Determination of fentanyl contamination on United States paper currency by LC-QQQ-MS.

Previous research has evaluated the extent to which cocaine and other drugs were detectable on currency in the USA. The literature was in agreement that the majority of bills exhibited some degree of contamination. With the increase of fentanyl in the illicit drug supply, this study was designed to evaluate the extent that fentanyl, cocaine, methamphetamine and other substances were present on circulating currency in 2022. A quantitative assay using liquid chromatography-triple quadrupole mass spectrometry was developed and validated to detect six analytes: fentanyl, 4-anilino-N-phenethylpiperidine, acetylfentanyl, benzylfentanyl, cocaine and methamphetamine. One-dollar bills were collected from 13 cities across the country. Sample preparation consisted of soaking the bills in methanol followed by liquid-liquid extraction. Chromatographic separation was achieved using a C18 analytical column and gradient elution with ammonium formate in water (5 mM, pH 3) and 0.1% formic acid in acetonitrile. The quantitative working range for this assay was 0.1 µg to 1.0 µg per bill (equivalent to 1 ng/mL to 100 ng/mL of extract). Fentanyl was detected on the majority (63%) of samples, with 61% of samples having ≥0.1 µg of fentanyl and 4% of samples having ≥1.0 µg. Cocaine and methamphetamine were detected on 100% and 98% of bills, respectively, typically in amounts >1.0 µg. The remaining fentanyl-related substances were detected in 15% of samples in amounts no >0.69 µg per bill and exclusively in the presence of fentanyl. Unsurprisingly, areas of the country with higher incidence of fentanyl use yielded higher frequency of contaminated bills and higher concentrations. Human exposure to drugs on currency is unlikely to have any significant impacts toxicologically or pharmacologically; however, our research findings suggest that paper currency could serve as a useful substrate for surveillance of drug trends regionally, nationally and/or internationally.

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.

Beyond a spec: assessing heterogeneity in the unregulated opioid supply.

BACKGROUND: Drug checking services aim to provide compositional information for the illicit drug supply and are being employed in public health responses to extreme rates of overdose associated with fentanyl within street opioids. The technologies used within these services range from basic qualitative tests, such as immunoassay test strips, to comprehensive quantitative analyses, such as mass spectrometry. In general, there is concern that heterogeneity of a drug mixture adds significant uncertainty when using drug checking results based on a small subsamples. The presence of hot spots of active drug components in this context is often termed the 'chocolate chip cookie effect'. Establishing the limitations of the service are essential for interpretation of the results. METHODS: This study assesses the consequence of drug heterogeneity and sampling of consumer level opioid purchased in Victoria, British Columbia ( n = 21 , 50-100 mg each) on quantitative fentanyl results determined from testing with paper spray mass spectrometry. RESULTS: Using descriptive statistics, such as relative standard deviation and interquartile range, the results demonstrate varied distributions of fentanyl concentrations within a single drug batch. However, the presence of hot spots, defined as outliers, were relatively rare. CONCLUSIONS: This study found that the variability in fentanyl concentration from drug heterogeneity and sampling is greater than that attributed to the analytical technique. On a practical level, this provides data to help guide communication of limitations of drug checking services, supporting the aim of trust and transparency between services and people who use drugs. However, if drug checking services continue to be restricted from fully engaging with the reality of manufacturing, buying, selling, mixing and dosing practices, the accuracy, usefulness, and impact will always be limited.

Magnetic solid-phase extraction based on polydopamine-coated magnetic nanoparticles for rapid and sensitive analysis of eleven illicit drugs and metabolites in wastewater with the aid of UHPLC-MS/MS.

The quantification of illicit drugs in wastewater has become a valuable tool for monitoring illicit drug abuse. The commonly utilized methods for detecting drugs in wastewater require a substantial sample volume, extended pretreatment durations, and intricate procedures. This study first employed polydopamine-coated magnetic nanocomposites as adsorbents for magnetic solid-phase extraction, combined with UPLC-MS/MS, to simultaneously determine the concentrations of eleven common illicit drugs in wastewater. The synthesis process for Fe3O4@PDA is straightforward and high-yield. Benefiting from the strong magnetic response, good dispersibility, and abundant binding sites of the prepared nanocomposites, the extraction of illicit drugs from wastewater could be achieved in just 15 min. The method exhibited satisfactory limits of quantitation (ranging from 5 to 10 ng/L), commendable accuracy (ranging from 90.59 % to 106.80 %), good precision (with RSDs below 10 %), and less sample consumption (only 1 mL). The efficacy of this method was successfully validated through its application to actual wastewater samples collected from ten wastewater treatment plants. The results indicated that morphine, codeine, methamphetamine, and ketamine were the predominant illicit drugs present in the samples. The method developed is able to meet the needs of common illicit drug monitoring and high-throughput analysis requirements.

Validation and application of a method for the quantification of 137 drugs of abuse and new psychoactive substances in hair.

INTRODUCTION: In the dynamic universe of new psychoactive substances (NPS), the identification of multiple and chemically diverse compounds remains a challenge for forensic laboratories. Since hair analysis represents a gold-standard to assess the prevalence of NPS, which are commonly detected together with classical drugs of abuse (DoA), our study aimed at developing a wide-screen method to detect and quantify 127 NPS and 15 DoA on hair. MATERIALS AND METHODS: A multi-analyte ultra-high performance liquid chromatography mass spectrometry method for the identification and quantification of 127 NPS (phenethylamines, arylcyclohexylamines, synthetic opioids, tryptamines, synthetic cannabinoids, synthetic cathinones, designer benzodiazepines) and 15 DoA in hair samples was developed. A full validation was performed according to the European medicines Agency (EMA) guidelines, by assessing selectivity, linearity, accuracy, precision, limit of quantification (LOQ), limit of detection (LOD), matrix effect and recovery. As a proof of the applicability, the method was applied to 22 authentic hair samples collected for forensic purposes. RESULTS: Successful validation was achieved, by meeting the required technical parameters, for 137 compounds (122 NPS and 15 DoA), with LOQ set at 4 pg/mg for 129 compounds, at 10 pg/mg for 6 and at 40 pg/mg for 2. The method was not considered validated for 5 NPS, as LLOQ resulted too high for a forensic analysis (80 pg/mg). Among authentic forensic samples, 17 tested positive for DoA, and 10 to NPS, most samples showing positivity for both. Detected NPS were ketamine and norketamine, 5-MMPA, ritalinic acid, methoxyacetyl fentanyl, methylone and RCS-4. CONCLUSION: The present methodology represents an easy, low cost, wide-panel method for the quantification of 122 NPS and 15 DoA, for a total of 137 analytes, in hair samples. The method can be profitably applied by forensic laboratories. Similar multi-analyte methods on the hair matrix might be useful in the future to study the prevalence of NPS and the co-occurrence of NPS-DoA abuse.

Analytical techniques for screening of cannabis and derivatives from human hair specimens.

Cannabis and associated substances are some of the most frequently abused drugs across the globe, mainly due to their anxiolytic and euphorigenic properties. Nowadays, the analysis of hair samples has been given high importance in forensic and analytical sciences and in clinical studies because they are associated with a low risk of infection, do not require complicated storage conditions, and offer a broad window of non-invasive detection. Analysis of hair samples is very easy compared to the analysis of blood, urine, and saliva samples. This review places particular emphasis on methodologies of analyzing hair samples containing cannabis, with a special focus on the preparation of samples for analysis, which involves screening and extraction techniques, followed by confirmatory assays. Through this manuscript, we have presented an overview of the available literature on the screening of cannabis using mass spectroscopy techniques. We have presented a detailed overview of the advantages and disadvantages of this technique, to establish it as a suitable method for the analysis of cannabis from hair samples.

Wastewater-based monitoring of the nitazene analogues: First detection of protonitazene in wastewater.

Synthetic opioids, particularly the nitazene analogues class, have become a public health concern due to their high potency. Wastewater-based epidemiology can detect community use of these compounds. The objective of this work was to detect nitazene analogues in wastewater from samples collected from eight sites in the United States. Influent wastewater samples were collected from eight sites in seven states (Arizona, Oregon, New Mexico, Illinois, New Jersey, Washington and Georgia) in the United States. Samples were collected from each site on three days between 27 December 2022 and 4 January 2023, acidified on collection, stored frozen and shipped to Arizona State University (Tempe, AZ) for sample processing. Samples were then shipped to The University of Queensland (Brisbane, Australia) for sample analysis. Protonitazene was found in samples collected from two sites in Washington and Illinois. The concentration was estimated up to 0.5 ng/L, with estimated excreted mass loads up to 0.3 mg/day/1000 people. This work has shown that it is possible to detect nitazene analogues in wastewater using a combination of sample pre-concentration and sensitive instrumentation, thereby further expanding the utility of wastewater-based epidemiology.

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.

Drug driving in Italy. The results of the first roadside drug testing service utilizing on-site confirmatory analysis between 2019 and 2022.

BACKGROUND: Drug driving represents a public safety concern, and the size of this issue in Italy is not fully known. Drug testing is composed of two steps: 1) screening and 2) confirmatory analysis. The second step, and the associate medical examination to assess the state of impairment, usually are not performed right after the screening as they require specialized personnel and instrumental equipment that are not historically available at roadblocks. These pitfalls make this process both complicated and time-consuming. METHODS: A mobile laboratory was set up in 2019 by the Forensic Lab Service S.r.l. (limited liability company) to improve roadblock timing, planning, as well as to shed light on the extent of the drug driving issue in Italy. Drug screenings were performed using DrugWipe® Saliva testing. Confirmatory analysis was performed on oral fluids by liquid chromatography coupled with tandem mass spectrometry. A dedicated room of the mobile laboratory was also designed for drug driving medical assessment. RESULT: 2082 samples were collected during 88 road safety services held in different locations across Italy. In total, 9 % of the tested subjects were positive to both the screening and the confirmatory analysis. The most prevalent illicit drugs found in this study were THC (72 %), followed by cocaine (41 %). Drug drivers were mostly male (93 %) and younger than 30 years of age (58 %). CONCLUSIONS: The prevalence of drivers testing positive for illicit drugs resulted to be higher compared to the results obtained in the DRUID project and to other surveys previously performed in Italy. These data demonstrate the need for control services to improve road safety in regards to drug driving.

In-sample stability and postsampling analysis of 21 illicit drugs, their metabolites and cotinine in wastewater.

A thorough understanding of the degradation of chemical biomarkers in wastewater after the sampling is critical in the surveillance of illicit drug use based on the back-calculation technique. Herein, three temperatures, eight groups of matrices, and acidification were applied to simulate the preservation condition of 21 illicit drugs, their metabolites, and cotinine for a 240-day stability study. It was proved that the temperature, matrices, and acidification play vital roles in their stability in wastewater. Most of them demonstrated high stability (transformation rates < 20%) during room temperature for 45 days, and the transformation rates decreased while the storage temperature reduced. The stability of the target compounds such as cocaine (COC), 6-monoacetylmorphine (6-MAM), and amphetamine (AM) is influenced by matrices. Acidification prevented the majority of analytes from transforming, making it a feasible solution for preservation after sampling. A model that combined the effects of temperature and matrix was developed to back-calculate the concentration of target compounds during the postsampling process. The feasibility of this model was validated by correcting the loss of COC and 6-MAM from 24.2% and 16.2% to 2.98% and 2.77%. This study simulated a typical large-scale sampling and storage scenario. The effect of the temperature, pH, and matrix on in-sample stability and the postsampling analysis of selected target compounds was investigated for the first time in this study.

Recommendations from people who use drugs in Philadelphia, PA about structuring point-of-care drug checking.

BACKGROUND: Adulterants, such as fentanyl and xylazine, among others, are present in a high percentage of the illicit drug supply, increasing the risk for overdose and other adverse health events among people who use drugs (PWUD). Point-of-care drug checking identifies components of a drug sample and delivers results consumers. To successfully meet the diverse needs of PWUD, more information is needed about the utility of drug checking, motivations for using services contextualized in broader comments on the drug supply, hypothesized actions to be taken after receiving drug checking results, and the ideal structure of a program. METHODS: In December 2021, semi-structured interviews were conducted with 40 PWUD who were accessing harm reduction services in Philadelphia, PA. Participants were asked about opinions and preferences for a future drug checking program. Interviews were audio recorded, transcribed and coded using content analysis to identify themes. RESULTS: Participants were primarily White (52.5%) and male (60%). Heroin/fentanyl was the most frequently reported drug used (72.5%, n = 29), followed by crack cocaine (60.0%, n = 24) and powder cocaine (47.5%, n = 19). Emerging themes from potential drug checking consumers included universal interest in using a drug checking program, intentions to change drug use actions based on drug checking results, deep concern about the unpredictability of the drug supply, engaging in multiple harm reduction practices, and concerns about privacy while accessing a service. CONCLUSIONS: We offer recommendations for sites considering point-of-care drug checking regarding staffing, safety, logistics, and cultural competency. Programs should leverage pre-existing relationships with organizations serving PWUD and hire people with lived experiences of drug use. They should work with local or state government to issue protections to people accessing drug checking programs and ensure the service is anonymous and that data collection is minimized to keep the program low-threshold. Programs will ideally operate in multiple locations and span "atmosphere" (e.g., from clinical to a drop-in culture), offer in-depth education to participants about results, engage with a community advisory board, and not partner with law enforcement.

Toward automated infrared spectral analysis in community drug checking.

The body of knowledge surrounding infrared spectral analysis of drug mixtures continues to grow alongside the physical expansion of drug checking services. Technicians trained in the analysis of spectroscopic data are essential for reasons that go beyond the accuracy of the analytical results. Significant barriers faced by people who use drugs in engaging with drug checking services include the speed and accuracy of the results, and the availability and accessibility of the service. These barriers can be overcome by the automation of interpretations. A random forest model for the detection of two compounds, MDA and fluorofentanyl, was trained and optimized with drug samples acquired at a community drug checking site. This resulted in a 79% true positive and 100% true negative rate for MDA, and 61% true positive and 97% true negative rate for fluorofentanyl. The trained models were applied to selected drug samples to demonstrate a proposed workflow for interpreting and validating model predictions. The detection of MDA was demonstrated on three mixtures: (1) MDMA and MDA, (2) MDA and dimethylsulfone, and (3) fentanyl, etizolam, and benzocaine. The classification of fluorofentanyl was applied to a drug mixture containing fentanyl, fluorofentanyl, 4-anilino-N-phenethylpiperidine, caffeine, and mannitol. Feature importance was calculated using shapely additive explanations to better explain the model predictions and k-nearest neighbors was used for visual comparison to labelled training data. This is a step toward building appropriate trust in computer-assisted interpretations in order to promote their use in a harm reduction context.

Five cases of unintentional exposure to BZO-4en-POXIZID among nightclub attendees in New York City.

A new class of synthetic cannabinoids called OXIZIDs has emerged in recent years. This class consists of compounds with oxindole cores and hydrazide/hydrazone linker moieties and has often been described as being designed to circumvent a Chinese class-wide ban that was effective as of 1 July 2021. However, through hair testing of nightclub attendees in New York City-a high-risk population for recreational drug use-we have evidence suggesting exposures to an OXIZID called BZO-4en-POXIZID (4en-pentyl MDA-19) prior to the effective ban. Through analysis of 6 cm segmented hair samples from attendees collected in 2021, we detected five cases of exposure. Specifically, we detected a cluster of three cases based on hair samples collected on 20 June 2021, and then two additional cases from samples collected on 16 July 2021. Four of these hair samples were long enough to analyze two 6 cm hair segments (representing approximately two 6-month timeframes) and three of four of these cases tested positive for repeated exposure (for an estimated exposure over 6 months prior to hair collection). All cases included young adult females reporting past-year cannabis use but all tested negative for tetrahydrocannabinol exposure. Three cases also reported past-year use of cocaine, ecstasy, and/or ketamine, and four cases tested positive for exposure to cocaine, 3,4-methylenedioxymethamphetamine (MDMA), 3,4-methylenedioxyamphetamine (MDA), methamphetamine and/or eutylone. These subjects were exposed to BZO-4en-POXIZID-likely as an adulterant in other drugs, and these cases are among the first documented cases which occurred approximately half a year before the Chinese legislative ban.

A comprehensive LC-MS/MS method for simultaneous analysis of 65 synthetic cannabinoids in human hair samples and application to forensic investigations.

Synthetic cannabinoids (SCs) represent a diverse class of new psychoactive substances characterized by extensive substance variety and severe abuse implications. The current situation of synthetic cannabinoid abuse in China is getting worse, with an increasing number of SC variants emerging. Therefore, it is imperative to improve synthetic cannabinoid detecting methods to align with the prevalent abuse situation in the region. In this study, a reliable and validated liquid chromatography-tandem mass spectrometry method was developed for the qualitative and quantitative analysis of 65 SC analogues in human hair samples. The validation results demonstrated satisfactory linearity (r ≥ 0.99) within the range of 25-2500 pg/mg for each SC analogue. The method exhibited limits of detection ranging from 10 to 15 pg/mg and limits of quantification ranging from 25 to 40 pg/mg. The relative standard deviations of intra-day precision and inter-day precision were below 15 %. Furthermore, negligible matrix effects were observed, with recovery rates ranging from 85.70 % to 119.43 %. Analysis of abuser demographics revealed that the primary group engaged in SC analogue abuse consisted of adolescents, predominantly males, accounting for 79.5 % of cases. Among the suspected individuals, ADB-BUTINACA and MDMB-4en-PINACA were the most frequently detected substances. The present study develops a highly sensitive analytical method and provides a comprehensive overview of the prevalence of SC abuse in the eastern region of China.

Dual Microfluidic Sensor System for Enriched Electrochemical Profiling and Identification of Illicit Drugs On-Site.

Electrochemical sensors have emerged as a new analytical tool for illicit drug detection to facilitate ultrafast and accurate identification of suspicious compounds on-site. Drugs of abuse can be identified using their unique voltammetric fingerprint at a given pH. Today, the right buffer solution is manually selected based on drug appearance, and in some cases, a consecutive analysis in two different pH solutions is required. In this work, we present a disposable microfluidic multichannel sensor system that automatically records fingerprints in two pH solutions (e.g., pH 5 and pH 12). This system has two advantages. It will overcome the manual selection of a buffer solution at the right pH, decrease analysis time, and minimize the risk of human errors. Second, the combination of two fingerprints, the superfingerprint, contains more detailed information about the samples, which enhances the selectivity of the analytical technique. First, real-time pH measurements proved that the sample can be brought to the desired pH within a minute. Subsequently, an electrochemical study on the microfluidic platform with 1 mM illicit drug standards of MDMA, cocaine, heroin, and methamphetamine showed that the characteristic voltammetric fingerprints and peak potentials are reproducible, also in the presence of common cutting agents. Finally, the microfluidic concept was validated with real confiscated samples, showing promising results for the user-friendly identification of drugs of abuse. In short, this paper presents a successful proof-of-concept study of a multichannel microfluidic sensor system to enrich the fingerprints of illicit drugs at pH 5 and pH 12, thus providing a low-cost, portable, and rapid identification system of illicit drugs with minimal user intervention.

First drug-checking study at an electronic festival and fentanyl detection in the central region of Mexico.

BACKGROUND: Perception of drug adulteration has increased in Mexico, but there is little research on adulterants and toxicity. The aim of this study was to identify drug composition in an electronic music outdoor festival nearby Mexico City. METHODS: The participants completed a questionnaire with demographic data, harm reduction strategies, drug-use patterns, history, and the drug they expected to find. We took a small sample of each substance and prepared it for drug checking. A two-section drug testing station was placed within the grounds of the festival. Interaction with participants occurred at the front part. Drug checking was conducted at the rear part. The service was free of charge, voluntary and confidential. Forty persons aged 22 to 48 years participated (mode = 28), of which 92.5% were male, most (82.5%) were single. Through the Substance Analysis Program of "ReverdeSer Collective," we conducted the testing with the attendants that provided 51 drug samples, following ethical and biosafety protocols. We used colorimetry, Fourier Transform Infrared Spectroscopy, and fentanyl immunoassay strips for sample analysis. RESULTS: Substances of choice among attendants were psychostimulants (MDMA and other amphetamine-like drugs) and hallucinogens. Most samples contained what the users expected plus adulterants. Main adulterants were methylene-dioxy-ethyl-amphetamine, methylene-dioxy-propyl-amphetamine, hydroxyamphetamine, and the selective serotonin reuptake inhibitor venlafaxine. Fentanyl was present in 2 out of 4 cocaine samples and in 14 of the 22 confirmed MDMA samples. CONCLUSIONS: Some of the adulterants found pose serious health risks, especially fentanyl, amphetamine-like substances, and venlafaxine. Therefore, it is urgent to monitor these adulterants at electronic music festivals and to implement prevention, treatment, and harm reduction public policies. Naloxone distribution and drug-assisted therapies should be part of government programs in Mexico.

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.

Assessment of two brands of fentanyl test strips with 251 synthetic opioids reveals "blind spots" in detection capabilities.

BACKGROUND: Fentanyl test strips (FTS) are a commonly deployed tool in drug checking, used to test for the presence of fentanyl in street drug samples prior to consumption. Previous reports indicate that in addition to fentanyl, FTS can also detect fentanyl analogs like acetyl fentanyl and butyryl fentanyl, with conflicting reports on their ability to detect fentanyl analogs like Carfentanil and furanyl fentanyl. Yet with hundreds of known fentanyl analogs, there has been no large-scale study rationalizing FTS reactivity to different fentanyl analogs. METHODS: In this study, 251 synthetic opioids-including 214 fentanyl analogs-were screened on two brands of fentanyl test strips to (1) assess the differences in the ability of two brands of fentanyl test strips to detect fentanyl-related compounds and (2) determine which moieties in fentanyl analog chemical structures are most crucial for FTS detection. Two FTS brands were assessed in this study: BTNX Rapid Response and WHPM DanceSafe. RESULTS: Of 251 screened compounds assessed, 121 compounds were detectable at or below 20,000 ng/mL by both BTNX and DanceSafe FTS, 50 were not detectable by either brand, and 80 were detectable by one brand but not the other (n = 52 BTNX, n = 28 DanceSafe). A structural analysis of fentanyl analogs screened revealed that in general, bulky modifications to the phenethyl moiety inhibit detection by BTNX FTS while bulky modifications to the carbonyl moiety inhibit detection by DanceSafe FTS. CONCLUSIONS: The different "blind spots" are caused by different haptens used to elicit the antibodies for these different strips. By utilizing both brands of FTS in routine drug checking, users could increase the chances of detecting fentanyl analogs in the "blind spot" of one brand.

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.

A risk-based approach to community illicit drug toxicosurveillance: operationalisation of the Emerging Drugs Network of Australia - Victoria (EDNAV) project.

INTRODUCTION: The Emerging Drugs Network of Australia - Victoria (EDNAV) project is a newly established toxicosurveillance network that collates clinical and toxicological data from patients presenting to emergency departments with illicit drug related toxicity in a centralised clinical registry. Data are obtained from a network of sixteen public hospital emergency departments across Victoria, Australia (13 metropolitan and three regional). Comprehensive toxicological analysis of a purposive sample of 22 patients is conducted each week, with reporting of results to key alcohol and other drug stakeholders. This paper describes the overarching framework and risk-based approach developed within Victoria to assess drug intelligence from EDNAV toxicosurveillance. METHODS: Risk management principles from other spheres of public health surveillance and healthcare clinical governance have been adapted to the EDNAV framework with the aim of facilitating a consistent and evidence-based approach to assessing weekly drug intelligence. The EDNAV Risk Register was reviewed over the first two years of EDNAV project operation (September 2020 - August 2022), with examples of eight risk assessments detailed to demonstrate the process from signal detection to public health intervention. RESULTS: A total of 1112 patient presentations were documented in the EDNAV Clinical Registry, with 95 signals of concern entered into the EDNAV Risk Register over the two-year study period. The eight examples examined in further detail included suspected drug adulteration (novel opioid adulterated heroin, para-methoxymethamphetamine adulterated 3,4-methylenedioxymethamphetamine (MDMA)), drug substitution (25B-NBOH sold as lysergic acid diethylamide, five benzodiazepine-type new psychoactive substances in a single tablet, protonitazene sold as ketamine), new drug detection (N,N-dimethylpentylone), contamination (unreported acetylfentanyl) and a fatality subsequent to MDMA use. A total of four public Drug Alerts were issued over this period. CONCLUSIONS: Continued toxicosurveillance efforts are paramount to characterising the changing landscape of illicit drug use. This work demonstrates a functional model for risk assessment of illicit drug toxicosurveillance, underpinned by analytical confirmation and evidence-based decision-making.