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Scaling of pharmacokinetics across paediatric populations: the lack of interpolative power of allometric models
Author(s) -
Cella Massimo,
Knibbe Catherijne,
de Wildt Saskia N.,
Van Gerven Joop,
Danhof Meindert,
Della Pasqua Oscar
Publication year - 2012
Publication title -
british journal of clinical pharmacology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.216
H-Index - 146
eISSN - 1365-2125
pISSN - 0306-5251
DOI - 10.1111/j.1365-2125.2012.04206.x
Subject(s) - covariate , extrapolation , nonmem , population , allometry , context (archaeology) , statistics , medicine , pharmacokinetics , econometrics , mathematics , pharmacology , biology , ecology , paleontology , environmental health
WHAT IS ALREADY KNOWN ABOUT THIS SUBJECT • No consensus has been reached so far on the suitability of different methodologies for dose selection in children. • In paediatric drug development, initial estimation of the paediatric dose is obtained by extrapolation. This is usually performed using the dosing regimen in another population as reference. This approach also implies the possibility of using interpolations across age groups. • Midazolam, the paradigm compound selected for the purposes of our investigation, is a short‐acting imidazobenzodiazepine used for inducing sedation before medical procedures. WHAT THIS STUDY ADDS • The results of this analysis show that the use of allometric models to interpolate pharmacokinetics between paediatric subpopulations has limitations and drawbacks. • Estimation of covariate effects is critical, but not sufficient to interpolate parameter distributions and drug exposures from a reference population to another population. • The covariate–parameter relationship does not remain constant beyond the range of observations. Exponential relationships used by allometry do not correct for these discrepancies. AIM 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 with 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.