Genomic Data-Sharing Practices

Creating personas for exposome research: the experience from the HEAP project

The exposome is a complex scientific field that has enjoyed consistent growth over the last two decades, defined as the composite of every exposure to which an individual is subjected from conception to death. The study of the exposome requires consideration of both the nature of those exposures and their changes over time, and as such necessitates high quality data and software solutions. As the exposome is both a broad and a recent concept, it is challenging to define or to introduce in a structured way. Thus, an approach to assist with clear definitions and a structured framework is needed for the wider scientific and public communication. Results: A set of 14 personas were developed through three focus groups and a series of 14 semi-structured interviews. The focus groups defined the broad themes specific to exposome research, while the sub-themes emerged to saturation via the interviews process. Personas are imaginary individuals that represent segments/groups of real people within a population. Within the context of the HEAP project, the created personas represented both exposome data generators and users. Conclusion: Personas have been implemented successfully in computer science, improving the understanding of human-computer interaction. The creation of personas specific to exposome research adds a useful tool supporting education and outreach activities for a complex scientific field.

Diversity, Profit, Control: An Empirical Study of Industry Employees' Views on Ethics in Private Sector Genomics

BACKGROUND

Large amounts of capital are currently being invested in genomics companies across the "bench to clinic pipeline" - companies which are now shaping the future of biomedicine globally. Understanding the perspectives of people who work in such companies can contribute to shaping this industry in service of just and equitable futures of medicine.

METHODS

Using in-depth interviews as the primary method, this paper analyzes perspectives on ethical and social issues in private sector genomics expressed by members of the commercial genomics industry in the US.

RESULTS

Interviewees described a wide range of issues as pressing ethical concerns in commercial genomics. Key themes included concerns about diversity in genetic datasets, data governance and control, and pricing and profits in the industry. However, concern about diversity of datasets was not accompanied by expressions of concern about diversity in the industry workforce.

CONCLUSIONS

Most interviewees described concerns in the industry that are rather removed from their own work. But along with this "ethical distancing," moral concerns appeared to be the basis for competition amongst companies - to attract both employees and customers. Research in business ethics suggests that expanding moral analysis of one's own work helps improve day to day decision-making in the interest of justice. Opening space for people to examine ethics in their own subsector may provide a means for the private sector genomics industry to become a leader in ethics in the biosciences and a model for equity in our current moment of late capitalism.

Sensor Data Integration: A New Cross-Industry Collaboration to Articulate Value, Define Needs, and Advance a Framework for Best Practices

Data integration, the processes by which data are aggregated, combined, and made available for use, has been key to the development and growth of many technological solutions. In health care, we are experiencing a revolution in the use of sensors to collect data on patient behaviors and experiences. Yet, the potential of this data to transform health outcomes is being held back. Deficits in standards, lexicons, data rights, permissioning, and security have been well documented, less so the cultural adoption of sensor data integration as a priority for large-scale deployment and impact on patient lives. The use and reuse of trustworthy data to make better and faster decisions across drug development and care delivery will require an understanding of all stakeholder needs and best practices to ensure these needs are met. The Digital Medicine Society is launching a new multistakeholder Sensor Data Integration Tour of Duty to address these challenges and more, providing a clear direction on how sensor data can fulfill its potential to enhance patient lives.

Longitudinal Health Studies: Secondary Uses Serving the Future

Our research compares the ethical and institutional conditions that govern the sharing and secondary use of longitudinal population health data from multiple cohorts. The data use and data sharing conditions applicable to 27 population health cohorts were assessed. This assessment was performed in consulting the informed consent materials and institutional policies applicable to the use of data. Descriptions drawn from the research ethics consent materials were refined through dialog with the institutional staff responsible for overseeing access to data, where possible. Our results demonstrate that data of longitudinal population health cohorts assessed can generally be shared and used for secondary purposes. However, the purposes of secondary use and the preconditions applicable thereto are highly variable. Heterogeneous use conditions can also impede the storage of legacy research data and the pooling thereof for the purpose of common reuse.

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.

A Scenario-Based Methodology for Analyzing the Ethical, Legal, and Social Issues in Genomic Data Sharing

Sharing of genomic and associated data is essential to clinical practice and biomedical research, and is increasingly encouraged by journals and funding bodies. Grappling with the range of legal and ethical issues raised by genomic data sharing presents a significant challenge, given the diversity of practices: from defined sharing of individual patient data, to broad-scale public sharing of research data, to uploading of direct-to-consumer test data by community members. Most commentary to date has discussed these issues in broad terms, but the debate can only progress if we engage with more granularity, grounded in jurisdictional and contextual specifics. We developed an empirical approach, creating a set of prototypical scenarios that capture the diversity of current genomic data sharing practices, which allows legal and ethical analysis of key issues at a granular level. The specificity of this approach provides a strong foundation for developing useful and relevant regulatory recommendations.

Rare disease data stewardship in Canada

The Canadian Genomics Partnership for Rare Diseases, spearheaded by Genome Canada, will integrate genome-wide sequencing to rare disease clinical care in Canada. Centralized and tiered models of data stewardship are proposed to ensure that the data generated can be shared for secondary clinical, research, and quality assurance purposes in compliance with ethics and law. The principal ethico-legal obligations of clinicians, researchers, and institutions are synthesized. Governance infrastructures such as registered access platforms, data access compliance offices, and Beacon systems are proposed as potential organizational and technical foundations of responsible rare disease data sharing. The appropriate delegation of responsibilities, the transparent communication of rights and duties, and the integration of data privacy safeguards into infrastructure design are proposed as the cornerstones of rare disease data stewardship.

Characterizing the Biomedical Data-Sharing Landscape

Advances in technologies and biomedical informatics have expanded capacity to generate and share biomedical data. With a lens on genomic data, we present a typology characterizing the data-sharing landscape in biomedical research to advance understanding of the key stakeholders and existing data-sharing practices. The typology highlights the diversity of data-sharing efforts and facilitators and reveals how novel data-sharing efforts are challenging existing norms regarding the role of individuals whom the data describe.