Handheld Raman Spectroscopy in the First UK Home Office Licensed Pharmacist-Led Community Drug Checking Service

Field-Portable Technology for Illicit Drug Discrimination via Deep Learning of Hybridized Reflectance/Fluorescence Spectroscopic Fingerprints

Novel psychoactive substances (NPS) pose one of the greatest challenges across the illicit drug landscape. They can be highly potent, and coupled with rapid changes in structure, tracking and identifying these drugs is difficult and presents users with a "Russian roulette" if used. Benzodiazepines, synthetic opioids, synthetic cannabinoids, and synthetic cathinones account for the majority of NPS-related deaths and harm. Detecting these drugs with existing field-portable technologies is challenging and has hampered the development of community harm reduction services and interventions. Herein, we demonstrate that hybridizing fluorescence and reflectance spectroscopies can accurately identify NPS and provide concentration information with a focus on benzodiazepines and nitazenes. The discrimination is achieved through a deep learning algorithm trained on a library of preprocessed spectral data. We demonstrate the potential for these measurements to be made using a low-cost, portable device that requires minimal user training. Using this device, we demonstrate the discrimination of 11 benzodiazepines from "street" tablets that include bulking agents and other excipients. We show the detection of complex mixtures of multiple drugs, with the key example of nitazene + benzodiazepine (metonitazene + bromazolam), fentanyl + xylazine, and heroin + nitazene (etonitazene) combinations. These samples represent current drug trends and are associated with drug-related deaths. When combined with the implementation of detection technology in a portable device, these data point to the immediate potential to support harm reduction work in community-based settings. Finally, we demonstrate that the approach may be generalized to other drug classes outside NPS discrimination.

Evaluation of ATR-FTIR, HPLC-DAD, GC-MS, and GC-IR for the Analysis of 145 Street Drug Samples From Drug Checking Services

Drug checking services (DCS) are entities that allow recreational drug users to have street drug samples analyzed. Diverse analytical methods are applied for DCS, ranging from test strips to mass spectrometry (MS). This work evaluates the performance and utility of common methodologies used for DCS operating with off-site drug testing, while additionally assessing the potential of gas chromatography coupled to vapor phase infrared spectroscopy (GC-IR). Gas chromatography MS (GC-MS), GC-IR, and high-performance liquid chromatography with diode array detector (HPLC-DAD) were evaluated based on the analysis of 145 street drug samples obtained from two Swiss DCS. Additionally, attenuated total reflection Fourier-transform infrared spectroscopy (ATR-FTIR) was applied and is briefly discussed. A combined total of 245 analytes (including adulterants and cutting agents) were detected. GC-MS presented the greatest number of detected compounds, with a sensitivity of 96% compared with the sum of all analytes, followed by HPLC-DAD with 82%, while GC-IR showed limited sensitivity with 70%. GC-IR underperformed regarding the detection of low-abundant adulterants and of the main active ingredients in strongly adulterated samples. This study discusses the limitations and strengths of the evaluated methods in the specific context of DCS, while providing insights into the occurrence of false declarations (differing analytical results compared with alleged drug identity) and the distributions of adulterants and cutting agents in street drug samples. Based on our results, complementary approaches are considered the most valuable. Finally, the promotion of comprehensive guidelines regarding the quality and suitability of analytical methods for DCS would be highly desired.

Trace Detection of Adulterants in Illicit Opioid Samples Using Surface-Enhanced Raman Scattering and Random Forest Classification

The detection of trace adulterants in opioid samples is an important aspect of drug checking, a harm reduction measure that is required as a result of the variability and unpredictability of the illicit drug supply. While many analytical methods are suitable for such analysis, community-based approaches require techniques that are amenable to point-of-care applications with minimal sample preparation and automated analysis. We demonstrate that surface-enhanced Raman spectroscopy (SERS), combined with a random forest classifier, is able to detect the presence of two common sedatives, bromazolam (0.32-36% w/w) and xylazine (0.15-15% w/w), found in street opioid samples collected as a part of a community drug checking service. The Raman predictions, benchmarked against mass spectrometry results, exhibited high specificity (88% for bromazolam, 96% for xylazine) and sensitivity (88% for bromazolam, 92% for xylazine) for the compounds of interest. We additionally provide evidence that this exceeds the performance of a more conventional approach using infrared spectral data acquired on the same samples. This demonstrates the feasibility of SERS for point-of-care analysis of challenging multicomponent samples containing trace adulterants.

Benzodiazepine Boom: Tracking Etizolam, Pyrazolam, and Flubromazepam from Pre-UK Psychoactive Act 2016 to Present Using Analytical and Social Listening Techniques

INTRODUCTION

The designer benzodiazepine (DBZD) market continues to expand whilst evading regulatory controls. The widespread adoption of social media by pro-drug use communities encourages positive discussions around DBZD use/misuse, driving demand. This research addresses the evolution of three popular DBZDs, etizolam (E), flubromazepam (F), and pyrazolam (P), available on the drug market for over a decade, comparing the quantitative chemical analyses of tablet samples, purchased from the internet prior to the implementation of the Psychoactive Substances Act UK 2016, with the thematic netnographic analyses of social media content.

METHOD

Drug samples were purchased from the internet in early 2016. The characterisation of all drug batches were performed using UHPLC-MS and supported with 1H NMR. In addition, netnographic studies across the platforms X (formerly Twitter) and Reddit, between 2016-2023, were conducted. The latter was supported by both manual and artificial intelligence (AI)-driven thematic analyses, using numerous.ai and ChatGPT, of social media threads and discussions.

RESULTS

UHPLC-MS confirmed the expected drug in every sample, showing remarkable inter/intra batch variability across all batches (E = 13.8 ± 0.6 to 24.7 ± 0.9 mg; F = 4.0 ± 0.2 to 23.5 ± 0.8 mg; P = 5.2 ± 0.2 to 11.5 ± 0.4 mg). 1H NMR could not confirm etizolam as a lone compound in any etizolam batch. Thematic analyses showed etizolam dominated social media discussions (59% of all posts), with 24.2% of posts involving sale/purchase and 17.8% detailing new administration trends/poly-drug use scenarios. Artificial intelligence confirmed three of the top five trends identified manually.

CONCLUSIONS

Purity variability identified across all tested samples emphasises the increased potential health risks associated with DBZD consumption. We propose the global DBZD market is exacerbated by surface web social media discussions, recorded across X and Reddit. Despite the appearance of newer analogues, these three DBZDs remain prevalent and popularised. Reporting themes on harm/effects and new developments in poly-drug use trends, demand for DBZDs continues to grow, despite their potent nature and potential risk to life. It is proposed that greater controls and constant live monitoring of social media user content is warranted to drive active regulation strategies and targeted, effective, harm reduction strategies.

Experience and views of healthcare professionals towards people who use new psychoactive substances: Evidence from statutory, non-statutory, and private mental health and addiction healthcare services

OBJECTIVE

It is unclear how healthcare professionals (HCPs) experience and view the challenges of working with people who use New Psychoactive Substances (PWUNPS), in different healthcare services (HCS). The aim of the study was to explore HCPs' experiences of working with individuals who use NPS across statutory, non-statutory, and private mental health and addiction HCSs.

METHODS

HCPs completed in-depth semi-structured interviews. Audio recordings were transcribed verbatim with a mean duration of 30 min 55 s. Data were analysed through thematic analysis.

RESULTS

A purposive sample of 14 HCPs (6 men, 8 women) with a mean age of 42.5 years were interviewed in 2019. Organisational issues, including funding, impacted the treatment for PWUNPS and HCPs perceived a lack of support dependent on their qualifications. They reported a lack of assessment, policy, harm reduction, and awareness of NPS-related symptoms including mental health problems and stigma faced by PWUNPS.

CONCLUSION

HCPs need better training, education, and assessment processes to manage acute NPS intoxications and address the stigma associated with PWUNPS. There is a need for policy-making opportunities across different HCSs to ensure better healthcare outcomes for PWUNPS.