Predictive Performance of Physiology‐Based Pharmacokinetic Dose Estimates for Pediatric Trials: Evaluation With 10 Bayer Small‐Molecule Compounds in Children

Abstract

Development and guidance of dosing schemes in children have been supported by physiology‐based pharmacokinetic (PBPK) modeling for many years. PBPK models are built on a generic basis, where compound‐ and system‐specific parameters are separated and can be exchanged, allowing the translation of these models from adults to children by accounting for physiological differences. Owing to these features, PBPK modeling is a valuable approach to support clinical decision making for dosing in children. In this analysis, we evaluate pediatric PBPK models for 10 small‐molecule compounds that were applied to support clinical decision processes at Bayer for their predictive power in different age groups. Ratios of PBPK‐predicted to observed PK parameters for the evaluated drugs in different pediatric age groups were estimated. Predictive performance was analyzed on the basis of a 2‐fold error range and the bioequivalence range (ie, 0.8 ≤ predicted/observed ≤ 1.25). For all 10 compounds, all predicted‐to‐observed PK ratios were within a 2‐fold error range (n = 27), with two‐thirds of the ratios within the bioequivalence range (n = 18). The findings demonstrate that the pharmacokinetics of these compounds was successfully and adequately predicted in different pediatric age groups. This illustrates the applicability of PBPK for guiding dosing schemes in the pediatric population.

Another Step Toward Qualification of Pediatric Physiologically Based Pharmacokinetic Models to Facilitate Inclusivity and Diversity in Pediatric Clinical Studies

“…Such an approach has been highlighted previously. 50 Although the predictive capacity of P-PBPK models has increased over time, 19,51 there is a pressing need to further integrate comorbid impairments in anatomic, physiological, and biochemical variables for diseased populations (e.g., cancer, infectious diseases, and in pediatric male and female subjects of different ethnicities) to fully utilize P-PBPK modeling and assess their impacts on the PKs and pharmacodynamics of new chemical entities and new biological entities moving forward. Indeed, one of the advantages of PBPK modeling is that different populations can be generated based on gender, ethnicity, and disease.…”

Application of physiologically‐based pharmacokinetic model approach to predict pharmacokinetics and drug–drug interaction of rivaroxaban: A case study of rivaroxaban and carbamazepine

“…Over the last decade, PK model-based prediction using in vitro and in vivo data has increased significantly. [33][34][35] A PBPK model for RIV was previously developed in adults by Willmann et al [8][9][10][11] Wherein, the role of the efflux transporter (P-gp) was considered only in the renal elimination process of RIV. The authors assumed that P-gp was the major transport protein accounting for the net tubular secretion of RIV.…”

“…A physiologically-based pharmacokinetic (PBPK) model for RIV was developed in adults and scaled to the pediatric population by Willmann et al 8 The model was applied for several purposes, including the prediction of the potential DDI of RIV. [9][10][11] The role of active transporters (P-gp/BCRP) was not directly implemented in that model. For application purposes relevant to transporters, the efflux function of the P-gp was considered in the renal elimination process.…”

A proposed de-identification framework for a cohort of children presenting at a health facility in Uganda

“…The physiology of children changes rapidly following birth with rapid transitions occurring in the first year or two of life. 35 The loss of the number of months of age in these children is potentially limiting. The granularity in the data was lost due to generalization.…”