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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.

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, [...]