Biobanking for Personalized Medicine: GANI_MED

Grabe et al. (2014) describe the approach taken by the University Medicine Greifswald in Germany in setting up a scientific and clinical infrastructure to support research into personalized medicine.¹ In addition to describing the scientific aims of the project, the authors also describe steps taken to ensure a reliable and efficient biobanking system to support the research.

Personalized or individualized medicine is becoming more important for developing effective therapeutics tailored to patient and disease characteristics. Researchers frequently employ multiple –omics technologies to search for relevant and reliable biomarkers to indicate disease, therapeutic progression and prognosis. For this work, they must be able to access large numbers of biosamples and allied clinical data from both patients and the general population. The Greifswald Approach to Individualized Medicine, or GANI_MED, seeks to support this process by providing high-quality biospecimens from donor representatives of a number of diseases of interest in conjunction with standardized medical and lifestyle data.

The GANI_MED project, a cohort study with individual follow-up within a single institution, comprises three major approaches:

1. Establishment of patient cohorts (n > 5,000 each) representative of major cardiovascular, metabolic and clinical areas of concern
2. Biomarker assessment and discovery using multi-omics technologies
3. Comparison between patient cohorts and an established background general population

Recruitment started in July 2011, with researchers collecting samples and data from patients already enrolled in the hospital for treatment of heart failure, stroke, periodontal disease, renal insufficiency, fatty liver disease or metabolic syndrome. The project added three further conditions—sepsis, pulmonary disease and adverse reactions to medications—as the collection progressed.

Overall, the associated biobank had three major objectives:

1. Create a centralized bank of biospecimens
2. Link –omics data with clinical details
3. Enable research and collaboration, internally and externally

The GANI_MED team set out to achieve these objectives by setting up an automated biobanking facility with centralized data management and medical informatics.

• Data collection: Staff are fully trained in the use and delivery of computer-assisted standardized interviews to collect medical history, and they follow standard operating procedures for clinical examinations. In this way, data collection is consistent, allowing routine automated monitoring for quality control that flags deviations from accepted protocols. Standardization includes disease-specific protocols for each cohort to ensure collection of relevant life history, clinical details and biosamples. Once collected, individual patient records integrate phenotype details with proteomic, genomic and metabolomics data generated for biomarker discovery.
• Biosample storage: Biobanking is fully automated, allowing efficient management of biosample storage and retrieval. On recruitment, sample collection generates approximately 19 cryotubes (1 ml volume) per patient.
• Ethical issues: Trained staff collect informed consent in person from each patient on recruitment. The consent includes a full description of study details. Furthermore, consent is modular, allowing more personalized patient control over permissions for sample access and use. Ongoing ethical research projects examine issues arising, including issues involved in relaying clinically relevant information back to donors, and developing therapeutic strategies from research findings.
• Patient safety and privacy: In compliance with national and international regulations, GANI_MED uses an independent trusted third party to assign unique identifiers that do not compromise confidentiality for digital and other records. There is an established protocol for dealing with requests from external collaborators.

For future consideration, Grabe et al. note that GANI_MED will extend its communication and health data to general practitioners and other academics, in addition to the health care and biotechnology industries.

Reference
1. Grabe, H.J., et al. (2014) “Cohort profile: Greifswald approach to individualized medicine (GANI_MED),” Journal of Translational Medicine, 12(144), doi: 10.1186/1479-5876-12-144.