Pharmacokinetic–Pharmacodynamic Modeling in Pediatric Drug Development, and the Importance of Standardized Scaling of Clearance

Abstract

Pharmacokinetic/pharmacodynamic (PKPD) modeling is important in the design and conduct of clinical pharmacology research in children. During drug development, PKPD modeling and simulation should underpin rational trial design and facilitate extrapolation to investigate efficacy and safety. The application of PKPD modeling to optimize dosing recommendations and therapeutic drug monitoring is also increasing, and PKPD model-based dose individualization will become a core feature of personalized medicine. Following extensive progress on pediatric PK modeling, a greater emphasis now needs to be placed on PD modeling to understand age-related changes in drug effects. This paper discusses the principles of PKPD modeling in the context of pediatric drug development, summarizing how important PK parameters, such as clearance (CL), are scaled with size and age, and highlights a standardized method for CL scaling in children. One standard scaling method would facilitate comparison of PK parameters across multiple studies, thus increasing the utility of existing PK models and facilitating optimal design of new studies. Key PointsPharmacokinetic/pharmacodynamic (PKPD) modeling is important in the design and conduct of clinical pharmacology research in children, and the so-called 'population' approach is suitable for rich or sparse data in terms of the number of samples per subjectThe utility of pediatric PK models can be increased by using a standardized approach to scaling: a suggested method for scaling clearance (CL) is a combination of allometric weight scaling with a sigmoid function to account for organ maturation. This should be used a priori, as a 'base' approach, allowing the effects of age and size to be delineated from other patient-specific factors, such as disease state and organ (dys)function When determining the pediatric dose, instead of directly scaling the dose from adults to children, the pediatric PK parameter estimates should be obtained from a PK model with a standardized scaling approach in order to avoid the use of arbitrary cut-off values (of age/weight) according to a specific (nonstandardized) CL-scaling formula Significant progress has recently been made on pediatric PK modeling; a greater emphasis now needs to be placed on PD modeling to understand age-related changes in drug effects PKPD model-based dose individualization is becoming increasingly popular as the age of personalized medicine dawns

Pediatric Drug–Drug Interaction Studies: Barriers and Opportunities

“…PopPK modeling combined with sparse sampling is widely used to characterize drug disposition in neonates and children . Implementing allometric scaling for size in addition to a sigmoidal function accounting for organ maturation may be able to distinguish age and size effects on clearance from other patient‐specific factors, including DDIs . If a concomitant drug is identified as a significant predictor of variability in a PK parameter, simulations can be performed to optimize dosing for children receiving the drug combination.…”

“…7 Implementing allometric scaling for size in addition to a sigmoidal function accounting for organ maturation may be able to distinguish age and size effects on clearance from other patientspecific factors, including DDIs. 8 If a concomitant drug is identified as a significant predictor of variability in a PK parameter, simulations can be performed to optimize dosing for children receiving the drug combination. PBPK modeling, which integrates physiological information along with drug-specific properties to predict drug disposition throughout the body, can facilitate the evaluation of potential pediatric DDIs.…”

Revising Pediatric Vancomycin Dosing Accounting for Nephrotoxicity in a Pharmacokinetic-Pharmacodynamic Model

“…. Most of these studies used small sample sizes or focused on pediatric subpopulations, such as neonates, meaning parameter comparisons between studies is challenging, not least because important covariates, such as age and weight, are often not parameterized in a standard way (13). Moreover, vancomycin distribution often requires two and, in some cases, three disposition compartments (14), although most pediatric vancomycin PK papers have previously reported a one-compartment model (2)(3)(4)(5)(6)(7).…”

Implementation of a Physiologically Based Pharmacokinetic Modeling Approach to Guide Optimal Dosing Regimens for Imatinib and Potential Drug Interactions in Paediatrics

“…All the ontogeny equations used in the current study were driven by postnatal age. Postmenstrual age is more useful if preterm neonates are included in PBPK simulations (Abduljalil et al, 2019;Germovsek et al, 2019).…”