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BackgroundEthics 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 textIn 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.ConclusionsWe 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.

Digital health innovation is expected to transform healthcare, but it also generates ethical and societal concerns, such as privacy risks, and biases that can compound existing health inequalities. While such concerns are widely recognized, existing regulatory principles, oversight methods and ethical frameworks seem out of sync with digital health innovation. New governance and innovation best practices are thus needed to bring such principles to bear with the reality of business, innovation, and regulation. To grant practical insight into best practices for responsible digital health innovation, we conducted a qualitative study based on an interactive engagement methodology. We engaged key stakeholders (n = 46) operating at the translational frontier of digital health. This approach allowed us to identify three clusters of governance and innovation best practices in digital health innovation: i) inclusive co-creation, ii) responsive regulation, and iii) value-driven innovation. Our study shows that realizing responsible digital health requires diverse stakeholders' commitment to adapt innovation and regulation practices, embracing co-creation as the default modus operandi for digital health development. We describe these collaborative practices and show how they can ensure that innovation is neither slowed by overregulation, nor leads to unethical outcomes. [ABSTRACT FROM AUTHOR]

Over the last decade, bioengineering has seen a sustained growth in scientific publications, patents, and clinical trials. As the field attempts to bridge the gap between discovery and clinical application, a broader societal dialogue is needed to build public trust and address potential ethical, societal, and regulatory challenges. In this essay, we discuss societal aspects linked to the clinical use of biomedical engineering approaches and technologies, with a specific focus on molecular systems engineering. Drawing on data from interviews with 24 scientists, we identified four key aspects for fostering societal support for translational efforts in this domain: (1) effective science communication and internal awareness; (2) open societal dialogue; (3) fair and equitable access to new technologies; and (4) adequate science and technology policies. We conclude that molecular systems engineering would benefit from anticipating future challenges with the view of building a robust bond of trust with lay publics, regulators, and society at large. [ABSTRACT FROM AUTHOR]

Recent research has challenged the notion that dementia is an inevitable outcome of age-related cognitive decline, highlighting the possibility of preventing or delaying onset by addressing specific risk factors. This paradigm shift suggests that prevention through lifestyle modifications and early interventions is possible, potentially averting millions of cases worldwide. This study explores the translation of scientific evidence on dementia prevention into public health policy in Switzerland. Combining the analysis of official policy documents and qualitative interviews with stakeholders, the study explores potential barriers and challenges to implementing preventive intervenions or programs, as well as opportunities for improvement. Results indicate a significant gap in incorporating emerging scientific evidence on dementia prevention into health policies and disseminating information to the public in Switzerland. This study underscores the need for a collaborative and coordinated approach to address these barriers and effectively translate scientific findings into preventive policies and campaigns. These insights can inform policy and targeted programs in Switzerland both at the federal and the cantonal level, eventually serving as a model for other countries seeking to translate evidence-based dementia prevention strategies into public health policies. By bridging the gap between research and policy, significant progress can be made in preventing or delaying the onset of dementia, providing significant benefits to individuals, families, and society. [ABSTRACT FROM AUTHOR]

Massive amounts of data are collected and stored on a routine basis in virtually all domains of human activities. Such data are potentially useful to biomedicine. Yet, access to data for research purposes is hindered by the fact that different kinds of individual-patient data reside in disparate, unlinked silos. We propose that data cooperatives can promote much needed data aggregation and consequently accelerate research and its clinical translation. Data cooperatives enable direct control over personal data, as well as more democratic governance of data pools. This model can realize a specific kind of data economy whereby citizens and communities are empowered to steer data use according to their motivations, preferences, and concerns. Policy makers can promote this model by recognizing citizens' rights to access and to obtain a copy of their own data, and by funding distributed data infrastructures piloting new data aggregation models., Author(s): Alessandro Blasimme [sup.1] , Effy Vayena [sup.1] , Ernst Hafen [sup.2] Author Affiliations: (Aff1) 0000 0001 2156 2780, grid.5801.c, Department of Health Sciences and Technology, ETH Zurich, , Zurich, [...]

This paper describes the results of a multi-country survey of governance approaches for the use of digital contact tracing (DCT) in response to the COVID-19 pandemic. We argue that the countries in our survey represent two distinct models of DCT governance, both of which are flawed. The "data protection model" emphasizes privacy protections at the expense of public health benefit, while the "emergency response model" sacrifices transparency and accountability, prompting concerns about excessive governance surveillance. The ethical and effective use of DCT in the future requires a new governance approach that is better suited to this novel use of mobile phone data to promote public health." [ABSTRACT FROM AUTHOR]

Author(s): Effy Vayena 1,*, Alessandro Blasimme 1, I. Glenn Cohen 2 A recent United Kingdom survey reports that 63% of the adult population is uncomfortable with allowing personal data to [...]