ArticleBritish journal of clinical pharmacology2026
Model-informed vancomycin precision dosing by population pharmacokinetics combined with machine learning algorithms.
Article in British journal of clinical pharmacology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Model-informed vancomycin precision dosing by population pharmacokinetics combined with machine learning algorithms.British journal of clinical pharmacology · 2026Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
aimsAchieving the target AUC/MIC remains a critical challenge in vancomycin therapeutic drug monitoring, with traditional empirical dosing regimens often leading to suboptimal outcomes. This study aimed to develop and validate a novel population pharmacokinetic (PopPK)-informed machine learning model to optimize TDM-guided dose adjustments. By accurately predicting the 24-h area under the curve (AUC), the model assists clinicians in rapidly individualizing regimens, thereby improving target attainment, reducing subsequent modifications and minimizing toxicity.
methodsA total of 1140 vancomycin TDM samples were analysed. Five machine learning models were developed and compared. Model performance assessed using R
resultsThe ANN (MLP) model demonstrated the best comprehensive performance. It achieved the highest R
conclusionsThe ANN model achieved exceptional accuracy, robustness and clinical safety in predicting individualized vancomycin clearance. This model is deployable as an instantaneous, point-of-care CDSS tool, offering a powerful new pathway to solve the long-standing challenges of accessibility and accuracy in routine TDM practice.
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