ArticleClinical and translational science2025
Predicting Vancomycin Clearance in Neonates and Infants by Integrating Machine Learning and Metabolomics With Population Pharmacokinetics.
Article in Clinical and translational science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
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.
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Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Systematic review and scoring-based selection of pharmacokinetic models for precision dosing of vancomycin in neonates and children.British journal of clinical pharmacology · 2026Pooled it
- Machine Learning-Integrated Metabolomics for Precision Pharmacotherapy: Advances, Challenges, and Clinical Translation.Metabolites · 2026Review
- Machine-learning prediction of pre-dose pharmacokinetics optimizes initial vancomycin dosing in critically ill children.Frontiers in pharmacology · 2026Article
- Predicting Vancomycin Clearance in Neonates and Infants by Integrating Machine Learning and Metabolomics With Population Pharmacokinetics.Clinical and translational science · 2025Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The pharmacokinetics of vancomycin in neonates and infants exhibits significant variability, presenting challenges in achieving target exposures. This study aimed to investigate the influence of patient-specific covariates on vancomycin clearance and evaluate the predictive performance of various machine learning (ML) methods using clinical covariates and plasma metabolomics data. A retrospective population pharmacokinetic (PK) analysis was conducted on 42 neonates and infants treated at the University of Michigan Neonatal Intensive Care Unit from 2019 to 2022. Vancomycin was administered intravenously at doses ranging from 3.5 to 25 mg/kg every 6 to 24 h. A total of 214 vancomycin concentration measurements, including trough, peak, and random levels, were included in the analysis. Plasma samples collected from the patients were analyzed by an LC-MS/MS-based untargeted metabolomics assay. A one-compartment model with first-order elimination best described the pharmacokinetics of vancomycin, with serum creatinine (SCr), postmenstrual age (PMA), and weight identified as significant covariates influencing clearance. Among the ML methods evaluated, Gradient Boosting Regressor (GBR) achieved the highest predictive performance using clinical covariates (MSE: 0.0033; R
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.