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Sequential Updating of a New Dynamic Pharmacokinetic Model for Caffeine in Premature Neonates

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Abstract

Background and objective: Caffeine treatment is widely used in nursing care to reduce the risk of apnoea in premature neonates. To check the therapeutic efficacy of the treatment against apnoea, caffeine concentration in blood is an important indicator. The present study was aimed at building a pharmacokinetic model as a basis for a medical decision support tool.

Methods: In the proposed model, time dependence of physiological parameters is introduced to describe rapid growth of neonates. To take into account the large variability in the population, the pharmacokinetic model is embedded in a population structure. The whole model is inferred within a Bayesian framework. To update caffeine concentration predictions as data of an incoming patient are collected, we propose a fast method that can be used in a medical context. This involves the sequential updating of model parameters (at individual and population levels) via a stochastic particle algorithm.

Results: Our model provides better predictions than the ones obtained with models previously published. We show, through an example, that sequential updating improves predictions of caffeine concentration in blood (reduce bias and length of credibility intervals). The update of the pharmacokinetic model using body mass and caffeine concentration data is studied. It shows how informative caffeine concentration data are in contrast to body mass data.

Conclusion: This study provides the methodological basis to predict caffeine concentration in blood, after a given treatment if data are collected on the treated neonate.

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Acknowledgements

The authors wish to thank Dr C. Diack for his helpful remarks and the reviewers for comments that improved the manuscript. Partial funding for this work was provided by the French Ministry of Research and Technology, project DIADEME, decision 02 C 0141. This work has also been supported by the research project BCRD-AP2001-DRC07 provided by the French Ministry of the Ecology and Sustainable Development and by the Regional Council of Picardie. The authors have no conflicts of interest that are directly relevant to the content of this study.

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Authors and Affiliations

  1. Institut National de l’Environnement Industriel et des Risques, Verneuil-en-Halatte, France

    Sandrine Micallef & Frédéric Y. Bois

  2. NOVARTIS PHARMA AG, Basel, Switzerland

    Billy Amzal

  3. Université Picardie Jules Verne, Amiens, France

    Véronique Bach & Karen Chardon

  4. Department of the Hospital of Amiens, Neonatal Unit and Intensive Care of the Pediatric, Amiens, France

    Pierre Tourneux

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  1. Sandrine Micallef
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  2. Billy Amzal
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  3. Véronique Bach
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  4. Karen Chardon
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  5. Pierre Tourneux
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  6. Frédéric Y. Bois
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Correspondence to Sandrine Micallef.

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Micallef, S., Amzal, B., Bach, V. et al. Sequential Updating of a New Dynamic Pharmacokinetic Model for Caffeine in Premature Neonates. Clin Pharmacokinet 46, 59–74 (2007). https://doi.org/10.2165/00003088-200746010-00003

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