JOURNAL ARTICLE

A validated dilute-and-shoot LC–MS-MS urine screening for the analysis of 95 illicit drugs and medicines: Insights from clinical and forensic Brazilian cases.

  • Published In: Journal of Analytical Toxicology, 2024, v. 48, n. 5. P. 314 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Santos, Bruno Pereira Dos; Birk, Letícia; Schwarz, Patrícia; Sebben, Viviane Cristina; Sgaravatti, Ângela Malysz; Gouveia, Giovanna Cristiano de; Petry, Adriana Ubirajara Silva; Menezes, Francisco Paz de; Gonzaga, Alexsandro Pinto; Schlickmann, Paula Flores; Arbo, Marcelo Dutra; Oliveira, Tiago Franco de; Eller, Sarah 3 of 3

Abstract

This article focuses on the development, optimization, and validation of a comprehensive liquid chromatography–tandem mass spectrometry (LC–MS-MS) screening method using the dilute-and-shoot technique for the analysis of 95 illicit drugs and medicines in urine samples. Validated according to the American Academy of Forensic Science (AAFS) ANSI/ASB Standard 036 guideline, the method demonstrated satisfactory sensitivity, precision, and accuracy, with a total chromatographic run time of 7.5 minutes. Applied to 839 urine samples from clinical and forensic cases in Brazil, the method detected substances in 90.9% of samples, with lidocaine, acetaminophen, and cocaine metabolites being the most prevalent. The study highlights the method's utility for poisoning diagnosis, substance use verification, and forensic investigations, providing valuable data to inform public health and safety policies in Brazil.

Additional Information

  • Source:Journal of Analytical Toxicology. 2024/06, Vol. 48, Issue 5, p314
  • Document Type:Article
  • Subject Area:Law
  • Publication Date:2024
  • ISSN:0146-4760
  • DOI:10.1093/jat/bkae005
  • Accession Number:177948127
  • 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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