Leveraging Pharmacogenomics in Asthma for Predication, Mechanism and Endotyping

In this study, a new method will be used to evaluate response to 2 approved biologic therapies, and assess how well each patient responds to each asthma treatment. This study will measure the response to these treatments using genomic and biologic measurements obtained from participants biosamples. By evaluating response to 2 different biologic therapies, this study has the potential to provide an in-depth understanding of the mechanisms underlying severe asthma that will inform and change treatment decisions, and may ultimately lead to a change in the way that asthma patients are evaluated for potential personalized therapies and maximize the probability that the subject will respond to treatment.

The study design mirrors standard of care for this study population (moderate to severe asthmatics) in that the procedures are drugs and not outside of standard of care and not experimental. The drugs were chosen based on safety, availability, and their use in patient care. The use of the drugs/biologics and other asthma related processes and procedures are not experimental. Eligible participants will have the option of receiving Symbicort as their controller medication, during their involvement in the study. The study focuses on a series of pre- and post-therapy characterizations or 'evoked phenotypes' that are not studied in traditional randomized clinical trials. Specifically, in a broad spectrum of 120 moderate-severe nonsmoking asthmatics, after evaluating pharmacologic response to systemic corticosteroids, each subject will undergo 'evoked phenotypes' with anti-IL-5R (benralizumab) and anti-IL-4Rα (dupilumab) in a random order along with comprehensive transcriptomic data interrogation prior to and during each therapeutic intervention. A specific strength of our approach is the longitudinal assessment of within individual response related to therapeutic immunomodulation combined with state-of-the-art computational methods that will further define disease biology. Current biomarkers are inadequate to distinguish responders and non-responders because they are not sensitive or specific enough for true predictive precision medicine. This study will use novel genomics approaches to assess and predict responses using therapy-induced phenotypes across a spectrum of asthma severity and endotypes.