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Cella, M.; Knibbe, C.; Wildt, S.N. de; Gerven, J. van; Danhof, M.; Pasqua, O. della
2012
Scaling of pharmacokinetics across paediatric populations: the lack of interpolative power of allometric models
Article / Letter to editor
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Aims: The objective of this investigation was to assess the performance of an allometric model as the basis for interpolating drug exposure in the context of pharmacokinetic bridging across...
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Aims: The objective of this investigation was to assess the performance of an allometric model as the basis for interpolating drug exposure in the context of pharmacokinetic bridging across paediatric subpopulations. Methods: Midazolam was selected as a paradigm compound. Two nonlinear mixed effects models were developed to describe midazolam pharmacokinetics in infants, toddlers and adults (model 1) and in children and adolescents (model 2). Subsequently, systemic drug exposure, expressed in terms of the area under the concentration vs. time curve (AUC), in children and adolescents was interpolated based on pharmacokinetic parameter distributions obtained from the model describing infants, toddlers and adults (model 1). Results were compared to the values obtained from modelling of the data in the corresponding population (model 2). Results: The two pharmacokinetic models accurately described midazolam exposure in the population on which they were built. However, the model based on data from infants, toddlers and adults failed to predict the exposure observed in children and adolescents: the mean difference between the predicted and estimated AUC(0-180) was of -17.8%, with a range of -6.8 to -38.4%.The discrepancy between estimated and interpolated exposure increased proportionally with body weight. Conclusions: The current results indicate that irrespective of whether extrapolation or interpolation methods are to be applied during paediatric drug development, model predictions beyond the range of the data used for parameter estimation may be biased. For accurate inter- or extrapolation to different populations, the assumption of identical parameter-covariate correlations across age groups may not be taken for granted. © 2012 The Authors. British Journal of Clinical Pharmacology © 2012 The British Pharmacological Society.
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