Abstract
Aims
Population pharmacokinetic (popPK) modelling is widely used to support paediatric dose optimization, yet consensus on appropriate modelling approaches remains limited. This study compared pooled and Bayesian popPK approaches for paediatric pharmacokinetics (PK) analysis using monoclonal antibody (mAb) examples.
Methods
Paediatric and adult PK datasets were simulated using popPK models inspired by a published mepolizumab model, incorporating two clinically relevant scenarios reflecting different mechanisms of paediatric–adult mAb PK differences. Six paediatric study designs were evaluated. Paediatric PK was analysed using pooled and Bayesian approaches, and model performance was assessed based on absolute prediction error (PE) and precision of population and individual PK parameters.
Results
When paediatric–adult PK differences were explained primarily by body size, pooled approach estimated paediatric population clearance more accurately (median absolute PE: 1.1%–1.2% with pooled approach
vs
. 4.1%–10.4% with the Bayesian approach) and was robust across study designs. In contrast, when age‐related PK differences were present and paediatric sample size was small (≤ 30 subjects), the Bayesian approach provided more accurate population clearance estimates for 11‐year‐old population (median absolute PE: 3.4%–8.2% with the Bayesian approach
vs
.7.4%–15.7% with pooled approach). Individual exposure estimates were comparable between modelling approaches.
Conclusions
In this case study based on mAbs acting on soluble targets, relative performance of pooled and Bayesian popPK approaches varied with the analysis objective, paediatric age group, ADME characteristics and paediatric study design. These findings provide practical considerations for applying pooled and Bayesian approaches in this context and may help inform the selection of popPK strategies to support model‐informed paediatric dosing decisions.