Evaluating Data-Driven Automated Discovery of Disconnected Negative Controls Using Plasmode Simulations

This poster describes a project that adapted Data-driven Automated Negative Control Estimation (DANCE) for high-dimensional real-world data, extended its use to studies with binary variables and time-to-event outcomes, and evaluated its ability to identify valid disconnected negative controls using plasmode simulations informed by real-world healthcare data. It was presented at the 2026 ISPE Annual Meeting.