Ann W McMahon1, Kevin Watt2, Jian Wang3, Dionna Green3, Ram Tiwari4, Gilbert J Burckart3. 1. Office of Pediatric Therapeutics, Office of the Commissioner, Food and Drug Administration, Silver Spring, MD, USA. 2. Duke University Medical Center, Durham, NC, USA. 3. Office of Clinical Pharmacology, Office of Translational Sciences, Food and Drug Administration, Silver Spring, MD, USA. 4. Office of Biostatistics, Office of Translational Sciences, Food and Drug Administration, Silver Spring, MD, USA.
Abstract
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.
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 KDpatients 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.
Entities:
Keywords:
Kawasaki disease; age groups; modeling; pharmacokinetics pharmacodynamics
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