Influent wastewater analysis to investigate emerging trends of new psychoactive substances use in Europe.

Wastewater-based epidemiology (WBE) can provide objective and timely information on the use of new psychoactive substances (NPS), originally designed as legal alternatives of internationally controlled drugs. NPS have rapidly emerged on the global drug market, posing a challenge to drug policy and constituting a risk to public health. In this study, a WBE approach was applied to monitor the use of more than 300 NPS, together with fentanyl and its main metabolite norfentanyl, in influent wastewater collected from 12 European cities during March-June 2021. Quantitative and qualitative analysis of NPS in composite 24 h influent wastewater samples were based on solid phase extraction and liquid chromatography-mass spectrometry. In-sample stability tests demonstrated the suitability of most investigated biomarkers, except for a few synthetic opioids, synthetic cannabinoids and phenetylamines. Fentanyl, norfentanyl and eight NPS were quantified in influent wastewater and at least three substances were found in each city, demonstrating their use in Europe. N,N-dimethyltryptamine and 3-methylmethcathinone (3-MMC) were the most common NPS found, with the latter having the highest mass loads (up to 24.8 mg/day/1000 inhabitants). Seven additional substances, belonging to five categories of NPS, were identified in different cities. Spatial trends of NPS use were observed between cities and countries, and a changing weekly profile of use was observed for 3-MMC. WBE is a useful tool to rapidly evaluate emerging trends of NPS use, complementing common indicators (i.e. population surveys, seizures) and helping to establish measures for public health protection.

PS2MS: A Deep Learning-Based Prediction System for Identifying New Psychoactive Substances Using Mass Spectrometry.

The rapid proliferation of new psychoactive substances (NPS) poses significant challenges to conventional mass-spectrometry-based identification methods due to the absence of reference spectra for these emerging substances. This paper introduces PS2MS, an AI-powered predictive system designed specifically to address the limitations of identifying the emergence of unidentified novel illicit drugs. PS2MS builds a synthetic NPS database by enumerating feasible derivatives of known substances and uses deep learning to generate mass spectra and chemical fingerprints. When the mass spectrum of an analyte does not match any known reference, PS2MS simultaneously examines the chemical fingerprint and mass spectrum against the putative NPS database using integrated metrics to deduce possible identities. Experimental results affirm the effectiveness of PS2MS in identifying cathinone derivatives within real evidence specimens, signifying its potential for practical use in identifying emerging drugs of abuse for researchers and forensic experts.

Deep learning-assisted mass spectrometry imaging for preliminary screening and pre-classification of psychoactive substances.

Currently, it is of great urgency to develop a rapid pre-classification and screening method for suspected drugs as the constantly springing up of new psychoactive substances. In most researches, psychoactive substances classification approaches depended on the similar chemical structures and pharmacological action with known drugs. Such approaches could not face the complicated circumstance of emerging new psychoactive substances. Herein, mass spectrometry imaging and convolutional neural networks (CNN) were used for preliminary screening and pre-classification of suspected psychoactive substances. Mass spectrometry imaging was performed simultaneously on two brain slices as one was from blank group and another one was from psychoactive substance-induced group. Then, fused neurotransmitter variation mass spectrometry images (Nv-MSIs) reflecting the difference of neurotransmitters between two slices were achieved through two homemade programs. A CNN model was developed to classify the Nv-MSIs. Compared with traditional classification methods, CNN achieved better estimation accuracy and required minimal data preprocessing. Also, the specific region on Nv-MSIs and weight of each neurotransmitter that affected the classification most could be unraveled by CNN. Finally, the method was successfully applied to assist the identification of a new psychoactive substance seized recently. This sample was identified as cannabinoids, which greatly promoted the screening process.

Trace analysis of 47 psychotropic medications in environmental samples by ultra-performance liquid chromatography tandem mass spectrometry (UPLC-MS/MS).

Psychotropic medications are one of the most prescribed pharmaceuticals in the world. Given their frequent detection and ecotoxicity to the no-target organism, the emission of these medications into environments has gradually draw attention. The study developed a sensitive and reliable analytic method to simultaneously investigate 47 psychotropic medications in four matrices: wastewater, surface water, activated sludge, and sediment by ultra-performance liquid chromatography-electrospray ionization-tandem mass spectrometry (UPLC-ESI-MS/MS). These 47 target analytes include 24 antidepressants, 17 antianxiety drugs, 5 anticonvulsants, and 1 relevant hormone. Solid phase extraction (SPE) was employed to extract analytes from water-phase samples. Ultrasonic Solvent Extraction method with Enhanced Matrix Removal clean-up (USE-EMR) was utilized to extract target compounds from solid-phase samples, which requires more straightforward and convenient procedures than previous methods. The extraction recoveries of all analytes ranged from 80 % to 120 % in these four sample matrices. In this study, The limit of quantitation for 47 psychotropic medications were 0.15 ng/L (estazolam) to 2.27 ng/L (lorazepam), 0.08 ng/L (desvenlafaxine) to 2 ng/L (mianserin), 0.22 ng/g (dry weight, dw) (nordiazepam) to 3.65 ng/g (dw) (lorazepam), and 0.07 ng/g (dw) (carbamazepine) to 2.85 ng/g (lorazepam), in wastewater, surface water, sludge, and sediment, respectively. In addition, the developed method was employed to analyse actual samples in two wastewater treatment plants and their receiving rivers. Carbamazepine, escitalopram, clozapine, desvenlafaxine, diazepam, lamotrigine, sertraline, temazepam, and venlafaxine were nearly ubiquitous in all matrices. Moreover, this study indicated that the inadequate removal efficiencies of psychotropic medications in wastewater treatment plants (WWTPs) had resulted in a persistent discharge of these contaminants from human sources into environments.

Monitoring the use of novel psychoactive substances in Australia by wastewater-based epidemiology.

Users of novel psychoactive substances (NPS) are at risk, due to limited information about the toxicity and unpredictable effects of these compounds. Wastewater-based epidemiology (WBE) has been used as a tool to provide insight into NPS use at the population level. To understand the preferences and trends of NPS use in Australia, this study involved liquid chromatography mass spectrometry analysis of wastewater collected from Australian states and territories from February 2022 to February 2023. In total, 59 different NPS were included across two complementary analytical methods and covered up to 57 wastewater catchments over the study. The NPS detected in wastewater were 25-B-NBOMe, buphedrone, 1-benzylpiperazine (BZP), 3-chloromethcathinone, N,N-dimethylpentylone (N,N-DMP), N-ethylheptedrone, N-ethylpentylone, eutylone, 4F-phenibut, 2-fluoro deschloroketamine, hydroxetamine, mephedrone, methoxetamine, methylone, mitragynine, pentylone, phenibut, para-methoxyamphetamine (PMA), alpha-pyrrolidinovalerophenone (α-PVP) and valeryl fentanyl. The detection frequency for these NPS ranged from 3 % to 100 % of the sites analysed. A noticeable decreasing trend in eutylone detection frequency and mass loads was observed whilst simultaneously N,N-DMP and pentylone increased over the study period. The emergence of some NPS in wastewater pre-dates other sources of monitoring and provides further evidence that WBE can be used as an additional early warning system for alerting potential NPS use.

Recent advances in analysis of new psychoactive substances by means of liquid chromatography coupled with low-resolution tandem mass spectrometry.

The number of methods for the analysis of new psychoactive substances (NPS) is continually increasing, and there is no indication that this trend will change in the near future. The constantly growing market of "designer drugs" makes it necessary to develop new methods of their analysis. The aim of this review is to present the multi-component methods of detection and identification of NPS using low-resolution tandem mass spectrometry coupled with liquid chromatography. For this purpose, 36 articles were selected by applying strictly defined search criteria. Due to the large differences in the matrices and physicochemical properties of the analytes, the described research methods are diverse. These differences are visible in sample preparation methods, chromatographic columns, mobile phases, gradients, or additives to mobile phases used. This work collects and organizes the existing information on the subject of NPS screening analysis methods and will be helpful to forensic scientists working on this topic.

Combining surface-enhanced Raman spectroscopy and paper spray mass spectrometry for the identification and confirmation of psychotropic substances in alcoholic beverages.

Criminal practices in which an individual becomes vulnerable and prone to sexual assault after ingesting drinks spiked with doping substances have become a social concern globally. As forensic protocols require a multi-tiered strategy for chemical evidentiary analysis, the backlog of evidence has become a significant problem in the community. Herein, a fast, sensible, and complementary dual analytical methodology was developed using a single commercial paper substrate for surface-enhanced Raman spectroscopy (SERS) and paper spray mass spectrometry (PS-MS) analysis to identify psychotropic substances added to alcoholic beverages irrefutably. To study and investigate this criminal practice, pharmaceutical formulations containing distinct psychotropic substances (zolpidem, clonazepam, diazepam, and ketamine) were added to drinks typically consumed at parties and festivals (Pilsen beer, açaí Catuaba®, gin tonic, and vodka mixed with Coca-Cola Zero®). A simple liquid-liquid extraction with a low-temperature partitioning (LLE-LTP) procedure was applied to the drinks and effectively minimized matrix effects. As a preliminary analysis, SERS spectra combined with Hierarchical Clustering Analysis (HCA) provided sufficient information to investigate the samples further. The presence of the protonated species for the psychotropic substances in the spiked drinks was readily verified in the mass spectra and confirmed by tandem mass spectrometry. Finally, the results demonstrate the potential of this methodology to be easily implemented into the routine of forensic laboratories and to be further employed at harm reduction tends at parties and festivals to detect contaminated beverages promptly and irrefutably as an efficient tool to prevent such crimes.

Deep Learning-Enabled MS/MS Spectrum Prediction Facilitates Automated Identification Of Novel Psychoactive Substances.

The market for illicit drugs has been reshaped by the emergence of more than 1100 new psychoactive substances (NPS) over the past decade, posing a major challenge to the forensic and toxicological laboratories tasked with detecting and identifying them. Tandem mass spectrometry (MS/MS) is the primary method used to screen for NPS within seized materials or biological samples. The most contemporary workflows necessitate labor-intensive and expensive MS/MS reference standards, which may not be available for recently emerged NPS on the illicit market. Here, we present NPS-MS, a deep learning method capable of accurately predicting the MS/MS spectra of known and hypothesized NPS from their chemical structures alone. NPS-MS is trained by transfer learning from a generic MS/MS prediction model on a large data set of MS/MS spectra. We show that this approach enables a more accurate identification of NPS from experimentally acquired MS/MS spectra than any existing method. We demonstrate the application of NPS-MS to identify a novel derivative of phencyclidine (PCP) within an unknown powder seized in Denmark without the use of any reference standards. We anticipate that NPS-MS will allow forensic laboratories to identify more rapidly both known and newly emerging NPS. NPS-MS is available as a web server at https://nps-ms.ca/, which provides MS/MS spectra prediction capabilities for given NPS compounds. Additionally, it offers MS/MS spectra identification against a vast database comprising approximately 8.7 million predicted NPS compounds from DarkNPS and 24.5 million predicted ESI-QToF-MS/MS spectra for these compounds.

Identification of Emerging Novel Psychoactive Substances by Retrospective Analysis of Population-Scale Mass Spectrometry Data Sets.

Over the last two decades, hundreds of new psychoactive substances (NPSs), also known as "designer drugs", have emerged on the illicit drug market. The toxic and potentially fatal effects of these compounds oblige laboratories around the world to screen for NPS in seized materials and biological samples, commonly using high-resolution mass spectrometry. However, unambiguous identification of a NPS by mass spectrometry requires comparison to data from analytical reference materials, acquired on the same instrument. The sheer number of NPSs that are available on the illicit market, and the pace at which new compounds are introduced, means that forensic laboratories must make difficult decisions about which reference materials to acquire. Here, we asked whether retrospective suspect screening of population-scale mass spectrometry data could provide a data-driven platform to prioritize emerging NPSs for assay development. We curated a suspect database of precursor and diagnostic fragment ion masses for 83 emerging NPSs and used this database to retrospectively screen mass spectrometry data from 12,727 urine drug screens from one Canadian province. We developed integrative computational strategies to prioritize the most reliable identifications and tracked the frequency of these identifications over a 3 year study period between August 2019 and August 2022. The resulting data were used to guide the acquisition of new reference materials, which were in turn used to validate a subset of the retrospective identifications. Last, we took advantage of matching clinical reports for all 12,727 samples to systematically benchmark the accuracy of our retrospective data analysis approach. Our work opens up new avenues to enable the rapid detection of emerging illicit drugs through large-scale reanalysis of mass spectrometry data.

Psychoactive substances and previous hospital admissions, triage and length of stay in rural injuries: a prospective observational study.

BACKGROUND: Patients admitted to hospital after an injury are often found to have used psychoactive substances prior to the injury. The aim of this study was to investigate the associations between psychoactive substances (alcohol, psychoactive medicinal drugs and illicit drugs) and previous hospital admissions, triage and length of stay in the arctic Norwegian county of Finnmark. METHODS: Patients ≥ 18 years admitted due to injury to trauma hospitals in Finnmark from January 2015 to August 2016 were approached. Parameters regarding admittance and hospital stay were collected from 684 patients and blood was analysed for psychoactive substances. Using a prospective, observational design, time, triage, length of stay in hospital, use of intensive care unit (ICU), injury severity, Alcohol Use Disorder Identification Test-Consumption (AUDIT-C) and number of previous admittances were investigated by bivariable testing and logistical regression analysis. RESULTS: Of 943 patients approached, 81% consented and 684 were included in the study. During the weekend, 51.5% tested positive for any substance versus 27.1% Monday-Friday. No associations were identified between testing positive and either triage or injury severity for any substance group although triage level was lower in patients with AUDIT-C ≥ 5. Short length of stay was associated with alcohol use prior to injury [odds ratio (OR) 0.48 for staying > 12 h, confidence interval (CI) 0.25-0.90]. The OR for staying > 24 h in the ICU when positive for an illicit substance was 6.33 (CI 1.79-22.32) while negatively associated with an AUDIT-C ≥ 5 (OR 0.30, CI 0.10-0.92). Patients testing positive for a substance had more often previously been admitted with the strongest association for illicit drugs (OR 6.43 (CI 1.47-28.08), compared to patients in whom no substances were detected. CONCLUSIONS: Triage level and injury severity were not associated with psychoactive substance use. Patients using alcohol are more often discharged early, but illicit substances were associated with longer ICU stays. All psychoactive substance groups were associated with having been previously admitted.

Rapid analysis of amphetamine-type substances using Agilent's QuickProbe gas chromatograph/mass spectrometer technology.

The Agilent QuickProbe gas chromatograph/mass spectrometer (QP-GCMS) is a rapid analytical instrument requiring minimal sample preparation. The instrument was considered for the screening of samples for potential implementation at New Zealand's border screening laboratory. One of the project's primary aims was to validate the method for the analysis of border seizures, including drug concealments, novel psychoactive substances (NPS), low-dose drugs and unknown substances. For the application to be useful beyond the capabilities of current handheld point-of-contact (POC) devices, the initial evaluation has included the analysis of a large variety of compounds in a large variety of matrices. These data will be reported separately. However, during the evaluation, several chromatographical challenges were encountered during the analysis of amphetamine-type substances (ATS). As such, the QP-GCMS required some troubleshooting and method development to improve resolution for this class of compounds.

Method development, validation, and application for simultaneous determination of 56 new psychoactive substances in surface water by LC-MS/MS.

Despite preventive legislation, the popularity and consumption of new psychoactive substances (NPS) have been steadily increasing in recent years. This study provides a rapid and sensitive method for the quantitation and the detection of 56 NPS from surface water. Sample clean-up and pre-concentration were performed by solid-phase extraction (SPE) with Oasis HLB (6 cc/500 mg) cartridge. Following the chromatographic separation with Shim-pack FC-ODS column, the all substances were quantified by liquid chromatography-tandem mass spectrometry. The method was optimized and validated for all NPS. Despite the wide variety of physicochemical properties of the analytes, the recoveries for all compounds studied were in the range of 69-117%. The limit of quantitation (LOQ) ranging from 2.5 to 15 ng/L was reached for reliable and accurate quantification of analytes. The analytical method developed was successfully applied to the surface water samples. While synthetic cannabinoids were not detected, mephedrone from the synthetic cathinone group was detected under the LOQ. This novel method was expected to be a part of future environmental routine analyses as a satisfactory method.

Cork sheet as an efficient biosorbent for forensic toxicology: Application to vitreous humor analysis.

There is an increasing number of people affected worldwide by mental health disorders, such as depression and anxiety. One of the main courses of treatment, along with psychotherapy, is the use of psychoactive medications, like antidepressants and benzodiazepines. Also, the unprescribed use of these substances is a concerning public health issue. Hence, the analysis of psychotropic medications is mandatory in postmortem toxicology and various biological samples can be used for this detection, among them the vitreous humor (VH) stands out. Also, there is a demand for more sustainable and more efficient extraction methodologies according to green chemistry. An example is solid phase microextraction techniques (SPME), which use a solid sorbent and small solvent amounts. Biosorbents are substances of natural origin with sorptive properties, and they have been successfully used in SPME in environmental toxicology for water analysis, mainly. This study aimed to develop a sustainable, fast, cheap and simple SPME methodology using cork sheet strips as a biosorbent, to extract antidepressants, benzodiazepines and others from VH samples by liquid chromatography coupled to tandem mass spectrometry. The extraction was conducted in a 96-well plate using 200 µL of VH and optimization of relevant parameters for extraction was performed. For solvent optimization, two simplex-centroid experiments were planned for extraction and desorption and to evaluate time and pH, a Doehlert design experiment was performed. The analytical method for the determination and quantification of 17 substances was validated. The quantification limits were 5 ng/mL for all analytes and the calibration curves were linear between 5 and 30 ng/mL. This study was able to develop an efficient, cheap, simple and fast microextraction method for 17 analytes in VH, using strips of cork sheet for extraction and a 96-well plate as a container. Furthermore, this approach system could be automated for routine toxicology laboratories.

Nail analysis for the assessment of caffeine abuse in Northwest China: A population-based study.

Caffeine is the most widely consumed psychoactive agent worldwide and has the potential for abuse, but studies monitoring caffeine abuse in China are scarce. This study aims to estimate the prevalence of caffeine abuse in northwest China and investigate the correlation between caffeine and other drugs in hair and nails using an ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). Fingernail clippings were collected from 376 participants in northwest China to detect caffeine and 13 other illicit psychoactive drugs and their metabolites. Paired hair and nail samples were collected from 39 participants to investigate the correlation between caffeine and other drugs in hair and nails. The samples were decontaminated, pulverized, and extracted by a high-throughput nail sample preparation method and analyzed by UPLC-MS/MS. The results showed a risk of caffeine abuse in northwest China, with concentrations ranging from 0.43 to 10.6 ng/mg for healthy volunteers, 0.49-246 ng/mg for caffeine abusers, and 0.25-363 ng/mg for drug addicts in community rehabilitation centers. Caffeine was detected together with other illicit psychoactive drugs and their metabolites. Furthermore, positive detection correlations were found between hair and nail samples. This study provides a current perspective on caffeine abuse in northwest China and demonstrates the practical use of UPLC-MS/MS for the simultaneous detection of caffeine and 13 illicit psychoactive drugs and their metabolites in hair and nails. The results highlight the potential of nails as a supplementary matrix when hair samples are unavailable and emphasize the need for handling caffeine carefully given its potential for abuse.

Screening strategy for ketamine-based new psychoactive substances using fragmentation characteristics from high resolution mass spectrometry.

Recreational designer drugs called new psychoactive substances (NPS) are emerging and pose enormous risks to public health. Detection of recently discovered or unreported NPS remains a huge challenge by using traditional targeted mass spectrometry methods. Here a novel screening strategy was developed to detect both known and novel analogs of NPS based on fragmentation characteristics from liquid chromatography-high resolution mass spectrometry (LC-HRMS). The HRMS fragmentation pathway of one selected NPS family was investigated to form a database containing predicted drugs as well as their mass characteristics. During the study, an unexpected substituent effect was found to distinguish geometric isomers. Seventy-eight seized samples were analyzed using this strategy, four ketamine-based NPS were detected and three of them were newly marketed. The substituent effect predicted the position of their phenylic substituent, the results were confirmed by NMR.

Direct analysis in real-time tandem mass spectrometry method for the rapid screening of 11 new psychoactive substances in blood and urine.

RATIONALE: With the continuous renewal of new psychoactive substances (NPS), the abuse of NPS has seriously harmed social security and public safety. The number of deaths from the abuse of NPS is increasing year by year. Therefore, there is an immediate need to develop an effective method for detecting NPS. METHODS: Direct analysis in real-time tandem mass spectrometry (DART-MS/MS) was used to detect 11 NPS in blood and urine. The temperature of the ion source was optimized and set to 400°C. The mixture solvent of acetonitrile/methanol (4:1, v/v) was used as the precipitant. SKF-525 (2-(diethylamino)ethyl 2,2-diphenylpentanoate) was selected as the internal standard for quantification. After the pretreatment of the analytes in blood or urine, the supernatant was prepared for instrumental analysis. RESULTS: The results indicated that the correlation coefficients (r2 ) of all analytes ranged from 0.99 to 1 in the linear range. The recoveries of 11 analytes at three spiked levels ranged between 83.4% and 110.4% in blood and between 81.7% and 108.5% in urine. The matrix effects of 11 analytes ranged between 79.5% and 109.5% in blood and between 85.0% and 109.4% in urine. The relative standard deviations of intra-day and inter-day precisions and repeatability were lower than 12.4%, 14.1%, and 14.3% in blood and lower than 11.4%, 13.9%, and 14.3% in urine, respectively. CONCLUSION: The method established for the detection of 11 NPS could meet the needs for the rapid screening of NPS samples. The DART-MS/MS method has the advantages of being efficient, fast, and green. Therefore, it may become a promising technology for the detection of NPS in the future.

Target and suspect screening of (new) psychoactive substances in South Korean wastewater by LC-HRMS.

New psychoactive substances (NPS) are a type of abused drug designed to mimic the effects of the currently known illicit drugs, whose structures are constantly changing to escape surveillance. The quick identification of NPS use in the community therefore demands immediate action. This study aimed to develop a target and suspect screening method using LC-HRMS to identify NPS in wastewater samples. An in-house database of 95 traditional and NPS was built using the reference standards, and an analytical method was developed. Wastewater samples were collected from 29 wastewater treatment plants (WWTP) across South Korea, representing 50 % of the total population. The psychoactive substances in waste water samples were screened using in-house database and developed analytical methods. A total of 14 substances were detected in the target analysis, including three NPS (N-methyl-2-AI, 25E-NBOMe, and 25D-NBOMe) and 11 traditional psychoactive substances and their metabolites (zolpidem phenyl-4-COOH, ephedrine, ritalinic acid, tramadol, phenmetrazine, phendimetrazine, phentermine, methamphetamine, codeine, morphine, and ketamine). Out of these, N-methyl-2-AI, zolpidem phenyl-4-COOH, ephedrine, ritalinic acid, tramadol, phenmetrazine, and phendimetrazine were detected with a detection frequency of over 50 %. Primarily, N-methyl-2-Al was detected in all the wastewater samples. Additionally, four NPSs (amphetamine-N-propyl, benzydamine, isoethcathinone, methoxyphenamine) were tentatively identified at level 2b in a suspect screening analysis. This is the most comprehensive study to investigate NPS using target and suspect analysis methods at the national level. This study raises a need for continuous monitoring of NPS in South Korea.

An overview of New Psychoactive Substances (NPS) in northeast Brazil: NMR-based identification and analysis of ecstasy tablets by GC-MS.

The actual illicit market for synthetic drugs is characterized by a wide variety of psychoactive substances of different chemical and pharmacological classes, such as amphetamine-type stimulants and new psychoactive substances. The knowledge about its chemical composition, as well as the nature and quantity of the active substances present, is important for emergency care in intoxication cases by these substances and to establish adequate chemical and toxicological analysis procedures in forensic laboratories. The aim of this work was to study the prevalence of amphetamine-type stimulants and new psychoactive substances in the states of Bahia and Sergipe, in the northeast region of Brazil, involving samples of drugs seized by the local police forces from 2014 to 2019. In a total of 121 seized and analyzed samples, in which ecstasy tablets predominated (n = 101), nineteen substances were identified using GC-MS and 1D NMR techniques, comprising classical synthetic drugs and new psychoactive substances (NPS). In order to determine the composition of ecstasy tablets, an analytical method based on GC-MS was applied after validation. Analyzes of 101 ecstasy tablets showed that MDMA was the main substance, being found in 57% of the samples, in amounts between 27.3 and 187.1 mg per tablet. In addition, mixtures of MDMA, MDA, synthetic cathinones and caffeine were observed in 34 samples. These results demonstrate that the variety of substances found and the composition of seized materials in northeast Brazil is similar to other studies carried out previously in other Brazilian regions.

Substances from unregulated drug markets - A retrospective data analysis of customer-provided samples from a decade of drug checking service in Zurich (Switzerland).

BACKGROUND: Drug checking services (DCS) are harm reduction interventions for people who consume illicit substances. Unregulated drug markets lead to samples with unexpected and variable contents. A retrospective data analysis of Zurich's DCS was performed to determine the nature of these samples. METHODS: This study aims to investigate the qualitative and quantitative properties of 16,815 customer-provided psychoactive drug samples analyzed chemically through the DCS in Zurich from 1st January 2011 to 31st December 2021. The main analytical method utilized for characterizing these substances was high-performance liquid chromatography and gas chromatography-mass spectrometry. Data sets are summarized using descriptive statistics. RESULTS: There was a 2.5-fold increase in the number of tested samples over the past decade. An overall proportion of 57.9% (weighted mean) of samples within our database demonstrates unexpected analytical findings and additional low sample contents during the observation period. Substantial differences in quality and quantity between substance groups were detected and an increase of sample quality and content over time was demonstrated. CONCLUSIONS: Chemical analysis reveals that over half of substances acquired from unregulated drug markets analyzed through DCS in Zurich are with low qualitative and quantitative properties, which may expose users to risks. Based on longitudinal analyses over a decade, this study contributes to the body of evidence that DCS may potentially manipulate unregulated drug markets towards providing better quality substances, as well as may stabilize these markets over time. The necessity for drug policy changes to make this service accessible in further settings was highlighted, as DCS still often take place in legal grey zones.