The past two decades have seen the practice of medicine increasingly shift from using general guidelines to how best treat each person based on their individual characteristics and context. The promise of identifying and using new biomarkers to tailor healthcare delivery – from genomic, imaging, mHealth, and other sources – is the vision of precision health. Realizing this new future requires novel approaches for research infrastructure, patient education, and risk modeling. Projects at the Center for SMART Health are forging the path towards precision health through technology development and collaborations with key stakeholders at UCLA.
Notably, bringing together expertise from the CTSI and IPH, we are helping to establish new methods supporting UCLA’s ATLAS initiative. For example, we are developing a next-generation framework for data and result sharing within the scientific community. A key element of precision health is the ability to use biomarkers to predict, for the purposes of screening, diagnosis, treatment, and/or other future health-related outcomes. However, the development, testing, dissemination – and ultimately, the scientific reproducibility – of such predictive models is presently challenging, particularly as new types of data from the electronic health record (EHR) and emergent methods come into play. We are helping to design and implement infrastructure that will enable well-annotated datasets, intermediate results, and end models to be documented and shared in a FAIR (findable, accessible, interoperable, reusable) manner.