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

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