Advancing precision oncology through innovative and adaptive master protocol designs: statistical, operational, and...

Master protocol trials-including basket, umbrella, and platform designs-have revolutionized precision oncology by enabling the simultaneous evaluation of multiple therapies, biomarkers, and tumor subtypes within a unified adaptive framework. They operationalize the core vision of precision oncology-delivering the right therapy to the right patient efficiently-through harmonized infrastructure and adaptive statistical learning. These designs can improve statistical efficiency and operational feasibility by sharing infrastructure, controls, and information across related substudies. However, their benefits are not automatic and depend critically on the rigor of implementation, calibration, and governance. In this review, we synthesize recent methodological, operational, and regulatory advances in master protocol design, with a focus on how these elements jointly enable reliable inference in molecularly heterogeneous oncology settings. Recent statistical innovations have enhanced information sharing across related cohorts while maintaining control of false-positive results under clinical heterogeneity. Platform trials may extend these principles through multi-stage calibration and latent-subgroup dose optimization, providing flexibility for adding or dropping arms while preserving inferential rigor. By explicitly examining the trade-offs, limitations, and practical constraints underlying these designs, this review clarifies when and how master protocols can fulfill their promise in precision oncology. Collectively, these advances establish master protocol trials as powerful and efficient engines for precision oncology, capable of integrating hierarchical modeling, adaptive learning, and real-world data to accelerate therapeutic discovery and regulatory translation. With continued progress in assay standardization, real-time data infrastructure, and adaptive governance, master protocols are poised to transform clinical development, advancing precision oncology from concept to scalable, executable reality.