An ethics safe harbor for international genomics research?

Considerations for an integrated population health databank in Africa: lessons from global best practices

Background: The rising digitisation and proliferation of data sources and repositories cannot be ignored. This trend expands opportunities to integrate and share population health data. Such platforms have many benefits, including the potential to efficiently translate information arising from such data to evidence needed to address complex global health challenges. There are pockets of quality data on the continent that may benefit from greater integration. Integration of data sources is however under-explored in Africa. The aim of this article is to identify the requirements and provide practical recommendations for developing a multi-consortia public and population health data-sharing framework for Africa.

Methods: We conducted a narrative review of global best practices and policies on data sharing and its optimisation. We searched eight databases for publications and undertook an iterative snowballing search of articles cited in the identified publications. The Leximancer software © enabled content analysis and selection of a sample of the most relevant articles for detailed review. Themes were developed through immersion in the extracts of selected articles using inductive thematic analysis. We also performed interviews with public and population health stakeholders in Africa to gather their experiences, perceptions, and expectations of data sharing.

Results: Our findings described global stakeholder experiences on research data sharing. We identified some challenges and measures to harness available resources and incentivise data sharing.  We further highlight progress made by the different groups in Africa and identified the infrastructural requirements and considerations when implementing data sharing platforms. Furthermore, the review suggests key reforms required, particularly in the areas of consenting, privacy protection, data ownership, governance, and data access.

Conclusions: The findings underscore the critical role of inclusion, social justice, public good, data security, accountability, legislation, reciprocity, and mutual respect in developing a responsive, ethical, durable, and integrated research data sharing ecosystem.

Revolutionizing Medical Data Sharing Using Advanced Privacy-Enhancing Technologies: Technical, Legal, and Ethical Synthesis

Multisite medical data sharing is critical in modern clinical practice and medical research. The challenge is to conduct data sharing that preserves individual privacy and data utility. The shortcomings of traditional privacy-enhancing technologies mean that institutions rely upon bespoke data sharing contracts. The lengthy process and administration induced by these contracts increases the inefficiency of data sharing and may disincentivize important clinical treatment and medical research. This paper provides a synthesis between 2 novel advanced privacy-enhancing technologies-homomorphic encryption and secure multiparty computation (defined together as multiparty homomorphic encryption). These privacy-enhancing technologies provide a mathematical guarantee of privacy, with multiparty homomorphic encryption providing a performance advantage over separately using homomorphic encryption or secure multiparty computation. We argue multiparty homomorphic encryption fulfills legal requirements for medical data sharing under the European Union's General Data Protection Regulation which has set a global benchmark for data protection. Specifically, the data processed and shared using multiparty homomorphic encryption can be considered anonymized data. We explain how multiparty homomorphic encryption can reduce the reliance upon customized contractual measures between institutions. The proposed approach can accelerate the pace of medical research while offering additional incentives for health care and research institutes to employ common data interoperability standards.

Responsible data sharing in international health research: a systematic review of principles and norms

BACKGROUND

Large-scale linkage of international clinical datasets could lead to unique insights into disease aetiology and facilitate treatment evaluation and drug development. Hereto, multi-stakeholder consortia are currently designing several disease-specific translational research platforms to enable international health data sharing. Despite the recent adoption of the EU General Data Protection Regulation (GDPR), the procedures for how to govern responsible data sharing in such projects are not at all spelled out yet. In search of a first, basic outline of an ethical governance framework, we set out to explore relevant ethical principles and norms.

METHODS

We performed a systematic review of literature and ethical guidelines for principles and norms pertaining to data sharing for international health research.

RESULTS

We observed an abundance of principles and norms with considerable convergence at the aggregate level of four overarching themes: societal benefits and value; distribution of risks, benefits and burdens; respect for individuals and groups; and public trust and engagement. However, at the level of principles and norms we identified substantial variation in the phrasing and level of detail, the number and content of norms considered necessary to protect a principle, and the contextual approaches in which principles and norms are used.

CONCLUSIONS

While providing some helpful leads for further work on a coherent governance framework for data sharing, the current collection of principles and norms prompts important questions about how to streamline terminology regarding de-identification and how to harmonise the identified principles and norms into a coherent governance framework that promotes data sharing while securing public trust.

Ethics and Epistemology in Big Data Research

Biomedical innovation and translation are increasingly emphasizing research using "big data." The hope is that big data methods will both speed up research and make its results more applicable to "real-world" patients and health services. While big data research has been embraced by scientists, politicians, industry, and the public, numerous ethical, organizational, and technical/methodological concerns have also been raised. With respect to technical and methodological concerns, there is a view that these will be resolved through sophisticated information technologies, predictive algorithms, and data analysis techniques. While such advances will likely go some way towards resolving technical and methodological issues, we believe that the epistemological issues raised by big data research have important ethical implications and raise questions about the very possibility of big data research achieving its goals.

Use of Real-World Data for the Research, Development, and Evaluation of Oncology Precision Medicines

Although randomized controlled trials remain the scientific ideal for determining the efficacy and safety of new treatments, they are sometimes insufficient to address the evidentiary requirements of regulators and payers. This is particularly the case when it comes to precision medicines because trials are often small, deliver incomplete insights into outcomes of most interest to policymakers (eg, overall survival), and may fail to address other complex diagnostic and treatment-related questions. Additional methods, both experimental and observational, are increasingly being used to fill critical evidentiary gaps. A number of modified early- and late-phase trial designs have been proposed to better support earlier biomarker validation, patient identification, and selection for regulatory studies, but there is still a need for confirmatory evidence from real-world data sources. These data are usually provided through observational, postapproval, phase IIIB and IV studies, which rely heavily on registries and other electronic data sets—most notably data from electronic health records. It is, therefore, crucial to understand what ethical, practical, and scientific challenges are raised by the use of electronic health records to generate evidence about precision medicines.

Participation in Genetic Research: Amazon's Mechanical Turk Workforce in the United States and India

BACKGROUND

Genomic research has innumerable benefits. However, if people are unwilling to participate in genomic research, application of knowledge will be limited. This study examined the likelihood of respondents from a high- and a low- to middle-income country to participate in genetic research.

METHODS

Cross-sectional data were collected using Amazon's Mechanical Turk workforce to ascertain attitudes toward participation in genetic research. Registered country of residence was either the US (n = 505) or India (n = 505). Multiple logistic regression models were used to assess adjusted effects of demographic characteristics, health, social status, beliefs and concerns on 4 genetic research outcomes.

RESULTS

Participants from India who believed chance and powerful others influenced their health were more likely to participate in genetic research (OR = 1.0, 95% CI 1.0-1.1) and to agree with sharing of DNA data (OR = 1.1, 95% CI 1.1-1.2). US participants were more likely to be concerned about protection of family history, which they indicated would affect participation (OR = 3.6, 95% CI 2.1-6.0). Commonalities for the likelihood of participation were beliefs that genetic research could help find new treatments (India OR = 2.3, 95% CI 1.0-5.4; US OR = 4.7, 95% CI 2.0-11.2) and descendants would benefit (India OR = 2.6, 95% CI 1.2-5.5; US OR = 3.0, 95% CI 1.3-7.1).

CONCLUSIONS

Concurrence of beliefs on benefits and concerns about genetic research suggest they may be common across countries. Consideration of commonalities may be important to increase global participation in genetic research.

What Does Anonymization Mean? DataSHIELD and the Need for Consensus on Anonymization Terminology

Anonymization is a recognized process by which identifiers can be removed from identifiable data to protect an individual's confidentiality and is used as a standard practice when sharing data in biomedical research. However, a plethora of terms, such as coding, pseudonymization, unlinked, and deidentified, have been and continue to be used, leading to confusion and uncertainty. This article shows that this is a historic problem and argues that such continuing uncertainty regarding the levels of protection given to data risks damaging initiatives designed to assist researchers conducting cross-national studies and sharing data internationally. DataSHIELD and the creation of a legal template are used as examples of initiatives that rely on anonymization, but where the inconsistency in terminology could hinder progress. More broadly, this article argues that there is a real possibility that there could be possible damage to the public's trust in research and the institutions that carry it out by relying on vague notions of the anonymization process. Research participants whose lack of clear understanding of the research process is compensated for by trusting those carrying out the research may have that trust damaged if the level of protection given to their data does not match their expectations. One step toward ensuring understanding between parties would be consistent use of clearly defined terminology used internationally, so that all those involved are clear on the level of identifiability of any particular set of data and, therefore, how that data can be accessed and shared.

A role for research ethics committees in exchanges of human biospecimens through material transfer agreements

International transfers of human biological material (biospecimens) and data are increasing, and commentators are starting to raise concerns about how donor wishes are protected in such circumstances. These exchanges are generally made under contractual material transfer agreements (MTAs). This paper asks what role, if any, should research ethics committees (RECs) play in ensuring legal and ethical conduct in such exchanges. It is recommended that RECs should play a more active role in the future development of best practice MTAs involving exchange of biospecimens and data and in monitoring compliance.

Building a data sharing model for global genomic research

Data sharing models designed to facilitate global business provide insights for improving transborder genomic data sharing. We argue that a flexible, externally endorsed, multilateral arrangement, combined with an objective third-party assurance mechanism, can effectively balance privacy with the need to share genomic data globally.

A human rights approach to an international code of conduct for genomic and clinical data sharing

Fostering data sharing is a scientific and ethical imperative. Health gains can be achieved more comprehensively and quickly by combining large, information-rich datasets from across conventionally siloed disciplines and geographic areas. While collaboration for data sharing is increasingly embraced by policymakers and the international biomedical community, we lack a common ethical and legal framework to connect regulators, funders, consortia, and research projects so as to facilitate genomic and clinical data linkage, global science collaboration, and responsible research conduct. Governance tools can be used to responsibly steer the sharing of data for proper stewardship of research discovery, genomics research resources, and their clinical applications. In this article, we propose that an international code of conduct be designed to enable global genomic and clinical data sharing for biomedical research. To give this proposed code universal application and accountability, however, we propose to position it within a human rights framework. This proposition is not without precedent: international treaties have long recognized that everyone has a right to the benefits of scientific progress and its applications, and a right to the protection of the moral and material interests resulting from scientific productions. It is time to apply these twin rights to internationally collaborative genomic and clinical data sharing.