BBMRI-ERIC Directory: 515 Biobanks with Over 60 Million Biological Samples

Common conditions of use elements. Atomic concepts for consistent and effective information governance

Myriad policy, ethical and legal considerations underpin the sharing of biological resources, implying the need for standardised and yet flexible ways to digitally represent diverse 'use conditions'. We report a core lexicon of terms that are atomic, non-directional 'concepts of use', called Common Conditions of use Elements. This work engaged biobanks and registries relevant to the European Joint Programme for Rare Diseases and aimed to produce a lexicon that would have generalised utility. Seventy-six concepts were initially identified from diverse real-world settings, and via iterative rounds of deliberation and user-testing these were optimised and condensed down to 20 items. To validate utility, support software and training information was provided to biobanks and registries who were asked to create Sharing Policy Profiles. This succeeded and involved adding standardised directionality and scope annotations to the employed terms. The addition of free-text parameters was also explored. The approach is now being adopted by several real-world projects, enabling this standard to evolve progressively into a universal basis for representing and managing conditions of use.

Getting your DUCs in a row - standardising the representation of Digital Use Conditions

Improving patient care and advancing scientific discovery requires responsible sharing of research data, healthcare records, biosamples, and biomedical resources that must also respect applicable use conditions. Defining a standard to structure and manage these use conditions is a complex and challenging task. This is exemplified by a near unlimited range of asset types, a high variability of applicable conditions, and differing applications at the individual or collective level. Furthermore, the specifics and granularity required are likely to vary depending on the ultimate contexts of use. All these factors confound alignment of institutional missions, funding objectives, regulatory and technical requirements to facilitate effective sharing. The presented work highlights the complexity and diversity of the problem, reviews the current state of the art, and emphasises the need for a flexible and adaptable approach. We propose Digital Use Conditions (DUC) as a framework that addresses these needs by leveraging existing standards, striking a balance between expressiveness versus ambiguity, and considering the breadth of applicable information with their context of use.

Update of the Minimum Information About BIobank Data Sharing (MIABIS) Core Terminology to the 3rd Version

Introduction: The Minimum Information About BIobank Data Sharing (MIABIS) is a biobank-specific terminology enabling the sharing of biobank-related data for different purposes across a wide range of database implementations. After 4 years in use and with the first version of the individual-level MIABIS component Sample, Sample donor, and Event, it was necessary to revise the terminology, especially to include biobanks that work more in the data domain than with samples. Materials & Methods: Nine use-cases representing different types of biobanks, studies, and networks participated in the development work. They represent types of data, specific sample types, or levels of organization that were not included earlier in MIABIS. To support our revision of the Biobank entity, we conducted a survey of European biobanks to chart the services they provide. An important stakeholder group for biobanks include researchers as the main users of biobanks. To be able to render MIABIS more researcher-friendly, we collected different sample/data requests to analyze the terminology adjustment needs in detail. During the update process, the Core terminology was iteratively reviewed by a large group of experts until a consensus was reached. Results: With this update, MIABIS was adjusted to encompass data-driven biobanks and to include data collections, while also describing the services and capabilities biobanks offer to their users, besides the retrospective samples. The terminology was also extended to accommodate sample and data collections of nonhuman origin. Additionally, a set of organizational attributes was compiled to describe networks. Discussion: The usability of MIABIS Core v3 was increased by extending it to cover more topics of the biobanking domain. Additionally, the focus was on a more general terminology and harmonization of attributes with the individual-level entities Sample, Sample donor, and Event to keep the overall terminology minimal. With this work, the internal semantics of the MIABIS terminology was improved.

Unlocking the potential of big data and AI in medicine: insights from biobanking

Big data and artificial intelligence are key elements in the medical field as they are expected to improve accuracy and efficiency in diagnosis and treatment, particularly in identifying biomedically relevant patterns, facilitating progress towards individually tailored preventative and therapeutic interventions. These applications belong to current research practice that is data-intensive. While the combination of imaging, pathological, genomic, and clinical data is needed to train algorithms to realize the full potential of these technologies, biobanks often serve as crucial infrastructures for data-sharing and data flows. In this paper, we argue that the 'data turn' in the life sciences has increasingly re-structured major infrastructures, which often were created for biological samples and associated data, as predominantly data infrastructures. These have evolved and diversified over time in terms of tackling relevant issues such as harmonization and standardization, but also consent practices and risk assessment. In line with the datafication, an increased use of AI-based technologies marks the current developments at the forefront of the big data research in life science and medicine that engender new issues and concerns along with opportunities. At a time when secure health data environments, such as European Health Data Space, are in the making, we argue that such meta-infrastructures can benefit both from the experience and evolution of biobanking, but also the current state of affairs in AI in medicine, regarding good governance, the social aspects and practices, as well as critical thinking about data practices, which can contribute to trustworthiness of such meta-infrastructures.

Building a rheumatology biobank for reliable basic/translational research and precision medicine

Research biobanks are non-profit structures that collect, manipulate, store, analyze and distribute systematically organized biological samples and data for research and development purposes. Over the recent years, we have established a biobank, the Rheumatology BioBank (RheumaBank) headed by the Medicine and Rheumatology unit of the IRCCS Istituto Ortopedico Rizzoli (IOR) in Bologna, Italy for the purpose of collecting, processing, storing, and distributing biological samples and associated data obtained from patients suffering from inflammatory joint diseases. RheumaBank is a research biobank, and its main objective is to promote large-scale, high-quality basic, translational, and clinical research studies that can help elucidate pathogenetic mechanisms and improve personalization of treatment choice in patients with rheumatoid arthritis (RA), psoriatic arthritis (PsA) and other spondyloarthritides (SpA).

Applied Molecular-Based Quality Control of Biobanked Samples for Multi-Omics Approach

Biobanks are vital for high-throughput translational research, but the rapid development of novel molecular techniques, especially in omics assays, poses challenges to traditional practices and recommendations. In our study, we used biospecimens from oncological patients in Polish clinics and collaborated with the Indivumed Group. For serum/plasma samples, we monitored hemolysis, controlled RNA extraction, assessed cDNA library quality and quantity, and verified NGS raw data. Tissue samples underwent pathologic evaluation to confirm histology and determine tumor content. Molecular quality control measures included evaluating the RNA integrity number, assessing cDNA library quality and quantity, and analyzing NGS raw data. Our study yielded the creation of distinct workflows for conducting preanalytical quality control of serum/plasma and fresh-frozen tissue samples. These workflows offer customization options to suit the capabilities of different biobanking entities. In order to ensure the appropriateness of biospecimens for advanced research applications, we introduced molecular-based quality control methods that align with the demands of high-throughput assays. The novelty of proposed workflows, rooted in innovative molecular techniques, lies in the integration of these QC methods into a comprehensive schema specifically designed for high-throughput research applications.

Post-identifiability in changing sociotechnological genomic data environments

Data practices in biomedical research often rely on standards that build on normative assumptions regarding privacy and involve 'ethics work.' In an increasingly datafied research environment, identifiability gains a new temporal and spatial dimension, especially in regard to genomic data. In this paper, we analyze how genomic identifiability is considered as a specific data issue in a recent controversial case: publication of the genome sequence of the HeLa cell line. Considering developments in the sociotechnological and data environment, such as big data, biomedical, recreational, and research uses of genomics, our analysis highlights what it means to be (re-)identifiable in the postgenomic era. By showing how the risk of genomic identifiability is not a specificity of the HeLa controversy, but rather a systematic data issue, we argue that a new conceptualization is needed. With the notion of post-identifiability as a sociotechnological situation, we show how past assumptions and ideas about future possibilities come together in the case of genomic identifiability. We conclude by discussing how kinship, temporality, and openness are subject to renewed negotiations along with the changing understandings and expectations of identifiability and status of genomic data.

No time for complacency: The CoVaRR-Net Biobank is an essential element of laboratory preparedness for infectious disease outbreaks

The SARS-CoV-2 pandemic highlighted the need for rapid, collaborative, and population-centric research to define health impact, develop health care policies and establish reliable diagnostic and surveillance tests. Critical for these objectives were in-depth clinical data collected in standardized fashion and large numbers of various types of human samples prior and post-viral encounter. As the pandemic evolved with the emergence of new variants of concern (VOCs), access to samples and data from infected and vaccinated individuals were needed to monitor immune durability, the possibility of increased transmissibility and virulence, and vaccine protection against new and emerging VOCs. Therefore, essential to the pandemic response is a strong laboratory and data research component, supported by effective biobanking and data sharing. Critically important to the speed of the research response is the rapid access to biobanked samples. To address critical challenges brought to light by the pandemic, the Coronavirus Variants Rapid Response Network (CoVaRR-Net), funded by the Canadian Institutes of Health Research, was established to coordinate research efforts to provide rapid evidence-based responses to emerging VOCs. The purpose of this paper is to introduce the CoVaRR-Net Biobank and define its contribution to pandemic preparedness.

Biobanking as a Tool for Genomic Research: From Allele Frequencies to Cross-Ancestry Association Studies

In recent years, great advances have been made in the field of collection, storage, and analysis of biological samples. Large collections of samples, biobanks, have been established in many countries. Biobanks typically collect large amounts of biological samples and associated clinical information; the largest collections include over a million samples. In this review, we summarize the main directions in which biobanks aid medical genetics and genomic research, from providing reference allele frequency information to allowing large-scale cross-ancestry meta-analyses. The largest biobanks greatly vary in the size of the collection, and the amount of available phenotype and genotype data. Nevertheless, all of them are extensively used in genomics, providing a rich resource for genome-wide association analysis, genetic epidemiology, and statistical research into the structure, function, and evolution of the human genome. Recently, multiple research efforts were based on trans-biobank data integration, which increases sample size and allows for the identification of robust genetic associations. We provide prominent examples of such data integration and discuss important caveats which have to be taken into account in trans-biobank research.

Towards an Interoperable Ecosystem of Research Cohort and Real-world Data Catalogues Enabling Multi-center Studies

OBJECTIVES

Existing individual-level human data cover large populations on many dimensions such as lifestyle, demography, laboratory measures, clinical parameters, etc. Recent years have seen large investments in data catalogues to FAIRify data descriptions to capitalise on this great promise, i.e. make catalogue contents more Findable, Accessible, Interoperable and Reusable. However, their valuable diversity also created heterogeneity, which poses challenges to optimally exploit their richness.

METHODS

In this opinion review, we analyse catalogues for human subject research ranging from cohort studies to surveillance, administrative and healthcare records.

RESULTS

We observe that while these catalogues are heterogeneous, have various scopes, and use different terminologies, still the underlying concepts seem potentially harmonizable. We propose a unified framework to enable catalogue data sharing, with catalogues of multi-center cohorts nested as a special case in catalogues of real-world data sources. Moreover, we list recommendations to create an integrated community of metadata catalogues and an open catalogue ecosystem to sustain these efforts and maximise impact.

CONCLUSIONS

We propose to embrace the autonomy of motivated catalogue teams and invest in their collaboration via minimal standardisation efforts such as clear data licensing, persistent identifiers for linking same records between catalogues, minimal metadata 'common data elements' using shared ontologies, symmetric architectures for data sharing (push/pull) with clear provenance tracks to process updates and acknowledge original contributors. And most importantly, we encourage the creation of environments for collaboration and resource sharing between catalogue developers, building on international networks such as OpenAIRE and research data alliance, as well as domain specific ESFRIs such as BBMRI and ELIXIR.

Stakeholder engagement to ensure the sustainability of biobanks: a survey of potential users of biobank services

Biobanks are important infrastructures facilitating biomedical research. After a decade of rolling out such infrastructures, a shift in attention to the sustainability of biobanks could be observed in recent years. In this regard, an increase in the as yet relatively low utilisation rates of biobanks has been formulated as a goal. Higher utilisation rates can only be achieved if the perspectives of potential users of biobanks-particularly researchers not yet collaborating with biobanks-are adequately considered. To better understand their perspectives, a survey was conducted at ten different research institutions in Germany hosting a centralised biobank. The survey targeted potential users of biobank services, i.e. researchers working with biosamples. It addressed the general demand for biosamples, strategies for biosample acquisition/storage and reasons for/against collaborating with biobanks. In total, 354 researchers filled out the survey. Most interestingly, only a minority of researchers (12%) acquired their biosamples via biobanks. Of the respondents not collaborating with biobanks on sample acquisition, around half were not aware of the (services of the) respective local biobank. Those who actively decided against acquiring biosamples via a biobank provided different reasons. Most commonly, respondents stated that the biosamples required were not available, the costs were too high and information about the available biosamples was not readily accessible. Biobanks can draw many lessons from the results of the survey. Particularly, external communication and outreach should be improved. Additionally, biobanks might have to reassess whether their particular collection strategies are adequately aligned with local researchers' needs.

Position paper on management of personal data in environment and health research in Europe

Management of datasets that include health information and other sensitive personal information of European study participants has to be compliant with the General Data Protection Regulation (GDPR, Regulation (EU) 2016/679). Within scientific research, the widely subscribed'FAIR' data principles should apply, meaning that research data should be findable, accessible, interoperable and re-usable. Balancing the aim of open science driven FAIR data management with GDPR compliant personal data protection safeguards is now a common challenge for many research projects dealing with (sensitive) personal data. In December 2020 a workshop was held with representatives of several large EU research consortia and of the European Commission to reflect on how to apply the FAIR data principles for environment and health research (E&H). Several recent data intensive EU funded E&H research projects face this challenge and work intensively towards developing solutions to access, exchange, store, handle, share, process and use such sensitive personal data, with the aim to support European and transnational collaborations. As a result, several recommendations, opportunities and current limitations were formulated. New technical developments such as federated data management and analysis systems, machine learning together with advanced search software, harmonized ontologies and data quality standards should in principle facilitate the FAIRification of data. To address ethical, legal, political and financial obstacles to the wider re-use of data for research purposes, both specific expertise and underpinning infrastructure are needed. There is a need for the E&H research data to find their place in the European Open Science Cloud. Communities using health and population data, environmental data and other publicly available data have to interconnect and synergize. To maximize the use and re-use of environment and health data, a dedicated supporting European infrastructure effort, such as the EIRENE research infrastructure within the ESFRI roadmap 2021, is needed that would interact with existing infrastructures.

The Availability of Human Biospecimens to Support Biomarker Research

Preserved biospecimens held in biobank inventories and clinical archives are important resources for biomarker research. Recent advances in technologies have led to an increase in use of clinical archives in particular, in order to study retrospective cohorts and to generate data relevant to tissue biomarkers. This raises the question of whether the current sizes of biobank inventories are appropriate to meet the demands of biomarker research. This commentary discusses this question by considering data concerning overall biobank and biospecimen numbers to estimate current biospecimen supply and use. The data suggests that biospecimen supply exceeds current demand. Therefore, it may be important for individual biobanks to reassess the targets for their inventories, consider culling unused portions of these inventories, and shift resources towards providing prospective custom biobanking services.

Integrating Biological and Radiological Data in a Structured Repository: a Data Model Applied to the COSMOS Case Study

Integrating the information coming from biological samples with digital data, such as medical images, has gained prominence with the advent of precision medicine. Research in this field faces an ever-increasing amount of data to manage and, as a consequence, the need to structure these data in a functional and standardized fashion to promote and facilitate cooperation among institutions. Inspired by the Minimum Information About BIobank data Sharing (MIABIS), we propose an extended data model which aims to standardize data collections where both biological and digital samples are involved. In the proposed model, strong emphasis is given to the cause-effect relationships among factors as these are frequently encountered in clinical workflows. To test the data model in a realistic context, we consider the Continuous Observation of SMOking Subjects (COSMOS) dataset as case study, consisting of 10 consecutive years of lung cancer screening and follow-up on more than 5000 subjects. The structure of the COSMOS database, implemented to facilitate the process of data retrieval, is therefore presented along with a description of data that we hope to share in a public repository for lung cancer screening research.

LongITools: Dynamic longitudinal exposome trajectories in cardiovascular and metabolic noncommunicable diseases

The current epidemics of cardiovascular and metabolic noncommunicable diseases have emerged alongside dramatic modifications in lifestyle and living environments. These correspond to changes in our "modern" postwar societies globally characterized by rural-to-urban migration, modernization of agricultural practices, and transportation, climate change, and aging. Evidence suggests that these changes are related to each other, although the social and biological mechanisms as well as their interactions have yet to be uncovered. LongITools, as one of the 9 projects included in the European Human Exposome Network, will tackle this environmental health equation linking multidimensional environmental exposures to the occurrence of cardiovascular and metabolic noncommunicable diseases.

The European Genome-phenome Archive in 2021

The European Genome-phenome Archive (EGA - https://ega-archive.org/) is a resource for long term secure archiving of all types of potentially identifiable genetic, phenotypic, and clinical data resulting from biomedical research projects. Its mission is to foster hosted data reuse, enable reproducibility, and accelerate biomedical and translational research in line with the FAIR principles. Launched in 2008, the EGA has grown quickly, currently archiving over 4,500 studies from nearly one thousand institutions. The EGA operates a distributed data access model in which requests are made to the data controller, not to the EGA, therefore, the submitter keeps control on who has access to the data and under which conditions. Given the size and value of data hosted, the EGA is constantly improving its value chain, that is, how the EGA can contribute to enhancing the value of human health data by facilitating its submission, discovery, access, and distribution, as well as leading the design and implementation of standards and methods necessary to deliver the value chain. The EGA has become a key GA4GH Driver Project, leading multiple development efforts and implementing new standards and tools, and has been appointed as an ELIXIR Core Data Resource.

Biobanking and risk assessment: a comprehensive typology of risks for an adaptive risk governance

Biobanks act as the custodians for the access to and  responsible use of human biological samples and related data that have been generously donated by individuals to serve the public interest and scientific advances in the health research realm. Risk assessment has become a daily practice for biobanks and has been discussed from different perspectives. This paper aims to provide a literature review on risk assessment in order to put together a comprehensive typology of diverse risks biobanks could potentially face. Methodologically set as a typology, the conceptual approach used in this paper is based on the interdisciplinary analysis of scientific literature, the relevant ethical and legal instruments and practices in biobanking to identify how risks are assessed, considered and mitigated. Through an interdisciplinary mapping exercise, we have produced a typology of potential risks in biobanking, taking into consideration the perspectives of different stakeholders, such as institutional actors and publics, including participants and representative organizations. With this approach, we have identified the following risk types: economic, infrastructural, institutional, research community risks and participant's risks. The paper concludes by highlighting the necessity of an adaptive risk governance as an integral part of good governance in biobanking. In this regard, it contributes to sustainability in biobanking by assisting in the design of relevant risk management practices, where they are not already in place or require an update. The typology is intended to be useful from the early stages of establishing such a complex and multileveled biomedical infrastructure as well as to provide a catalogue of risks for improving the risk management practices already in place.

How Many Health Research Biobanks Are There?

Introduction: It is important for many research stakeholders to know how many biobanks exist. There are several potential data sources that might be expected to provide biobank numbers, such as institutions, research funders, and literature databases (e.g., PubMed), but in practice this information is rarely available and is hard to find. However, the maturation of several online health research biobank locators (also known as directories and catalogs) that relate to 12 countries and/or states has now provided some initial data to address the question of how many health research biobanks exist in relation to population size. Methods: We have analyzed four biobank locators: the Biobanking and Biomolecular Resources Research Infrastructure-European Research Infrastructure Consortium directory, the Canadian Tissue Repository Network locator, the Australian New South Wales Australia Health Pathology locator, and the UK Clinical Research Collaboration Tissue Directory. Results: We conclude that across these locators, and in those regions with potential for high research capacity as indicated by comparable gross domestic products, there are 11-30 health research biobanks/million population (2 large biobanks with >1000 samples and a further 9-28 are medium-small biobanks). Conclusion: Many locators were established primarily to increase utilization of biobanks. However, locators may be more useful in tracking the numbers of biobanks and in assisting funders and institutions to monitor research strategy and prevent unnecessary duplication of biobank resources.

The Dutch National TissueArchive Portal enables efficient, consistent, and transparent procurement of diagnostic tissue samples for scientific use

Biobanks play a crucial role in enabling biomedical research by facilitating scientific use of valuable human biomaterials. The PALGA foundation—a nationwide network and registry of histo- and cytopathology in the Netherlands—was established to promote the provision of data within and between pathology departments, and to make the resulting knowledge available for healthcare. Apart from the pathology data, we aimed to utilize PALGA’s nationwide network to find and access the rich wealth of Formalin-Fixed Paraffin-Embedded (FFPE) tissue samples for scientific use.  We implemented the Dutch National TissueArchive Portal (DNTP) to utilize PALGA’s nationwide network for requesting FFPE tissue samples. The DNTP consists of (1) a centrally organized internet portal to improve the assessing, processing, harmonization, and monitoring of the procurement process, while (2) dedicated HUB-employees provide practical support at peripheral pathology departments. Since incorporation of the DNTP, both the number of filed requests for FFPE tissue samples and the amount of HUB-mediated support increased 55 and 29% respectively. In line, the sample procurement duration time decreased significantly (− 47%). These findings indicate that implementation of the DNTP improved the frequency, efficiency, and transparency of FFPE tissue sample procurement for research in the Netherlands. To conclude, the need for biological resources is growing persistently to enable precision medicine. Here, we access PALGA’s national, pathology network by implementation of the DNTP to allow for efficient, consistent, and transparent exchange of FFPE tissue samples for research across the Netherlands.

Basic principles of biobanking: from biological samples to precision medicine for patients

The term "biobanking" is often misapplied to any collection of human biological materials (biospecimens) regardless of requirements related to ethical and legal issues or the standardization of different processes involved in tissue collection. A proper definition of biobanks is large collections of biospecimens linked to relevant personal and health information (health records, family history, lifestyle, genetic information) that are held predominantly for use in health and medical research. In addition, the International Organization for Standardization, in illustrating the requirements for biobanking (ISO 20387:2018), stresses the concept of biobanks being legal entities driving the process of acquisition and storage together with some or all of the activities related to collection, preparation, preservation, testing, analysing and distributing defined biological material as well as related information and data. In this review article, we aim to discuss the basic principles of biobanking, spanning from definitions to classification systems, standardization processes and documents, sustainability and ethical and legal requirements. We also deal with emerging specimens that are currently being generated and shaping the so-called next-generation biobanking, and we provide pragmatic examples of cancer-associated biobanking by discussing the process behind the construction of a biobank and the infrastructures supporting the implementation of biobanking in scientific research.

Data quality for federated medical data lakes

Purpose

Medical research requires biological material and data collected through biobanks in reliable processes with quality assurance. Medical studies based on data with unknown or questionable quality are useless or even dangerous, as evidenced by recent examples of withdrawn studies. Medical data sets consist of highly sensitive personal data, which has to be protected carefully and is available for research only after the approval of ethics committees. The purpose of this research is to propose an architecture to support researchers to efficiently and effectively identify relevant collections of material and data with documented quality for their research projects while observing strict privacy rules.

Design/methodology/approach

Following a design science approach, this paper develops a conceptual model for capturing and relating metadata of medical data in biobanks to support medical research.

Findings

This study describes the landscape of biobanks as federated medical data lakes such as the collections of samples and their annotations in the European federation of biobanks (Biobanking and Biomolecular Resources Research Infrastructure – European Research Infrastructure Consortium, BBMRI-ERIC) and develops a conceptual model capturing schema information with quality annotation. This paper discusses the quality dimensions for data sets for medical research in-depth and proposes representations of both the metadata and data quality documentation with the aim to support researchers to effectively and efficiently identify suitable data sets for medical studies.

Originality/value

This novel conceptual model for metadata for medical data lakes has a unique focus on the high privacy requirements of the data sets contained in medical data lakes and also stands out in the detailed representation of data quality and metadata quality of medical data sets.

BBMRI-ERIC Negotiator: Implementing Efficient Access to Biobanks

Various biological resources, such as biobanks and disease-specific registries, have become indispensable resources to better understand the epidemiology and biological mechanisms of disease and are fundamental for advancing medical research. Nevertheless, biobanks and similar resources still face significant challenges to become more findable and accessible by users on both national and global scales. One of the main challenges for users is to find relevant resources using cataloging and search services such as the BBMRI-ERIC Directory, operated by European Research Infrastructure on Biobanking and Biomolecular Resources (BBMRI-ERIC), as these often do not contain the information needed by the researchers to decide if the resource has relevant material/data; these resources are only weakly characterized. Hence, the researcher is typically left with too many resources to explore and investigate. In addition, resources often have complex procedures for accessing holdings, particularly for depletable biological materials. This article focuses on designing a system for effective negotiation of access to holdings, in which a researcher can approach many resources simultaneously, while giving each resource team the ability to implement their own mechanisms to check if the material/data are available and to decide if access should be provided. The BBMRI-ERIC has developed and implemented an access and negotiation tool called the BBMRI-ERIC Negotiator. The Negotiator enables access negotiation to more than 600 biobanks from the BBMRI-ERIC Directory and other discovery services such as GBA/BBMRI-ERIC Locator or RD-Connect Finder. This article summarizes the principles that guided the design of the tool, the terminology used and underlying data model, request workflows, authentication and authorization mechanism(s), and the mechanisms and monitoring processes to stimulate the desired behavior of the resources: to effectively deliver access to biological material and data.

The landscape of biobanks in Poland-characteristics of Polish biobanking units at the beginning of BBMRI.pl organization

Background

Biobanking is an area of scientific activity that is growing in strength and importance. The variety of collections combining biological samples and medical scientific information makes biobanking an indispensable tool in the development of modern medicine. In 2016, Poland, a country with one of the largest populations in Europe, joined the Biobanking and BioMolecular resources Research Infrastructure-European Research Infrastructure Consortium (BBMRI-ERIC) to facilitate access to quality-defined human disease-relevant biological resources. This push led to the development of the Polish Biobanking Network. The purpose of this paper is to present the current state of biobanks in Poland in the context of their location, nature and resources.

Methods

To obtain information about and overall characteristics of Polish entities dealing with biobanking biological material, the dedicated Information Survey was designed. The survey was prepared in an electronic form and consisted of 53 questions—both open and closed, single and multiple choice—with some questions depending on each other. Sixty-five Polish biobanks/biorepositories participated in the survey.

Results

Polish biobanks are mostly affiliated with research entities (universities—42% and research institutes—30%). The data collected indicate that a considerable number of Polish biobanks are specialized (33 units), in contrast to population-based biobanks (8 units). These biobanks are mostly focused on collecting samples from oncological (23 biobanks) and rare diseases (12 biobanks). In general, great diversity was found in the material collected. Scientists working in Polish biobanks are very open to scientific cooperation (declared by 60% of units) and sharing their collections with the international scientific environment. In terms of quality issues, most biobanks declared that their quality management system was in the process of implementation (45%) or had already been implemented (23%).

Conclusions

Although biobanking in Poland is still in its infancy, the results of this study seem promising and may be valuable to the wider biobanking research community. The distribution of biobanks throughout the Polish territory, their connection with scientific and clinical units, and their involvement in research on rare diseases may contribute to an increase in the number of multicenter studies.

DICOM-MIABIS integration model for biobanks: a use case of the EU PRIMAGE project

PRIMAGE is a European Commission-financed project dealing with medical imaging and artificial intelligence aiming to create an imaging biobank in oncology. The project includes a task dedicated to the interoperability between imaging and standard biobanks. We aim at linking Digital imaging and Communications in Medicine (DICOM) metadata to the Minimum Information About BIobank data Sharing (MIABIS) standard of biobanking. A very first integration model based on the fusion of the two existing standards, MIABIS and DICOM, has been developed. The fundamental method was that of expanding the MIABIS core to the imaging field, adding DICOM metadata derived from CT scans of 18 paediatric patients with neuroblastoma. The model was developed with the relational database management system Structured Query Language. The integration data model has been built as an Entity Relationship Diagram, commonly used to organise data within databases. Five additional entities have been linked to the “Image Collection” subcategory in order to include the imaging metadata more specific to the particular type of data: Body Part Examined, Modality Information, Dataset Type, Image Analysis, and Registration Parameters. The model is a starting point for the expansion of MIABIS with further DICOM metadata, enabling the inclusion of imaging data in biorepositories.

GenoPheno: cataloging large-scale phenotypic and next-generation sequencing data within human datasets

Precision medicine promises to revolutionize treatment, shifting therapeutic approaches from the classical one-size-fits-all to those more tailored to the patient's individual genomic profile, lifestyle and environmental exposures. Yet, to advance precision medicine's main objective-ensuring the optimum diagnosis, treatment and prognosis for each individual-investigators need access to large-scale clinical and genomic data repositories. Despite the vast proliferation of these datasets, locating and obtaining access to many remains a challenge. We sought to provide an overview of available patient-level datasets that contain both genotypic data, obtained by next-generation sequencing, and phenotypic data-and to create a dynamic, online catalog for consultation, contribution and revision by the research community. Datasets included in this review conform to six specific inclusion parameters that are: (i) contain data from more than 500 human subjects; (ii) contain both genotypic and phenotypic data from the same subjects; (iii) include whole genome sequencing or whole exome sequencing data; (iv) include at least 100 recorded phenotypic variables per subject; (v) accessible through a website or collaboration with investigators and (vi) make access information available in English. Using these criteria, we identified 30 datasets, reviewed them and provided results in the release version of a catalog, which is publicly available through a dynamic Web application and on GitHub. Users can review as well as contribute new datasets for inclusion (Web: https://avillachlab.shinyapps.io/genophenocatalog/; GitHub: https://github.com/hms-dbmi/GenoPheno-CatalogShiny).

Biobanking for Cancer Biomarker Research: Issues and Solutions

Biomarkers are critical tools that underpin precision medicine. However there has been slow progress and frequent failure of biomarker development. The root causes are multifactorial. Here, we focus on the need for fast, efficient, and reliable access to quality biospecimens as a critical area that impacts biomarker development. We discuss the past history of biobanking and the evolution of biobanking processes relevant to the specific area of cancer biomarker development as an example, and describe some solutions that can improve this area, thus potentially accelerating biomarker research.

Cardiovascular risk and metabolic profile of Polish citizens from Lower Silesia. First signs of metabolic crisis?

Introduction

Population biobanks are essential for the development of public health screening and improvement of personalized medicine. Since 2012, Biobank of Łukasiewicz Research Network - PORT Polish Center for Technology Development (PORT Biobank) has collected more than 120 000 biological samples from nearly 5000 inhabitants of Lower Silesia, together with a variety of demographic, anthropometric, life style and health information.

Material and methods

The analyzed group consisted of 2274 participants (1398 women, 876 men). Both women and men were further subdivided into five age decades (20+, 30+, 40+, 50+, 60+). For this study, the level of lipids (total cholesterol, high-density lipoprotein (HDL), low-density lipoprotein (LDL), triglycerides) was estimated and correlated with the level of high-sensitivity C-reactive protein (hs-CRP) and biometric parameters.

Results

We have demonstrated for the first time that biochemical changes that may lead to cardiovascular diseases (CVD) occurred already in the group of people aged 30+. Our observation is based on measurements of lipids, glucose, inflammatory (hs-CRP) and biometric markers such as body mass index (BMI) and waist-to-hip ratio (WHR).

Conclusions

Positive correlations with age for these variables suggest the ongoing progress of metabolic changes, which in the end may lead to a fatal outcome such as myocardial infarction or stroke. It suggests that CVD screening programs should be dedicated to a wider group, especially younger citizens, in order to prevent fatal outcomes related to CVD.

N-Glycome changes reflecting resistance to platinum-based chemotherapy in ovarian cancer

A number of studies have reported aberrant glycosylation in connection with malignancy. Our investigation further expands on this topic through the examination of N-glycans, which could be associated with the resistance of advanced stage, high-grade non-mucinous ovarian cancer to platinum/taxane based chemotherapy. We used tissue samples of 83 ovarian cancer patients, randomly divided into two independent cohorts (basic and validation). Both groups involved either cases with/without postoperative tumor residue or the cases determined either resistant or sensitive to this chemotherapy. In the validation cohort, preoperative serum samples were also available. N-glycans released from tumors and sera were permethylated and analyzed by matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS). The MS analysis yielded a consecutive detection of 68 (tissue) and 63 (serum) N-glycan spectral signals. Eight of these were found to be differentially abundant in tissues of both independent cohorts including the cases with a postoperative cancer residue. One of these glycans was detected as differentially abundant in sera of the validation cohort. No statistically significant differences in intensities due to the same N-glycans were found in the cases without postoperative macroscopic residues in either the basic or validation cohort. From the biochemical point of view, the statistically significant N-glycans correspond to the structures carrying bisecting (terminal) GlcNAc residue and tetra-antennary structures with sialic acid and/or fucose residues. Among them, six tissue N-glycans could be considered potential markers connected with a resistance to chemotherapy in ovarian cancer patients. The prediction of primary resistance to standard chemotherapy may identify the group of patients suitable for alternative treatment strategies. SIGNIFICANCE: Drug resistance has become a major impediment to a successful treatment of patients with advanced ovarian cancer. The glycomic measurements related to cancer are becoming increasingly popular in identification of the key molecules as potential diagnostic and prognostic indicators. Our report deals with identification of differences in N-glycosylation of proteins in tissue and serum samples from the individuals showing sensitivity or resistance to platinum/taxane-based chemotherapy. The detection sensitivity to chemotherapy is vitally important for these patients.

A Federated Online Search Tool for Biospecimens (Sample Locator): Usability Study

BACKGROUND

The German Biobank Alliance (GBA) aims to establish a cross-site biobank network. For this endeavor, the so-called Sample Locator, a federated search tool for biospecimens and related data, has been developed, forming the heart of its information technology (IT) infrastructure.

OBJECTIVE

To ensure the sustainable use of such a tool, we included researchers as participants in an end user-based usability evaluation.

METHODS

To develop a prototype ready for evaluation, we needed input from GBA IT experts. Thus, we conducted a 2-day workshop with 8 GBA IT team members. The focus was on the respective steps of a user-centered design process. With the acquired knowledge, the participants designed low-fidelity mock-ups. The main ideas of these mock-ups were discussed, extracted, and summarized into a comprehensive prototype using Microsoft PowerPoint. Furthermore, we created a questionnaire concerning the usability of the prototype, including the System Usability Scale (SUS), questions on negative and positive aspects, and typical tasks to be fulfilled with the tool. Subsequently, the prototype was pretested on the basis of this questionnaire with researchers who have a biobank background. Based on this preliminary work, the usability analysis was ultimately carried out with researchers and the results were evaluated.

RESULTS

Altogether, 27 researchers familiar with sample requests evaluated the prototype. The analysis of the feedback certified a good usability, given that the Sample Locator prototype was seen as intuitive and user-friendly by 74% (20/27) of the participants. The total SUS score by the 25 persons that completed the questionnaire was 80.4, indicating good system usability. Still, the evaluation provided useful advice on optimization potential (eg, offering a help function).

CONCLUSIONS

The findings of this usability analysis indicate that the considerations regarding a user-friendly application that have been made in the development process so far strongly coincide with the perception of the study participants. Nevertheless, it was important to engage prospective end users to ensure that the previous development is going in the desired direction and that the Sample Locator will be used in the future. The user comments and suggestions for improvement will be considered in upcoming iterations for refinement.

The LifeCycle Project-EU Child Cohort Network: a federated analysis infrastructure and harmonized data of more than 250,000 children and parents

Early life is an important window of opportunity to improve health across the full lifecycle. An accumulating body of evidence suggests that exposure to adverse stressors during early life leads to developmental adaptations, which subsequently affect disease risk in later life. Also, geographical, socio-economic, and ethnic differences are related to health inequalities from early life onwards. To address these important public health challenges, many European pregnancy and childhood cohorts have been established over the last 30 years. The enormous wealth of data of these cohorts has led to important new biological insights and important impact for health from early life onwards. The impact of these cohorts and their data could be further increased by combining data from different cohorts. Combining data will lead to the possibility of identifying smaller effect estimates, and the opportunity to better identify risk groups and risk factors leading to disease across the lifecycle across countries. Also, it enables research on better causal understanding and modelling of life course health trajectories. The EU Child Cohort Network, established by the Horizon2020-funded LifeCycle Project, brings together nineteen pregnancy and childhood cohorts, together including more than 250,000 children and their parents. A large set of variables has been harmonised and standardized across these cohorts. The harmonized data are kept within each institution and can be accessed by external researchers through a shared federated data analysis platform using the R-based platform DataSHIELD, which takes relevant national and international data regulations into account. The EU Child Cohort Network has an open character. All protocols for data harmonization and setting up the data analysis platform are available online. The EU Child Cohort Network creates great opportunities for researchers to use data from different cohorts, during and beyond the LifeCycle Project duration. It also provides a novel model for collaborative research in large research infrastructures with individual-level data. The LifeCycle Project will translate results from research using the EU Child Cohort Network into recommendations for targeted prevention strategies to improve health trajectories for current and future generations by optimizing their earliest phases of life.

Implementation of data access and use procedures in clinical data warehouses. A systematic review of literature and publicly available policies

BACKGROUND

The promises of improved health care and health research through data-intensive applications rely on a growing amount of health data. At the core of large-scale data integration efforts, clinical data warehouses (CDW) are also responsible for data governance, managing data access and (re)use. As the complexity of the data flow increases, greater transparency and standardization of criteria and procedures are required in order to maintain objective oversight and control. Therefore, the development of practice oriented and evidence-based policies is crucial. This study assessed the spectrum of data access and use criteria and procedures in clinical data warehouses governance internationally.

METHODS

We performed a systematic review of (a) the published scientific literature on CDW and (b) publicly available information on CDW data access, e.g., data access policies. A qualitative thematic analysis was applied to all included literature and policies.

RESULTS

Twenty-three scientific publications and one policy document were included in the final analysis. The qualitative analysis led to a final set of three main thematic categories: (1) requirements, including recipient requirements, reuse requirements, and formal requirements; (2) structures and processes, including review bodies and review values; and (3) access, including access limitations.

CONCLUSIONS

The description of data access and use governance in the scientific literature is characterized by a high level of heterogeneity and ambiguity. In practice, this might limit the effective data sharing needed to fulfil the high expectations of data-intensive approaches in medical research and health care. The lack of publicly available information on access policies conflicts with ethical requirements linked to principles of transparency and accountability. CDW should publicly disclose by whom and under which conditions data can be accessed, and provide designated governance structures and policies to increase transparency on data access. The results of this review may contribute to the development of practice-oriented minimal standards for the governance of data access, which could also result in a stronger harmonization, efficiency, and effectiveness of CDW.

Extending the Minimum Information About BIobank Data Sharing Terminology to Describe Samples, Sample Donors, and Events

Introduction: The Minimum Information About BIobank data Sharing (MIABIS) was initiated in 2012. MIABIS aims to create a common biobank terminology to facilitate data sharing in biobanks and sample collections. The MIABIS Core terminology consists of three components describing biobanks, sample collections, and studies, in which information on samples and sample donors is provided at aggregated form. However, there is also a need to describe samples and sample donors at an individual level to allow more elaborate queries on available biobank samples and data. Therefore the MIABIS terminology has now been extended with components describing samples and sample donors at an individual level. Materials and Methods: The components were defined according to specific scope and use cases by a large group of experts, and through several cycles of reviews, according to the new MIABIS governance model of BBMRI-ERIC (Biobanking and Biomolecular Resources Research Infrastructure-European Research Infrastructure Consortium). The guiding principles applied in developing these components included the following terms: model should consider only samples of human origin, model should be applicable to all types of samples and all sample donors, and model should describe the current status of samples stored in a given biobank. Results: A minimal set of standard attributes for defining samples and sample donors is presented here. We added an "event" component to describe attributes that are not directly describing samples or sample donors but are tightly related to them. To better utilize the generic data model, we suggest a procedure by which interoperability can be promoted, using specific MIABIS profiles. Discussion: The MIABIS sample and donor component extensions and the new generic data model complement the existing MIABIS Core 2.0 components, and substantially increase the potential usability of this terminology for better describing biobank samples and sample donors. They also support the use of individual level data about samples and sample donors to obtain accurate and detailed biobank availability queries.

Future-proofing biobanks' governance

Good biobank governance implies—at a minimum—transparency and accountability and the implementation of oversight mechanisms. While the biobanking community is in general committed to such principles, little is known about precisely which governance strategies biobanks adopt to meet those objectives. We conducted an exploratory analysis of governance mechanisms adopted by research biobanks, including genetic biobanks, located in Europe and Canada. We reviewed information available on the websites of 69 biobanks, and directly contacted them for additional information. Our study identified six types of commonly adopted governance strategies: communication, compliance, expert advice, external review, internal procedures, and partnerships. Each strategy is implemented through different mechanisms including, independent ethics assessment, informed consent processes, quality management, data access control, legal compliance, standard operating procedures and external certification. Such mechanisms rely on a wide range of bodies, committees and actors from both within and outside the biobanks themselves. We found that most biobanks aim to be transparent about their governance mechanisms, but could do more to provide more complete and detailed information about them. In particular, the retrievable information, while showing efforts to ensure biobanks operate in a legitimate way, does not specify in sufficient detail how governance mechanisms support accountability, nor how they ensure oversight of research operations. This state of affairs can potentially undermine biobanks’ trustworthiness to stakeholders and the public in a long-term perspective. Given the ever-increasing reliance of biomedical research on large biological repositories and their associated databases, we recommend that biobanks increase their efforts to future-proof their governance.

Standardization in biobanking – between cooperation and competition

This article presents the current situation of German biobanks and shows future fields of action in the European and international context on the basis of upcoming legal and normative challenges. It gives an overview of the development of the international biobank standard ISO 20387 and the commitment of German biobank experts in the ISO committee TC276. Less attention than the biobank standard per se has so far been paid to the basic mechanisms by which standards are developed and the potential of their application and accreditation. In this sense, this article deals with the motivation for active participation in standardization projects. We discuss the status of ISO 20387 as a conformity assessment standard and the consequence of accreditation as a performance monitor.

Inflammatory Bowel Disease (IBD)-A Textbook Case for Multi-Centric Banking of Human Biological Materials

Inflammatory bowel disease (IBD) is a chronic relapsing inflammatory condition affecting mainly the gastro-intestinal tract with two main entities: Crohn's disease (CD) and ulcerative colitis (UC). Although the exact mechanisms underlying the initial development of IBD are not fully understood, it is believed that an abnormal immune response is elicited against the intestinal microbiota in genetically predisposed individuals. Crucial elements of the etiopathogenesis have been elucidated by research using human biological materials. The estimated prevalence of IBD is 0.5% in the Western world. Although incidence rates are increasing, both conditions are not "common" in general terms mandating a multicentric approach. Biological material from numerous Belgian patients have been collected over time in a number of university hospitals in Belgium (UH Ghent: 800 CD patients, 350 UC patients, 600 normal controls; UH Leuven: 2,600 CD patients, 1,380 UC patients, 98 IC/IBDU patients, 6,260 normal controls). Within the setting of the Flemish Center Medical Innovation (CMI) initiative and later on the Flemish biobank network a prospective study was set-up across three Belgian IBD centers (University Hospitals Brussels, Ghent, and Leuven). Human biological materials and data have been collected prospectively from newly diagnosed CD and UC patients. The analyses hereof have generated new insights which have been published in the most renowned journals. The approach of well-thought off, multi-centric, structured, and systematic biobanking has proven to be a success-story and thus a textbook case for multi-centric banking of human biological materials. This story is being told in this article.

Leveraging European infrastructures to access 1 million human genomes by 2022

Human genomics is undergoing a step change from being a predominantly research-driven activity to one driven through health care as many countries in Europe now have nascent precision medicine programmes. To maximize the value of the genomic data generated, these data will need to be shared between institutions and across countries. In recognition of this challenge, 21 European countries recently signed a declaration to transnationally share data on at least 1 million human genomes by 2022. In this Roadmap, we identify the challenges of data sharing across borders and demonstrate that European research infrastructures are well-positioned to support the rapid implementation of widespread genomic data access.

Raising to the Challenge: Building a Federated Biobank to Accelerate Translational Research-The University Biobank Limburg

Irreproducibility of research results is one of the major contributing factors to the failure of translating basic research results into tangible bedside progress. To address this, the University Biobank Limburg (UBiLim) was founded by a collaboration between Hasselt University, the Hospital East-Limburg, and the Jessa Hospital. This paper describes the evolution of this process and the barriers encountered on the way. UBiLim evolved from an archival collection over a single-site biobank into a federated structure, supporting translational research at the founding institutions. Currently, UBiLim is a federated biobank, with an established organizational structure and processing, and storage facilities at each of the three sites. All activities are integrated in an ISO15189-accredited Quality Management System and based on (inter)national biobank guidelines. Common methods for processing and storage of a plethora of sample types, suitable for state-of-the-art applications, were validated and implemented. Because the biobank is embedded in two hospitals, the request of researchers to include certain sample types or enroll specific patient groups can quickly be met. Funding has been a major challenge in each step of its evolution and remains the biggest issue for long-term biobank sustainability. To a lesser extent, the Belgian legislation and the operational cost of information management system are also concerns for smooth biobank operations. Nonetheless, UBiLim serves as a facilitator and accelerator for translational research in the Limburg area of Belgium that, given the fields of research, may have an impact on international patient care.

Performance of Finnish biobanks in nationwide pulmonary carcinoid tumour research

Finnish hospital-integrated biobanks administer millions of formalin-fixed paraffin-embedded tissue samples collected within the clinical diagnostics. According to the Finnish Biobank Act, these samples can be coupled with patients' clinical follow-up data and the data retrieved from national health registries. We collected a nationwide pulmonary carcinoid tumour series from Finnish biobanks to study prognostic factors as well as to explore how the number of tumours found in the Finnish biobanks corresponds to the number of tumours registered by the Finnish Cancer Registry (FCR). Finnish biobanks identified 88% of the tumours registered by the FCR and were able to deliver 63%. The main reasons for lacking samples were paucity of resected primary tumour tissue, incompatible primary diagnosis, and the absence of tissue blocks in the archives. The main bottleneck in the sample application process was retrieving patient data. Altogether, we received 224 tumour samples with appropriate patient data and identified six prognostic factors for shorter disease-specific survival: age over 56 years at the time of diagnosis, tumour size over 2.5 cm, atypical histology, Ki-67 proliferation index higher than 2.5%, hilar/mediastinal lymph node involvement at the time of diagnosis, and the presence of metastatic disease. In conclusion, the Finnish biobank infrastructure offers excellent opportunities for tissue-based research. However, to be able to develop the biobank operations further, involving more medical knowledge in the sample and data acquisition process is a necessity. Also, when working with tissue samples collected over decades, histological expertise is essential for re-evaluation and re-classification of the samples.

Biomolecular Data Resources: Bioinformatics Infrastructure for Biomedical Data Science

Technological advances have continuously driven the generation of bio-molecular data and the development of bioinformatics infrastructure, which enables data reuse for scientific discovery. Several types of data management resources have arisen, such as data deposition databases, added-value databases or knowledgebases, and biology-driven portals. In this review, we provide a unique overview of the gradual evolution of these resources and discuss the goals and features that must be considered in their development. With the increasing application of genomics in the health care context and with 60 to 500 million whole genomes estimated to be sequenced by 2022, biomedical research infrastructure is transforming, too. Systems for federated access, portable tools, provision of reference data, and interpretation tools will enable researchers to derive maximal benefits from these data. Collaboration, coordination, and sustainability of data resources are key to ensure that biomedical knowledge management can scale with technology shifts and growing data volumes.

The 1000IBD project: multi-omics data of 1000 inflammatory bowel disease patients; data release 1

BACKGROUND

Inflammatory bowel disease (IBD) is a chronic complex disease of the gastrointestinal tract. Patients with IBD can experience a wide range of symptoms, but the pathophysiological mechanisms that cause these individual differences in clinical presentation remain largely unknown. In consequence, IBD is currently classified into subtypes using clinical characteristics. If we are to develop a more targeted treatment approach, molecular subtypes of IBD need to be discovered that can be used as new drug targets. To achieve this, we need multiple layers of molecular data generated from the same IBD patients.

CONSTRUCTION AND CONTENT

We initiated the 1000IBD project ( https://1000ibd.org ) to prospectively follow more than 1000 IBD patients from the Northern provinces of the Netherlands. For these patients, we have collected a uniquely large number of phenotypes and generated multi-omics profiles. To date, 1215 participants have been enrolled in the project and enrolment is on-going. Phenotype data collected for these participants includes information on dietary and environmental factors, drug responses and adverse drug events. Genome information has been generated using genotyping (ImmunoChip, Global Screening Array and HumanExomeChip) and sequencing (whole exome sequencing and targeted resequencing of IBD susceptibility loci), transcriptome information generated using RNA-sequencing of intestinal biopsies and microbiome information generated using both sequencing of the 16S rRNA gene and whole genome shotgun metagenomic sequencing.

UTILITY AND DISCUSSION

All molecular data generated within the 1000IBD project will be shared on the European Genome-Phenome Archive ( https://ega-archive.org , accession no: EGAS00001002702). The first data release, detailed in this announcement and released simultaneously with this publication, will contain basic phenotypes for 1215 participants, genotypes of 314 participants and gut microbiome data from stool samples (315 participants) and biopsies (107 participants) generated by tag sequencing the 16S gene. Future releases will comprise many more additional phenotypes and -omics data layers. 1000IBD data can be used by other researchers as a replication cohort, a dataset to test new software tools, or a dataset for applying new statistical models.

CONCLUSIONS

We report on the establishment and future development of the 1000IBD project: the first comprehensive multi-omics dataset aimed at discovering IBD biomarker profiles and treatment targets.

BioSCOOP - Biobank Sample Communication Protocol. New approach for the transfer of information between biobanks

Dynamic development of biobanking industry (both business and science) resulted in an increased number of IT systems for samples and data management. The most difficult and complicated case for the biobanking community was cooperation between institutions, equipped with different IT systems, in the field of scientific research, mainly data interchange and information flow. Tools available on the market relate mainly to the biobank or collection level. Efficient and universal protocols including the detailed information about the donor and the sample are still very limited. Here, we have developed BioSCOOP, a communication protocol in the form of a well documented JSON API. The main aim of this study was to harmonize and standardize the rules of communication between biobanks on the level of information about the donor together with information about the sample. The purpose was to create a communication protocol for two applications: to transfer the information between different biobanks and to allow the searching and presentation of the sample and data sets.

Current practices for access, compensation, and prioritization in biobanks. Results from an interview study

Human biological materials and related data stored in biobanks are valuable resources for biomedical research. Transparent, effective, and efficient governance structures and procedures for access, compensation, and priority setting are needed, but recent debates indicate challenges in the practical application of such governance processes. This study aimed to assess the practical experiences and attitudes of biobank experts regarding the governance of biosample access, prioritization, and compensation. Qualitative, semi-structured telephone interviews were conducted with 20 biobank directors from eight countries. Respondents highlighted the need for sound governance structures in order to ensure acceptance by all stakeholders (patients/donors, researchers, research funders, public, and others). They stressed practical difficulties in trying to make best use of biomaterials. As biobanks often form part of larger academic and clinical settings, the different and sometimes conflicting interests of researchers, clinicians, patients, funders, and biobank staff currently affect the governance of access decisions. Investments such as intellectual input, financial, and human resources need to be compensated adequately. Biobanks thereby have a dual role stewarding the hosted biosamples and acting as a service provider for local researchers from universities or hospitals. In order to facilitate efficient use of human biological materials, greater harmonization of at least minimum standards for access and compensation are required at both a national and an international level.

The FAIR guiding principles for data stewardship: fair enough?

The FAIR guiding principles for research data stewardship (findability, accessibility, interoperability, and reusability) look set to become a cornerstone of research in the life sciences. A critical appraisal of these principles in light of ongoing discussions and developments about data sharing is in order. The FAIR principles point the way forward for facilitating data sharing more systematically-provided that a number of ethical, methodological, and organisational challenges are addressed as well.

Biobanks and scientists: supply and demand

The biobanks, providers of biospecimens, and the scientists, users of biological material, are both strategic actors in translational medicine but the communication about those two subjects seems to be delicate. Recently, biobank managers from US and Europe stressed the danger of underuse of biospecimens stored in their biobanks thus stimulating the debate about innovative ways to collect samples and to communicate their availability. We hypothesize that the already stored collections meet the interest of present scientists only in specific situations. Serial biospecimens from patients with large associated clinical data concerning voluptuary habits, environmental exposure, anthropomorphic information are needed to meet the even more specific projects the scientists are planning. The hypothesis of activation of specific sections in ranked journals aimed to facilitate the communication between partners interested in finding/collecting ad hoc biospecimens is discussed.

Launch of an Infrastructure for Health Research: BBMRI-ERIC

Biobanking and BioMolecular resources Research Infrastructure (BBMRI)- European Research Infrastructure Consortium (ERIC) is the largest infrastructure launched in Europe in health research. By nature it is a distributed infrastructure, in which biological samples and data are hosted by the European Member States biobanks. As of today, BBMRI-ERIC consists of 19 European Member States and 1 international organization, the International Agency for Research on Cancer. This means that BBMRI-ERIC has a population of >500 million individuals in Europe. BBMRI-ERIC is a truly Pan-European Research Infrastructure for health research. Given that BBMRI-ERIC is set up to become a key source for users in both academic and scientific institutions as well as in the pharmaceutical and life science industries, it contributes directly to the Innovation Union concept. It is pan-European because BBMRI-ERIC already shows an excellent geographic and regional coverage all over Europe involving countries from South, East, West, North, and Central Europe. BBMRI-ERIC is a service-driven infrastructure for the European Member States, driven by science. The BBMRI-ERIC Directory consists of 100 million samples and a roadmap for better-defined quality in European biobanks for improving reproducibility and reliability of the biological sample and data.