期刊
ARCHIVES OF TOXICOLOGY
卷 96, 期 4, 页码 949-967出版社
SPRINGER HEIDELBERG
DOI: 10.1007/s00204-022-03224-2
关键词
New psychoactive substances; Illicit drugs; HRMS; Machine learning; Molecular networking; Metabolomics
类别
资金
- CAUL
This paper reviews the novel applications of HRMS techniques in the analysis of NPS, including the identification of usage trends in the community through wastewater analysis and the examination of the effects of drugs of abuse on endogenous compounds using metabolomic approaches.
The proliferation of new psychoactive substances (NPS) has necessitated the development and improvement of current practices for the detection and identification of known NPS and newly emerging derivatives. High-resolution mass spectrometry (HRMS) is quickly becoming the industry standard for these analyses due to its ability to be operated in data-independent acquisition (DIA) modes, allowing for the collection of large amounts of data and enabling retrospective data interrogation as new information becomes available. The increasing popularity of HRMS has also prompted the exploration of new ways to screen for NPS, including broad-spectrum wastewater analysis to identify usage trends in the community and metabolomic-based approaches to examine the effects of drugs of abuse on endogenous compounds. In this paper, the novel applications of HRMS techniques to the analysis of NPS is reviewed. In particular, the development of innovative data analysis and interpretation approaches is discussed, including the application of machine learning and molecular networking to toxicological analyses.
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