I-Corps: Immune Profiling for Patient Stratification in Clinical Drug Development of Autoimmune and Cancer Biologic Therapies

University Of California-San Francisco, San Francisco CA

Investigators

Abstract

The broader impact/commercial potential of this I-Corps project is validating the value of using a comprehensive immune profiling technology to identify predictive biomarkers for streamlining clinical trial drug development. Targeted treatments can be very effective when matched with a responsive patient population. One way to increase treatment efficacy, reduce cost, and mitigate risk for therapies in clinical development is to sub-segment a patient population into likely responders and non-responders. This immune profiling technology has the potential to stratify patients this way by identifying predictive biomarkers that correlate with treatment. The project's focus is on immunotherapies and biologics for autoimmune diseases, two areas where the immune system activity is central to therapy success and avoidance of adverse side effects. By examining the immune profile of patients, this project hopes to identify mis-regulated cellular and gene pathways and therefore elucidate therapeutic efficacy in patients. Predicting patient response to therapies will streamline clinical trial drug approval, reduce healthcare costs on ineffective treatments, and ultimately, improve patient outcomes. This I-Corps project is based on a powerful sequencing-based immune profiling platform for patient stratification for applications in precision medicine and drug development. This technology enables high-throughput isolation and comprehensive transcriptional profiling of individual immune cells directly from microliters of whole blood. From the data generated, high-resolution, multi-scale immune profiles are developed that present a readout of the interactions across cell types and within individual cells. These unbiased and high-dimensional profiles provide three distinct tiers of information: 1) Cellular level: the frequency of each cell type observed, 2) Module level: the transcriptional programs for inflammatory and immune pathways and 3) Gene level: individual biomarkers within each cell type. In contrast to DNA sequencing, these measurements are sensitive to cellular heterogeneity and captures the genetic and environmental factors driving the dynamic processes of disease pathogenesis and response to drug therapy. This compact representation of the immune state will enable the identifcation of features of the immune profile that are predictive of disease, drug response, and more.