Measuring and Predicting Glycemic Response to Food in Patients With Type 1 Diabetes

This proposal joins together clinical practitioners, biologists, and computer scientists to set up the infrastructure for research that will facilitate, for the first time, the use of big-data, machine-learning approaches in the application of personalized medicine methods in the management of type 1 diabetes mellitus. We will model the clinical, microbial, and nutritional factors underlying the variability in glycemic response to food in this population; develop algorithms for prediction of this response and for the accurate administration of insulin, assisting the clinical management of the disease and discover intervention targets in the gut microbiome aimed at improving glycemic control.