Alexandros Sagkriotis
Abstract Purpose Real-world evidence (RWE) and real-world data (RWD) have become integral to regulatory, clinical, and policy decision-making. Yet oncology registries—the most structured and disease-specific RWD sources—remain fragmented, inconsistently governed, and poorly integrated with AI-driven analytical systems. This conceptual perspective synthesizes regulatory guidance, best practices, and three decades of professional experience to propose a pragmatic roadmap for transforming oncology registries into scalable, interoperable RWE platforms. Methods The approach integrates practice-based evidence, international regulatory frameworks (EMA, FDA, MHRA), and case analyses from established registries and digital infrastructures. A three-year phased roadmap is proposed, focusing on governance, interoperability, artificial intelligence (AI) readiness, and multi-stakeholder collaboration. Although not a systematic review, the manuscript draws on applied use-cases and policy frameworks to illustrate transferability across healthcare systems. Results Three conceptual models are developed to describe: (1) the main RWD domains; (2) the bidirectional alignment between RWE and RWD strategies; and (3) a phased roadmap for data activation, hybrid platform development, and AI-ready evidence generation. Case studies from the UK, France, Italy, Germany, and Finland demonstrate how registry modernization can enhance completeness, quality, and regulatory utility. Conclusions Oncology registries can evolve from static repositories into dynamic learning infrastructures that generate regulatory-grade RWE. Achieving this transformation requires transparent governance, federated data architectures, Findable, Accessible, Interoperable, and Reusable (FAIR)-compliant interoperability, and ethically grounded AI integration. The proposed roadmap offers actionable guidance for regulators, payers, clinicians, and data scientists committed to advancing trustworthy, AI-enabled evidence ecosystems.