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Rapid High-throughput Species Identification of Botanical Material Using Direct Analysis in Real Time High Resolution Mass Spectrometry
Published on: October 2, 2016
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Developments in high-resolution mass spectrometric analyses of new psychoactive substances
Joshua Klingberg1, Bethany Keen2, Adam Cawley3
1Australian Racing Forensic Laboratory, Racing NSW, Sydney, NSW, 2000, Australia. joshua.c.klingberg@gmail.com.
Archives of Toxicology
|February 10, 2022
Summary
High-resolution mass spectrometry (HRMS) advances the detection of new psychoactive substances (NPS). Novel data analysis, including machine learning, enhances identification and understanding of NPS trends and effects.
Area of Science:
- Forensic Chemistry
- Analytical Chemistry
- Toxicology
Background:
- The rise of new psychoactive substances (NPS) requires improved detection methods.
- Existing analytical techniques struggle to keep pace with emerging NPS derivatives.
- High-resolution mass spectrometry (HRMS) offers advanced capabilities for NPS analysis.
Purpose of the Study:
- To review novel applications of high-resolution mass spectrometry (HRMS) in the analysis of new psychoactive substances (NPS).
- To discuss innovative data analysis and interpretation approaches for NPS identification.
- To explore the utility of HRMS in community-level drug usage monitoring and understanding drug effects.
Main Methods:
- Utilization of high-resolution mass spectrometry (HRMS) in data-independent acquisition (DIA) modes.
- Application of broad-spectrum wastewater analysis for community NPS usage trends.
- Employment of metabolomic-based approaches to study drug effects on endogenous compounds.
- Development of advanced data analysis techniques, including machine learning and molecular networking.
Main Results:
- HRMS enables comprehensive data collection and retrospective analysis for NPS identification.
- Wastewater analysis with HRMS provides insights into community drug usage patterns.
- Metabolomic approaches reveal the impact of drugs of abuse on biological systems.
- Machine learning and molecular networking enhance the interpretation of complex toxicological data.
Conclusions:
- High-resolution mass spectrometry (HRMS) is a powerful tool for the detection and identification of new psychoactive substances (NPS).
- Innovative data analysis strategies, such as machine learning and molecular networking, are crucial for maximizing the potential of HRMS in toxicology.
- HRMS-based approaches offer significant advancements in forensic analysis, public health surveillance, and understanding the biological effects of drugs.
Keywords:
HRMSIllicit drugsMachine learningMetabolomicsMolecular networkingNew psychoactive substancesMore Related Videos
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