Feature-Based Molecular Network for New Psychoactive Substance Identification: The Case of Synthetic Cannabinoids in a Seized e-Liquid and Biological Samples

• DOI: 10.1021/jasms.4c00009
• Publication Date: 2024-08-26T17:31:02Z
• Authors: Romain Magny; Bertrand Lefrère; Emmanuel Roulland; Nicolas Auzeil; Soha Farah; Camille Richeval; Alexandr Gish; Dominique Vodovar; Laurence Labat; Pascal Houzé
• Keywords: Synthetic cannabinoids; Designer drug; Psychoactive substance; Identification; Feature (linguistics)

The comprehensive detection of new psychoactive substances, including synthetic cannabinoids along with their associated metabolites in biological samples, remains an analytical challenge. To detect these chemicals, untargeted approaches using appropriate bioinformatic tools such as molecular networks are useful, albeit it necessitates a prerequisite the identification node interest within cluster. illustrate it, we reported this study and some seized e-liquid, urine, hair collected from 18-year-old poisoned patient hospitalized for neuropsychiatric disorders. A analysis e-liquid was performed gas chromatography coupled electron ionization mass spectrometry,