A simulation study to assess the influence of population pharmacokinetic model selection on Bayesian forecasting of vancomycin exposure in preterm neonates.

Mehdi El Hassani; Mathieu Blouin; Van Nguyen; Alexandre Duong; Amélie Marsot

doi:10.1080/17512433.2026.2639035

February 26, 2026

A simulation study to assess the influence of population pharmacokinetic model selection on Bayesian forecasting of vancomycin exposure in preterm neonates.

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Key Points

This study explores how selecting different pharmacokinetic models affects the forecasting of vancomycin exposure in preterm neonates.
Conducted simulation study to assess different population pharmacokinetic models.
Evaluated the impact on vancomycin AUC24 values and probability of target attainment (PTA).
Analyzed correlations between model characteristics and dosing outcomes.
Different models led to variations in AUC24 values for vancomycin.
Observed significant differences in PTA across models.
Findings suggest certain model characteristics enhance target attainment.

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Implication

Simulation study assesses vancomycin exposure in preterm neonates, suggesting model choice impacts dosing decisions.

Abstract

Model selection affects simulated vancomycin AUC24 values and PTA in neonates, influencing dosing decisions. These findings highlight model characteristics correlating with target attainment.

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Hassani et al. (2026) studied this question.

synapsesocial.com/papers/69a3d8b8ec16d51705d2fd4c https://doi.org/10.1080/17512433.2026.2639035

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A simulation study to assess the influence of population pharmacokinetic model selection on Bayesian forecasting of vancomycin exposure in preterm neonates.

Key Points

Ask about this paper

Implication

Abstract

Discussion

Cite This Study

A simulation study to assess the influence of population pharmacokinetic model selection on Bayesian forecasting of vancomycin exposure in preterm neonates.

Key Points

Ask about this paper

Implication

Abstract

Discussion

Cite This Study

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