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Data Governance and Distribution of Biobank: A Case from a Chinese Cancer Hospital
Jingjing Shi1, Yan Guo1, Na He1
1Cancer Biobank, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute & Hospital, Tianjin, China.
Biopreservation and Biobanking
|December 13, 2024
Summary
Biobanks need better data governance for regionalization and digitization. Implementing standardized data management, patient-centered models, and Minimum Information About Biobank Data Sharing (MIABIS) enhances data integrity and research collaboration.
Area of Science:
- Biobanking
- Data Science
- Health Informatics
Background:
- Facilitating biobank regionalization, specialization, and digitization requires addressing data governance challenges.
- Key issues include data governance integration, distribution, efficiency, efficacy, and sustainability.
- Stakeholder collaboration and continuous evaluation are crucial for assessing infrastructure needs.
Purpose of the Study:
- To develop and implement robust data management solutions for biobanks.
- To optimize data collection, distribution, and application processes.
- To enhance data integrity and support data-intensive research.
Main Methods:
- Collaborative stakeholder engagement to identify priorities and infrastructure needs.
- Development of data management solutions, catalogs, and data models.
- Utilization of ontologies for data integration and Minimum Information About Biobank Data Sharing (MIABIS) standardization.
- Implementation of retrospective and prospective follow-up studies for data integrity.
- Infrastructure upgrades and development of specialized information management software.
- Transition to a patient-centered, service-oriented biospecimen accumulation model.
Main Results:
- Completed infrastructure upgrades and developed a six-division information management software for data governance.
- Specified 85 MIABIS attributes for comprehensive biobank content description.
- Implemented a dual-pillar approach for data expansion through institutional collaboration, using MIABIS as a network bridge.
- Collected 156,997 biospecimens/data from 20 cancer types (2003–2021), with 53,113 follow-up cases.
- Supplied over 40,000 biospecimens/data points for more than 300 research projects.
Conclusions:
- A standardized scientific data structure and an appropriate information platform are fundamental for biobank data management in data-intensive research.
- Sustainable biobank development relies on scientific, standardized, and service-oriented data governance.
- Efficient utilization of emerging technologies is key to advancing biobank capabilities.
