The Information Technology (IT) Infrastructure of the Multicenter Archipelago of Ovarian Cancer Research Biobank: A Potential Blueprint for Other Biobanks

Objective: Biobanks play a crucial role in fundamental and translational research by storing valuable biomaterials and data for future analyses. However, the design of their information technology (IT) infrastructures is often customized to specific requirements, thereby lacking the ability to be used for biobanks comprising other (types of) diseases. This results in substantial costs, time, and efforts for each new biobank project. The Dutch multicenter Archipelago of Ovarian Cancer Research (AOCR) biobank has developed an innovative, reusable IT infrastructure capable of adaptation to various biobanks, thereby enabling cost-effective and efficient implementation and management of biobank IT systems. Methods and Results: The AOCR IT infrastructure incorporates preexisting biobank software, mainly managed by Health-RI. The web-based registration tool Ldot is used for secure storage and pseudonymization of patient data. Clinicopathological data are retrieved from the Netherlands Cancer Registry and the Dutch nationwide pathology databank (Palga), both established repositories, reducing administrative workload and ensuring high data quality. Metadata of collected biomaterials are stored in the OpenSpecimen system. For digital pathology research, a hematoxylin and eosin-stained slide from each patient's tumor is digitized and uploaded to Slide Score. Furthermore, adhering to the Findable, Accessible, Interoperable, and Reusable (FAIR) principles, genomic data derived from the AOCR samples are stored in cBioPortal. Conclusion: The IT infrastructure of the AOCR biobank represents a new standard for biobanks, offering flexibility to handle diverse diseases and types of biomaterials. This infrastructure bypasses the need for disease-specific, custom-built software, thereby being cost- and time-effective while ensuring data quality and legislative compliance. The adaptability of this infrastructure highlights its potential to serve as a blueprint for the development of IT infrastructures in both new and existing biobanks.

Biobanking for Neurodegenerative Diseases: Challenge for Translational Research and Data Privacy

Biobanking has emerged as a strategic challenge to promote knowledge on neurological diseases, by the application of translational research. Due to the inaccessibility of the central nervous system, the advent of biobanks, as structure collecting biospecimens and associated data, are essential to turn experimental results into clinical practice. Findings from basic research, omics sciences, and in silico studies, definitely require validation in clinically well-defined cohorts of patients, even more valuable when longitudinal, or including preclinical and asymptomatic individuals. Finally, collecting biological samples requires a great effort to guarantee respect for transparency and protection of sensitive data of patients and donors. Since the European General Data Protection Regulation 2016/679 has been approved, concerns about the use of data in biomedical research have emerged. In this narrative review, we focus on the essential role of biobanking for translational research on neurodegenerative diseases. Moreover, we address considerations for biological samples and data collection, the importance of standardization in the preanalytical phase, data protection (ethical and legal) and the role of donors in improving research in this field.

Risk management in biobanking

Risk management is a key aspect of the organization and management of biobanks, which is part of the overall quality management system aimed at early detection, analysis and minimization of events, that can lead to negative consequences for the biobank, as well as affect the quality of biosamples and related data. The article presents the biobanking risk classification with the description of each category.

Aim. To develop and implement the methodology for identification, analysis, evaluation and development of risk management measures for the biobanking process in the biobank of the National Medical Research Center for Therapy and Preventive Medicine.

Material and methods. We present the methodology of the risk management process developed on the basis of the literary data, world experience and experience of the biobank of the National Medical Research Center for Therapy and Preventive Medicine.

Results. The biobanking risk management procedure was developed and implemented in the biobank of the National Medical Research Center for Therapy and Preventive Medicine in 2020. The work carried out made it possible to identify, analyze and evaluate a wide range of potential negative events and actions that could lead to biobank damage, both in the form of financial losses and ethical and technical issues related to the biobanking process. A significant reduction in the frequency of emergency events and the high stability of the biobank operation under the influence of various external factors prove the effectiveness of the approach used.

Conclusion. The creation and maintenance of a risk management system in the biobank allows, in combination with other measures, to ensure the safety and high quality of the procedures for collecting, processing and long-term storage of biomaterial and related data by creating an environment that rules out or minimizes the impact of various risks.

Willingness to Donate Remnant Human Biospecimens in the Context of the COVID-19 Pandemic

Background: Studies using biospecimens can help reveal pathogenic mechanisms and improve prevention, diagnosis, and treatment of diseases. However, there is still a lack of relevant investigation data, which can provide initial evidence for establishing or improving relevant laws and regulations, on people's willingness to donate biospecimens, and whether they agree to waive the right of obtaining informed consent in the special period of sudden outbreak of new infectious diseases. Objectives: To investigate people's willingness to donate their remnant biospecimens of clinical tests for research in the context of the COVID-19 pandemic and their willingness to sign the informed consent for research using their biospecimens. Methods: We conducted a survey using an online questionnaire, which included questions on basic personal information, COVID-19-related information, donation of remnant biospecimens, willingness to sign informed consent, and reasons to do so. Results: Among the 721 valid responses, 620 respondents (86.0%) reported that they would be willing to donate their remnant biospecimens for research, of whom 434 (70.0%) reported that they would donate their remnant biospecimens without signing the informed consent. Of the 11 specified influencing factors, occupation, household income, and degree of concern about the COVID-19 pandemic were associated with willingness to donate remnant biospecimens. Gender and age were associated with willingness to donate remnant biospecimens without signing the informed consent. The main reasons for unwillingness to donate remnant biospecimens and sign the informed consent were a limited knowledge of research and privacy concerns. Conclusions: Most respondents reported that they would be willing to donate their remnant biospecimens for biomedical research without signing an informed consent in the context of the COVID-19 pandemic. Lack of understanding of the proposed research and concerns about personal privacy were the main reasons for unwillingness to donate biospecimens and signing the informed consent.

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.

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.

Pseudonymization for research data collection: is the juice worth the squeeze?

BACKGROUND

The collection of data and biospecimens which characterize patients and probands in-depth is a core element of modern biomedical research. Relevant data must be considered highly sensitive and it needs to be protected from unauthorized use and re-identification. In this context, laws, regulations, guidelines and best-practices often recommend or mandate pseudonymization, which means that directly identifying data of subjects (e.g. names and addresses) is stored separately from data which is primarily needed for scientific analyses.

DISCUSSION

When (authorized) re-identification of subjects is not an exceptional but a common procedure, e.g. due to longitudinal data collection, implementing pseudonymization can significantly increase the complexity of software solutions. For example, data stored in distributed databases, need to be dynamically combined with each other, which requires additional interfaces for communicating between the various subsystems. This increased complexity may lead to new attack vectors for intruders. Obviously, this is in contrast to the objective of improving data protection. What is lacking is a standardized process of evaluating and reporting risks, threats and countermeasures, which can be used to test whether integrating pseudonymization methods into data collection systems actually improves upon the degree of protection provided by system designs that simply follow common IT security best practices and implement fine-grained role-based access control models. To demonstrate that the methods used to describe systems employing pseudonymized data management are currently heterogeneous and ad-hoc, we examined the extent to which twelve recent studies address each of the six basic security properties defined by the International Organization for Standardization (ISO) standard 27,000. We show inconsistencies across the studies, with most of them failing to mention one or more security properties.

CONCLUSION

We discuss the degree of privacy protection provided by implementing pseudonymization into research data collection processes. We conclude that (1) more research is needed on the interplay of pseudonymity, information security and data protection, (2) problem-specific guidelines for evaluating and reporting risks, threats and countermeasures should be developed and that (3) future work on pseudonymized research data collection should include the results of such structured and integrated analyses.

Enhancing Reuse of Data and Biological Material in Medical Research: From FAIR to FAIR-Health

The known challenge of underutilization of data and biological material from biorepositories as potential resources for medical research has been the focus of discussion for over a decade. Recently developed guidelines for improved data availability and reusability-entitled FAIR Principles (Findability, Accessibility, Interoperability, and Reusability)-are likely to address only parts of the problem. In this article, we argue that biological material and data should be viewed as a unified resource. This approach would facilitate access to complete provenance information, which is a prerequisite for reproducibility and meaningful integration of the data. A unified view also allows for optimization of long-term storage strategies, as demonstrated in the case of biobanks. We propose an extension of the FAIR Principles to include the following additional components: (1) quality aspects related to research reproducibility and meaningful reuse of the data, (2) incentives to stimulate effective enrichment of data sets and biological material collections and its reuse on all levels, and (3) privacy-respecting approaches for working with the human material and data. These FAIR-Health principles should then be applied to both the biological material and data. We also propose the development of common guidelines for cloud architectures, due to the unprecedented growth of volume and breadth of medical data generation, as well as the associated need to process the data efficiently.

A Scalable and Pragmatic Method for the Safe Sharing of High-Quality Health Data

The sharing of sensitive personal health data is an important aspect of biomedical research. Methods of data de-identification are often used in this process to trade the granularity of data off against privacy risks. However, traditional approaches, such as HIPAA safe harbor or -anonymization, often fail to provide data with sufficient quality. Alternatively, data can be de-identified only to a degree which still allows us to use it as required, e.g., to carry out specific analyses. Controlled environments, which restrict the ways recipients can interact with the data, can then be used to cope with residual risks. The contributions of this article are twofold. First, we present a method for implementing controlled data sharing environments and analyze its privacy properties. Second, we present a de-identification method which is specifically suited for sanitizing health data which is to be shared in such environments. Traditional de-identification methods control the uniqueness of records in a dataset. The basic idea of our approach is to reduce the probability that a record in a dataset has characteristics which are unique within the underlying population. As the characteristics of the population are typically not known, we have implemented a pragmatic solution in which properties of the population are modeled with statistical methods. We have further developed an accompanying process for evaluating and validating the degree of protection provided. The results of an extensive experimental evaluation show that our approach enables the safe sharing of high-quality data and that it is highly scalable.

Towards biobank privacy regimes in responsible innovation societies: ESBB conference in Granada 2012

The creation of socially and technically robust biobank privacy regimes presupposes knowledge of and compliance with legal rules, professional standards of the biomedical community, and state-of-the-art data safety and security measures. The strategies in privacy management and data protection presented in this review show a trend that goes beyond searching for compromises or efforts of balancing scientific demands for efficiency and societal demands for effective privacy regimes. They focus on developing synergies that facilitate cooperative use of biomaterials and data and enhance sample search efficiency for researchers on the one hand, and protect rights and interests of donors and citizens on the other hand. Among the issues covered are: a) ethical sensitivities and public perceptions on privacy in biobanking b) tools and procedures that allow maintenance of the rights and dignity of donors, without jeopardizing legitimate information needs of researchers and autonomy of biobanks, and c) a privacy sensitive framework for sharing of data and biomaterials in the research context.

Secure Secondary Use of Clinical Data with Cloud-based NLP Services. Towards a Highly Scalable Research Infrastructure

OBJECTIVES

The secondary use of clinical data provides large opportunities for clinical and translational research as well as quality assurance projects. For such purposes, it is necessary to provide a flexible and scalable infrastructure that is compliant with privacy requirements. The major goals of the cloud4health project are to define such an architecture, to implement a technical prototype that fulfills these requirements and to evaluate it with three use cases.

METHODS

The architecture provides components for multiple data provider sites such as hospitals to extract free text as well as structured data from local sources and de-identify such data for further anonymous or pseudonymous processing. Free text documentation is analyzed and transformed into structured information by text-mining services, which are provided within a cloud-computing environment. Thus, newly gained annotations can be integrated along with the already available structured data items and the resulting data sets can be uploaded to a central study portal for further analysis.

RESULTS

Based on the architecture design, a prototype has been implemented and is under evaluation in three clinical use cases. Data from several hundred patients provided by a University Hospital and a private hospital chain have already been processed.

CONCLUSIONS

Cloud4health has shown how existing components for secondary use of structured data can be complemented with text-mining in a privacy compliant manner. The cloud-computing paradigm allows a flexible and dynamically adaptable service provision that facilitates the adoption of services by data providers without own investments in respective hardware resources and software tools.

Testing an online, dynamic consent portal for large population biobank research

BACKGROUND

Michigan's BioTrust for Health, a public health research biobank comprised of residual dried bloodspot (DBS) cards from newborn screening contains over 4 million samples collected without written consent. Participant-centric initiatives are IT tools that hold great promise to address the consent challenges in biobank research.

METHODS

Working with Private Access Inc., a pioneer in patient-centric web solutions, we created and pilot tested a dynamic informed consent simulation, paired with an educational website, focusing on consent for research utilizing DBSs in Michigan's BioTrust for Health.

RESULTS

Out of 187 pilot testers recruited in 2 groups, 137 completed the consent simulation and exit survey. Over 50% indicated their willingness to set up an account if the simulation went live and to recommend it to others. Participants raised concerns about the process of identity verification and appeared to have little experience with sharing health information online.

CONCLUSIONS

Applying online, dynamic approaches to address the consent challenges raised by biobanks with legacy sample collections should be explored, given the positive reaction to our pilot test and the strong preference for active consent. Balancing security and privacy with accessibility and ease of use will continue to be a challenge.

How to build an integrated biobank: the Washington University Translational Cardiovascular Biobank & Repository experience

Translational studies that assess and extend observations made in animal models of human pathology to elucidate relevant and important determinants of human diseases require the availability of viable human tissue samples. However, there are a number of technical and practical obstacles that must be overcome in order to perform cellular and electrophysiological studies of the human heart. In addition, changing paradigms of how diseases are diagnosed, studied and treated require increasingly complex integration of rigorous disease phenotyping, tissue characterization and detailed delineation of a multitude of "_omics". Realizing the need for quality-controlled human cardiovascular tissue acquisition, annotation, biobanking and distribution, we established the Translational Cardiovascular Biobank & Repository at Washington University School of Medicine. Several critical details are essential for the success of cardiovascular biobanking including coordinated, trained and dedicated staff members; adequate, nonrestrictive informed consent protocols; and fully integrated clinical data management applications for annotating, tracking and sharing of tissue and data resources. Labor and capital investments into growing biobanking resources will facilitate collaborative efforts aimed at limiting morbidity and mortality due to heart disease and improving overall cardiovascular health.