Biobanking for intelligent medicine: assessment and evaluation with the SHARE principle.

BACKGROUND: Biobanks are essential for intelligent medicine but face fragmentation and heterogeneity. No standardized framework exists for assessing biobank data value using public information; this study addresses this gap. MATERIALS AND METHODS: We systematically evaluated 94 global biobanks (2010-2024) through a literature review and structured data extraction. Based on 12 international standards, we developed the 5-dimensional SHARE principle (Standardization, Hierarchical structuring, Analytical compatibility, Regulatory compliance, Evolutionary adaptability), operationalized into 10 indicators with a 4-tier scoring system. GPT-4o provided AI-supported prescoring, which was validated by 10 experts and through case studies, including RARPKB. RESULTS: The SHARE principle and a classification map of 94 biobanks were generated. AI and expert scoring showed substantial consistency (κ = 0.62; 95% CI, 0.54-0.70). Biobanks were categorized into 4 tiers: Traditional (60-69), Data-Driven (70-79), Knowledge-Guided (80-89), and Generative and Reasoning-oriented Biobank (90-100). Case validation confirmed utility for disease-specific biobanks. DISCUSSION: We highlight the principal findings, critically examine the reliance on public documentation, propose mitigation strategies, and discuss indicator weighting and implications for translational informatics. CONCLUSIONS: The SHARE principle provides a scalable, standardized method for assessing biobank data value, supporting biobank development, resource discovery, and the development of AI-driven biomedical ecosystems for intelligent medicine.