Advances in analytical methodologies for detecting novel psychoactive substances: a review

Area of Science:

• Forensic Toxicology
• Analytical Chemistry
• Pharmacology

Background:

• Novel psychoactive substances (NPSs) present significant analytical challenges in forensic toxicology due to their rapid emergence, short detection windows, and variable potencies.
• Accurate identification, detection, and quantitation of NPSs and their metabolites are crucial for public health and legal proceedings.

Purpose of the Study:

• To review and compare the advantages and disadvantages of various analytical instruments used for NPS analysis.
• To provide a reference for forensic laboratories to select appropriate technologies based on their capabilities.

Main Methods:

• A comprehensive literature review of over 200 articles published between 2010 and 2023, with 180 articles included in the final analysis.
• Categorization of reviewed articles based on analytical technology employed: immunoassay, gas chromatography-mass spectrometry (GC-MS), liquid chromatography-low resolution MS (LC-MS-LR), and liquid chromatography-high resolution MS (LC-MS-HR).
• Organization of data into tables detailing authors, NPS drug classes, and instrumentation for easy reference.

Main Results:

• Advancements in analytical instrumentation, especially high-resolution mass spectrometry (HRMS), have significantly enhanced the ability to analyze NPSs.
• Traditional immunoassays remain valuable screening tools for specific NPS classes, such as benzodiazepines.
• The review provides a categorized overview of analytical techniques, aiding laboratories in method selection.

Conclusions:

• High-resolution mass spectrometry is a key technology for overcoming NPS analytical hurdles, offering improved sensitivity and specificity.
• A combination of techniques, including immunoassays and various forms of chromatography coupled with MS, offers a robust approach to NPS detection.
• This review serves as a valuable resource for forensic toxicologists navigating the complexities of NPS analysis.