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“Electrochemical profiling and liquid chromatography–mass spectrometry characterization of synthetic cathinones : from methodology to detection in forensic samples”. Schram J, Parrilla M, Sleegers N, Van Durme F, van den Berg J, van Nuijs ALN, De Wael K, Drug Testing And Analysis 13, 1282 (2021). http://doi.org/10.1002/DTA.3018
Abstract: 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 (SC) 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 (SPE). 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.
Keywords: A1 Journal article; Pharmacology. Therapy; Engineering sciences. Technology; AXES (Antwerp X-ray Analysis, Electrochemistry and Speciation); Toxicological Centre
Impact Factor: 3.469
DOI: 10.1002/DTA.3018
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“Practical tool for sampling and fast analysis of large cocaine seizures”. Eliaerts J, Meert N, Van Durme F, Samyn N, De Wael K, Dardenne P, Drug testing and analysis 10, 1039 (2018). http://doi.org/10.1002/DTA.2364
Abstract: Large quantities of illicit drugs are frequently seized by law enforcement. In such cases, a representative number of samples needs to be quickly examined prior to destruction. No procedure has yet been set up which rapidly provides information regarding the homogeneity of the samples, the presence of controlled substances and the degree of purity. This study establishes a protocol for fast analysis of cocaine and its most common cutting agent, levamisole, in large seizures. The protocol is based on a hypergeometric sampling approach combined with FTIR spectrometry and Support Vector Machines (SVM) algorithms as analysis methods. To demonstrate the practical use of this approach, five large cocaine seizures (consisting between 45 and 85 units) were analysed simultaneously with GC-MS, GC-FID and a portable FTIR spectrometer using Attenuated Total Reflectance (ATR) sampling combined with SVM models. According to the hypergeometric sampling plan of the Drugs Working Group ENFSI guidelines, the required number of subsamples ranged between 19 and 23. Considering the identification analyses, the SVM models detected cocaine and levamisole in all subsamples of cases 1 to 5 (100% correct classification), which was confirmed by GC-MS analysis. Considering the quantification analyses, the SVM models were able to estimate the cocaine and levamisole content in each subsample, compared to GC-FID data. The developed strategy is easy, cost effective and provides immediate information about both the presence and concentration of cocaine and levamisole. By using this new strategy, the number of confirmation analyses with laborious and expensive chromatographic techniques could be significantly reduced.
Keywords: A1 Journal article; Pharmacology. Therapy; AXES (Antwerp X-ray Analysis, Electrochemistry and Speciation)
Impact Factor: 3.469
Times cited: 1
DOI: 10.1002/DTA.2364
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“Rapid classification and quantification of cocaine in seized powders with ATR-FTIR and chemometrics”. Eliaerts J, Dardenne P, Meert N, Van Durme F, Samyn N, Janssens K, De Wael K, Drug testing and analysis 9, 1480 (2017). http://doi.org/10.1002/DTA.2149
Abstract: Traditionally, fast screening for the presence of cocaine in unknown powders is performed by means of colour tests. The major drawbacks of these tests are subjective colour evaluation depending on the operator (50 shades of blue) and a lack of selectivity. An alternative fast screening technique is Fourier Transform InfraRed (FTIR) spectrometry. This technique provides spectra that are difficult to interpret without specialized expertise and showing a lack of sensitivity for the detection of cocaine in mixtures. To overcome these limitations, a portable FTIR spectrometer using Attenuated Total Reflectance (ATR) sampling was combined with a multivariate technique, called Support Vector Machines (SVM). Representative street drug powders (n = 482), seized during the period January 2013 to July 2015, and reference powders (n = 33) were used to build and validate a classification model (n = 515) and a quantification model (n = 378). Both models were compared with the conventional chromatographic techniques. The SVM classification model showed a high sensitivity, specificity and efficiency (99%). The SVM quantification model determined cocaine content with a root mean squared error of prediction (RMSEP) of 6% calculated over a wide working range from 4 to 99 w%. In conclusion, the developed models resulted in a clear output (cocaine detected or cocaine not detected) and a reliable estimation of the cocaine content in a wide variety of mixtures. The ATR-FTIR technique combined with SVM is a straightforward, user-friendly and fast approach for routine classification and quantification of cocaine in seized powders.
Keywords: A1 Journal article; Pharmacology. Therapy; AXES (Antwerp X-ray Analysis, Electrochemistry and Speciation)
Impact Factor: 3.469
Times cited: 9
DOI: 10.1002/DTA.2149
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