Is there a protocol for using the SPREC?

Liquid materials for biomedical research: a highly IT-integrated and automated biobanking solution

Various information technology (IT) infrastructures for biobanking, networks of biobanks and biomaterial management are described in the literature. As pre-analytical variables play a major role in the downstream interpretation of clinical as well as research results, their documentation is essential. A description for mainly automated documentation of the complete life-cycle of each biospecimen is lacking so far. Here, the example taken is from the University Medical Center Göttingen (UMG), where the workflow of liquid biomaterials is standardized between the central laboratory and the central biobank. The workflow of liquid biomaterials from sample withdrawal to long-term storage in a biobank was analyzed. Essential data such as time and temperature for processing and freezing can be automatically collected. The proposed solution involves only one major interface between the main IT systems of the laboratory and the biobank. It is key to talk to all the involved stakeholders to ensure a functional and accepted solution. Although IT components differ widely between clinics, the proposed way of documenting the complete life-cycle of each biospecimen can be transferred to other university medical centers. The complete documentation of the life-cycle of each biospecimen ensures a good interpretability of downstream routine as well as research results.

Rationalized Development of a Campus-Wide Cell Line Dataset for Implementation in the Biobank LIMS System at Bioresource Center Ghent

The Bioresource center Ghent is the central hospital-integrated biobank of Ghent University Hospital. Our mission is to facilitate translational biomedical research by collecting, storing and providing high quality biospecimens to researchers. Several of our biobank partners store large amounts of cell lines. As cell lines are highly important both in basic research and preclinical screening phases, good annotation, authentication, and quality of these cell lines is pivotal in translational biomedical science. A Biobank Information Management System (BIMS) was implemented as sample and data management system for human bodily material. The samples are annotated by the use of defined datasets, based on the BRISQ (Biospecimen Reporting for Improved Study Quality) and Minimum Information About Biobank data Sharing (MIABIS) guidelines completed with SPREC (Standard PREanalytical Coding) information. However, the defined dataset for human bodily material is not ideal to capture the specific cell line data. Therefore, we set out to develop a rationalized cell line dataset. Through comparison of different datasets of online cell banks (human, animal, and stem cell), we established an extended cell line dataset of 156 data fields that was further analyzed until a smaller dataset—the survey dataset of 54 data fields—was obtained. The survey dataset was spread throughout our campus to all cell line users to rationalize the fields of the dataset and their potential use. Analysis of the survey data revealed only small differences in preferences in data fields between human, animal, and stem cell lines. Hence, one essential dataset for human, animal and stem cell lines was compiled consisting of 33 data fields. The essential dataset was prepared for implementation in our BIMS system. Good Clinical Data Management Practices formed the basis of our decisions in the implementation phase. Known standards, reference lists and ontologies (such as ICD-10-CM, animal taxonomy, cell line ontology…) were considered. The semantics of the data fields were clearly defined, enhancing the data quality of the stored cell lines. Therefore, we created an essential cell line dataset with defined data fields, useable for multiple cell line users.

"Life in Data"--Outcome of a Multi-Disciplinary, Interactive Biobanking Conference Session on Sample Data

INTRODUCTION

Clinical, biodiversity, and environmental biobanks share many data standards, but there is a lack of harmonization on how data are defined and used among biobank fields. This article reports the outcome of an interactive, multidisciplinary session at a meeting of the European, Middle Eastern, and African Society for Biopreservation and Biobanking (ESBB) designed to encourage a 'learning-from-each-other' approach to achieve consensus on data needs and data management across biobank communities.

MATERIALS, METHODS, AND RESULTS

The Enviro-Bio and ESBBperanto Working Groups of the ESBB co-organized an interactive session at the 2013 conference (Verona, Italy), presenting data associated with biobanking processes, using examples from across different fields. One-hundred-sixty (160) diverse biobank participants were provided electronic voting devices with real-time screen display of responses to questions posed during the session. The importance of data standards and robust data management was recognized across the conference cohort, along with the need to raise awareness about these issues within and across different biobank sectors.

DISCUSSION AND CONCLUSION

While interactive sessions require a commitment of time and resources, and must be carefully coordinated for consistency and continuity, they stimulate the audience to be pro-active and direct the course of the session. This effective method was used to gauge opinions about significant topics across different biobanking communities. The votes revealed the need to: (a) educate biobanks in the use of data management tools and standards, and (b) encourage a more cohesive approach for how data and samples are tracked, exchanged, and standardized across biobanking communities. Recommendations for future interactive sessions are presented based on lessons learned.

Biobanking Comes of Age: The Transition to Biospecimen Science

Biobanking involves the collection, processing, storage, and distribution of biological specimens and the policies and procedures necessary to accomplish those aims successfully. Although biobanking may also involve collections for environmental studies or museum archives, most efforts to standardize biobanking practices have been directed toward human biomedical research. Initially focused primarily on collecting samples for diagnostic purposes in pathology settings, biobanks have evolved into complex organizations engaged in advancing personalized (or precision) medicine and translational research. This evolution has involved the development of biobanking best practices and the transformation of a field driven by empirical approaches into the emerging area of biospecimen science. It has become increasingly important to develop evidence-based practices for collecting biospecimens and data that can be shared with confidence with international collaborators. Aside from these technical approaches, other factors play crucial roles, such as ethical and regulatory issues, business planning and sustainability, and approaches to data collection and sharing.

Individual investigator profiles of biospecimen use in cancer research

BACKGROUND

Establishing targets for case accrual is an important component of a strategic plan for a biobank. We have previously assessed overall patterns of biospecimen use in cancer research publications in selected journals. Here we extend this analysis to consider patterns of biospecimen use in relation to cancer research programs developed by individual investigators.

METHODS

We selected three individual cancer research investigators whose independent research programs began circa 1986, have been characterized by extensive use of human tumor biospecimens, and have primarily involved translational research in the areas of breast, lung, and ovarian cancer. We analyzed biospecimen and data usage in their career publications categorized by numbers, type, and format, and accompanying annotating data in terms of conformance with BRISQ reporting and ethics related criteria.

RESULTS

Biospecimens were used in 313/474 (66%) of publications analyzed. The average number of biospecimens used by these research programs increased six-fold from less than 1000 in 2001-2003 to greater than 6000 in 2010-2012, and the average cohort sizes per article also increased from approximately 50 to 200 cases per study over the same period in most biospecimen categories (p<0.05). The relative proportions of different formats of biospecimens used has varied significantly and continues to change with the emergence of digital biospecimen derived data. In these three translational research programs, BRISQ elements relating to 'Biobank' categories were significantly less well reported for biospecimens used in publications than data corresponding to 'Clinical chart' categories (p<0001).

CONCLUSIONS

This study shows that overall use of biospecimens in cancer research has increased significantly and that dynamic variation in the relative use of different biospecimen formats has also occurred. This study also confirms our previous findings on patterns of biospecimen use and also those concerning incomplete reporting of relevant data elements that has not improved in the past decade.