Children in clinical trials: towards evidence-based pediatric pharmacotherapy using pharmacokinetic-pharmacodynamic modeling

Abstract

Beside pharmacokinetic (PK) studies, pharmacodynamic (PD) studies are urgently needed. Validated PKPD models can be used to derive optimal dosing regimens for children of different ages, which can be evaluated in a prospective study before implementation in clinical practice. Strategies should be developed to ensure that formularies update their drug dosing guidelines regularly according to the most recent advances in research, allowing for clinicians to integrate these guidelines in daily practice. Expert commentary: We anticipate a trend towards a systems-level approach in pediatric modeling to optimally use the information gained in pediatric trials. For this approach, properly designed clinical PKPD studies will remain the backbone of pediatric research.

How to optimise drug study design: pharmacokinetics and pharmacodynamics studies introduced to paediatricians

“…Evidence of the influence of such covariates on PK or PKPD relationships can be used to predict the impact of overall variability on drug exposure and treatment response. Most importantly, the parameter estimates obtained by extrapolation can be directly used as the basis for dosing recommendations …”

Beyond the Randomized Clinical Trial: Innovative Data Science to Close the Pediatric Evidence Gap

“…Historically, the evidence basis of pediatric treatments has lagged behind those in adult patients. A key aspect of this is the lack of pediatric data, which originates from the logistic, ethical, and legal challenges of performing clinical investigations in children . Additionally, the pediatric population is more heterogeneous than the adult population, with maturational differences in pharmacokinetics, pharmacodynamics, and disease etiology across the pediatric age range from preterm neonates to adolescents .…”

“…1 Additionally, the pediatric population is more heterogeneous than the adult population, with maturational differences in pharmacokinetics, pharmacodynamics, and disease etiology across the pediatric age range from preterm neonates to adolescents. 1 Consequently, data collected in children within a narrow age range might still leave us with limited information regarding the treatment of children outside the studied age range. Finally, similar to other patient populations, optimal treatment will also differ for individuals within the same age group, for instance, because of obesity, genetic polymorphisms, or disease severity, and should be improved with more personalized treatment approaches.…”

“…3 Population pharmacometric modeling approaches have been successfully used to deal with these unbalanced data to better understand pediatric pharmacology. 1,3 More recently, we have seen an increased use of mechanistic or physiologically based models, which leverage prior knowledge regarding the physiological changes in organ weight, blood flow, and protein expression during a child's life. 2,4,5 An important aspect of such models is their improved predictive performance when used to extrapolate from adults to children.…”

“…6 These pharmacometric modeling approaches are now, despite limited data, being used with success to support neonatal and pediatric drug development as well as dosing of commonly used off-label drugs. 1,4,7 However, recent failures of RCTs in children have taught us that there is more to these studies than confirming model-based predictions. 8 These failures have been attributed to different reasons, such as an increased placebo effect in children, different disease etiology compared with adults, and inadequate dose selection.…”