibitor prescribed for the treatment of various pathologies. It is also used in doping and is prohibited in and out of sportive competitions. ACZ was reported not to undergo metabolization. However, the detection of ACZ metabolites may be critical for documenting ACZ use. We aimed to further investigate ACZ metabolic fate in humans. ACZ putative metabolites were generated in silico to assist in metabolite identification. ACZ was incubated with primary human hepatocytes to identify in vitro metabolites (10 µmol/l ACZ and 106 cells/ml), and urine and plasma samples from patients receiving a single 5.0 mg/kg BW PO ACZ dose were analyzed to confirm the results in vivo. Analyses were performed with reversed-phase liquid chromatography and hydrophilic interaction chromatography coupled with high-resolution tandem mass spectrometry (RPLC-HRMS/MS and HILIC-HRMS/MS, respectively). Data were screened with a software-assisted targeted/untargeted workflow. ACZ was quantified in urine samples with creatinine normalization. We identified two metabolites in hepatocyte incubations and three additional metabolites in urine and plasma. Major transformations included cysteine conjugation, glucuronidation, and N-acetylation. All metabolites were detected in plasma, 1.5 h after intake. Major metabolites were detected in urine from 0.25 to 24 h (last collection) after intake. As opposed to the literature, ACZ does undergo metabolization in humans. We propose ACZ, ACZ-Cys, and N-acetyl-ACZ in urine, and ACZ and N-acetyl-ACZ in plasma as specific biomarkers of ACZ intake in doping.

3F-α-pyrrolydinovalerophenone (3F-α-PVP) in vitro human metabolism: Multiple in silico predictions to assist in LC-HRMS/MS analysis and targeted/untargeted data mining.

Synthetic cathinones (SCs) constitute a heterogenous class of new psychoactive substances (NPS), structurally related to cathinone. SCs represent the widest NPS class, second to synthetic cannabinoids, accounting for approximately 160 different analogues with substitution at the phenyl group, the amine group, or the alkyl chain. In 2020, α-pyrrolidonophenone analogues were the most trafficked SCs, and were involved in many fatalities and intoxication cases. In particular, 3F-α-pyrrolidinovalerophenone (3F-α-PVP) was the cause of the highest number of SC-related fatal intoxications in Sweden in 2018. Minor structural modifications are used to avoid legal controls and analytical detection, but may also induce different toxicological profile. Therefore, the identification of specific markers of consumption is essential to discriminate SCs in clinical and forensic toxicology. In this study, we assessed 3F-α-PVP metabolic profile. 3F-α-PVP was incubated with 10-donor-pooled human hepatocytes, LC-HRMS/MS analysis, and software-assisted data mining. This well-established workflow was completed by in silico metabolite predictions using three different freeware. Ten metabolites were identified after 3 h incubation, including hydrogenated, hydroxylated, oxidated, and N-dealkylated metabolites. A total of 51 phase I and II metabolites were predicted, among which 7 were detected in the incubations. We suggest 3F-α-PVP N-butanoic acid, 3F-α-PVP pentanol, and 3F-α-PVP 2-ketopyrrolidinyl-pentanol as specific biomarkers of 3F-α-PVP consumption. This is the first time that an N-ethanoic acid is detected in the metabolic pathway of a pyrrolidine SC, demonstrating the importance of a dual targeted/untargeted data mining strategy.

Acute Intoxications and Fatalities Associated With Benzimidazole Opioid (Nitazene Analog) Use: A Systematic Review.

BACKGROUND: Synthetic benzimidazole opioids (BOs) are highly potent µ-opioid receptor agonists with heroin-like effects. Isotonitazene was first available in 2019 in the drug market, although new analogs have multiplied recently. The authors aimed to identify BO use trends and gather toxicological data from BO-related cases to assist in clinical and forensic investigations. METHODS: A systematic literature search was conducted according to the PRISMA guidelines. PubMed and Scopus databases were accessed in October 2021 to identify scientific reports of BO-related intoxication and fatalities. Publication dates, case descriptions, symptoms, autopsy findings, and concentrations of BOs and metabolites in biological matrices were compiled. RESULTS: Data from 8 case reports with 93 fatalities involving isotonitazene ( n = 65), metonitazene ( n = 20), etonitazepyne ( N -pyrrolidino etonitazene) ( n = 8), flunitazene ( n = 4), and/or butonitazene ( n = 1), and 1 acute intoxication involving etonitazepyne were collected. Autopsy findings included pulmonary congestion/high lung weight (66%), cardiomegaly/high cardiac weight (39%), cerebral edema (22%), gastric contents in the airways (22%), and organ congestion (22%). Median peripheral blood concentrations were 1.7 ng/mL for isotonitazene (0.4-9.5 ng/mL, n = 13), 5.4 ng/mL for metonitazene (0.52-33 ng/mL, n = 17), 5.4 ng/mL for etonitazepyne (2.4-8.3 ng/mL, n = 2), 1.3 ng/mL for flunitazene (0.58-2.1 ng/mL, n = 2), and 3.2 ng/mL for butonitazene ( n = 1). Central nervous system depressants were almost always coadministered. CONCLUSIONS: Isotonitazene was predominant in cases from 2019 to mid-2020 and was replaced by metonitazene after scheduling in the United States. Typical findings on opioid overdoses have been reported. Peripheral blood concentrations were consistent with a potency similar to that of fentanyl. These results must be interpreted carefully, considering the scarcity of reports on BO-related cases and drug co-exposures.

Biomarkers of 4-hydroxy-N,N-methylpropyltryptamine (4-OH-MPT) intake identified from human hepatocyte incubations.

BACKGROUND: 4-Hydroxy-N,N-methylpropyltryptamine (4-OH-MPT) is a psychedelic tryptamine whose use is regulated in several countries. Due to unspecific effects, consumption can be ascertained only through toxicological analyses. However, the trace amounts of tryptamines are usually challenging to detect in biological samples. 4-OH-MPT metabolism was characterized to identify optimal metabolite markers of intake in clinical/forensic toxicology. RESEARCH DESIGN AND METHODS: 4-OH-MPT was incubated with 10-donor-pooled human hepatocytes to simulate in vivo conditions; samples were analyzed by liquid chromatography-high-resolution tandem mass spectrometry (LC-HRMS/MS), and data were processed with Compound Discoverer from Thermo Scientific. LC-HRMS/MS and data mining were supported by in silico metabolite predictions (GLORYx). RESULTS: Three phase I and four phase II metabolites were identified, including N-oxidation and N-demethylation at the alkylamine chain, and O-glucuronidation and sulfation at the hydroxylindole core. CONCLUSIONS: 4-OH-MPT metabolic fate was consistent with the human metabolism of tryptamine analogues: we suggest 4-OH-MPT-N-oxide and 4-hydroxy-N,N-propyltryptamine (4-OH-PT) as metabolite biomarkers of 4-OH-MPT consumption after glucuronide/sulfate hydrolysis in biological samples to improve detection of 4-OH-MPT and phase I metabolites; 4-OH-MPT-glucuronide is suggested as an additional biomarker when hydrolysis is not performed. Further research on the metabolism of structural analogues is necessary to evaluate the specificity of 4-OH-MPT metabolite biomarkers.

In silico prediction, LC-HRMS/MS analysis, and targeted/untargeted data-mining workflow for the profiling of phenylfentanyl in vitro metabolites.

Illicit fentanyl and analogues have been involved in many fatalities and cases of intoxication across the United States over the last decade, and are becoming a health concern in Europe. New potent analogues emerge onto the drug market every year to circumvent analytical detection and legislation, and little pharmacological/toxicological data are available when the substances first appear. However, pharmacokinetic data are crucial to determine specific biomarkers of consumption in clinical and forensic settings, considering the low active doses and the rapid metabolism of fentanyl analogues. Phenylfentanyl is a novel analogue that was first detected in seized material in 2017, and little is currently known about this substance and its metabolism. We studied phenylfentanyl metabolic fate using in silico predictions with GLORYx freeware, human hepatocyte incubations, and liquid chromatography-high-resolution tandem mass spectrometry (LC-HRMS/MS). We applied a specific targeted/untargeted workflow using data-mining software to allow the rapid and partially automated screening of LC-HRMS/MS raw data. Approximately 90,000 substances were initially individuated after 3-h incubation with hepatocytes, and 115 substances were automatically selected for a manual check by the operators. Finally, 13 metabolites, mostly produced by N-dealkylation, amide hydrolysis, oxidation, and combinations thereof, were identified. We suggest phenylnorfentanyl as the main biological marker of phenylfentanyl use, and we proposed the inclusion of its fragmentation pattern in mzCloud and HighResNPS online libraries. Other major metabolites include N-Phenyl-1-(2-phenylethyl)-4-piperidinamine (4-ANPP), 1-(2-phenylethyl)-4-piperidinol, and other non-specific metabolites. Phase II transformations were infrequent, and the hydrolysis of the biological samples is not required to increase the detection capability of non-conjugated metabolites. The overall workflow is easily adaptable for the metabolite profiling of other novel psychoactive substances.

A 2017-2019 Update on Acute Intoxications and Fatalities from Illicit Fentanyl and Analogs.

The aim of this review was to report the most recent cases of acute intoxication, fatalities and "driving under the influence" cases, involving illicit fentanyl and its newest analogs. When available, information on age, sex, circumstances of exposure, intoxication symptoms, cause of death (if applicable) and toxicology results from biological fluid testing was described. Scientific publications reporting fatalities or acute intoxications involving use of fentanyl derivatives were identified from PubMed, Scopus and institutional/governmental websites from January 2017 up to December 2019. The search terms, used alone and in combination, were as follows: fentanyl, street fentanyl, analogs, compounds, derivatives, abuse, fatality, fatalities, death, toxicity, intoxication and adverse effects. When considered relevant, reports not captured by the initial search but cited in other publications were also included. Of the 2890 sources initially found, only 44 were suitable for the review. Emergent data showed that the most common analogs detected in biological samples and seized materials are acetylfentanyl, acrylfentanyl, butyrfentanyl, carfentanil, cyclopropylfentanyl, fluorofentanyl, 4-fluorobutyrfentanyl, 4-fluoroisobutyrfentanyl, furanylfentanyl, 2-methoxyacetylfentanyl, 3-methylfentanyl and ocfentanil. These compounds were frequently administered in association with other illicit substances, medicinal drugs and/or alcohol; patients and the victims often had a previous history of drug abuse. The trend of fentanyl analogs is rapidly evolving with illicit market fluctuations. Since information about potency and lethal dosage are frequently unknown, it is important to identify the new trends for further investigation on therapeutic use, toxicity and fatal doses, and implement public health measures. Recently marketed fentanyl analogs such as crotonylfentanyl and valerylfentanyl were not involved in intoxications to date, but should be carefully monitored. Many intoxications and fatalities might have gone unnoticed, and research efforts should focus on metabolite identification studies and the implementation of updated and comprehensive analytical methods.

Pyrrolidinyl Synthetic Cathinones α-PHP and 4F-α-PVP Metabolite Profiling Using Human Hepatocyte Incubations.

For more than ten years, new synthetic cathinones (SCs) mimicking the effects of controlled cocaine-like stimulants have flooded the illegal drug market, causing numerous intoxications and fatalities. There are often no data on the pharmacokinetics of these substances when they first emerge onto the market. However, the detection of SC metabolites is often critical in order to prove consumption in clinical and forensic settings. In this research, the metabolite profile of two pyrrolidinyl SCs, α-pyrrolidinohexaphenone (α-PHP) and 4''-fluoro-α-pyrrolidinovalerophenone (4F-α-PVP), were characterized to identify optimal intake markers. Experiments were conducted using pooled human hepatocyte incubations followed by liquid chromatography-high-resolution tandem mass spectrometry and data-mining software. We suggest α-PHP dihydroxy-pyrrolidinyl, α-PHP hexanol, α-PHP 2'-keto-pyrrolidinyl-hexanol, and α-PHP 2'-keto-pyrrolidinyl as markers of α-PHP use, and 4F-α-PVP dihydroxy-pyrrolidinyl, 4F-α-PVP hexanol, 4F-α-PVP 2'-keto-pyrrolidinyl-hexanol, and 4F-α-PVP 2'-keto-pyrrolidinyl as markers of 4F-α-PVP use. These results represent the first data available on 4F-α-PVP metabolism. The metabolic fate of α-PHP was previously studied using human liver microsomes and urine samples from α-PHP users. We identified an additional major metabolite (α-PHP dihydroxy-pyrrolidinyl) that might be crucial for documenting exposure to α-PHP. Further experiments with suitable analytical standards, which are yet to be synthesized, and authentic specimens should be conducted to confirm these results.