ArticleTherapeutic drug monitoring2025
Predictive Performance of Bayesian Dosing Software for Vancomycin in Intensive Care Unit Patients.
Article in Therapeutic drug monitoring, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Integrating Real-World Data and Pharmacometrics to Bridge Evidence Gaps in Special Populations: A State-of-the-Art Review.Pharmaceutics · 2026Review
- Commentary: Awareness, use, attitudes, and implementation challenges of Bayesian dose prediction software in clinical practice: a multi-organizational survey.Frontiers in pharmacology · 2026Article
- Population Pharmacokinetics and Clinical Application of Vancomycin in Critically Ill Adults: A NONMEM-Based Review.Drug design, development and therapy · 2026Review
- Vancomycin levels for Bayesian dose-optimization in critical care: a prospective cohort study.Frontiers in medicine · 2025Article
- A Reinforcement Learning (RL)-Motivated Simulation Framework for Evaluating Vancomycin Dosing Strategies.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2024Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
backgroundAccording to the updated guidelines, Bayesian-derived area under the curve estimation is recommended to guide vancomycin dosing. However, the Bayesian dosing software that facilitates this procedure has not been adequately assessed in intensive care unit (ICU) patients. This study evaluated the performance of 3 commonly used Bayesian software programs in predicting vancomycin concentrations in ICU patients before they could be utilized for personalized dosing in this population.
methodsRetrospective data from adult ICU patients who were administered vancomycin intravenously were obtained to predict serum concentrations a priori (based solely on patient characteristics) or a posteriori (Bayesian forecasting using measured concentrations). The predictive performance was evaluated via bias and precision using relative bias (rBias) and relative root mean squared error, respectively.
resultsData from 139 patients with 284 vancomycin concentrations were evaluated using 3 software programs: SmartDose (He model), Pharmado (Yasuhara model), and PrecisePK (Rodvald and Goti model). All 3 programs showed clinically acceptable bias with the exception of the Goti model of PrecisePK in an a priori estimation (rBias, 27.44%). A relatively low level of precision in terms of relative root mean squared error was observed in all these programs, but with a marked improvement in the a posteriori estimation (27.69%-37.64%) compared with the a priori situation (45.12%-68.59%).
conclusionsBayesian dosing software is a potential tool for vancomycin dose optimization in ICU patients. Patients with different physiological and pathological features may be referred to specific Bayesian programs.
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