Development & Validation of A Rapid GC-MS Method for Seized Drug Screening

Published

February 15, 2023

Author(s)

Madeline Bloom, Edward Sisco, Ira Lurie

Abstract

Controlled substances are one of the most frequently analyzed types of evidence in forensic laboratories. An increase in frequency of seizures in recent years has necessitated a need for rapid screening techniques to decrease case backlogs and expedite confirmatory analyses. The most utilized technique for the analysis of seized drugs is gas chromatography mass spectrometry (GC-MS). While this approach typically takes tens of minutes, advances in the technique have enabled approximately 1 min run times with a short column and rapid (ºC/s) temperature program. These advances were used to develop and validate a rapid GC-MS method for screening seized drug samples. Method validation was completed to determine the retention time repeatability and reproducibility, limits of detection, identification accuracy, selectivity, and carryover. Validation results showed the utility of this method for accurate and precise qualitative analyses for the screening of seized drugs across seven different drug classes. The optimized method was then applied to 15 real case samples from the Maryland State Police Forensic Sciences Division. Controlled substances, cutting agents, and other diluents were identified from these samples using acceptance criteria of retention time and mass spectral comparisons that are currently used in casework. Use of rapid GC-MS methods like this in casework could enable faster, more reliable presumptive testing results for the analysis of seized drug exhibits.

Citation

Forensic Chemistry

Volume

33

Pub Type

Journals

Download Paper

https://doi.org/10.1016/j.forc.2023.100479

Local Download

Keywords

GC-MS, Seized drugs, Rapid screening method, Method validation

Citation

Bloom, M. , Sisco, E. and Lurie, I. (2023), Development & Validation of A Rapid GC-MS Method for Seized Drug Screening, Forensic Chemistry, [online], https://doi.org/10.1016/j.forc.2023.100479, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=935899 (Accessed April 29, 2024)