Workflow to facilitate the detection of new psychoactive substances and drugs of abuse in influent urban wastewater.

The complexity around the dynamic markets for new psychoactive substances (NPS) forces researchers to develop and apply innovative analytical strategies to detect and identify them in influent urban wastewater. In this work a comprehensive suspect screening workflow following liquid chromatography - high resolution mass spectrometry analysis was established utilising the open-source InSpectra data processing platform and the HighResNPS library. In total, 278 urban influent wastewater samples from 47 sites in 16 countries were collected to investigate the presence of NPS and other drugs of abuse. A total of 50 compounds were detected in samples from at least one site. Most compounds found were prescription drugs such as gabapentin (detection frequency 79%), codeine (40%) and pregabalin (15%). However, cocaine was the most found illicit drug (83%), in all countries where samples were collected apart from the Republic of Korea and China. Eight NPS were also identified with this protocol: 3-methylmethcathinone 11%), eutylone (6%), etizolam (2%), 3-chloromethcathinone (4%), mitragynine (6%), phenibut (2%), 25I-NBOH (2%) and trimethoxyamphetamine (2%). The latter three have not previously been reported in municipal wastewater samples. The workflow employed allowed the prioritisation of features to be further investigated, reducing processing time and gaining in confidence in their identification.

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.

The use of novel electronic nose technology to locate missing persons for criminal investigations.

The search for missing persons is a major challenge for investigations involving presumed deceased individuals. Currently, the most effective tool is the use of cadaver-detection dogs; however, they are limited by their cost, limited operation times, and lack of granular information reported to the handler. Thus, there is a need for discrete, real-time detection methods that provide searchers explicit information as to whether human-decomposition volatiles are present. A novel e-nose (NOS.E) developed in-house was investigated as a tool to detect a surface-deposited individual over time. The NOS.E was able to detect the victim throughout most stages of decomposition and was influenced by wind parameters. The sensor responses from different chemical classes were compared to chemical class abundance confirmed by two-dimensional gas chromatography - time-of-flight mass spectrometry. The NOS.E demonstrated its ability to detect surface-deposited individuals days and weeks since death, demonstrating its utility as a detection tool.

Identification of the synthetic cannabinoid-type new psychoactive substance, CH-PIACA, in seized material.

Synthetic cannabinoids (SCs) remain the largest class of new psychoactive substances (NPS), and while the number of NPS that are reported to the European Monitoring Centre for Drugs and Drug Addiction (EMCDDA) for the first time each year declines, the number of newly reported SCs still exceeds other NPS classes. This decline can be seen as a result of legislative changes by different jurisdictions which have sometimes transitioned to a more generalized approach when controlling substances by defining common structural scaffolds rather than explicit structures. While the consequences of such legislative changes have been expected over the years, the introduction of so-called "class-wide" bans puts further pressure on clandestine laboratories to synthesize compounds which are out of the scope of the legislation, and thus, these compounds are initially harder to detect and/or identify in the absence of analytical data. Recently, a SC with an indole-3-acetamide core-linker scaffold, AD-18 (i.e., ADB-FUBIATA or ADB-FUBIACA), was reported for the first time in China in 2021. Here, an additional cannabinoid with the indole-3-acetamide scaffold, N-cyclohexyl-2-(1-pentyl-1H-indol-3-yl)acetamide (CH-PIACA), is reported which was identified for the first time in a seized material in Denmark. Structural characterization was performed using gas chromatography-mass spectrometry (GC-MS), liquid chromatography-high-resolution mass spectrometry (LC-HRMS), and nuclear magnetic resonance (NMR) spectroscopy.

Developments in high-resolution mass spectrometric analyses of new psychoactive substances.

The proliferation of new psychoactive substances (NPS) has necessitated the development and improvement of current practices for the detection and identification of known NPS and newly emerging derivatives. High-resolution mass spectrometry (HRMS) is quickly becoming the industry standard for these analyses due to its ability to be operated in data-independent acquisition (DIA) modes, allowing for the collection of large amounts of data and enabling retrospective data interrogation as new information becomes available. The increasing popularity of HRMS has also prompted the exploration of new ways to screen for NPS, including broad-spectrum wastewater analysis to identify usage trends in the community and metabolomic-based approaches to examine the effects of drugs of abuse on endogenous compounds. In this paper, the novel applications of HRMS techniques to the analysis of NPS is reviewed. In particular, the development of innovative data analysis and interpretation approaches is discussed, including the application of machine learning and molecular networking to toxicological analyses.

Metabolomics-driven determination of targets for salicylic acid and ibuprofen in positive electrospray ionization using LC-HRMS.

Due to the large number of basic therapeutic and illicit drugs, systematic toxicological analysis has widely been performed with liquid chromatography coupled to mass spectrometry using positive electrospray ionization. However, there exist a smaller number of drugs, typically acidic drugs, which require the use of negative electrospray ionization either via a separate analysis or polarity switching. Here, targets relating to salicylic acid and ibuprofen in positive electrospray ionization were determined through a metabolomics-driven retrospective investigation of forensic casework. Samples were previously screened using liquid chromatography coupled with high-resolution mass spectrometry with quantification of target analytes performed using liquid chromatography with tandem mass spectrometry. Of the 1,717 whole-blood samples submitted between 2014 and 2019, 48 were positive for salicylic acid (1.1-1,400 mg/kg) and 78 for ibuprofen (1-46 mg/kg). Based on the retrospective analysis, 19 and 90 targets were identified for salicylic acid and ibuprofen, respectively. For targets of salicylic acid, the protonated adduct of salicyluric acid ([M + H]+ , m/z 196.0605) was present in 89.6% (n = 32) of the salicylic acid positive cases, while the [M + HCOOH + CH3 CN + Ca - H]+ adduct (m/z 264.0179) of salicylic acid was present in all positive samples with concentrations above 66 mg/kg salicylic acid. Similarly, the [M + 2Na - H]+ adduct (m/z 251.1018) of ibuprofen was present in 98.7% (n = 77) of positive cases and was present in all samples with concentrations above 3 mg/kg ibuprofen.

Development of a single retention time prediction model integrating multiple liquid chromatography systems: Application to new psychoactive substances.

Database-driven suspect screening has proven to be a useful tool to detect new psychoactive substances (NPS) outside the scope of targeted screening; however, the lack of retention times specific to a liquid chromatography (LC) system can result in a large number of false positives. A singular stream-lined, quantitative structure-retention relationship (QSRR)-based retention time prediction model integrating multiple LC systems with different elution conditions is presented using retention time data (n = 1281) from the online crowd-sourced database, HighResNPS. Modelling was performed using an artificial neural network (ANN), specifically a multi-layer perceptron (MLP), using four molecular descriptors and one-hot encoding of categorical labels. Evaluation of test set predictions (n = 193) yielded coefficient of determination (R2) and mean absolute error (MAE) values of 0.942 and 0.583 min, respectively. The model successfully differentiated between LC systems, predicting 54%, 81% and 97% of the test set within ±0.5, ±1 and ±2 min, respectively. Additionally, retention times for an analyte not previously observed by the model were predicted within ±1 min for each LC system. The developed model can be used to predict retention times for all analytes on HighResNPS for each participating laboratory's LC system to further support suspect screening.

Finding the proverbial needle: Non-targeted screening of synthetic opioids in equine plasma.

Synthetic opioids are a class of compounds that are of particular concern due to their high potency and potential health impacts. With the relentless emergence of new synthetic opioid derivatives, non-targeted screening strategies are required that do not rely on the use of library spectra or reference materials. In this study, product ion searching, and Kendrick mass defect analysis were investigated for non-targeted screening of synthetic opioids. The estimated screening cut-offs for these techniques ranged between 0.05 and 0.1 ng/mL. These techniques were designed to not be reliant on a particular vendor's software, meaning that they can be applied to existing drug screening protocols, without requiring the development and validation of new analytical procedures. The efficacy of the developed techniques was tested through blind trials, with spiked samples inserted amongst authentic plasma samples, which demonstrated the usefulness of these methods for high-throughput screening. The use of a non-targeted screening workflow that contains complementary techniques can increase the likelihood of detecting compounds of interest within a sample, as well as the confidence in detections that are made.

Current applications of high-resolution mass spectrometry for the analysis of new psychoactive substances: a critical review.

The proliferation of new psychoactive substances (NPS) in recent years has resulted in the development of numerous analytical methods for the detection and identification of known and unknown NPS derivatives. High-resolution mass spectrometry (HRMS) has been identified as the method of choice for broad screening of NPS in a wide range of analytical contexts because of its ability to measure accurate masses using data-independent acquisition (DIA) techniques. Additionally, it has shown promise for non-targeted screening strategies that have been developed in order to detect and identify novel analogues without the need for certified reference materials (CRMs) or comprehensive mass spectral libraries. This paper reviews the applications of HRMS for the analysis of NPS in forensic drug chemistry and analytical toxicology. It provides an overview of the sample preparation procedures in addition to data acquisition, instrumental analysis, and data processing techniques. Furthermore, it gives an overview of the current state of non-targeted screening strategies with discussion on future directions and perspectives of this technique. Graphical Abstract Missing the bullseye - a graphical respresentation of non-targeted screening. Image courtesy of Christian Alonzo.

Characterization of hallucinogenic phenethylamines using high-resolution mass spectrometry for non-targeted screening purposes.

Hallucinogenic phenethylamines such as 2,5-dimethoxyphenethylamines (2C-X) and their N-(2-methoxybenzyl) derivatives (25X-NBOMe) have seen an increase in novel analogues in recent years. These rapidly changing analogues make it difficult for laboratories to rely on traditional targeted screening methods to detect unknown new psychoactive substances (NPS). In this study, twelve 2C-X, six 2,5-dimethoxyamphetamines (DOX), and fourteen 25X-NBOMe derivatives, including two deuterated derivatives (2C-B-d6 and 25I-NBOMe-d9 ), were analyzed using ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-QTOF-MS). Collision-induced dissociation (CID) experiments were performed using collision energies set at 10, 20, and 40 eV. For 2C-X and DOX derivatives, common losses were observed including neutral and radical losses such as NH3 (17.0265 Da), •CH6 N (32.0500 Da), C2 H7 N (45.0578 Da) and C2 H9 N (47.0735 Da). 2C-X derivatives displayed common product ions at m/z 164.0837 ([C10 H12 O2 ]+• ), 149.0603 ([C9 H9 O2 ]+ ), and 134.0732 ([C9 H10 O]+• ) while DOX derivatives had common product ions at m/z 178.0994 ([C11 H14 O2 ]+• ), 163.0754 ([C10 H11 O2 ]+ ), 147.0804 ([C10 H11 O]+ ), and 135.0810 ([C9 H11 O]+ ). 25X-NBOMe had characteristic product ions at m/z 121.0654 ([C8 H9 O]+ ) and 91.0548 ([C7 H7 ]+ ) with minor common losses corresponding to 2-methylanisole (C8 H10 O, 122.0732 Da), 2-methoxybenzylamine (C8 H11 NO, 137.0847 Da), and •C9 H14 NO (152.1074 Da). Novel analogues of the selected classes can be detected by applying neutral loss filters (NLFs) and extracting the common product ions. Copyright © 2017 John Wiley & Sons, Ltd.

Simultaneous Screening and Quantification of Basic, Neutral and Acidic Drugs in Blood Using UPLC-QTOF-MS.

An analytical method using ultra performance liquid chromatography (UPLC) quadrupole time-of-flight mass spectrometry (QTOF-MS) was developed and validated for the targeted toxicological screening and quantification of commonly used pharmaceuticals and drugs of abuse in postmortem blood using 100 µL sample. It screens for more than 185 drugs and metabolites and quantifies more than 90 drugs. The selected compounds include classes of pharmaceuticals and drugs of abuse such as: antidepressants, antipsychotics, analgesics (including narcotic analgesics), anti-inflammatory drugs, benzodiazepines, beta-blockers, amphetamines, new psychoactive substances (NPS), cocaine and metabolites. Compounds were extracted into acetonitrile using a salting-out assisted liquid-liquid extraction (SALLE) procedure. The extracts were analyzed using a Waters ACQUITY UPLC coupled with a XEVO QTOF mass spectrometer. Separation of the analytes was achieved by gradient elution using Waters ACQUITY HSS C18 column (2.1 mm x 150 mm, 1.8 µm). The mass spectrometer was operated in both positive and negative electrospray ionization modes. The high-resolution mass spectrometry (HRMS) data was acquired using a patented Waters MSE acquisition mode which collected low and high energy spectra alternatively during the same acquisition. Positive identification of target analytes was based on accurate mass measurements of the molecular ion, product ion, peak area ratio and retention times. Calibration curves were linear over the concentration range 0.05-2 mg/L for basic and neutral analytes and 0.1-6 mg/L for acidic analytes with the correlation coefficients (r2) > 0.96 for most analytes. The limits of detection (LOD) were between 0.001-0.05 mg/L for all analytes. Good recoveries were achieved ranging from 80% to 100% for most analytes using the SALLE method. The method was validated for sensitivity, selectivity, accuracy, precision, stability, carryover and matrix effects. The developed method was tested on a number of authentic forensic samples producing consistent results that correlated with results obtained from other validated methods.

Analysis of new designer drugs in post-mortem blood using high-resolution mass spectrometry.

An analytical method was developed and validated for the purpose of detecting and quantifying 37 new designer drugs including cathinones, hallucinogenic phenethylamines and piperazines. Using only 100 µL whole blood, a salting-out-assisted liquid-liquid extraction with acetonitrile was performed to isolate target compounds followed by chromatographic separation using a Waters ACQUITY ultra performance liquid chromatograph coupled to a Waters XEVO quadrupole time-of-flight mass spectrometer. Mephedrone-d3 was used as an internal standard. A gradient elution was used in combination with a Waters ACQUITY HSS C18 column (2.1 × 150 mm, 1.8 µm). Samples were analyzed using the detector in positive electrospray ionization mode with MS(E) acquisition. All compounds of interest were resolved in a 15 min run time and positively identified based on accurate mass of the molecular ion, two product ions and retention time. All analyte calibration curves were linear over the range of 0.05-2 mg/L with most correlation coefficient (r(2)) values >0.98. The limits of detection were within the range of 0.007-0.07 mg/L and limits of quantification within 0.05-0.1 mg/L. All analytes were stable 48 h after extraction and most were stable in blood after 1 week stored in a refrigerator and 3 freeze-thaw cycles. No carryover was observed up to 10 mg/L and no interferences from common therapeutic drugs or endogenous compounds. Recoveries ranged from 71 to 100% and matrix effects were assessed for blank, post-mortem and decomposed blood. All bias and % coefficient of variation values were within the acceptable values of ±15 and ≤15%, respectively (±20 and ≤20% at lower limit of quantification). The method was applied to several forensic cases where the subject exhibited behavior characteristic of designer drug intoxication and where routine screening for a panel of drugs was negative.