Examines the role of quantitative models in regulatory decision-making, suggesting improved drug access in the UK.
Quantitative medicine supports modern drug development and regulatory decision‐making by integrating non‐clinical and clinical data to inform dose selection, trial optimization, and extrapolation across populations and benefit–risk assessment. The Medicines and Healthcare products Regulatory Agency (MHRA) has adopted quantitative approaches across the product lifecycle within a risk‐proportionate regulatory framework. Internationally, the ICH M15 guideline provides a harmonized framework for planning, evaluation and documentation of model‐informed drug development (MIDD) evidence which is aligned with MHRA practice. This perspective describes the application of quantitative medicine to UK regulatory decision‐making using two case studies: sugemalimab (Eqjubi) in oncology and lecanemab (Leqembi) in Alzheimer's disease. The case studies are assessed using ICH M15 concepts, including context of use, model influence, and consequence of a wrong decision. For sugemalimab, quantitative pharmacokinetic modeling supported a high‐impact dosing decision with clinically meaningful consequences of a wrong decision requiring proportionate scrutiny and mitigation of uncertainty. For lecanemab, multiple quantitative models with lower individual influence supported interpretation of pharmacokinetic variability, biomarkers, and clinical outcomes within the overall benefit–risk assessment. These case studies demonstrate how quantitative models can support decisions with differential impact ranging from critical dosing decisions to interpretation of complex data. Regulatory policy that is aligned with ICH M15 can be used to support the use of quantitative medicine to link complex modeling approaches with regulatory decision‐making and enable patient access to medicines.
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Ghazaly et al. (2026) studied this question.
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