Oversight of Genomic Data Sharing: What Roles for Ethics and Data Access Committees?

Specific measures for data-intensive health research without consent: a systematic review of soft law instruments and academic literature

It is a common misunderstanding of current European data protection law that when consent is not being used as lawful basis, the processing of personal data is prohibited. Article 9(2)(j) of the European General Data Protection Regulation (GDPR) permits Member States to establish a legal basis in national law that allows for the processing of personal data for scientific research purposes without consent. However, the European legislator has formulated this "research exemption" as an opening clause, rendering the GDPR not specific as to what measures exactly are required to comply with the research exemption. This may have significant implications for both the protection of personal data and the advancement of data-intensive health research. We performed a systematic review of relevant soft law instruments and academic literature to identify what measures are mentioned in those documents. Our analysis resulted in the identification of four overarching themes of suggested measures: organizational measures; technical measures; oversight and review mechanisms; and public engagement and participation. Some of the suggested measures do not substantially contribute to the clarification of the GDPR's "suitable and specific measures" requirement because they remain vague or broad in nature and encompass all types of data processing. However, the themes oversight and review mechanisms and public engagement and participation provide valuable insights which can be put to practice. Nevertheless, further clarification of the measures and safeguards that should be installed when invoking the research exemption remains necessary.

Artificial intelligence and medical research databases: ethical review by data access committees

BACKGROUND

It has been argued that ethics review committees-e.g., Research Ethics Committees, Institutional Review Boards, etc.- have weaknesses in reviewing big data and artificial intelligence research. For instance, they may, due to the novelty of the area, lack the relevant expertise for judging collective risks and benefits of such research, or they may exempt it from review in instances involving de-identified data.

MAIN BODY

Focusing on the example of medical research databases we highlight here ethical issues around de-identified data sharing which motivate the need for review where oversight by ethics committees is weak. Though some argue for ethics committee reform to overcome these weaknesses, it is unclear whether or when that will happen. Hence, we argue that ethical review can be done by data access committees, since they have de facto purview of big data and artificial intelligence projects, relevant technical expertise and governance knowledge, and already take on some functions of ethical review. That said, like ethics committees, they may have functional weaknesses in their review capabilities. To strengthen that function, data access committees must think clearly about the kinds of ethical expertise, both professional and lay, that they draw upon to support their work.

CONCLUSION

Data access committees can undertake ethical review of medical research databases provided they enhance that review function through professional and lay ethical expertise.

Dynamic consent, communication and return of results in large-scale health data reuse: Survey of public preferences

Dynamic consent forms a comprehensive, tailored approach for interacting with research participants. We conducted a survey study to inquire how research participants evaluate the elements of consent, information provision, communication and return of results within dynamic consent in a hypothetical health data reuse scenario. We distributed a digital questionnaire among a purposive sample of patient panel members. Data were analysed using descriptive and nonparametric inferential statistics. Respondents favoured the potential to manage changing consent preferences over time. There was much agreement between people favouring closer and more specific control over data reuse approval and those in favour of broader approval, facilitated by an opt-out system or an independent data reuse committee. People want to receive more information about reuse, outcomes and return of results. Respondents supported an interactive model of research participation, welcoming regular, diverse and interactive forms of communication, like a digital communication platform. Approval for reuse and providing meaningful information, including meaningful return of results, are intricately related to facilitating better communication. Respondents favoured return of actionable research results. These findings emphasize the potential of dynamic consent for enabling participants to maintain control over how their data are being used for which purposes by whom. Allowing different options to shape a dynamic consent interface in health data reuse in a personalized manner is pivotal to accommodate plurality in a flexible though robust manner. Interaction via dynamic consent enables participants to tailor the elements of participation they deem relevant to their own preferences, engaging diverse perspectives, interests and preferences.

Access to Biobanks: Responsibilities Within a Research Ecosystem

The past few decades have seen rapid increases in the size and scope of biobanks, with large-scale publicly funded ventures supporting health-related research becoming the norm. As these biobanks are increasingly asked to share their data, including for example, genome-wide analyses, questions arise about how such decisions are made, including whether applicants' research aligns with the aims of the biobank. To better understand how biobanks make decisions relating to their data use, we sought the views and experiences of those involved in decision-making relating to data access at 11 large-scale publicly funded health biobanks. We were particularly interested in how potentially contentious applications were approached. Interviewees had some concerns about decisions on applications they felt their governance structures could not reach. We ask broader questions about the responsibility of those involved in biobank access decisions-those working early in the research process-when considering such issues.

Leveraging Algorithms to Improve Decision-Making Workflows for Genomic Data Access and Management

Studies on the ethics of automating clinical or research decision making using artificial intelligence and other algorithmic tools abound. Less attention has been paid, however, to the scope for, and ethics of, automating decision making within regulatory apparatuses governing the access, use, and exchange of data involving humans for research. In this article, we map how the binary logic flows and real-time capabilities of automated decision support (ADS) systems may be leveraged to accelerate one rate-limiting step in scientific discovery: data access management. We contend that improved auditability, consistency, and efficiency of the data access request process using ADS systems have the potential to yield fairer outcomes in requests for data largely sourced from biospecimens and biobanked samples. This procedural justice rationale reinforces a broader set of participant and data subject rights that data access committees (DACs) indirectly protect. DACs protect the rights of citizens to benefit from science by bringing researchers closer to the data they need to advance that science. DACs also protect the informational dignities of individuals and communities by ensuring the data being accessed are used in ways consistent with participant values. We discuss the development of the Global Alliance for Genomics and Health Data Use Ontology standard as a test case of ADS for genomic data access management specifically, and we synthesize relevant ethical, legal, and social challenges to its implementation in practice. We conclude with an agenda of future research needed to thoughtfully advance strategies for computational governance that endeavor to instill public trust in, and maximize the scientific value of, health-related human data across data types, environments, and user communities.

Governance of Access in Biobanking: The Case of Telethon Network of Genetic Biobanks

The discussion concerning the measure of the quality of a biobank should focus not only on the number of stored samples and their quality but also on the assessment of their access arrangements and governance. This article aims at contributing to the ongoing debate on samples and data access governance in biobanking by presenting the case of the Telethon Network of Genetic Biobanks (TNGB). We attempt to contribute to the need for clear and available access criteria and harmonization in access arrangements to maximize the influence of biobanks in the progress of biomedical research. We reviewed all the sample requests submitted to the TNGB from 2008 to 2020, focusing on those rejected by the Access Committee and the reasons behind the rejections. The analysis of the reasons behind the rejected requests allowed us to analyze how those relate to the issues of scientific misconduct, prioritization, and noncompliance with the biobank's mission. We discuss those issues in light of the actions and motivations used by TNGB in the access decision-making process. Based on this analysis, we suggest that a cross-implementation of a checklist for access assessment would improve the whole access process, ensuring a more transparent and smoother governance. Finally, we conclude that the TNGB's Charter and approach toward access governance could contribute as an important reference point to deal with the issues that have emerged in the international discussion on the topic.

The social licence for data-intensive health research: towards co-creation, public value and trust

Background

The rise of Big Data-driven health research challenges the assumed contribution of medical research to the public good, raising questions about whether the status of such research as a common good should be taken for granted, and how public trust can be preserved. Scandals arising out of sharing data during medical research have pointed out that going beyond the requirements of law may be necessary for sustaining trust in data-intensive health research. We propose building upon the use of a social licence for achieving such ethical governance.

Main text

We performed a narrative review of the social licence as presented in the biomedical literature. We used a systematic search and selection process, followed by a critical conceptual analysis. The systematic search resulted in nine publications. Our conceptual analysis aims to clarify how societal permission can be granted to health research projects which rely upon the reuse and/or linkage of health data. These activities may be morally demanding. For these types of activities, a moral legitimation, beyond the limits of law, may need to be sought in order to preserve trust. Our analysis indicates that a social licence encourages us to recognise a broad range of stakeholder interests and perspectives in data-intensive health research. This is especially true for patients contributing data. Incorporating such a practice paves the way towards an ethical governance, based upon trust. Public engagement that involves patients from the start is called for to strengthen this social licence.

Conclusions

There are several merits to using the concept of social licence as a guideline for ethical governance. Firstly, it fits the novel scale of data-related risks; secondly, it focuses attention on trustworthiness; and finally, it offers co-creation as a way forward. Greater trust can be achieved in the governance of data-intensive health research by highlighting strategic dialogue with both patients contributing the data, and the public in general. This should ultimately contribute to a more ethical practice of governance.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12910-021-00677-5.

A policy Delphi study to validate the key implications of data sharing (KIDS) framework for pediatric genomics in Canada

BACKGROUND

The highly sensitive nature of genomic and associated clinical data, coupled with the consent-related vulnerabilities of children together accentuate ethical, legal and social issues (ELSI) concerning data sharing. The Key Implications of Data Sharing (KIDS) framework was therefore developed to address a need for institutional guidance on genomic data governance but has yet to be validated among data sharing practitioners in practice settings. This study qualitatively explored areas of consensus and dissensus of the KIDS Framework from the perspectives of Canadian clinician-scientists, genomic researchers, IRB members, and pediatric ethicists.

METHODS

Twelve panelists participated in a three-round online policy Delphi to determine the desirability, feasibility, relative importance and confidence of twelve individual statements of the KIDS Framework. Mean and IQR were calculated from panelists' ratings to determine the strength of consensus and polarity. Qualitative content analysis of panelists' written responses was used to assess degree of support. Statements were validated when their combined ratings and qualitative rationales indicated high-moderate consensus (at least 70% agreement across two contiguous categories), low to no polarity (IQR at least 1.0) and strong support.

RESULTS

Nine original, and one new statement reached consensus. These statements outlined essential elements of the informed consent process, including a realistic evaluation of benefits and risks and assurance of future ethics oversight for secondary data use. Discrepant views on appropriate protections for anonymized and coded i.e. de-identified genomic data were primary sources of dissensus.

CONCLUSIONS

The validated statements provide institutions with empirically supported best practices for sharing genomic and associated clinical data involving children from the perspectives of key stakeholders. Concerted efforts to quantify informational risks that can be conveyed to patients and families are further needed to align data sharing policy with stakeholder priorities.

Ethics review of big data research: What should stay and what should be reformed?

BACKGROUND

Ethics review is the process of assessing the ethics of research involving humans. The Ethics Review Committee (ERC) is the key oversight mechanism designated to ensure ethics review. Whether or not this governance mechanism is still fit for purpose in the data-driven research context remains a debated issue among research ethics experts.

MAIN TEXT

In this article, we seek to address this issue in a twofold manner. First, we review the strengths and weaknesses of ERCs in ensuring ethical oversight. Second, we map these strengths and weaknesses onto specific challenges raised by big data research. We distinguish two categories of potential weakness. The first category concerns persistent weaknesses, i.e., those which are not specific to big data research, but may be exacerbated by it. The second category concerns novel weaknesses, i.e., those which are created by and inherent to big data projects. Within this second category, we further distinguish between purview weaknesses related to the ERC's scope (e.g., how big data projects may evade ERC review) and functional weaknesses, related to the ERC's way of operating. Based on this analysis, we propose reforms aimed at improving the oversight capacity of ERCs in the era of big data science.

CONCLUSIONS

We believe the oversight mechanism could benefit from these reforms because they will help to overcome data-intensive research challenges and consequently benefit research at large.

At a Moment's Notice: Community Advisory Board Perspectives on Biobank Communication to Supplement Broad Consent

INTRODUCTION

To address ethical concerns about the of future research authorization, biobanks employing a broad model of consent can design ongoing communication with contributors. Notifying contributors at the time of sample distribution provides one form of communication to supplement broad consent. However, little is known about how community-informed governance might anticipate contributor responses and inform communication efforts.

OBJECTIVE

We explored the attitudes of members of a three-site Community Advisory Board (CAB) network. CAB members responded to a hypothetical proposal for notifying biobank contributors at the time of sample distribution to researchers utilizing the biobank.

METHODS

We used regularly scheduled CAB meetings to facilitate 3 large-group and 6 small-group discussions. Discussions were audio-recorded, transcribed, and analyzed for thematic content using descriptive thematic analysis.

RESULTS

The results challenged our expectation of general support for the proposed communications. While CAB members identified some advantages, they were concerned about several potential harms to biobank contributors and the biobank. The CABs understood biobank communication in terms of an ongoing relationship with the biobank and a personal contribution to research.

CONCLUSION

Our findings contribute to the emerging literature on community engagement in biobanking. Additional communication with biobank contributors can serve a variety of value-based objectives to supplement broad consent. Design of communication efforts by biobanks can be improved by CAB members' anticipation of the unintended consequences of additional contact with contributors. CAB members' holistic interpretation of communication efforts suggests that biobank leadership considers all communication options as part of a more comprehensive communications strategy.

Humanizing Big Data: Recognizing the Human Aspect of Big Data

The term “big data” refers broadly to large volumes of data, often gathered from several sources, that are then analyzed, for example, for predictive analytics. Combining and mining genetic data from varied sources including clinical genetic testing, for example, electronic health records, what might be termed as “recreational” genetic testing such as ancestry testing, as well as research studies, provide one type of “big data.” Challenges and cautions in analyzing big data include recognizing the lack of systematic collection of the source data, the variety of assay technologies used, the potential variation in classification and interpretation of genetic variants. While advanced technologies such as microarrays and, more recently, next-generation sequencing, that enable testing an individual's DNA for thousands of genes and variants simultaneously are briefly discussed, attention is focused more closely on challenges to analysis of the massive data generated by these genomic technologies. The main theme of this review is to evaluate challenges associated with big data in general and specifically to bring the sophisticated technology of genetic/genomic testing down to the individual level, keeping in mind the human aspect of the data source and considering where the impact of the data will be translated and applied. Considerations in this “humanizing” process include providing adequate counseling and consent for genetic testing in all settings, as well as understanding the strengths and limitations of assays and their interpretation.

The Data Tags Suite (DATS) model for discovering data access and use requirements

BACKGROUND

Data reuse is often controlled to protect the privacy of subjects and patients. Data discovery tools need ways to inform researchers about restrictions on data access and re-use.

RESULTS

We present elements in the Data Tags Suite (DATS) metadata schema describing data access, data use conditions, and consent information. DATS metadata are explained in terms of the administrative, legal, and technical systems used to protect confidential data.

CONCLUSIONS

The access and use metadata items in DATS are designed from the perspective of a researcher who wants to find and re-use existing data. We call for standard ways of describing informed consent and data use agreements that will enable automated systems for managing research data.

Responsible data sharing in a big data-driven translational research platform: lessons learned

BACKGROUND

To foster responsible data sharing in health research, ethical governance complementary to the EU General Data Protection Regulation is necessary. A governance framework for Big Data-driven research platforms will at least need to consider the conditions as specified a priori for individual datasets. We aim to identify and analyze these conditions for the Innovative Medicines Initiative's (IMI) BigData@Heart platform.

METHODS

We performed a unique descriptive case study into the conditions for data sharing as specified for datasets participating in BigData@Heart. Principle investigators of 56 participating databases were contacted via e-mail with the request to send any kind of documentation that possibly specified the conditions for data sharing. Documents were qualitatively reviewed for conditions pertaining to data sharing and data access.

RESULTS

Qualitative content analysis of 55 relevant documents revealed overlap on the conditions: (1) only to share health data for scientific research, (2) in anonymized/coded form, (3) after approval from a designated review committee, and while (4) observing all appropriate measures for data security and in compliance with the applicable laws and regulations.

CONCLUSIONS

Despite considerable overlap, prespecified conditions give rise to challenges for data sharing. At the same time, these challenges inform our thinking about the design of an ethical governance framework for data sharing platforms. We urge current data sharing initiatives to concentrate on: (1) the scope of the research questions that may be addressed, (2) how to deal with varying levels of de-identification, (3) determining when and how review committees should come into play, (4) align what policies and regulations mean by "data sharing" and (5) how to deal with datasets that have no system in place for data sharing.

Population's perspectives toward biobanks in scientific research: a study from Jordan

Background

Biobanks (biorepositories) were established to compile collected bio-specimens for future research and usage. The collection/storage of bio-specimens triggers several social, legal, and ethical implications where public attitudes can represent the core measurement/parameter in defining the most acceptable practices and ethical approaches when dealing with biobanks.

Aim

The aim of this study was to explore and understand population’s perspectives, expectations, and concerns toward biobanks in Jordan.

Methods

A cross-sectional survey that included closed-ended questions was distributed among Jordanians. A total of 500 participants who are representative of the Jordanian population were included in this study.

Results

There was overwhelming support (>85%) for the establishment of biobanks in Jordan, and most of the participants agreed on the importance of biobanks and samples’ donation for promoting medical research. Enthusiasm in biobanking participation was associated with the sociodemographic characteristics of participants including age, educational level, and previous knowledge of biobanks. Moreover, considering sample donation as a religiously good deed appeared to have the strongest positive correlation with willingness to donate bio-specimens for future research. Also, participants’ trust in medical and research services, especially the protection of their privacy and confidentiality, was the most critical concern when they decided to participate in biobanks.

Conclusion

Population’s attitude toward biobanks in Jordan was positive and promising, and can encourage the future establishment of different biobanks. It is also necessary to take into consideration certain sociodemographic characteristics when discussing specific information with potential biobanks’ donors.

Sharing data for future research-engaging participants' views about data governance beyond the original project: a DIRECT Study

PURPOSE

Biomedical data governance strategies should ensure that data are collected, stored, and used ethically and lawfully. However, research participants' preferences for how data should be governed is least studied. The Diabetes Research on Patient Stratification (DIRECT) project collected substantial amounts of health and genetic information from patients at risk of, and with type II diabetes. We conducted a survey to understand participants' future data governance preferences. Results will inform the postproject data governance strategy.

METHODS

A survey was distributed in Denmark, Sweden, The Netherlands, and the United Kingdom.

RESULTS

In total 855 surveys were returned. Ninety-seven percent were supportive of sharing data postproject, and 90% were happy to share data with universities, and 56% with commercial companies. The top three priorities for data sharing were highly secure database, DIRECT researchers to monitor data used by other researchers, and researchers cannot identify participants. Respondents frequently suggested that a postproject Data Access Committee should involve a DIRECT researcher, diabetes clinician, patient representative, and a DIRECT participant.

CONCLUSION

Preferences of how data should be governed, and what data could be shared and with whom varied between countries. Researchers are considered as key custodians of participant data. Engaging participants aids in designing governance to support their choices.

Of Straws, Camels, Research Regulation, and IRBs

Institutional review boards (IRBs) have become beleaguered by a growth in responsibilities related to research oversight in the past several decades. A number of regulatory bodies have appeared in response to these novel and complex responsibilities, seeking to respond to among other issues, conflicts of interest, new technologies, and the potential misuse of research findings. Here, we examine several examples of these novel regulatory bodies as well as a number of concerns related to them that have been largely unacknowledged. Evidence suggests that there can be disharmony and conflicts between these regulatory bodies and IRBs, a lack of clarity with regard to their roles and responsibilities, as well as shortcomings within these entities that, at times, look a lot like the worries that have long been raised in relation to IRBs. We offer a brief discussion of how some of these concerns might be ameliorated, either through a significant restructuring of the system of research oversight, or perhaps through smaller changes to these regulatory bodies.

The Genomic Commons

Over its 30 or so years of existence, the genomic commons-the worldwide collection of publicly accessible repositories of human and nonhuman genomic data-has enjoyed remarkable, perhaps unprecedented, success. Thanks to the rapid public data release policies initiated by the Human Genome Project, free access to a vast array of scientific data is now the norm, not only in genomics, but in scientific disciplines of all descriptions. And far from being a monolithic creation of bureaucratic fiat, the genomic commons is an exemplar of polycentric, multistakeholder governance. But like all dynamic and rapidly evolving systems, the genomic commons is not without its challenges. Issues involving scientific priority, intellectual property, individual privacy, and informed consent, in an environment of data sets of exponentially expanding size and complexity, must be addressed in the near term. In this review, we describe the characteristics and unique history of the genomic commons, then address some of the trends, challenges, and opportunities that we envision for this valuable public resource in the years to come.