AIMS: To assess the predictive value of a model-based approach for dose selection across paediatric populations in early clinical drug development. METHODS: Abacavir was selected as a paradigm compound using data across a wide age range. Abacavir pharmacokinetics (PK) in children were analysed separately from infants and toddlers. Two independent models were obtained, and systemic exposure (AUC) was then simulated across populations based on the estimates from each model. Drug exposures in infants and toddlers were predicted using pharmacokinetic parameter distributions obtained from children, and the other way around. RESULTS: The pharmacokinetic models (a two-compartment PK model for infants and toddlers and a one compartment PK model for children) accurately described the exposure in the population from which they were built. However, neither model predicted exposure in a different population: in infants, the median AUC (95%(-) CI) was estimated at 7.03 (6.72, 7.48) µg ml(-1) h, whilst it was predicted at 5.75 (4.82, 6.26) µg ml(-1) h; in children, the estimated median AUC was 6.96 (5.85, 7.91) µg ml(-1) h, whilst the predicted value was 6.45 (5.80, 7.01) µg ml(-1) h. CONCLUSIONS: These findings suggest that the assumption of an identical (linear or nonlinear) correlation between pharmacokinetic parameters and demographic factors may not hold true across age groups. Whilst the use of modelling enables accurate characterization of pharmacokinetic properties, extrapolations based on such parameter estimates may have limited value due to differences in the impact of developmental growth across populations.
AIMS: To assess the predictive value of a model-based approach for dose selection across paediatric populations in early clinical drug development. METHODS:Abacavir was selected as a paradigm compound using data across a wide age range. Abacavir pharmacokinetics (PK) in children were analysed separately from infants and toddlers. Two independent models were obtained, and systemic exposure (AUC) was then simulated across populations based on the estimates from each model. Drug exposures in infants and toddlers were predicted using pharmacokinetic parameter distributions obtained from children, and the other way around. RESULTS: The pharmacokinetic models (a two-compartment PK model for infants and toddlers and a one compartment PK model for children) accurately described the exposure in the population from which they were built. However, neither model predicted exposure in a different population: in infants, the median AUC (95%(-) CI) was estimated at 7.03 (6.72, 7.48) µg ml(-1) h, whilst it was predicted at 5.75 (4.82, 6.26) µg ml(-1) h; in children, the estimated median AUC was 6.96 (5.85, 7.91) µg ml(-1) h, whilst the predicted value was 6.45 (5.80, 7.01) µg ml(-1) h. CONCLUSIONS: These findings suggest that the assumption of an identical (linear or nonlinear) correlation between pharmacokinetic parameters and demographic factors may not hold true across age groups. Whilst the use of modelling enables accurate characterization of pharmacokinetic properties, extrapolations based on such parameter estimates may have limited value due to differences in the impact of developmental growth across populations.