One of our projects, which is a collaboration with Dr. Sung Won Choi's lab and others, is aimed at finding new ways for personalized prediction of side effects of a new cancer therapy called CAR-T cell therapy. This is a potentially life-saving therapy that can also have serious side effects, including one called cytokine release syndrome (CRS) in which the body's immune system hyper-reacts when patients receive CAR-T cell therapy, and this immune hyper-reaction can be life-threatening. We have collected longitudinal, multi-modal data (multi-omics, electronic health record clinical data, and wearable sensor data) from patients receiving this therapy at Michigan Medicine and are performing analyses to identify both molecular and 'digital' biomarkers for predicting CRS. Early prediction of CRS could allow earlier intervention and potentially even prevention of this condition. Our multi-omics analysis has also identified new targets for therapeutic intervention to mitigate CRS. This project has received funding support from the A. Alfred Taubman Medical Research Institute.
Another project underway, in collaboration with Dr. Annelise Madison and others, involves using multi-modal, high time-resolution data collected from wearable sensors of participants subjected to psychological stress (i.e., social stress), to perform data analysis to identify physiological signatures of emotional distress. The ultimate goal of this project is to enable real-time monitoring to detect emotional distress through objective physiological measurements, and to then deliver interventions to relieve distress in real-time. We would like to ultimately use this to relieve distress in cancer patients and test the hypothesis that by doing so, this will have favorable effects on the immune system and lead to improved treatment outcomes, including higher cure rates.
I would like our lab and collaborators to use data science to study the relationship between mind and body, in particular how psychology can influence human physiology to improve treatment outcomes for cancer and other diseases. I believe quantitative methods and data science have a big role to play in this, through enabling continuously measured physiological data from wearable devices to serve as an objective measure of the effect of mindsets and psycho-emotional state on the body.