Non-targeted detection of cathinones by high-resolution mass spectrometry based on their fragmentation pattern prediction. Application to pyrrolidine analogues in a hair case of PV8

Cathinones (i.e., beta-keto phenyl ethyl amines) are one of the most numerous and widespread categories among new psychoactive substances. A selective methodology based on diagnostic fragment criteria using high resolution mass spectrometry, is comprehensively evaluated. Based on the different fragmentation spectra that have been published in public databases such as mzCloud (www.mzcloud.org) and HighResNPS (www.highresnps.com), we have coded and evaluated the different analogues and substituents in the benzyl position (R₁), in the α-alkyl chain (R₃) and N-alkyl analogues (R₄ and R₅) for existing cathinones, especially focusing on tertiary amines containing a pyrrolidine ring. The proposed fragmentation pattern allows the prediction of the expected fragments for each type of cathinone. The detection of selective diagnostic fragments ions supports the identification among different cathinone analogues. In this work, the proposed methodology is extended from the primary data to the generation of peridate, through their conceptualization and proposed SQL searches. A real case of pyrrolidine cathinones not yet present on the illicit market or recently introduced is used as an example. Using this strategy and specific software, we were able to detect cathinones such as α-pyrrolidinoheptaphenone (PV8) in hair.