Background: Pediatric drug development is plagued by small sample sizes, unvalidated clinical endpoints, and limited studies.
Objectives: The objective of this study was to determine whether age stratification within the pediatric population could be used to (1) assess response to a pharmacologic intervention and to (2) design future trials based upon published stratified disease data using clinical trial simulation (CTS).
Methods: Data available from the literature for Kawasaki disease (KD) was used in the model. Age-stratified CTS for a theoretical new drug was conducted.
Results: Population-specific differences due to age might affect trial success if not taken into account. CTS predicted inflammatory indices, and inclusion cutoff significantly altered the trial outcome. Finally, altered pharmacokinetics/pharmacodynamics in varying age groups of KD patients may alter drug exposure and response.
Conclusions: If assumptions regarding a pediatric disease process, such as KD, do not include age stratification with inclusion or response, then the wrong decision could result with regard to age-appropriateness or approval of a drug.
Keywords: Kawasaki disease; age groups; modeling; pharmacokinetics pharmacodynamics.