The UCI Institute for Precision Health (IPH) is an endeavor that combines our health sciences, engineering, statistics, machine learning, artificial intelligence, clinical genomics, data science, public health, and healthcare delivery system capabilities to provide personalized and effective health and wellness strategies. Driven by computer algorithms, statistical theory and predictive modeling, precision health uses advanced data analysis to make patient-controlled, personalized treatment and lifelong health maintenance plans possible. In doing so, IPH will confront the linked challenges of health equity and the high cost of care.
While the vision for IPH has long been in the works, the pandemic expedited a soft launch, showing how rapidly critical medical needs could be met. In 2020, UCI researchers, healthcare providers, and data scientists joined forces to create the COVID Vulnerability Index, a data-centric method of assessing the risk for COVID-19 patients and using that information to make treatment decisions.
IPH aims to change the healthcare landscape, focusing on the individual patient to empirically identify the most effective health and wellness strategies at a personal level. IPH will assess if the cost of treatments are validated by their utility, and open doors for breakthroughs in diseases where no current treatments change the course of the disease, such as Alzheimer’s, Huntington’s and Parkinson’s. The institute’s success will be measured by improvements in individual and community health.
IPH is an interdisciplinary ecosystem for collaboration across seven areas, including:
SMART (statistics, machine learning, artificial intelligence) develops novel statistical methodology to integrate and analyze health records, molecular data, and observational clinical outcomes. The unit is led by Daniel Gillen, Professor and Chair, Statistics, and Zhaoxia Yu, Associate Professor, Statistics.
A2IR (applied artificial intelligence research) designs practical solutions to real world clinical problems and cost-effective, value-based care. It is led by Peter Chang, Assistant Professor-in Residence, Radiological Sciences.
A3 (advanced analytics and artificial intelligence) brings solutions to inpatient, ambulatory and community settings and supports pilot applications. The area is led by Daniel Chow, Assistant Professor-in Residence, Radiological Sciences.
Precision omics generates, analyzes, and administers genomic, proteomic, and chemical data. It is led by Suzanne Sandmeyer, Professor and Grace Beekhuis Bell Chair in Biological Chemistry, and Leslie Thompson, Donald Bren Professor and Chancellor’s Professor, Psychiatry and Human Behavior and Neurobiology and Behavior.
Collaboratory for Health and Wellness (powered by Syntropy) houses the dynamic analytics platforms and patient-controlled data at the core of the IPH ecosystem. The group is led by Tom Andriola, Vice Chancellor, Information, Technology and Data, and Kai Zheng, Professor, Informatics.
Deployable Health Equity brings IPH into communities to create solutions to narrow the disparities gap in the health and wellbeing of vulnerable populations. The unit is led by Dan Cooper, Professor, Pediatrics and Associate Vice Chancellor, Clinical and Translational Research, and Bernadette Boden-Albala, Director and Founding Dean, Program in Public Health and Professor, Population Health and Disease Prevention and Epidemiology.
With leadership from each of the above areas, Education and Training brings courses, seminars, certificates and degrees in statistics, machine learning-artificial intelligence, omics, and bioinformatics to practitioners and students.
We are thrilled to launch this Institute and believe its work is an important step toward a healthcare revolution that will empower patients, confront health inequities, decrease cost and impartially judge the effectiveness of medications and devices.”Provost Hal Stern and Vice Chancellor Steve Goldstein
Operating now as an institute without walls, IPH aims to have a brick-and-mortar home on the UCI campus, which will serve as a hub to educate data-informed clinicians so they can practice at the top of their licenses, train data scientists to collaborate with clinical practitioners to develop the analytic tools that will drive the field, house personnel to facilitate translational research, and serve as a location for both community outreach and industry collaborations.