Big data trends in biomedical and health research enable large-scale and multi-dimensional aggregation and analysis of heterogeneous data sources, which could ultimately result in preventive, diagnostic and therapeutic benefit. The methodological novelty and computational complexity of big data health research raises novel challenges for ethics review. In this study, we conducted a scoping review of the literature using five databases to identify and map the major challenges of health-related big data for Ethics Review Committees (ERCs) or analogous institutional review boards. A total of 1093 publications were initially identified, 263 of which were included in the final synthesis after abstract and full-text screening performed independently by two researchers. Both a descriptive numerical summary and a thematic analysis were performed on the full-texts of all articles included in the synthesis. Our findings suggest that while big data trends in biomedicine hold the potential for advancing clinical research, improving prevention and optimizing healthcare delivery, yet several epistemic, scientific and normative challenges need careful consideration. These challenges have relevance for both the composition of ERCs and the evaluation criteria that should be employed by ERC members when assessing the methodological and ethical viability of health-related big data studies. Based on this analysis, we provide some preliminary recommendations on how ERCs could adaptively respond to those challenges. This exploration is designed to synthesize useful information for researchers, ERCs and relevant institutional bodies involved in the conduction and/or assessment of health-related big data research. 440 plosone PLoS ONE PLoS One PLOS PMC6181558 6181558 6181558 30308031 10.1371/journal.pone.0204937 Considerations for ethics review of big data health research: A scoping review Ienca Marcello Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Writing – original draft, Writing – review & editing 1 # Ferretti Agata Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Writing – original draft, Writing – review & editing 1 # Hurst Samia Conceptualization, Funding acquisition, Methodology, Project administration, Supervision, Writing – review & editing 2 Puhan Milo Conceptualization, Funding acquisition, Methodology, Writing – review & editing 3 Lovis Christian Conceptualization, Funding acquisition, Methodology, Writing – review & editing 4 Vayena Effy Conceptualization, Funding acquisition, Methodology, Project administration, Supervision, Writing – review & editing 1 * Biemba Godfrey Editor 5 1 Health Ethics and Policy Laboratory, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland 2 Institute for Ethics, History and the Humanities, Faculty of Medicine, University of Geneva, Geneva, Switzerland 3 Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland 4 Division of Medical Information Sciences, Department of Radiology and Medical Informatics, University Hospital of Geneva, Geneva, Switzerland 5 Paediatric Centre of Excellence, ZAMBIA Competing Interests: The authors have declared that no competing interests exist. The ethical, legal and social implications of health-related big data raise novel challenges also for Ethics Review Committees (ERCs). ERCs and institutional review boards are increasingly requested to evaluate an ever-growing number of research projects and associated activities involving big data (large data volumes and big data analytics), whose risks and benefits often appear hard to assess. Some authors have called for the development of comprehensive regulatory policies for healthcare entities and new computing safeguards that can address public concerns, such as the protection of individually identifiable information [ 25 ]. Second, several studies have shown that de-identified [ 30 ] and even anonymized data [ 31 ] can be reverse engineered to re-identify individuals, leading experts to the conclusion that “there is no such thing as anonymous data”. This raises the question of whether big data projects should require oversight by an ERC even when the data collected are public and anonymized or de-identified. A recent systematic review has concluded that most normative documents deem the review of an ERC as necessary to address the concerns associated with the use of anonymized data for research [ 32 ]. First, duplicates were removed both automatically using the Endnote tool for duplicate detection and manually based on abstract screening. A total of 226 articles was removed at this stage. Second, eligibility assessment was performed independently by two of the co-authors on the remaining 867 articles through title-abstract screening and, subsequently, full text screening. Diverging inclusion choices between the two reviewers were discussed with the research group with documented reasons. Empirical research in this domain could methodologically build upon previous studies involving ethics advisors working in big-data-related areas of research such as genomics governance [ 70 ]. Combining empirical and normative ethical research in the health-related big data domain would not only benefit the understanding of Finally, it is legitimate to raise the question of whether ERCs should be the only governance body responsible for the evaluation of biomedical big data research. Given their traditional mandate, which is deeply rooted in the pre-digital era of biomedical research, it might be reasonably argued that ERCs are ill-suited to exercise exclusive ethical oversight on health-related big data research. Research regulators should consider whether complementary governance mechanisms such as data boards, data security committees or allied bodies are necessary to expand the bandwidth and sensitivity of ethical oversight. Supporting information S1 File Search strategy.