Physiologically-based modeling and simulation explained unusual PK and helped an orphan drug achieve approval based on small clinical studies.
In rare diseases, with few patients available for clinical study, every data point becomes crucial to understanding a potential therapy’s benefit-risk profile. Model-based methods can help by gathering disparate information sources into a cohesive picture of the dose-concentration-effect relationship, enriching the scientific basis for development decisions. By enriching the models with information about physiological changes during maturation or specific disease states, scientists can confidently predict drug exposures and recommend dosing for special populations.
A promising new drug formulation for a very rare disease presented a mystery in clinical development. Expected to prove bioequivalent to an approved formulation, the new drug’s active metabolite instead seemed to disappear in the blood, with plasma levels well below those needed to show bioequivalence. Yet final metabolites excreted in urine tracked dosing as predicted.
