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Determination of amphetamine enantiomers in urine by conductive vial electromembrane extraction and ultra-high performance supercritical fluid chromatography tandem mass spectrometry

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  • معلومة اضافية
    • الموضوع:
      2023
    • Collection:
      University of Copenhagen: Research / Forskning ved Københavns Universitet
    • نبذة مختصرة :
      Separation and quantification of amphetamine enantiomers are commonly used to distinguish between consumption of prescription amphetamine (mostly S-amphetamine) and illicit forms of the drug (racemate). In this study, electromembrane extraction with prototype conductive vials was combined with ultra-high performance supercritical fluid chromatography (UHPSFC-MS/MS) to quantify R- and S-amphetamine in urine. Amphetamine was extracted from 100 μL urine, diluted with 25 μL internal standard solution and 175 μL 130 mM formic acid, across a supported liquid membrane (SLM) consisting of 9 μL of a 1:1(w/w) mixture of 2-nitrophenyloctyl ether (NPOE) and bis(2-ethylhexyl)phosphite (DEHPi) into an acceptor phase containing 300 μL 130 mM formic acid. The extraction was facilitated by the application of 30 V for 15 min. Enantiomeric separation was achieved using UHPSFC-MS/MS with a chiral stationary phase. The calibration range was 50–10,000 ng/mL for each enantiomer. The between-assay CV was ≤5%, within-assay CV ≤ 1.5%, and bias within ±2%. Recoveries were 83%–90% (CV ≤ 6%), and internal standard corrected matrix effects were 99–105 (CV ≤ 2%). The matrix effects ranged from 96% to 98% (CV ≤ 8%) when not corrected by the internal standard. The EME method was compared with a chiral routine method that employed liquid–liquid extraction (LLE) for sample preparation. Assay results were in agreement with the routine method, and the mean deviation between methods was 3%, ranging from −21% to 31%. Finally, sample preparation greenness was assessed using the AGREEprep tool, which resulted in a greenness score of 0.54 for conductive vial EME, opposed to 0.47 for semi-automated 96-well LLE.
    • File Description:
      application/pdf
    • الرقم المعرف:
      10.1002/dta.3487
    • الدخول الالكتروني :
      https://researchprofiles.ku.dk/da/publications/cac06b5d-ecd5-4d7f-a26a-db5e8e157292
      https://doi.org/10.1002/dta.3487
      https://curis.ku.dk/ws/files/361697787/Drug_Testing_and_Analysis_2023_Skaalvik.pdf
    • Rights:
      info:eu-repo/semantics/openAccess
    • الرقم المعرف:
      edsbas.4B586A9