RRL-RDD: A Versioned Evidence-Graph and Regulatory Risk-Debt Dynamics Framework for Quantitative Release Readiness
Abstract
This Zenodo record contains the preprint “RRL-RDD: A Versioned Evidence-Graph and Regulatory Risk-Debt Dynamics Framework for Quantitative Release Readiness.” The paper introduces RRL-RDD as a quantitative release-readiness framework for medical devices and IVDs that treats regulatory readiness not as a retrospective document checklist, but as a computable property of a structured evidence system. The framework models lifecycle evidence as a typed, versioned graph linking requirements, statements, risks and controls, verification activities, controlled documents, and change records across auditable snapshots. From this graph, the manuscript derives compact and interpretable indicators for evidence coverage, traceability integrity, evidence quality, and externally visible statement support. It further introduces deterministic contradiction gates that render release readiness falsifiable at decision time, and formalizes change-induced compliance backlog as Regulatory Risk Debt (RRD), making deferred remediation visible as a lifecycle state rather than a hidden operational burden. The contribution is methodological and operational rather than rhetorical. RRL-RDD provides a structured control layer for evidence completeness, traceability coherence, contradiction detection, and debt-aware release governance. The manuscript also includes a proof-of-mechanism synthetic study and a public empirical anchoring using FDA inspection-observation statistics and a warning-letter case, thereby linking the formal framework to observable regulatory failure modes. Related framework-level companion works in this research line include the author’s broader readiness and drift-governance preprints. A closely related Zenodo record can be consulted via DOI: 10.5281/zenodo.17518146. Files in this record:1. Main preprint PDF.
Fields of Study & Subjects
Healthcare Regulation
Safety Systems Engineering in Autonomy
Quality and Management Systems
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 3 February 2026
- Language
- EN
- Document type
- Preprint