Helene Haguet 1, Happy Phanio Djokoto 1, Jean-Michel Dogne 1,2, Grace Shalom Govere 1,2, Lisa Hanquet 1, Reagan Kilela Songela 3, Majad Mansoor 1, Camille Massaux 1, Adrien Olama 1, Lisa Wellin 1, Flora Musuamba 1,2,3
1 UNamur, Unité de recherche en pharmacologie et toxicologie (URPC), NAmur Research Institute for LIfe Sciences (NARILIS) (Namur, Belgium), 2 Federal Agency for Medicines and Health Products (FAMHP) (Brussels, Belgium), 3 Université de Lubumbashi, Faculté de Sciences Pharmaceutiques (Lubumbashi, Republic of the Congo)
Objectives
Several monoclonal antibodies (mAbs) are currently licensed for the treatment of severe eosinophilic asthma. Reslizumab and mepolizumab target IL-5, whereas benralizumab targets IL-5Rα. Paediatric patients may benefit from therapies targeting the IL-5 pathway.[1] Mepolizumab is approved in the paediatric population (6-17 years) by the EMA, while benralizumab is approved for this age group by the FDA, with a Paediatric Investigation Plan ongoing at the European level.
Additional anti-IL-5/IL-5Rα mAbs, including biosimilars, are under development and will require pharmacokinetic (PK) evaluation in paediatric populations.[2] However, paediatric clinical assessment remains challenging due to ethical and practical constraints.[3, 4] Optimising paediatric trial design is therefore essential to minimise patient exposure while ensuring adequate characterisation of PK.
The objective of this study was to develop a hierarchical model-based meta-analysis (MBMA) population PK model for anti-IL-5(Rα) mAbs and to provide quantitative recommendations for optimising paediatric PK trial designs using a stochastic simulation-estimation (SSE) framework.
Methods
A systematic literature review was conducted to identify clinical studies reporting PK data for anti-IL-5 and anti-IL-5Rα monoclonal antibodies. The following sources were searched: PubMed, abstracts from four international congresses (ERS, ACAAI, EAACI, ASCPT), regulatory assessment reports, and clinical trials registry (clinicaltrials.gov). Studies reporting PK as a primary, secondary, or exploratory outcome were included. Data was extracted using a structured extraction template.
A hierarchical nonlinear mixed-effects MBMA model was developed. Structural PK was described using a two-compartment model with first-order absorption (subcutaneous administration) and first-order elimination from the central compartment. The model incorporated: (i) inter-individual variability on clearance, central volume, peripheral volume and absorption rate constant, (ii) between-trial variability, (iii) between-compound variability, (iv) between-indication variability. The model was developed using adult data. Paediatric PK parameters were predicted using theory-based allometric scaling with bodyweight as covariate, fixing exponents to 0.75 for clearance parameters and 1 for distribution volumes. Data processing, visualisation and meta-analyses were performed using the R statistical software (R version 4.5.3). Model adequacy was evaluated using goodness-of-fit plot inspection and visual predictive checks.
A SSE framework was implemented to evaluate paediatric study design performance. For each candidate design, paediatric datasets were simulated using the final MBMA model. Model parameters were re-estimated. Relative bias and relative standard error were computed across replicates. The impact of the 9 numbers of SSE replicates (25 – 500), sample size, number of samples per patient, and sampling schedules was explored. Study design performance was assessed by comparing estimated parameters to true simulation values, using relative bias and relative standard error as evaluation metrics.
Results
A database including 12 clinical studies evaluating anti-IL-5 mAbs and 20 studies evaluating anti-IL-5Rα mAbs was compiled for meta-analysis. The hierarchical MBMA framework enabled integration of data across compounds, trial designs, and patient populations.
The final PK model was a two-compartment model with first-order absorption and elimination. The model adequately described observed adult and pediatric PK data, and predicted concentration-time profiles were consistent across indications. For anti-IL-5 mAbs, typical parameter estimates were CL = 0.26 L/day, V1 = 3.41 L, Q = 0.24 L/day, V2 = 2.70 L, and ka = 0.193 day⁻¹. For anti-IL-5Rα mAbs, corresponding estimates were CL = 0.291 L/day, V1 = 3.41 L, Q = 0.697 L/day, V2 = 2.45 L, and ka = 0.229 day⁻¹. Clearance was comparable between mAbs, while V1 was slightly higher for anti-IL-5Rα mAbs. Inter-individual variability on CL was between 33% and 58% and 25% for anti-IL-5 and anti-IL-5Rα, respectively. Parameter precision was high for two mAbs (RSE <15%), whereas the third mAb showed lower precision (RSE up to 40%), reflecting higher inter-individual variability.
The stochastic simulation-estimation framework enabled prospective optimisation of paediatric study designs leveraging adult development data. Design scenarios were identified in which key PK parameters (CL and V1) achieved relative standard errors below 30% and relative bias below 20%, while minimising the number of paediatric patients and blood samples required.
Conclusions
This study provides a quantitative model-informed framework to optimise paediatric PK study design for mAbs targeting IL-5 pathway. By leveraging an adult-based hierarchical MBMA population PK model and applying stochastic simulation-estimation methods, paediatric trial designs can be prospectively evaluated and optimised to reduce patient burden while ensuring robust parameter estimation.
A similar framework could be extended to pharmacodynamic endpoints to further support paediatric extrapolation strategies.
References:
[1] C. Lombardi et al., "Anti-IL-5 Pathway Agents in Eosinophilic-Associated Disorders Across the Lifespan," Drugs, vol. 84, no. 6, pp. 661-684, Jun 2024, doi: 10.1007/s40265-024-02037-0.
[2] European Medicines Agency, "Reflection paper on a tailored clinical approach in biosimilar development," European Medicines Agency, Amsterdam, The Netherlands, 2023. Accessed: 26 February 2026. [Online]. Available: https://www.ema.europa.eu/en/documents/other/reflection-paper-tailored-clinical-approach-biosimilar-development_en.pdf
[3] K. Singh et al., "Breaking the silence: challenges and opportunities in pediatric drug development," Pediatric Research, vol. 98, no. 3, pp. 807-812, 2025/09/01 2025, doi: 10.1038/s41390-025-03923-3.
[4] K. Heinig, E. Zwanziger, J. Potter, and D. Fraier, "Bioanalytical aspects and challenges in supporting pediatric drug development," (in eng), Bioanalysis, vol. 12, no. 21, pp. 1505-1508, Nov 2020, doi: 10.4155/bio-2020-0237.
Reference: PAGE 34 (2026) Abstr 11994 [www.page-meeting.org/?abstract=11994]
Poster: Methodology - Study Design