The Information Technology Infrastructure for the Translational Genomics Core and the Partners Biobank at Partners Personalized Medicine

The Biobank and Translational Genomics core at Partners Personalized Medicine requires robust software and hardware. This Information Technology (IT) infrastructure enables the storage and transfer of large amounts of data, drives efficiencies in the laboratory, maintains data integrity from the time of consent to the time that genomic data is distributed for research, and enables the management of complex genetic data. Here, we describe the functional components of the research IT infrastructure at Partners Personalized Medicine and how they integrate with existing clinical and research systems, review some of the ways in which this IT infrastructure maintains data integrity and security, and discuss some of the challenges inherent to building and maintaining such infrastructure

The Evolution of a Large Biobank at Mass General Brigham

The Mass General Brigham Biobank (formerly Partners HealthCare Biobank) is a large repository of biospecimens and data linked to extensive electronic health record data and survey data. Its objective is to support and enable translational research focused on genomic, environmental, biomarker and family history associations with disease phenotypes. The Biobank has enrolled more than 135,000 participants, generated genomic data on more than 65,000 of its participants, distributed approximately 153,000 biospecimens, and served close to 450 institutional studies with biospecimens or data. Although the Biobank has been successful, based on some measures of output, this has required substantial institutional investment. In addition, several challenges are ongoing, including: (1) developing a sustainable cost model that doesn’t rely as heavily on institutional funding; (2) integrating Biobank operations into clinical workflows; and (3) building a research resource that is diverse and promotes equity in research. Here, we describe the evolution of the Biobank and highlight key lessons learned that may inform other efforts to build biobanking efforts in health system contexts