This article presents research into a novel approach to identify cathinone-based drugs using statistical analysis processing in real time-high resolution mass spectrometry.
The authors describe a new method of statistical analysis processing of direct analysis in real time-high resolution mass spectrometry-derived neutral loss spectra of synthetic cathinones. The dark matter observed under collision-induced dissociation conditions is rendered as “neutral loss spectra,” and these are subsequently subjected to statistical analysis processing, specifically hierarchical clustering analysis. The resulting hierarchical clustering dendrogram provides a means by which to classify an unknown as a member of a subgroup of cathinones, based on structural similarity of its backbone to that of the scaffolds of the drugs represented in the training set. The described method can be utilized for the classification and identification of a number of classes of psychoactive compounds. (Published Abstract Provided)
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