This paper proposes methods for the analysis and characterization of emerging novel variant designer drugs, especially for the class of synthetic cathinone “bath salts,” in order to enable more comprehensive, rapid, and sensitive analysis for law enforcement agencies.
The author of this paper combined Direct Analysis in Real-time (DART) mass spectrometric methods (DART-MS) and multiple statistical strategies to analyze and characterize emerging new variant designer drugs, particularly for the class of synthetic cathinone “bath salts.” The methods described by the author aim to enable more comprehensive, rapid, and sensitive analysis for enforcement agencies, and to provide a pathway for dealing with sample testing backlogs and determination of unknowns, using multivariate statistical characterization. The author used DART-MS, a soft ionization method, to allow for a strong protonated parent peak for molecular formula determination, as well as a collision-induced dissociation (CID) spectrum. The fragmented spectrum allowed for comparison of fragmentation patterns within that class of compounds to identify common neutral losses that were applied for statistical characterization. Results showed success in differentiating cathinones from non-cathinones, and the ability to sub-characterize mass spectral patterns based on neutral loss values could predict cathinone functionality with reasonable success. Other results of this research include a better understanding of the power of DART-MS and the data-rich nature of the mass spectra produced; the contribution of generated data to NIST and the DART-MS community database; a better understanding of cathinone structure and fragmentation; and the development of statistical methods of analyzing chemical analogues of designer drugs.