Identification of closely related new psychoactive substances (NPS) using solid deposition gas-chromatography infra-red detection (GC–IRD) spectroscopy

Cyclic Ion Mobility of Isomeric New Psychoactive Substances Employing Characteristic Arrival Time Distribution Profiles and Adduct Separation

Analysis of new psychoactive substances (NPS), which is essential for toxicological and forensic reasons, can be made complicated by the presence of isomers. Ion mobility has been used as a standalone technique or coupled to mass spectrometry to detect and identify NPS. However, isomer separation has so far chiefly relied on chromatography. Here we report on the determination of isomeric ratios using cyclic ion mobility-mass spectrometry without any chromatographic separation. Isomers were distinguished by mobility separation of lithium adducts. Alternatively, we used arrival time distribution (ATD) profiles that were characteristic of individual isomers and were acquired for protonated molecules or fragment ions. Both approaches provided comparable results. Calculations were used to determine the structures and collision cross sections of both protonated and lithiated isomers that accurately characterized their ion mobility properties. The applicability of ATD profiles to isomer differentiation was demonstrated using direct infusion and flow injection analysis with electrospray of solutions, as well as desorption electrospray of solid samples. Data processing was performed by applying multiple linear regression to the ATD profiles. Using the proposed ATD profile-based approach, the relationships between the determined and given content of isomers showed good linearity with coefficients of determination typically greater than 0.99. Flow injection analysis using an autosampler allowed us to rapidly determine isomeric ratios in a sample containing two isomeric pairs with a minor isomer of 10% (determined 9.3% of 3-MMC and 11.0% of 3-FMC in a mixture with buphedrone and 4-FMC). The proposed approach is not only useful for NPS, but also may be applicable to small isomeric molecules analyzed by ion mobility when complete separation of isomers is not achieved.

Synthesis, characterization and differentiation of the structural isomers of valine and tert-leucine derived synthetic cannabinoids

The identification of the synthetic cannabinoids receptor agonists (SCRAs) has always posed a great challenge to drug testing laboratories with slight structural modifications aimed at evading drug legislation. In addition, the most prevalent synthetic cannabinoids have valine and tert-leucine amino acid moieties where re-arrangement of the carbon chains can result in structural isomers that are very similar to the parent synthetic cannabinoids. This makes their analysis and identification challenging, and the problem is compounded with the difficulty in purchasing reference standards quickly and a lack of literature for comparison. Therefore, in this investigation, four series of synthetic cannabinoids (AB-PINACA, AB-CHMINACA, MMB-FUBINACA and 5-fluoro-MDMB-PINACA) and their alkyl chain structural isomers at the amino acid moieties were synthesized and characterized using various analytical techniques-gas chromatography-mass spectrometry (GC-MS), gas chromatography-infrared detection (GC-IRD) and nuclear magnetic resonance (NMR) spectroscopy to evaluate the ability of each analytical technique to differentiate the respective isomers for their identification. A total of 12 isomers were synthesized and analysed together with the four parent synthetic cannabinoids. NMR was able to differentiate between all the compounds, whereas GC-IRD was able to discern between most of the synthetic cannabinoids and their isomers. GC-MS had the least discriminating power and was not able to differentiate some of the compounds that has very similar mass spectra. The results from this work will be useful to other drug testing laboratories that are facing the identification of related synthetic cannabinoids.

An interlaboratory study to evaluate the utility of gas chromatography-mass spectrometry and gas chromatography-infrared spectroscopy spectral libraries in the forensic analysis of fentanyl-related substances

Synthetic opioids such as fentanyl account for over 71,000 of the approximately 107,000 overdose deaths reported in the United States in 2021. Fentanyl remains the fourth most identified drug by state and local forensic laboratories, and the second most identified drug by federal laboratories. The unambiguous identification of fentanyl-related substances (FRS) is challenging due to the absence or low abundance of a molecular ion in a typical gas chromatography-mass spectrometry (GC-MS) analysis and due to a low number of fragment ions that are similar among the many potential isomers of FRS. This study describes the utility of a previously reported gas chromatography-infrared (GC-IR) library for the identification of FRS within a blind, interlaboratory study (ILS) involving seven forensic laboratories. Twenty FRS reference materials, including those with isomer pairs in the library, were selected based on either their presence in the NIST library and/or some similarity of the mass spectra information produced. The ILS participants were requested to use the Florida International University (FIU) GC-MS and GC-IR libraries supplied by FIU to search for matches to their unknown spectra generated from in-house GC-MS and GC-IR analysis. The laboratories reported improvement in the positive identification of unknown FRS from ~75% using GC-MS alone to 100% correct identification using GC-IR analysis. One laboratory participant used solid phase IR analysis, which produced spectra incompatible with the vapor phase GC-IR library to generate a good comparison spectrum. However, this improved when searched against a solid phase IR library.

Instrument-independent chemometric models for rapid, calibration-free NPS isomer differentiation from mass spectral GC-MS data

Chemometric analysis of mass spectral data for the purpose of differentiating positional isomers of novel psychoactive substances has seen a substantial increase in popularity in recent years. However, the process of generating a large and robust dataset for chemometric isomer identification is time consuming and impractical for forensic laboratories. To begin to address this problem, three sets of ortho/meta/para positional ring isomers (fluoroamphetamine (FA), fluoromethamphetamine (FMA), and methylmethcathinone (MMC)) were analyzed using multiple GC-MS instruments at three distinct laboratories. A diverse assortment of instrument manufacturers, model types, and parameters was utilized in order to incorporate substantial instrumental variation. The dataset was randomly split into 70% training and 30% validation sets, stratified by instrument. Following an approach based on Design of Experiments, the validation set was used to optimize the preprocessing steps performed prior to Linear Discriminant Analysis. Using the optimized model, a minimum m/z fragment threshold was determined to allow analysts to assess whether an unknown spectrum is of sufficient abundance and quality to be compared to the model. To assess the robustness of the models, a test set was developed utilizing two instruments from a fourth laboratory that was not involved in the generation of the primary dataset in addition to spectra from widely used mass spectral libraries. Of the spectra that reached the threshold, the classification accuracy was 100% for all three isomer types. Only two of the test and validation spectra that did not reach the threshold were misclassified. The results indicate that forensic illicit drug experts world-wide can use these models for robust NPS isomer identification on the basis of preprocessed mass spectral data without the need for acquiring reference drug standards and creating instrument specific GC-MS reference datasets. The continued robustness of the models could be ensured through international collaboration to collect data that captures all potential GC-MS instrumental variation encountered in forensic illicit drug analysis laboratories. This would allow every forensic institute to confidently assign isomeric structures without the need for additional chemical analysis.

Utilization of Machine Learning for the Differentiation of Positional NPS Isomers with Direct Analysis in Real Time Mass Spectrometry

The differentiation of positional isomers is a well established analytical challenge for forensic laboratories. As more novel psychoactive substances (NPSs) are introduced to the illicit drug market, robust yet efficient methods of isomer identification are needed. Although current literature suggests that Direct Analysis in Real Time-Time-of-Flight mass spectrometry (DART-ToF) with in-source collision induced dissociation (is-CID) can be used to differentiate positional isomers, it is currently unclear whether this capability extends to positional isomers whose only structural difference is the precise location of a single substitution on an aromatic ring. The aim of this work was to determine whether chemometric analysis of DART-ToF data could offer forensic laboratories an alternative rapid and robust method of differentiating NPS positional ring isomers. To test the feasibility of this technique, three positional isomer sets (fluoroamphetamine, fluoromethamphetamine, and methylmethcathinone) were analyzed. Using a linear rail for consistent sample introduction, the three isomers of each type were analyzed 96 times over an eight-week timespan. The classification methods investigated included a univariate approach, the Welch t test at each included ion; a multivariate approach, linear discriminant analysis; and a machine learning approach, the Random Forest classifier. For each method, multiple validation techniques were used including restricting the classifier to data that was only generated on one day. Of these classification methods, the Random Forest algorithm was ultimately the most accurate and robust, consistently achieving out-of-bag error rates below 5%. At an inconclusive rate of approximately 5%, a success rate of 100% was obtained for isomer identification when applied to a randomly selected test set. The model was further tested with data acquired as a part of a different batch. The highest classification success rate was 93.9%, and error rates under 5% were consistently achieved.

Spotting isomer mixtures in forensic illicit drug casework with GC-VUV using automated coelution detection and spectral deconvolution

Analysis of isomeric mixtures is a significant analytical challenge. In the forensic field, for example, over 1000 new psychoactive substances (NPSs), comprising of many closely related and often isomeric varieties, entered the drugs-of-abuse market within the last decade. Unambiguous identification of the isomeric form requires advanced spectroscopic techniques, such as GC-Vacuum Ultraviolet Spectroscopy (GC-VUV). The continuous development of NPSs makes the appearance of a novel compound in case samples a realistic scenario. While several analytical solutions have been presented recently to confidently distinguish NPS isomers, the presence of multiple isomers in a single drug sample is typically not considered. Due to their structural similarities it is possible that a novel NPS coelutes with a known isomer and thus remains undetected. This study investigates the capabilities of VUV spectral deconvolution for peak detection and identification in incompletely resolved drug mixtures. To mimic worst case scenarios, severe coelution was deliberately induced at elevated GC temperatures. The deconvolution software was nevertheless able to correctly detect both substances, even in case of near-identical VUV spectra at almost full coelution. As a next step, spectra were subsequently removed from the reference library to simulate the scenario in which a novel substance was encountered for the first time in forensic case work. However, also in this situation the deconvolution software still detected the coelution. This work shows that a VUV library match score below 0.998 may serve as a warning that a novel substance may be present in a street sample.

Analytical Characterization of 3-MeO-PCP and 3-MMC in Seized Products and Biosamples: The Role of LC-HRAM-Orbitrap-MS and Solid Deposition GC-FTIR

Among the phencyclidine (PCP) and synthetic cathinone analogs present on the street market, 3-methoxyphencyclidine (3-MeO-PCP) is one of the most popular dissociative hallucinogen drugs, while 3-methylmethcathinone (3-MMC) is a commonly encountered psychostimulant. Numerous 3-MeO-PCP- and 3-MMC-related intoxication cases have been reported worldwide. Identification of the positional isomers of MeO-PCP and MMC families are particularly challenging for clinical and forensic laboratories; this is mostly due to their difficult chromatographic separation (particularly when using liquid chromatography–LC) and similar mass spectrometric behaviors. 3-MeO-PCP and 3-MMC were identified in two powders, detained by two subjects and seized by the police, by different analytical techniques, including liquid chromatography-high-resolution accurate-mass Orbitrap mass spectrometry (LC-HRAM-Orbitrap-MS), and solid deposition gas chromatography-Fourier transform infrared spectroscopy (sd-GC-FTIR). LC-HRAM-Orbitrap-MS allowed us to assign the elemental formulae C₁₈H₂₇NO (MeO-PCP) and C₁₁H₁₅NO (MMC) through accurate mass measurement of the two MH⁺ ions, and the comparison of experimental and calculated MH⁺ isotopic patterns. However, MH⁺ collision-induced product ions spectra were not conclusive in discriminating between the positional isomers [(3-MeO-PCP vs. 4-MeO-PCP) and (3-MMC vs. 4-MMC and 2-MMC)]. Likewise, sd-GC-FTIR easily allowed us to differentiate between the MeO-PCP and MMC positional isomers unambiguously, confirming the presence of 3-MeO-PCP and 3-MMC, due to the high-quality match factor of the experimental FTIR spectra against the target FTIR spectra of MeO-PCP and MMC isomers in a dedicated library. 3-MeO-PCP (in contrast to 3-MMC) was also detected in blood and urine samples of both subjects and analyzed in the context of routine forensic casework by LC-HRAM-Orbitrap-MS following a simple deproteinization step. In addition, this untargeted approach allowed us to detect dozens of phase I and phase II 3-MeO-PCP metabolites in all biological specimens. Analysis of the extracted samples by sd-GC-FTIR revealed the presence of 3-MeO-PCP, thus confirming the intake of such specific methoxy-PCP isomer in both cases. These results highlight the effectiveness of LC-HRAM-Orbitrap-MS and sd-GC-FTIR data in attaining full structural characterization of the psychoactive drugs, even in absence of reference standards, in both non-biological and biological specimens.

Overview of the major classes of new psychoactive substances, psychoactive effects, analytical determination and conformational analysis of selected illegal drugs

The misuse of psychoactive substances is attracting a great deal of attention from the general public. An increase use of psychoactive substances is observed among young people who do not have enough awareness of the harmful effects of these substances. Easy access to illicit drugs at low cost and lack of effective means of routine screening for new psychoactive substances (NPS) have contributed to the rapid increase in their use. New research and evidence suggest that drug use can cause a variety of adverse psychological and physiological effects on human health (anxiety, panic, paranoia, psychosis, and seizures). We describe different classes of these NPS drugs with emphasis on the methods used to identify them and the identification of their metabolites in biological specimens. This is the first review that thoroughly gives the literature on both natural and synthetic illegal drugs with old known data and very hot new topics and investigations, which enables the researcher to use it as a starting point in the literature exploration and planning of the own research. For the first time, the conformational analysis was done for selected illegal drugs, giving rise to the search of the biologically active conformations both theoretically and using lab experiments.

Gas Chromatography-Fourier Transform Infrared Spectroscopy for Unambiguous Determination of Illicit Drugs: A Proof of Concept

The increasing number of synthetic molecules constantly introduced into the illicit drug market poses a great demand in terms of separation and identification power of the analytical tools. Therefore, forensic laboratories are challenged to develop multiple analytical techniques, allowing for the reliable analysis of illicit drugs. This goal is accomplished by means of spectroscopy measurements, usually after a separation step, consisting of liquid (LC) or gas (GC) chromatography. Within the wide range of hyphenated techniques, the coupling of GC to Fourier Transform Infrared Spectroscopy (FTIR) provides a powerful identification tool, also allowing discriminating between isobars and isomers. In this research, the effectiveness of GC-FTIR is demonstrated, in achieving structure elucidation of 1-pentyl-3-(1-naphthoyl)indole, commonly known as JWH-018, a synthetic cannabinoid identified as component of illegal “incense blends.” Moreover, solid deposition FTIR enabled for boosting the sensitivity of the technique, over conventional flow (light pipe) cells, scaling down the limit of identification to the ng scale. Calibration curves for JWH-018 standard were obtained in the 20–1,000 ng range, and the limit of detection and limit of quantification were assessed as equal to 4.3 and 14.3 ng, respectively. Finally, the proposed methodology has been adopted for the identification of active principles in a real “street” sample seized by the law enforcement, consisting of an herbal matrix containing four different synthetic cannabinoids belonging to the JWH class. The correct identification of such compounds, with a high degree of chemical similarity, demonstrated the usefulness of the proposed approach for reliable analysis of complex mixtures of illicit drugs, as viable alternative to widespread mass spectrometry-based approaches.