Justin S. Feigelman, Dr.rer.nat.: No financial relationships to disclose
Using quantitative systems pharmacology modeling, we examine the interplay between crucial inflammatory pathways including IL-4, IL-5, IL-13, TSLP and IL-33 in driving severe asthma. In this modeling framework, we explore the contributions of these pathways and associated cell types across multiple relevant tissues towards key clinical endpoints including FeNO and FEV1. The virtual population developed is able to capture several relevant biomarkers at baseline as well as in response to multiple therapies. We use this population to predict the effect of anti-IL33 therapy on clinical biomarkers, and utilize sensitivity analyses to explore the impact of the relative effect of anti-IL33 upon type 2 cytokines and other pathways. The developed model will be useful for further model-driven asthma therapy development in the severe asthma population.
