Using systems science techniques, the Analytics & Modeling Core focuses on creating, validating, and implementing models that will identify how screening and treatment based on omics data can reduce differential risk among vulnerable populations.

The Analytics and Modeling core develops generalizable models to understand the impact of emerging precision medicine approaches on health disparities. They also facilitate the development of models to study the impact of disparities on precision medicine developments. Some of their accomplishments include:

• Created a systematic modeling framework to understand how the transition towards precision medicine can affect race/ethnic disparities in health across the United States.
• Designed strategies to conduct randomized trials in ways that can clarify how and why some people benefit more than others from the same therapy.
• Created a set of equations that can be used to help identify the best treatments for people with type 2 diabetes, across multiple race/ethnic groups who have different risks and benefits from treatments.
• Looked at how variations in nutrition program management affected health disparities among low-income Americans.
• Examined how using precision risk/benefit calculators rather than single biomarkers can help improve treatment outcomes.
• Devised a strategy to improve modeling of population health disparities.