JOURNAL ARTICLE

Are the (New) Synthetic Opioids U-47700, Tramadol and Their Main Metabolites Prone to Time-Dependent Postmortem Redistribution?—A Systematic Study Using an In Vivo Pig Model.

  • Published In: Journal of Analytical Toxicology, 2023, v. 47, n. 3. P. 236 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Nordmeier, Frederike; Doerr, Adrian A; Potente, Stefan; Walle, Nadja; Laschke, Matthias W; Menger, Michael D; Schmidt, Peter H; Meyer, Markus R; Schaefer, Nadine 3 of 3

Abstract

This article focuses on the postmortem (PM) distribution and potential redistribution (PMR) of the synthetic opioids U-47700 and tramadol, along with their main metabolites N-desmethyl-U-47700 and O-desmethyltramadol (ODT), using a controlled toxicokinetic study in pigs. Following intravenous administration and euthanasia, tissue and fluid samples were collected up to 72 hours postmortem and analyzed via liquid chromatography–tandem mass spectrometry. The study found only low-to-moderate concentration changes over time in most tissues, with a notable increase of tramadol in liver tissue and decreases in bile and duodenum content, suggesting these latter matrices should be avoided for quantitative PM analysis. Central blood showed stable concentrations for both opioids and their metabolites, indicating it as the preferred matrix for PM quantification, while peripheral blood exhibited variable results. Overall, U-47700, tramadol, and their metabolites demonstrated a low tendency for PM redistribution under the study conditions.

Additional Information

  • Source:Journal of Analytical Toxicology. 2023/04, Vol. 47, Issue 3, p236
  • Document Type:Article
  • Subject Area:Anthropology
  • Publication Date:2023
  • ISSN:0146-4760
  • DOI:10.1093/jat/bkac082
  • Accession Number:162674310
  • 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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