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The authors discuss an article by Chandra and colleagues, published in the issue, which described the excess drug-related deaths attributable to the COVID-19 pandemic in the U.S. at a local scale. Topics include main factors proposed by Chandra and colleagues, a significant risk factor for illicit drug-related mortality, and the evolution of unregulated drug supply in British Columbia.

Drug checking services provide individuals who use drugs with the ability to test samples of their drugs for the presence of highly potent substances. However, there has been recent concern about whether the existing repertoire of point-of-care drug checking technologies, such as immunoassay strips and Fourier-transform infrared spectroscopy (FTIR), are adequate in identifying substances in the unregulated drug supply. Carfentanil and nitazene opioids, substances that are even more potent than fentanyl in vitro, have been found in the unregulated supply in North America and pose a challenge to our existing drug checking strategy. For example, etizolam has recently permeated the unregulated drug supply in North America, and has demonstrated the ability to evade point-of-care drug checking technologies. In response to the incessantly changing nature of the unregulated supply, we argue that drug checking technologies and service delivery models must continuously adapt alongside constantly changing drug markets. We provide two examples of emerging technologies, paper spray-mass spectrometry and surface-enhanced Raman spectroscopy, which address many of the shortcomings of existing technologies. For both technologies, we discuss their feasibility, where they can be offered, their advantages, and how they address gaps in our existing technologies. We contend that these technologies, and other emerging technologies, can be integrated into a future approach to drug checking that flexibly uses different technologies and service delivery methods to adapt to changes in the drug supply. [ABSTRACT FROM AUTHOR]

Introduction: Increasingly, Fourier-transform infrared (FTIR) spectroscopy is being used as a harm reduction tool to provide people who use drugs real-time information about the contents of their substances. However, FTIR spectroscopy has been shown to have a high detection limit for fentanyl and interpretation of results by a technician can be subjective. This poses concern, given that some synthetic opioids can produce serious toxicity at sub-detectable levels. The objective of this study was to develop a neural network model to identify fentanyl and related analogues more accurately in drug samples compared to traditional analysis by technicians. Methods: Data were drawn from samples analyzed point-of-care using combination FTIR spectroscopy and fentanyl immunoassay strips in British Columbia between August 2018 and January 2021. We developed neural network models to predict the presence of fentanyl based on FTIR data. The final model was validated against the results from immunoassay strips. Prediction performance was assessed using F1 score, accuracy, and area under the receiver-operating characteristic curve (AUROC), and was compared to results obtained from analysis by technicians. Results: A total of 12,684 samples were included. The neural network model outperformed results from those analyzed by technicians, with an F1 score of 96.4% and an accuracy of 96.4%, compared to 78.4% and 82.4% with a technician, respectively. The AUROC of the model was 99.0%. Fentanyl positive samples correctly detected by the model but not by the technician were typically those with low fentanyl concentrations (median: 2.3% quantity by weight; quartile 1–3: 0.0%-4.6%). Discussion: Neural network models can accurately predict the presence of fentanyl and related analogues using FTIR data, including samples with low fentanyl concentrations. Integrating this tool within drug checking services utilizing FTIR spectroscopy has the potential to improve decision making to reduce the risk of overdose and other negative health outcomes. [ABSTRACT FROM AUTHOR]

Introduction: The emergence of fentanyl and its analogues have contributed to a drastic rise in overdose‐related mortality in recent years. The objective of this study was to determine the number of drug checking samples containing fentanyl and fentanyl analogues using both point of care and confirmatory drug checking technologies. Methods: Point‐of‐care drug checking data, using a combination of fentanyl immunoassay strips and Fourier‐transform infrared spectroscopy (FTIR), were collected at harm reduction sites in Vancouver and Surrey, British Columbia. Based on current recommendations from the British Columbia Centre on Substance Use Drug Checking Project, a subset of these samples was sent for confirmatory analysis using quantitative nuclear resonance spectroscopy, gas chromatography–mass spectrometry and/or liquid chromatography‐mass spectrometry. Results: A total of 22,916 samples were tested using FTIR and fentanyl immunoassay strips, of which 6125 (29%) were positive for fentanyl and/or fentanyl analogues. FTIR identified a fentanyl analogue in five samples (all carfentanil). Of the 1467 samples sent for confirmatory analysis, fentanyl was identified in 855 (58%) and fentanyl analogues in 85 (6%), including: carfentanil (n = 56), acetyl fentanyl (n = 15), furanyl fentanyl (n = 9) and cyclopropyl fentanyl (n = 5). Discussion and Conclusion: Our research found that FTIR does not consistently distinguish between fentanyl and its analogues at point of care and that highly sensitive confirmatory drug checking technologies are needed to identify fentanyl analogues. These findings underscore the limitations of current drug checking technologies and the importance of using both point of care and confirmatory drug checking initiatives for monitoring changes in the drug supply. [ABSTRACT FROM AUTHOR]

North America has been contending with an unregulated street drug supply in which opioids are often adulterated with illicitly manufactured fentanyl. The unpredictability of composition may result in an increased risk of overdose due to unexpected elevated concentrations of the high-potency drug. Using data from a community-based drug-checking project, we evaluated trends in fentanyl concentration of illicit opioids in the context of an overdose epidemic. Using a quantification model for fentanyl hydrochloride, historical Fourier-transform infrared spectra from opioid drug-checking samples were analyzed to determine fentanyl concentrations. Median monthly fentanyl concentrations were plotted, and polynomial and autoregressive time-series analyses were performed to examine trends over time. A total of 3,621 fentanyl-positive samples were included in the study, spanning November 2017 to December 2019. Monthly median fentanyl concentrations ranged from 4.5% to 10.4%. Time-series analyses indicated that a third-degree polynomial model fit the data well (R 2 = 0.639), suggesting a cyclical pattern in median concentration over time. Notably, absolute variance in fentanyl concentration decreased by an average 0.1% per month (P  < 0.001). Future research should explore the relationship between fentanyl concentration and overdose to identify potential targeted harm-reduction interventions that can respond to changes in observed fentanyl concentration. [ABSTRACT FROM AUTHOR]

Introduction: Novel psychoactive substances (NPS) are increasingly being consumed worldwide, with synthetic cannabinoids and synthetic opioids being the second and third most commonly used NPS, respectively. Certain synthetic cannabinoids can produce significant harms, particularly when used with opioids. The objective of this study was to characterise the presence of synthetic cannabinoids in the unregulated drug supply in three Canadian settings Methods: In the British Columbia setting, all samples were first analysed at point‐of‐care using combination Fourier‐transform infrared (FTIR) spectroscopy and fentanyl immunoassay strips prior to confirmatory testing using quantitative nuclear magnetic resonance spectroscopy, gas chromatography/mass spectrometry (GC/MS) and/or liquid chromatography/mass spectrometry (LC/MS). In the Toronto, Ontario setting, the samples were analysed directly by GC/MS, LC/MS liquid chromatography‐high resolution/mass spectrometry. Results: Between January 2018 and December 2019, 38 (2.8%) synthetic cannabinoid samples were detected in the unregulated drug supply (25/909 in British Columbia and 13/440 in Ontario). In British Columbia and Ontario, 76% and 85% of samples, respectively, were expected by individuals to be an opioid. Synthetic cannabinoids detected included AMB‐FUBINACA, AB‐FUBINACA, 5‐fluoro‐MDMB‐PINACA, and 5‐fluoro‐MDMB‐PICA, and largely co‐occurred with fentanyl. In the British Columbia context, Fourier‐transform infrared spectroscopy failed to detect synthetic cannabinoid compounds in almost half (48%) of the samples at point‐of‐care. Discussion and Conclusions: As point‐of‐care technologies failed to detect these compounds in many occasions, our findings demonstrate the importance of laboratory confirmatory analysis to identify NPS. Given the high risk of harm associated with the consumption of synthetic cannabinoids, further research should investigate the reasons for adulteration. [ABSTRACT FROM AUTHOR]

Introduction and Aims: Drug checking is a harm reduction intervention increasingly used in the context of the opioid overdose epidemic. The aim of the study was to determine the limit of detection for fentanyl of two point-of-care drug checking technologies.Design and Methods: Samples tested at point-of-care using Bruker Fourier transform infrared (FTIR) spectroscopy and BTNX fentanyl immunoassay strips were sent for confirmatory laboratory analysis using quantitative nuclear magnetic resonance (qNMR) spectroscopy. Concentrations by weight were determined and compared to results obtained with point-of-care methods.Results: In total, 283 samples were sent for qNMR analysis; among these, 173 (61.1%) tested positive for fentanyl. As determined by qNMR, fentanyl concentration by weight ranged from 1% to 91%. Among these 173 samples, fentanyl was not detected in 30 (17.3%) samples by FTIR and in 4 (2.3%) samples by test strip. Samples containing fentanyl that went undetected by FTIR had concentrations ≤10%. The four samples containing fentanyl that went undetected by test strip had concentrations ≤5% (i.e. 1%, 3%, 4%, 5%).Discussion and Conclusions: Fentanyl immunoassay strips were able to consistently detect the presence of fentanyl in samples at lower concentrations than FTIR spectroscopy. Given that FTIR spectroscopy is able to quantify content, mixture and concentrations on an array of compounds beyond just fentanyl but requires concentrations generally greater than 10%, these findings provide evidence for use of FTIR spectroscopy and immunoassay strips in combination to compensate for the limitations of each technology alone. [ABSTRACT FROM AUTHOR]