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Sample Mining and Data Mining: Combined Real-Time and Retrospective Approaches for the Identification of Emerging Novel Psychoactive Substances

NCJ Number
253908
Journal
Journal of Forensic Sciences Volume: 65 Issue: 2 Dated: 2019 Pages: 550-562
Author(s)
Alex J. Krotulski; Susan Jansen-Varnum; Barry K. Logan
Date Published
2019
Length
13 pages
Annotation

This study developed, validated, and implemented for forensic toxicology testing a liquid chromatography quadrupole time of flight mass spectrometry (LC QTOF MS) assay.

Abstract

Novel psychoactive substances (NPS) are synthetic drugs that pose serious public health and safety concerns. A multitude of NPS have been identified in the United States, often implicated in forensic investigations. The most common and effective manner for identifying NPS is by use of mass spectrometry and the true utility lies within nontargeted acquisition techniques. In the current project, a SCIEX TripleTOF 5600 + with SWATH acquisition was used. Resulting data were compared against an extensive library database containing more than 800 compounds. The LC QTOFMS assay was applied to the reanalysis of biological sample extracts to discover emergent NPS. More than 3,000 sample extracts were analyzed, and more than 20 emerging NPS were detected for the first time. Among these were isopropyl U 47700, 3,4 methylenedioxy U 47700, fluorofuranylfentanyl, N methyl norfentanyl, 2F deschloroketamine, 3,4 methylenedioxy alpha PHP, eutylone, and N ethyl hexedrone. (publisher abstract modified)