Date of Award
Fall 12-2025
Document Type
Thesis
Degree Name
Master of Science (MS)
Department/Program
Forensic Science
Language
English
First Advisor or Mentor
Ana Pego
Second Reader
Marta Concheiro-Guisan
Third Advisor
Sarah Eller
Abstract
The continuous emergence of novel psychoactive substances (NPS) poses a significant challenge for forensic and clinical toxicologists, due to their structural diversity, rapid turnover on the illicit drug market, and limited toxicological information. Hair is a powerful matrix for retrospective drug exposure assessment and monitoring NPS worldwide. Not only does it provide a broad window of detection but also a simple sample exchange amongst laboratories. However, the extraction of multi-class NPS in a single method remains an analytical challenge. Therefore, there is an urgent need for extraction techniques and analytical methods that are both rapid and capable of multi-class quantitation to keep pace with the evolving drug landscape. This study aimed to develop a fast, high-throughput method capable of detecting and quantifying over 30 emerging NPS (most reported on the market since 2024) across multiple classes – including synthetic opioids, cathinones, cannabinoids, benzodiazepines, dissociatives, and hallucinogens. The goal is to support early monitoring efforts across different countries by targeting substances prioritized in the most recent Early Warning Systems. A fast and straightforward method for the analysis of 31 NPS in hair has been pre-validated. As a proof of concept, hair samples obtained from electronic music festivals in Europe and Brazil have been tested. The present study represents an advancement in NPS detection in hair, offering speed and a monitoring tool to aid the shifting NPS landscape. This method is applicable to research groups, law enforcement, regulatory agencies and provides a great tool towards establishing NPS global trends.
Recommended Citation
Hwang, Seokjin, "Fast & Forensic: Rapid Detection & Quantitation of 30 + Emerging Novel Psychoactive Substances in Hair Using LC-MS/MS" (2025). CUNY Academic Works.
https://academicworks.cuny.edu/jj_etds/345
