Mobile devices with health apps, direct-to-consumer genetic testing, crowd-sourced information, and other data sources have enabled research by new classes of researchers. Independent researchers, citizen scientists, patient-directed researchers, self-experimenters, and others are not covered by federal research regulations because they are not recipients of federal financial assistance or conducting research in anticipation of a submission to the FDA for approval of a new drug or medical device. This article addresses the difficult policy challenge of promoting the welfare and interests of (...) research participants, as well as the public, in the absence of regulatory requirements and without discouraging independent, innovative scientific inquiry. The article recommends a series of measures, including education, consultation, transparency, self-governance, and regulation to strike the appropriate balance. (shrink)

Public-private partnerships are established to specifically harness the potential of Big Data in healthcare and can include partners working across the data chain—producing health data, analysing data, using research results or creating value from data. This domain paper will illustrate the challenges that arise when partners from the public and private sector collaborate to share, analyse and use biomedical Big Data. We discuss three specific challenges for PPPs: working within the social licence, public antipathy to the commercialisation of public sector (...) health data, and questions of ownership, both of the data and any resulting intellectual property or products. As a specific example we consider the case of the UK National Health Service providing patient data to Google’s DeepMind AI program to develop a diagnostic app for kidney disease. This article is an application of the framework presented in this issue of ABR. Please refer to that article for more information on how this framework is to be used, including a full explanation of the key values involved and the balancing approach used in the case study at the end. We use four specific values to help analysis these issues: public benefit, stewardship, transparency and engagement. We demonstrate how the Deliberative Framework can support ethical governance of PPPs involving biomedical big data. (shrink)

Engaging patients in research has come to be viewed as a vital component of high‐quality research, and funders now regard engaging patients and other stakeholders as a core criterion for funding decisions. In response, numerous empirical and conceptual papers have emerged to guide the process of engagement. However, as Emily Largent and colleagues rightly note, the inquiry of whom to engage has received less attention. While several teams have suggested that the selection of patients for engagement is an important consideration, (...) researchers generally have little guidance on how to undertake this process. To that end, Largent and colleagues offer an important contribution to the literature. I agree with their argument regarding the centrality of critically examining which patients to engage in research and with their recommendations to maximize the positive goals of patient engagement. However, three issues warrant further consideration. (shrink)