ArticleTranslational and clinical pharmacology2026
Development and evaluation of automated screening algorithms for pre-analytical errors in pharmacokinetic data: a simulation-based study.
Article in Translational and clinical pharmacology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Pre-analytical errors such as sample mix-ups can compromise the integrity of pharmacokinetic (PK) data. We simulated vancomycin PK data and introduced two error types: intra-individual time point swap (TS) errors and inter-individual concentration swap (CS) errors. This study developed and validated two automated detection approaches-a run-test-based non-parametric method and a Mahalanobis distance-based method with leave-one-out cross-validation (LOOCV)-for identifying pre-analytical errors in PK datasets. Performance was evaluated using 12,500 simulated profiles comparing the two methods. The distance-based method demonstrated significantly higher error detection rate (79.7% vs. 59.6%,
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