Primary approaches to disease treatment are reactive, with patients diagnosed and treated only after symptoms develop. This project aims to improve chronic disease prediction by identifying early risk factors, piloting the technology on Type 2 Diabetes (T2DM). The results of this work should enable insight into the multimodal causes of disease, identify biomarkers to predict and diagnose disease, and ensure that we move towards a model where preventative care and early intervention reduce the burden of disease and improve the health span of all individuals. The Buck Institute, in partnership with 4YouandMe and Phenome Health, aims to generate in-depth data which will be analyzed using AI/ML techniques to develop noninvasive metrics to increase health personalization and help shift health care to the home. The performers will interrogate the genomic, proteomic, metabolomic, environmental, and social factors that precede disease onset, enabling elucidation of more comprehensive risk factors, determinants of disease and disease pathways, and novel biomarkers for early detection. PATH aims to focus on data-driven health care to provide actionable, personalized information to the individual for democratization of health care.