A Hybrid Design Incorporating External Data to Evaluate Dexamethasone Intracameral Drug Delivery Suspension for Post‐Cataract Surgery Inflammation

Traditional randomized controlled trials (RCTs) face increasing challenges due to lengthy recruitment and high costs. Regulators have encouraged the use of external data and real‐world evidence (RWE) to improve efficiency, yet adoption in confirmatory settings remains limited by concerns over heterogeneity and bias. We conducted a proof‐of‐concept study to assess the feasibility and regulatory value of a hybrid Bayesian borrowing design to support a Phase III RCT of Dexamethasone Intracameral Drug‐Delivery Suspension (DEXYCU) in China. Using the Equivalence Probability Propensity Score Meta‐Analytic‐Predictive (EQPSMAP) approach, we integrated three data sources—a global RCT, a regional Phase III RCT in China, and a real‐world data (RWD) in China. The method's performance was evaluated via point estimates and 95% credible intervals for the primary efficacy endpoint. The hybrid design based on EQPSMAP demonstrated greater robustness and accuracy in the presence of baseline imbalances and heterogeneous data. Compared to a traditional RCT, the hybrid design reduced the required sample size by 41 to 158 patients and shortened trial duration by approximately 2 to 5 months while preserving internal validity. This study demonstrated the feasibility and regulatory value of hybrid Bayesian designs in late‐phase trials. The approach offers a practical, bias‐controlled framework for integrating external data into regional drug development and regulatory decision making.