A data-driven approach for the detection of internal standard outliers in targeted LC-MS/MS assays.

ABSTRACT: Heavy-labelled internal standard (IS) compounds are commonly used in liquid chromatography-tandem mass spectrometry (LC-MS/MS) assays to control for stochastic and systematic variation. Identifying samples that suffer from unwanted variation is critically important in order to avoid factitiously inaccurate results. Current approaches for outlier detection typically employ arbitrary thresholds and ignore systematic drift. To improve this, we applied robust linear mixed-effects models (LMMs) to capture the within- and between-run variability in IS signal and generate data-driven acceptance ranges for routine use. Data from in-house LC-MS/MS assays for 25-hydroxyvitamin D₃ and D₂ and prednisolone were retrospectively collected. The variation in the percentage deviation o

SUBMITTER: Wilkes EH 

PROVIDER: S-EPMC8600994 | biostudies-literature | 2021 Apr

REPOSITORIES: biostudies-literature