Precision Immunology (Phases 1 & 2)

The Challenge

The initiative focuses on automating the development of a T Cell Health Index, an emerging biomarker with applications in infectious disease prevention and oncology, by applying advanced AI techniques to complex immunological data. A promising proof-of-concept developed from long COVID patient data demonstrated the Index’s potential, but the initial process was manual, time-consuming, and limited in scope. The new solution applies clustering, statistical normalization, and dimensionality reduction techniques, combined with reinforcement learning and support vector machine (SVM) classification, to clean, structure, and interpret multiplexed immune monitoring data. The result is a robust, scalable biomarker pipeline that improves accuracy, reduces turnaround time, and supports broader adoption in pharma and biotech settings. Expected impacts include more than $50 million in annual revenue growth and $2 million in operational cost savings through reduced manual data processing.