APeX Enabled Research
This poster will highlight the impact of the APeX Enabled Research (AER) team on implementing clinical and technical innovations at UCSF. The poster will explain the primary goals of the team, volume of project work, and breadth of technologies used to support research innovation. Ideally UC Tech attendees will learn more about what is technically possible today to support research, get inspiration for projects at their organization, get connected with others doing similar work, and lead to future collaboration and innovation across UC campuses. The AER team has supported dozens of research implementations over the last six years and would love an opportunity to share our learnings with the UC Tech community.
Speaker/Host
Primary/Host Speaker
Jory Purvis
APeX Enabled Research - Technical Lead at UC San Francisco
Jory Purvis is the Technical Lead for the APeX (Epic) Enabled Research Team at the University of California, San Francisco. He and his team support the full research project lifecycle—from initial study design, scoping, and budgeting to grant submissions and ongoing implementation. Their work includes developing innovative Epic configurations, supporting multi-site study implementations, and enabling external system integrations to advance clinical research across institutions.
Co-speaker(s)
Additional Speakers
Jassmine Vansise
APeX Enabled Research Build Analyst at UC San Francisco
The APeX Enabled Research (AER) team at UCSF supports researchers in utilizing UCSF's Epic instance to advance their research and clinical trials. In my role as an AER Build Analyst, I work closely with researchers to implement their algorithms, digital tools, and interventions within APeX. I collaborate with teams across UCSF and external sites to develop tailored technical solutions—from disease registries and clinical detection tools to SMART on FHIR integrations, SQL queries, and custom workflows. The work the AER team does aims to bridge the gap between the research and health systems, implementing technology to support data-driven clinical innovation and outcome evaluation.
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