Strategies for pediatric dose derivation from population pharmacokinetic models

Health authorities worldwide require clinical studies in children to ensure scientifically rigorous and consistent dosing. Before pediatric data are available, model-based methods provide a scientific and reproducible way to determine doses for pediatric studies. A general introduction to pediatric scaling is provided, followed by a focus on population pharmacokinetic methods to scale from adults to children using exposure matching. Exposure matching involves two steps: first, optimal pediatric doses are derived using a fine grid of body sizes and doses; second, feasible doses are selected based on availability of dose strengths. Three strategies are employed and compared, best fit (similar exposure in adults and children across ages and body sizes), conservative (children's exposure not exceeding adults'), and progressive (children's exposure not less than adults'). Each recommendation is evaluated against the exposure metrics C_max, C_trough, and AUC at steady state for the optimal dosing scheme. Simulations assess interindividual variability in exposure. Visualizations enable risk assessment of exposure distributions and post-hoc refinement of dosing schemes. The formalized approach offers clinical teams a reproducible basis for pediatric dose selection. An implementation in R and Monolix is provided.