Rapid and Accurate Simultaneous Quantitation of Low Concentration Amphetamines and Metabolites from Urine using Strata-X-C and LC–MS–MS on Gemini C18
The use of HPLC for determining amphetamines has not received much attention because of the poor response of UV spectrometric detectors to these compounds when present at low concentration levels. However, HPLC coupled with mass spectrometry can provide the sensitivity required for the analysis of analytes at low concentrations in biological samples. In comparison to GC–MS and LC-UV analyses, LC–MS–MS offers superior sensitivity, selectivity and robustness for a wide range of analytes without any need for derivatization. LC–MS–MS technology also makes possible the development of highly selective, sensitive and precise methods for the simultaneous analysis of amphetamines and their metabolic derivatives. In combination with LC–MS–MS, limits of quantitation (LOQ) of 0.54 ng/mL are achieved for MAMPH, HMMA, and MDMA and LOQ of 1.0 ng/mL are achieved for AMPH and MDA on Gemini C18 HPLC columns.
How feasible is it to integrate this Bayesian graph-theory methodology into existing commercial chromatography software workflows for semi-automated data curation in routine analytical laboratories?
Gabriel Vivó-Truyols outlines the benefits and challenges of combining graph theory with Bayesian statistics to automate peak assignment and alignment.
This week, Chromatography Online’s coverage spanned lipidomics-based early cancer detection, career paths in separation science, machine learning and uncertainty-driven approaches to LC method development, new EU wastewater rules for pharmaceutical micropollutants, automated Separation Quality Factor (SQF) evaluation in chromatography data systems, and solutions to GLP-1 peptide analysis challenges.
Gabriel Vivó-Truyols from the Spanish Council for Scientific Research, Madrid, Spain. discusses his work on using graph theory and Bayesian statistics for peak assignment and chromatographic alignment.
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