Chengli Yu 1, Moreno Ursino 2, Sylvie Retout 3,6, Marylore Chenel 4, Emmanuelle Comets 1,5, Yumi Cleary 6
1 Université Paris Cité and Université Sorbonne Paris Nord, IAME, Inserm (Paris, France), 2 Université Paris Cité, HeKA, Inserm (Paris, France), 3 Institut Roche (Boulogne-Billancourt, France), 4 Pharmetheus (Uppsala, Sweden), 5 Univ Rennes, Inserm, EHESP, Irset (Rennes, France), 6 Pharmaceutical Sciences, Roche Pharma Research and Early Development, Roche Innovation Center (Basel, Switzerland)
Introduction: The recent decade has seen considerable growth of paediatric physiologically-based pharmacokinetic (PBPK) applications both in academia and industry, however, the number of regulatory submissions that includes paediatric PBPK modelling remains relatively small (1). Among the current use of PBPK in marketing authorization applications, most of the cases were not considered qualified for the intended use (2). The recent ICH M15 guideline (3) provides a framework for Model-Informed Drug Development (MIDD) evidence assessment which can be applied to examine the reliability of a PBPK model.
Objectives: We searched and reviewed European Public Assessment Reports (EPARs) including paediatric PBPK modelling to summarise the context of use (CoU) and modelling approaches. We then retrospectively assessed their regulatory influence in decision making within the ICH M15 framework, considering model influence and consequence of wrong decision.
Method: We used the open database platform (https://paediatricdata.eu/) to retrieve all EPARs that included paediatric PBPK modelling between 2015 and 2024. A structural review was conducted to collect core elements of: 1) Product information, 2) General model attributes, 3) Context of use, 4) Modelling work flow and evaluation, 5) Regulatory review outcomes. Model influence and consequence of wrong decision were assessed as low/medium/high based on available information from EPARs. When available, comments on reasons for acceptance or rejection were noted. Each EPAR was read by two readers and discrepancies between the assessments were resolved by consensus. Descriptive data analysis was performed in R.
Results: A total of 25 distinct cases were included for the final EPARs review. Among the cases, oncology was the most common therapeutic area (N = 9), then central nervous system (CNS) disease (N = 3) and cardiovascular disease (N = 3). 14 products had both adult and paediatric oral formulations, with bioequivalence demonstrated in 9 cases.
Most paediatric PBPK analyses (N = 23) were intended to support paediatric dose extrapolation from adult exposure, 6 of which involved more than one CoU. Fifteen extrapolations mainly targeted patients aged 2-8 years based on sparse paediatric PK data, while 10 spanned broader age range around 0-8 years without paediatric PK data. Remaining objectives included prediction of drug-drug interactions (DDI, N = 4), food effect (N = 3), and organ impairment to inform label in lieu of clinical study (N = 1).
Most reported paediatric PBPK models were scaled from a previously developed adult PBPK models. CYP3A-mediated metabolism and renal elimination were frequent elimination processes. Over the 18 cases with reported data, a median of 48 (13 – 881) paediatric patients were included in the evaluation datasets. Details of model evaluation were mostly unreported, and exposure comparison between prediction and observation (eg, AUC0-24h, Cmax, Css) was common among reported cases. Six cases compared paediatric PBPK results with population PK results when paediatric data was available, and 14 cases mentioned uncertainty evaluation but further information was mostly unavailable.
According to the regulator’s decisions, most paediatric PBPK approaches were considered premature, but model adequacy was explicitly acknowledged in only half of the cases. EMA accepted 14 cases, 6 of them were applied to select dose for paediatric studies, 4 for dose extrapolation with limited paediatric data, and 3 for formulation extrapolation. Only 2 cases were approved for dose extrapolation without observations. Rejected cases were mostly intended for dose extrapolation (N = 8), including even 4 cases with PK data from targeted age groups. The remaining rejected cases applied for a waiver concerning DDI studies (N = 3) and paediatric study dose selection (N = 2). The main reason stated for rejection was lack of data for evaluation. A trend between model influence and the regulatory decision was noted. More approved cases were associated with low intended model influence (low/medium/high: 6/5/3 cases) and majority of rejected cases were high influence applications (2/4/5).
Conclusion: PBPK modelling shows promise to support paediatric clinical development, however, regulatory acceptance remains to be cautious. In our survey, approval of paediatric PBPK modelling was more likely when the model was intended for study dose selection, adequately evaluated, had low influence on the decision and involved low risk.
References:
(1) Johnson, T. N., Small, B. G. & Rowland Yeo, K. Increasing application of pediatric physiologically based pharmacokinetic models across academic and industry organizations. CPT Pharmacometrics Syst Pharmacol 11, 373–383 (2022).
(2) Paul, P. et al. Current Use of Physiologically Based Pharmacokinetic modeling in New Medicinal Product Approvals at EMA. Clin Pharmacol Ther 117, 808–817 (2025).
(2) https://database.ich.org/sites/default/files/ICH_M15_Step4_Final_Guideline_2026_0129.pdf
Reference: PAGE 34 (2026) Abstr 12136 [www.page-meeting.org/?abstract=12136]
Poster: Methodology - Other topics