JOURNAL ARTICLE

Metabolism of the Synthetic Cathinone Alpha-Pyrrolidinoisohexanophenone in Humans Using UHPLC--MS-QToF.

  • Published In: Journal of Analytical Toxicology, 2023, v. 47, n. 3. P. 253 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Kemenes, K; Hidvégi, E; Szabó, L; Kerner, Á; Süvegh, G 3 of 3

Abstract

This article focuses on the metabolic profiling of alpha-pyrrolidinoisohexanophenone (α-PiHP), a synthetic cathinone structurally related to α-PHP and considered an analog of α-PVP, a Schedule I drug under the United Nations Convention on Psychotropic Substances. Using in vitro human liver microsome (pHLM) and S9 fraction (pS9) incubations alongside in vivo urine samples from users, ten urinary metabolites of α-PiHP were tentatively identified and characterized via liquid chromatography–high-resolution mass spectrometry. The study found that five metabolites, including those formed by keto moiety reduction and combined pyrrolidine ring oxidation with aliphatic hydroxylation, were more abundant in urine than the parent compound, highlighting their importance as biomarkers for confirming α-PiHP consumption. The proposed metabolic pathways involve keto reduction, aliphatic hydroxylation, pyrrolidine ring oxidation or ring-opening followed by carboxylation, and their combinations. These findings emphasize the necessity of detecting specific metabolites alongside the parent drug to reliably identify α-PiHP intake, especially given the analytical challenges posed by structurally similar compounds.

Additional Information

  • Source:Journal of Analytical Toxicology. 2023/04, Vol. 47, Issue 3, p253
  • Document Type:Article
  • Subject Area:Health and Medicine
  • Publication Date:2023
  • ISSN:0146-4760
  • DOI:10.1093/jat/bkac085
  • Accession Number:162674312
  • 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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