Master Protocol Design With Hybrid Control for Efficient Early-Phase Trial Consolidation

Master protocols represent transformations, enabling multiple therapies or diseases under a single protocol. These designs streamline therapeutic development by reducing redundancies. Suited for evolving fields such as oncology and global emergencies such as the COVID-19 pandemic, master protocols have been exemplified by studies such as RECOVERY, Solidarity, and I-SPY 2, which accelerated effective treatment identification (with I-SPY 2 focused on molecular subtypes). Recent oncology examples, such as MORPHEUS, evaluate immunotherapy combinations with shared controls. Despite advantages, their application in early-phase oncology remains underutilized amid growing regulatory emphasis on randomization for robust evidence.

US Food and Drug Administration (FDA) Oncology Center of Excellence (OCE) initiatives, such as Project Optimus and Project FrontRunner, emphasize randomization in early-phase oncology trials. However, these initiatives pose challenges, including larger sample sizes, patient and physician reluctance to randomization, and high failure rates from poor accrual. To address these, this article adapts master protocol designs to consolidate early-phase trials for novel therapeutics sharing a common backbone therapy, integrating hybrid controls from published standard-of-care data to minimize randomization to the control arm.

By consolidating trials under a shared standard-of-care control arm, the proposed master protocol design reduces total sample size by as much as 55% when compared with independent trials (with control arm sizes 2.4-2.9 times lower), lowers costs and duration, and enhances enrollment through reduced randomization to controls. Incorporating hybrid controls from prior studies and sharing information among arms with common background standard-of-care further improve efficiency, increasing power (reaching 90% overall) while controlling type I error rates acceptable levels.

Master protocol designs with hybrid controls and Bayesian information sharing enable the efficient integration of randomization into early-phase oncology trials, enhancing efficiency, cost-effectiveness, and patient-centricity while aligning with FDA OCE initiatives.