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Biobank for Translational Medicine: Standard Operating Procedures for Optimal Sample Management
Published on: November 30, 2022
Methods and implementation of a central biosample and data management in a three-centre clinical study.
Aniela Angelow1, Matthias Schmidt, Kerstin Weitmann
1Institute for Community Medicine, Department of Epidemiology of Health Care and Community Health, Ellernholzstr. 1-2, 17487 Greifswald, Germany. aniela.angelow@uni-greifswald.de
Computer Methods and Programs in Biomedicine
|April 15, 2008
Summary
A central biosample and data management (CSDM) system was developed for a clinical study on inflammatory cardiomyopathy. This system ensures data security, privacy, and quality assurance for research data.
Area of Science:
- Biomedical research informatics
- Clinical trial data management
- Cardiovascular research
Background:
- Implementing a robust data management system is crucial for multi-center clinical studies.
- Inflammatory cardiomyopathy research requires secure and reliable handling of biosamples and patient data.
Purpose of the Study:
- To describe the concept, strategies, and implementation of a central biosample and data management (CSDM) system.
- To ensure high system availability, data security, privacy protection, and quality assurance for a clinical study.
Main Methods:
- Developed a web-based CSDM using Java 2 Enterprise Edition and an Oracle database.
- Implemented bar code labeling, a partitioning storage algorithm, and online documentation software for sample management.
- Utilized an online electronic case report form for patient data acquisition with strict access controls.
Main Results:
- Successfully implemented a CSDM system meeting requirements for availability, security, privacy, and quality.
- Established an efficient and reliable sample documentation and patient data acquisition process.
- Identified implementation challenges at project, technical, organizational, and staff levels.
Conclusions:
- The developed CSDM system effectively supports multi-center clinical research.
- Careful planning and execution are necessary to overcome implementation challenges in data management systems.
- The system enhances the integrity and security of research data in cardiovascular studies.
