JOURNAL ARTICLE
Development and validation of a simple chromatographic method to screen oral fluid samples for drugs in DUID investigations.
Published In: Journal of Analytical Toxicology, 2024, v. 48, n. 8. P. 528 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Sarris, Gregory G; Abbott, Dustin L; Moreno, Tiffany M; Maychack, Kelly J; Limoges, Jennifer F 3 of 3
Abstract
The article focuses on the development and validation of a rapid, qualitative liquid chromatography–tandem mass spectrometry (LC–MS-MS) screening method using a single-step liquid–liquid extraction (LLE) to detect 31 drugs and metabolites, including Tier I compounds and phencyclidine, in oral fluid samples for driving under the influence of drugs (DUID) investigations. The method meets or exceeds the National Safety Council's Alcohol, Drugs and Impairment Division Tier I recommendations and adheres to ANSI/ASB forensic toxicology standards. It utilizes the Quantisal™ oral fluid collection device, a unique solvent mixture (methyl tert-butyl ether, isopropanol, and hexane) for extraction, and a Restek Raptor™ biphenyl LC column, achieving an 8-minute run time with minimal sample volume (400 µl). Validation demonstrated adequate sensitivity, specificity, minimal carryover, and stability, with comprehensive interference testing addressing potential false positives and negatives, while confirmation methods provide further specificity. This approach offers a practical, efficient alternative to immunoassays and supports forensic toxicology laboratories in DUID casework with reduced sample consumption and improved analytical differentiation.
Additional Information
- Source:Journal of Analytical Toxicology. 2024/10, Vol. 48, Issue 8, p528
- Document Type:Article
- Subject Area:Chemistry
- Publication Date:2024
- ISSN:0146-4760
- DOI:10.1093/jat/bkae068
- Accession Number:180533332
- Copyright Statement:Copyright of Journal of Analytical Toxicology is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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