ChatGPT has taken the academic community by storm (Cotton, Cotton, and Shipway 2023; Cox and Tzoc 2023; Sullivan, Kelly, and McLaughlan 2023). Since its release in November 2022, chatGPT has predic...

Bayefsky and Berkman argue in favor of evidence-based policy development for expanded prenatal genetic testing. They propose to identify what kinds of information pregnant persons, their par...

In their proof-of-concept, Meier and colleagues describe the purpose and programming decisions underpinning Medical Ethics Advisor, an automated decision support system used t...

Background Institutional review board (IRB) expertise is necessarily limited by maintaining a manageable board size. IRBs are therefore permitted by regulation to rely on outside experts for review. However, little is known about whether, when, why, and how IRBs use outside experts.Methods We conducted a national survey of U.S. IRBs to characterize utilization of outside experts. Our study uses a descriptive, cross-sectional design to understand how IRBs engage with such experts and to identify areas where outside expertise is most frequently (...) requested.Results The survey response rate was 18.4%, with 55.4% of respondents reporting their institution’s IRB uses outside experts. Nearly all respondents who reported using outside experts indicated they do so less than once a month, but occasionally each year (95%). The most common method of identifying an outside expert was securing a previously known subject matter expert (83.3%). Most frequently, respondents sought consultation for scientific expertise not held by current members (69.6%). Almost all respondents whose IRBs had used outside experts reported an overall positive impact on the IRB review process (91.5%).Conclusions Just over half of the IRBs in our sample report use of outside experts; among them, outside experts were described as helpful, but their use was infrequent overall. Many IRBs report not relying on outside experts at all. This raises important questions about what type of engagement with outside experts should be viewed as optimal to promote the highest quality review. For example, few respondents sought assistance from a Community Advisory Board, which could address expertise gaps in community perspectives. Further exploration is needed to understand how to optimize IRB use of outside experts, including how to recognize when expertise is lacking, what barriers IRBs face in using outside experts, and perspectives on how outside expert review impacts IRB decision-making and review quality. (shrink)

How do we respect the legitimate privacy interests of individuals and communities about whom data relate while maximizing data’s utility as a fundamental resource? Pyrrho, Cambraia and de Vasconcel...

In their article, Cho and Martinez-Martin (2023) argue that developers and users of digital simulacra for modelling health and disease should involve a continued focus on causality of health states...

Private companies are data-rich. But market pressures to collect more, store more, and analyze more consumer data can often make them ethically bankrupt in the way of proactively protecting consume...

BackgroundThe highly sensitive nature of genomic and associated clinical data, coupled with the consent-related vulnerabilities of children together accentuate ethical, legal and social issues (ELSI) concerning data sharing. The Key Implications of Data Sharing (KIDS) framework was therefore developed to address a need for institutional guidance on genomic data governance but has yet to be validated among data sharing practitioners in practice settings. This study qualitatively explored areas of consensus and dissensus of the KIDS Framework from the perspectives of Canadian (...) clinician-scientists, genomic researchers, IRB members, and pediatric ethicists.MethodsTwelve panelists participated in a three-round online policy Delphi to determine the desirability, feasibility, relative importance and confidence of twelve individual statements of the KIDS Framework. Mean and IQR were calculated from panelists’ ratings to determine the strength of consensus and polarity. Qualitative content analysis of panelists’ written responses was used to assess degree of support. Statements were validated when their combined ratings and qualitative rationales indicated high-moderate consensus (at least 70% agreement across two contiguous categories), low to no polarity (IQR at least 1.0) and strong support.ResultsNine original, and one new statement reached consensus. These statements outlined essential elements of the informed consent process, including a realistic evaluation of benefits and risks and assurance of future ethics oversight for secondary data use. Discrepant views on appropriate protections for anonymized and coded i.e. de-identified genomic data were primary sources of dissensus.ConclusionsThe validated statements provide institutions with empirically supported best practices for sharing genomic and associated clinical data involving children from the perspectives of key stakeholders. Concerted efforts to quantify informational risks that can be conveyed to patients and families are further needed to align data sharing policy with stakeholder priorities. (shrink)

In this paper we report findings from a commissioned report to the COVID-19 Clinical Research Coalition on approaches to streamline multinational REC review/approval during public health emergencies. As currently envisioned in the literature, a system of REC mutual recognition is theoretically possible based on shared procedural REC standards, but raises numerous concerns about perceived inequities and mistrust.

In their recent article, Porsdam Mann et al propose to share biomedical research data more widely, securely and efficiently using blockchain technologies. 1 They present compelling arguments for how the blockchain presents both a technological innovation, and a deontologically grounded policy innovation to traditional research consent. Their proposal can be read in conversation with a rich body of evidence to suggest current consent processes are problematic on at least one of tripartite bases in biomedical research: that it be fully informed. (...) This response attempts to further the author’s discussion of social justice discourse in, and of their proposed prosent model to enhance engagement among under-represented and vulnerable populations in research, specifically. Motivating this response is the view that advancing technological capabilities is no doubt necessary, but on its own insufficient to reinvigorate distributive, procedural and social justice as guiding principles for con/prosent processes. I offer three pros and cons to consider in effort to deepen the model’s commitments to social justice to historically marginalised groups in the biomedical research enterprise. (shrink)

The ethics of artificial intelligence and machine learning exemplify the conceptual struggle between applying familiar pathways of ethical analysis versus generating novel strategies. Mel...