Strategy for identification of new psychoactive substances in illicit samples using attenuated total reflectance infrared spectroscopy

Simultaneous chemo- and enantio-separation of 2-, 3- and 4-chloro-methcatinones by high-performance liquid chromatography-tandem mass spectrometry and its application to oral fluid samples

A method of analysis was developed for the simultaneous chemo- and enantioseparation of 2-, 3-, and 4-chloromethcathinones by high-performance liquid chromatography tandem mass-spectrometry. The fast method enables the reliable identification of positional isomers of chloromethcathinones in biological samples. In addition, the same method can be used for the enantioselective quantitative determination of one of these compounds and its major phase-1 metabolites in biological fluids. The developed method was applied to oral fluid samples collected by police during routine random traffic control in Belgium from January to November, 2023. It was found that 3-CMC was more frequently abused compared to 4-CMC. Although some differences were observed between the concentrations of enantiomers in OF, most likely the drugs were abused in the racemic form. No abuse of 2-CMC was detected at the timepoint of sample collection.

Gaussian process regression coupled with mRMR to predict adulterant concentration in cocaine

Street cocaine is often mixed with various substances that intensify its harmful effects. This paper proposes a framework to identify attenuated total reflection Fourier transform infrared spectroscopy (ATR-FTIR) intervals that best predict the concentration of adulterants in cocaine samples. Wavelengths are ranked according to their relevance through ReliefF and mRMR feature selection approaches, and an iterative process removes less relevant wavelengths based on the ranking suggested by each approach. Gaussian Process (GP) regression models are constructed after each wavelength removal and the prediction performance is evaluated using RMSE. The subset balancing a low RMSE value and a small percentage of retained wavelengths is chosen. The proposed framework was validated using a dataset consisting of 345 samples of cocaine with different amounts of levamisole, caffeine, phenacetin, and lidocaine. Averaged over the four adulterants, the GP regression coupled with the mRMR retained 1.07 % of the 662 original wavelengths, outperforming PLS and SVR regarding prediction performance.

DFT-Spectroscopy Integrated Identification Method on Unknown Terrorist Chemical Mixtures by Incorporating Experimental and Theoretical GC-MS, NMR, IR, and DFT-NMR/IR Data

In the event of a chemical attack, the rapid identification of unknown chemical agents is critical for an effective emergency response and treatment of victims. However, identifying unknown compounds is difficult, particularly when relying on traditional methods such as gas and liquid chromatography-mass spectrometry (GC-MS, LC-MS). In this study, we developed a density functional theory and spectroscopy integrated identification method (D-SIIM) for the possible detection of unknown or unidentified terrorist materials, specifically chemical warfare agents (CWAs). The D-SIIM uses a combination of GC-MS, nuclear magnetic resonance (NMR) spectroscopy, infrared (IR) spectroscopy, and quantum chemical calculation-based NMR/IR predictions to identify potential CWA candidates based on their chemical signatures. Using D-SIIM, we successfully verified the presence of blister and nerve agent simulants in samples by excluding other compounds (ethyl propyl sulfide and methylphosphonic acid), which were predicted to be candidates with high probability by GC-MS. The findings of this study demonstrate that the D-SIIM can detect substances that are likely present in CWA mixtures and can be used to identify unknown terrorist chemicals.

ATR-FTIR combined with machine learning for the fast non-targeted screening of new psychoactive substances

Due to the diversity and fast evolution of new psychoactive substances (NPS), both public health and safety are threatened around the world. Attenuated total reflection-Fourier transform infrared spectroscopy (ATR-FTIR), which serves as a simple and rapid technique for targeted NPS screening, is challenging with the rapid structural modifications of NPS. To achieve the fast non-targeted screening of NPS, six machine learning (ML) models were constructed to classify eight categories of NPS, including synthetic cannabinoids, synthetic cathinones, phenethylamines, fentanyl analogues, tryptamines, phencyclidine types, benzodiazepines, and "other substances" based on the 1099 IR spectra data items of 362 types of NPS collected by one desktop ATR-FTIR and two portable FTIR spectrometers. All these six ML classification models, including k-nearest neighbor (KNN), support vector machine (SVM), random forest (RF), extra trees (ET), voting, and artificial neural networks (ANNs) were trained through cross validation, and f1-scores of 0.87-1.00 were achieved. In addition, hierarchical cluster analysis (HCA) was performed on 100 synthetic cannabinoids with the most complex structural variation to investigate the structure-spectral property relationship, which leads to a summary of eight synthetic cannabinoid sub-categories with different "linked groups". ML models were also constructed to classify eight synthetic cannabinoid sub-categories. For the first time, this study developed six ML models, which were suitable for both desktop and portable spectrometers, to classify eight categories of NPS and eight synthetic cannabinoids sub-categories. These models can be applied for the fast, accurate, cost-effective, and on-site non-targeted screening of newly emerging NPS with no reference data available.

New trends of new psychoactive substances (NPS)-infused chocolate: Identification and quantification of trace level of NPS in complex matrix by GC-MS and NMR

For the first time, the identification and quantification of trace level of new psychoactive substances (NPS) in a complex chocolate matrix have been reported. Since the beginning of 2022, suspected NPS-infused chocolate samples confiscated in inbound packages have been continuously sent to our laboratory for analysis. The qualitative gas chromatography-mass spectrometry (GC-MS) results were verified by ¹H nuclear magnetic resonance (¹H NMR) and ¹⁹F NMR to distinguish between potential aromatic isomers. A total of 11 NPS including deoxymethoxetamine, 3-OH-PCP, 6-APB, 4-APB, 4-OH-MiPT, 3-FEA, 2-FEA, 3-MMC, bromazolam, 2-FDCK, and ADB-BUTINACA were detected in 65 seized chocolate samples. A general ¹H quantitative NMR (¹H qNMR) method for quantification of 297 types of NPS in complex chocolate matrixes was devised for the first time after rigorous analysis of various critical features of merit, including suitable deuterated solvent, internal standard, quantitative peaks, and instrument acquisition parameters. Validation of the method using six different types of NPS afforded limits of detection of 0.05-0.1 mg/mL, limits of quantification of 0.01-0.03 mg/mL, repeatability and reproducibility lower than 0.5% and 3.6%, recoveries of 91.7%∼104.4%, and absence of matrix effect. The quantitative analysis of 65 seized chocolate samples by ¹H qNMR and ¹⁹F qNMR showed that the content of NPS was in the range of 0.5 mg/g∼44.1 mg/g. Generally, the developed qNMR method was simple, fast, precise, and can be performed without reference materials of NPS. Since the type and content of NPS are relatively random, chocolate consumers will face huge health risks. Therefore, this new trend of NPS-infused chocolate deserves and requires more attention from national NPS monitoring departments as well as forensic laboratories.

Comparative study of the analysis of seized samples by GC-MS, 1H NMR and FT-IR spectroscopy within a Night-Time Economy (NTE) setting

Rapid analysis of surrendered or seized drug samples provides important intelligence for health (e.g. treatment or harm reduction), and custodial services. Herein, three in-situ techniques, GC-MS, ¹H NMR and FT-IR spectroscopy, with searchable libraries, are used to analyse 318 samples qualitatively, using technique specific library-based searches, obtained over the period 24th - 29th August 2019. 259 samples were identified as consisting of a single component, of which cocaine was the most prevalent (n = 158). Median match scores for all three techniques were ≥ 0.84 and showed agreement except for metformin (n = 1), oxandrolone (identified as vitamin K by IR (n = 4)), diazepam (identified as zolpidem by FT-IR (n = 2)) and 2-Br-4,5-DMPEA (n = 1), a structural isomer of 2C-B identified as a polymer of cellulose (cardboard) by FT-IR. 51 samples were found to consist of two or more components, of which 49 were adulterated cocaine samples (45 binary and 4 tertiary samples). GC-MS identified all components present in the 49 adulterated cocaine samples, whereas IR identified only cocaine in 88 % of cases (adulterant only = 12 %). The breakdown for ¹H NMR spectroscopy was all components identified (51 %), cocaine only (33 %), adulterant only (10 %), cocaine and one adulterant (tertiary mixtures only, 6 %).

Quantification of mixtures of analogues of illicit substances by benchtop NMR spectroscopy

This paper investigates the possibility of using benchtop NMR spectroscopy for quantification of illicit drugs (methamphetamine) in binary and ternary mixtures with impurities and cutting agents (N-isopropylbenzylamine, phenethylamine and dimethylsulfone). To avoid handling regulated substances, methamphetamine in our experiments is substituted with amino-2-propanol, which has similar functional groups and chemical structure to methamphetamine and hence a related NMR spectrum. Binary and ternary mixtures at concentrations from 30 mmol/L up to 500 mmol/L for each of these species were measured using a 60 MHz benchtop spectrometer. The spectra were analysed using both integration and a model-based algorithm that relies on a full quantum mechanical description of the studied spin systems. Both techniques were able to quantify the composition of the mixtures. The root mean squared error in the measured concentration using the model-based algorithm was < 10 mmol/L, whereas the error using integration was typically > 20 mmol/L. Thus, we conclude benchtop NMR is viable for quantitative measurements of mixtures of illicit substances, particularly when coupled with a quantum mechanical model for the analysis.

Selectivity of identification of compounds from the group of phosphodiesterase-5 inhibitors (PDE-5i) in falsified products from the Polish market using attenuated total reflectance Fourier transform infrared spectroscopy and X-ray powder diffraction

Falsified drugs are a growing problem and a great threat all over the world. Searching for easy, fast, not expensive and reproducible methods for identification of active pharmaceutical ingredients (APIs) is an important issue. The application of ATR-IR technique for identification of phosphodiesterase-5 inhibitors (PDE-5i) in falsified products from the Polish market has been demonstrated. Furthermore, the strategy of confirmation of the product's originality inaquick and easy way has been developed. The advantages of this application are: exceptional simplicity, very short measurement time, high selectivity inrelation to structurally similar substances and almost no sample preparation. After validation, developed strategy has been successfully introduced into routine analysis.

Electrochemical profiling and liquid chromatography-mass spectrometry characterization of synthetic cathinones: From methodology to detection in forensic samples

The emergence of new psychoactive drugs in the market demands rapid and accurate tools for the on-site classification of illegal and legal compounds with similar structures. Herein, a novel method for the classification of synthetic cathinones (SCs) is presented based on their electrochemical profile. First, the electrochemical profile of five common SC (i.e., mephedrone, ethcathinone, methylone, butylone, and 4-chloro-alpha-pyrrolidinovalerophenone) is collected to build calibration curves using square wave voltammetry on graphite screen-printed electrodes (SPEs). Second, the elucidation of the oxidation pathways, obtained by liquid chromatography-high-resolution mass spectrometry, allows the pairing of the oxidation products to the SC electrochemical profile, providing a selective and robust classification. Additionally, the effect of common adulterants and illicit drugs on the electrochemical profile of the SC is explored. Interestingly, a cathodic pretreatment of the SPE allows the selective detection of each SC in presence of electroactive adulterants. Finally, the electrochemical approach is validated with gas chromatography-mass spectrometry by analyzing 26 confiscated samples from seizures and illegal webshops. Overall, the electrochemical method exhibits a successful classification of SC including structural derivatives, a crucial attribute in an ever-diversifying drug market.

Discrimination of phenethylamine regioisomers and structural analogues by Raman spectroscopy

In this study, the Raman spectra of 21 phenethylamines were obtained using far-red excitation (785 nm). The distinguishing ability of Raman for phenethylamines, especially for phenethylamine regioisomers and structural analogues, was investigated. Here, the evaluation of a cross section of Raman spectra demonstrated that all types of phenethylamines were distinguishable, even for certain structural analogues with high spectrum similarity. Raman exhibited high distinguishing ability for phenethylamine regioisomers that differ in the substitution position of halogen, methoxy, alkyl, or other substituted groups; as well as for structural analogues containing different groups, such as furanyl, 2,3-dihydrofuranyl, halogen, and alkyl substituted at the same position. The Raman spectra for homologues with differences in only a methyl group were found to be highly similar; however, their spectra demonstrated small but detectable differences. Four analogue mixtures and 59 seized samples were also analyzed to study the practical use of the Raman method in forensic field. 95% of the seized samples were correctly identified, which significantly validated the ability of Raman method in identifying the correct isomers. Accordingly, this study provides a non-destructive, high-throughput and minimal sample preparation technique for the discrimination of phenethylamines.