This document reports on a project with the central hypothesis that the capabilities of direct analysis in real time-high resolution of mass spectrometry can be applied to elucidate the structures of unknown novel variations of synthetic cathinones, cannabinoids, opioids, and tryptamines for the benefit of forensic science practitioners.
This report details a research project that was undertaken with four specific aims: collection of soft ionization and collision induced dissociation (CID) spectra of the commercially available standards of synthetic cathinones, cannabinoids, opioids, and tryptamines by direct analysis in real time-high resolution mass spectrometry (DART-HRMS); creation of DART-HRMS CID-derived neutral loss spectra to compile a database of neutral losses for each of the classes of molecules listed in the first specific aim; application of multivariate statistical analysis of neutral loss spectra to categorize molecules based on shared structural features; use of soft ionization spectra, neutral loss spectra, and clustering information to elucidate the structures of novel, emerging synthetic cathinones, cannabinoids, opioids, and tryptamines. Over the course of the project, most of the chemical standards were successfully analyzed by DART-HRMS. Those chemical standards included 47 cathinones, 112 cannabinoids, 53 tryptamines, and four opioids. Their neutral losses were compiled to populate a comprehensive database. The research project produced several deliverables along with four major findings: chemometric analysis of DART-HRMS mass spectrometry-derived neutral losses of the commercially available standards of synthetic drugs discussed can be used to identify new psychoactive compounds; there are a reliable set of experimental parameters that can be used to reproducibly generate neutral loss mass spectra and ATR-IR spectra; an optimized statistical analysis protocol can be applied to clarify the structures of novel psychoactive substances using fused neutral loss spectra and fused DART-HRMS neutral loss/ATR-IR spectra; a highly robust and accurate database of DART-HRMS derived-neutral loss spectra, along with an accompanying statistical analysis processing workflow can be developed against which the neutral loss spectra of unknowns can be screened.
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