The biorepository portal toolkit: an honest brokered, modular service oriented software tool set for biospecimen-driven translational research

Abstract

Background: High throughput molecular sequencing and increased biospecimen variety have introduced significant informatics challenges for research biorepository infrastructures. We applied a modular system integration approach to develop an operational biorepository management system. This method enables aggregation of the clinical, specimen and genomic data collected for biorepository resources.

Methods: We introduce an electronic Honest Broker (eHB) and Biorepository Portal (BRP) open source project that, in tandem, allow for data integration while protecting patient privacy. This modular approach allows data and specimens to be associated with a biorepository subject at any time point asynchronously. This lowers the bar to develop new research projects based on scientific merit without institutional review for a proposal.

Results: By facilitating the automated de-identification of specimen and associated clinical and genomic data we create a future proofed specimen set that can withstand new workflows and be connected to new associated information over time. Thus facilitating collaborative advanced genomic and tissue research.

Conclusions: As of Janurary of 2016 there are 23 unique protocols/patient cohorts being managed in the Biorepository Portal (BRP). There are over 4000 unique subject records in the electronic honest broker (eHB), over 30,000 specimens accessioned and 8 institutions participating in various biobanking activities using this tool kit. We specifically set out to build rich annotation of biospecimens with longitudinal clinical data; BRP/REDCap integration for multi-institutional repositories; EMR integration; further annotated specimens with genomic data specific to a domain; build application hooks for experiments at the specimen level integrated with analytic software; while protecting privacy per the Office of Civil Rights (OCR) and HIPAA.

Keywords: Biorepository research; Cancer genomics; Data integration; Data representation; Honest broker; Open source; Patient health information protection; Patient privacy; Precision medicine; Translational bioinformatics.

Fig. 1

Three workflow iterations. Iterations of the introduction of the modular tool kit from human intervention, electronic intervention to fully realized modular approach

Fig. 2

The interaction between the eHB and client applications. This takes place over HTTP through CRUD (GET, POST, PUT, DELETE) operations. Client applications (i.e., the BRP) determine the context of the information sent and received to the eHB service. Within the eHB, data is encrypted at rest, and in transit. A query of data can only take place through the eHB software service

Fig. 3

Sudo ER diagram of complex relationships between users and data sources. Users are granted access to subject records based on protocols. Each protocol groups a list of subjects that only authorized users can manage and are part are assigned to. Within the walls of a protocol, there are groups of subjects that allow for users to differentiate between institutional or site-based cohorts (i.e., organizations). Each unique subject enrollment creates a new record for that subject in the eHB. Within a protocol there are specific data entry points set up as protocol data sources (e.g., a REDCap case report form project or LIMS specimen project), and each user has credentials to each data source. Data sources are set up as clients to each external system represented in the BRP. In our case, we have created data sources for two systems, REDCap and ThermoFisher Nautilus LIMS

Fig. 4

Screenshot example. A screenshot from the BRP displaying identifiable data entry along the de-identified entry points for client systems’ data sources

Fig. 5

Integrated researcher view. Integrated non-human subject data and specimen query tool built on the Harvest platform. This interface allows for query across multiple systems in one place. The platform can be customized to allow for only certain data elements to be utilized that depend on domain and researcher requirements. Exposed in this example are elements captures in CRFs and the LIMS. There are also links out to genomics analysis tools

Fig. 6

Usage. A graph of specimen accessioning for the CBTTC which has accessioned over 10,000 specimens to date (end of January 2016). The blue shaded area represents the sum of all specimens collected by the project

Fig. 7

CbioPortal – harvest integration architecture. The integrated query tool allows for a back and forth search between genes of interest and visualization in CBioPortal, and the tool for phenotype and specimen requests. We perform this integration in a similar fashion to the other tools in the tool-kit. We utilize a combination of constructing web endpoints and traditional ETL. The cancer genomics integration starts with a scripted pull of mutation data via a secure database connection utilizing elements of CBioPortal’s relational data structure to store this large set of data. Specimens known to the repository are loaded into the CBioPortal by the bioinformatics team with known specimen identifiers from the LIMS. This creates a natural link between any granular genomic data, the specimen and ultimately the subject. URLs are constructed in the query platform that allow for researchers to move from clinical and specimen driven queries directly to CBioPortal to visualize mutation data of interest

Fig. 8

Specimen to cancer genomics. Screen shot of integration of the Harvest-based data and specimen query tool with a the CBioPortal for cancer genomic visualization of a specific case