PuSH - Publikationsserver des Helmholtz Zentrums München: Profiling of synthesis-related impurities of the synthetic cannabinoid Cumyl-5F-PINACA in seized samples of e-liquids via multivariate analysis of UHPLC-MSn data.

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Münster-Müller, S.* ; Matzenbach, I.* ; Knepper, T.* ; Zimmermann, R. ; Pütz, M.*

Profiling of synthesis-related impurities of the synthetic cannabinoid Cumyl-5F-PINACA in seized samples of e-liquids via multivariate analysis of UHPLC-MSn data.

Drug Test. Anal. 12, 119-126 (2020)

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Vaping of synthetic cannabinoids via e-cigarettes is growing in popularity. In the present study, we tentatively identified 12 by-products found in a pure sample of the synthetic cannabinoid Cumyl-5F-PINACA (1-(5-fluoropentyl)-N-(2-phenylpropan-2-yl)-1H-indazole-3-carboxamide), a prevalent new psychoactive substance (NPS) in e-liquids, via high-resolution mass spectrometry fragmentation experiments (HRMS/MS). Furthermore, we developed a procedure to reproducibly extract this synthetic cannabinoid and related by-products from an e-liquid matrix via chloroform and water. The extracts were submitted to flash chromatography (F-LC) to isolate the by-products from the main component. The chromatographic impurity signature was subsequently assessed by ultra-high-performance liquid chromatography coupled to mass spectrometry (UHPLC-MS) and evaluated by automated integration. The complete sample preparation sequence (F-LC + UHPLC-MS) was validated by comparing the semi-quantitative signal integrals of the chromatographic impurity signatures of five self-made e-liquids with varying concentrations of Cumyl-5F-PINACA [0.1, 0.2, 0.5, 0.7 and 1.0% (w/w)], giving an average relative standard deviation of 6.2% for triplicate measurements of preparations of the same concentration and 10.5% between the measurements of the five preparations with different concentrations. Lastly, the chromatographic signatures of 14 e-liquid samples containing Cumyl-5F-PINACA from police seizures and Internet test purchases were evaluated via hierarchical cluster analysis for potential links. For the e-liquid samples originating from test purchases, it was found that the date of purchase, the identity of the online shop, and the brand name are the critical factors for clustering of samples.

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