| dc.description.abstract | Lack of pediatric clinical data has led to a large gap in knowledge concerning drug efficacy, safety and dosing guidelines within the pediatric population. Many pediatric off-label doses are based largely on adult studies with little or no pediatric experience; this has the potential to lead to treatment failures, toxicities, and various other drug-related adverse events. Given that recruitment to pediatric trials is difficult, researchers have recently used physiologically-based pharmacokinetic (PBPK) models as a means to efficiently plan pediatric clinical studies. PBPK models are mechanistic in nature and mathematically describe the disposition of drugs in an organism. This in silico technique predicts pharmacokinetic (PK) profiles based on compound physicochemical properties and multiple physiological input parameters of the individual, such as organ volumes, tissue composition, blood flow, and clearance (CL). Pediatric PK parameters are typically predicted using a pediatric PBPK model that has been developed using an adult PBPK model and clinical PK data. Within this workflow for pediatric PBPK model development, adult intravenous (IV) data is typically used; however, there are many instances where there may not be an IV formulation available for certain compounds. As a result, the question remains if the workflow for pediatric PBPK modeling produces accurate pediatric PK predictions in the absence of adult IV data. In this case, IV data from pre-clinical species (i.e. rat) may be an alternative to human IV data. The objective of this study was to assess the ability of pediatric PBPK models to predict observed pediatric PK parameters using a model development workflow that uses rat IV PK data, as opposed to adult human IV PK data. The implications of both workflows were assessed by comparing the precision and bias of the predicted vs. observed PK exposure metrics in children. This study demonstrated that rat IV data is a viable alternative to using adult IV PK data within the pediatric PBPK model development workflow and the majority of exposure metrics were within 2 fold from the observed pediatric data, regardless of workflow or Biopharmaceutics Classification System (BCS) class of the compound. Ultimately, the model was not hindered in its prediction accuracy, despite a lack of distribution and clearance data that would otherwise have been derived from human IV data. Overall, the application of rat IV data as a substitute for human IV data in PBPK modeling is a novel approach that has significant potential for future application. | en |
