Methodological Quality and Validation Adequacy of Clinical Digital Twins in Healthcare: A Systematic Review Protocol

Digital twins (DTs) are dynamic, patient-specific virtual models that integrate real-time or longitudinal health data to simulate physiological processes and predict treatment responses. Despite growing interest, clinical adoption is limited by inconsistent, under-reported, and poorly standardised validation practices (e.g., limited external validation, small or incomplete datasets, and minimal uncertainty quantification). Digital twins are selectively validated against their stated objectives, yet the alignment between purpose, validation strategy, and clinical risk is often unclear, inconsistently reported, or insufficiently justified. This review will systematically evaluate the methodological quality and validation adequacy of clinical DTs, including studies reporting DT development, testing, or clinical use. Findings will highlight framework and reporting gaps and inform standardisation to support safe and equitable DT implementation and regulatory pathways.