Fusion designs and estimators for treatment effects

When trials compare new treatments to standards of care rather than to placebo, direct randomized comparisons are often unavailable. No formal data fusion estimator had been developed for this bridged treatment comparison problem.

Target RWE researchers and UNC collaborators developed and published a formal data fusion estimator for bridged treatment effects in Statistics in Medicine, combining data from two studies with shared arms using inverse probability weighting.

The fusion estimator provides pharma partners and regulators with a rigorous method for generating comparative evidence when head-to-head trials are unavailable, addressing a common evidence gap in drug development.

Fusion estimator development for bridged treatment comparison when head-to-head trial data is unavailable, Formal causal data fusion framework for evidence synthesis in drug development programs