ArticleDrug design, development and therapy2021
An Ensemble Model for Prediction of Vancomycin Trough Concentrations in Pediatric Patients.
Article in Drug design, development and therapy, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
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Who cites it
27 citing papers in PubMed, 52 citations in OpenAlex.
- Development and validation of a machine learning model for individualised meropenem dosing in CRRT patients.Scientific reports · 2026Article
- Rising Role of Artificial Intelligence in Clinical Pharmacometrics and Model-Informed Precision Dosing in Pediatrics.The journal of pediatric pharmacology and therapeutics : JPPT : the official journal of PPAG · 2026Article
- Machine Learning Models Reveal New Risk Factors for Sub-/Supra-Therapeutic Concentrations of Sirolimus in Children with Vascular Anomalies.Drug design, development and therapy · 2026Article
- Article
- Machine-learning prediction of pre-dose pharmacokinetics optimizes initial vancomycin dosing in critically ill children.Frontiers in pharmacology · 2026Article
- A Comparison of AI and Population PK Models to Predict the Concentrations of Antiepileptic Drugs Using Therapeutic Drug Monitoring Records.Clinical and translational science · 2025Article
- Prediction Trough Concentrations of Valproic Acid Among Chinese Adult Patients with Epilepsy Using Machine Learning Techniques.Pharmaceutical research · 2025Article
- A Real-Time Plasma Concentration Prediction Model for Voriconazole in Elderly Patients via Machine Learning Combined with Population Pharmacokinetics.Drug design, development and therapy · 2025Article
- Prediction of High-Dose Methotrexate Blood Concentration in Osteosarcoma Patients Using Machine Learning.Drug design, development and therapy · 2025Article
- Artificial Intelligence and Machine Learning Applications to Pharmacokinetic Modeling and Dose Prediction of Antibiotics: A Scoping Review.Antibiotics (Basel, Switzerland) · 2024Article
- Optimizing vancomycin dosing in pediatrics: a machine learning approach to predict trough concentrations in children under four years of age.International journal of clinical pharmacy · 2024Observational
- Optimal use of β-lactams in neonates: machine learning-based clinical decision support system.EBioMedicine · 2024Article
- Predicting quetiapine dose in patients with depression using machine learning techniques based on real-world evidence.Annals of general psychiatry · 2024Article
- Machine learning-based prediction of sertraline concentration in patients with depression through therapeutic drug monitoring.Frontiers in pharmacology · 2024Article
- Monitoring of the trough concentration of valproic acid in pediatric epilepsy patients: a machine learning-based ensemble model.Frontiers in pharmacology · 2024Article
- Vancomycin population pharmacokinetics analysis in Chinese paediatric patients with varying degrees of renal function and ages: development of new practical dosing recommendations.The Journal of antimicrobial chemotherapy · 2023Article
- Use of Machine Learning for Dosage Individualization of Vancomycin in Neonates.Clinical pharmacokinetics · 2023Article
- External Evaluation of Population Pharmacokinetic Models for Precision Dosing: Current State and Knowledge Gaps.Clinical pharmacokinetics · 2023Article
- Adoption of Machine Learning in Pharmacometrics: An Overview of Recent Implementations and Their Considerations.Pharmaceutics · 2022Article
- Application of Machine Learning Classification to Improve the Performance of Vancomycin Therapeutic Drug Monitoring.Pharmaceutics · 2022Article
Corrections and comments
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Authors and funding
11 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeThis study aimed to establish an optimal model to predict vancomycin trough concentrations by using machine learning. PATIENTS AND
methodsWe enrolled 407 pediatric patients (age < 18 years) who received vancomycin intravenously and underwent therapeutic drug monitoring from June 2013 to April 2020 at Xinhua Hospital affiliated to Shanghai Jiaotong University School of Medicine. The median (interquartile range) age and weight of the patients were 2 (0.63-5) years and 12 (7.8-19) kg. Vancomycin trough concentrations were considered as the target variable, and eight different algorithms were used for predictive performance comparison. The whole dataset (407 cases) was divided into training group and testing group at the ratio of 80%: 20%, which were 325 and 82 cases, respectively.
resultsUltimately, five algorithms (XGBoost, GBRT, Bagging, ExtraTree and decision tree) with high
conclusionTherefore, the ensemble model is useful for the vancomycin concentration prediction, especially in the population of children with great individual variation. As machine learning methods evolve, the clinical value of the ensemble model will be demonstrated in the clinical practice.
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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.