Big Data, Biomedical Research, and Ethics Review: New Challenges for IRBs

Abstract

T raditionally, human subjects research in the biomedical field engages healthy and sick people as research participants in order to test certain hypotheses about health and disease according to a well-defined study design. The study designs, such as randomized controlled trials and cohort studies, are carefully reviewed by institutional review boards (IRBs)-also known as ethical review committees (ERCs) in some countries. IRBs are committed to protecting the rights and welfare of human subjects recruited to participate in biomedical or behavioral research (including social science research). 1 This approach has long been the standard for biomedical research. Recently, however, biomedical research has begun to pursue opportunities afforded by big data. Big data research relies on large-scale databases, multiplication of data sources, advanced storage capacity, and novel computational tools that allow for high-velocity data analytics. 2 In the biomedical domain, big data trends are enabled by and allow for advances in areas such as whole genome sequencing, brain imaging, mobile health, and digital phenotyping. 3 Today, a large portion of health-related research relies on big data. Big data also enables researchers to draw health insights from data sources that are not strictly medical-data from wearable trackers, social media, and Internet searches, for example. 4 Big data research opens new prospects to accelerate health-related research and potentially elicit breakthroughs that will benefit patients. 5 Big data has been observed to shift the way biomedical researchers design and carry out their studies. 6 This research departs from the traditional research model because it is largely exploratory rather than hypothesis driven. Health-related big data research is based on the acquisition of large amounts of data from multiple and often heterogeneous sources, which are subsequently combined and mined using powerful data analytics tools. This reverse-engineered approach to health-related research allows researchers to extract features and valuable insights from large datasets, without being able to anticipate exactly what the data analysis will find.

Digital approaches to enhancing community engagement in clinical trials

“…Such regulatory innovations have been effectively implemented in the COVID-19 pandemic without compromising on patient safety or product quality 83 – 85 . Additionally, regulatory frameworks that govern research practices or community engagement in trials may also require further review to ensure that research protocols are aligned with practices that uphold patient privacy and safety in the context of novel digital approaches 86 , 87 .…”

The Challenges of Big Data for Research Ethics Committees: A Qualitative Swiss Study

“…In parallel with these changes in research practice, high profile cases of data misuse have emerged, exposing research participants to privacy breaches and risk of harm ( Fuller, 2019 ). In response, debate has increased about the role and effectiveness of the Research Ethics Committee (REC) as the chief ethical research oversight mechanism in research, given the specific challenges presented by research with big data ( Ferretti et al, 2020 ; Rennie et al, 2020 ). RECs, also known as Institutional Review Boards (IRBs) and Research Ethics Boards (REBs), were created in the 20th century to protect the safety and interests of human participants in research ( Friesen et al, 2019 ).…”

Embedded ethics: a proposal for integrating ethics into the development of medical AI

“…A final merit of the embedded ethics approach starts from the recognition, much like the concerns above, that there is currently little specific regulation for the development and use of AI in medicine. Medical AI technologies are often not tested as rigorously as other products, and although ethics guidelines are rapidly being deployed, the focus is often on the operation of such technologies and thereby too late to profoundly impact its development [ 58 ]. Regularly, applications only get assessed when tested in clinical trials and assessed by ethics committees, at which point significant parts of the development have already finished.…”