Spotting Isomer Mixtures in Forensic Illicit Drug Casework with GC–VUV using Automated Coelution Detection and Spectral Deconvolution

Open Access
Authors
Publication date 30-05-2021
Journal Journal of Chromatography B
Article number 122675
Volume | Issue number 1173
Number of pages 10
Organisations
  • Faculty of Science (FNWI) - Van 't Hoff Institute for Molecular Sciences (HIMS)
Abstract
Analysis of isomeric mixtures is a significant analytical challenge. In the forensic field, for example, over 1000 new psychoactive substances (NPSs), comprising of many closely related and often isomeric varieties, entered the drugs-of-abuse market within the last decade. Unambiguous identification of the isomeric form requires advanced spectroscopic techniques, such as GC-Vacuum Ultraviolet Spectroscopy (GC-VUV). The continuous development of NPSs makes the appearance of a novel compound in case samples a realistic scenario. While several analytical solutions have been presented recently to confidently distinguish NPS isomers, the presence of several isomers in a single drug sample is typically not considered. Due to their structural similarities it is possible that a novel NPS coelutes with a known isomer and thus remains undetected. This study investigates the capabilities of VUV spectral deconvolution for peak detection and identification in incompletely resolved drug mixtures. To mimic worst case scenarios, severe coelution was deliberately induced at elevated GC temperatures. The deconvolution software was nevertheless able to correctly detect both substances, even in case of near-identical VUV spectra at almost full coelution. As a next step, spectra were subsequently removed from the reference library to simulate the scenario in which a novel substance was encountered for the first time in forensic case work. However, also in this situation the deconvolution software still detected the coelution. This work shows that a library match score below 0.998 may serve as a warning that a novel substance may be present in a street sample.
Document type Article
Language English
Published at https://doi.org/10.1016/j.jchromb.2021.122675
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