The Ethics of Biomedical Big Data 29:221-238, August 2016
Rare diseases are individually rare but collectively form a population of
30 million people within Europe alone. Most rare diseases are genetic in origin
and recent research initiatives are bringing the latest genetic technologies, including whole genome sequencing, together with medical records and natural history data. The rareness of these conditions means that strategies for data sharing are a necessity to ensure that patients are able to obtain a diagnosis and the potential for treatment. Rare disease research is therefore a preeminent example of biomedical “Big Data”. This chapter explores the social and ethical challenges of biomedical “Big Data” with a focus on two case studies of contemporary rare disease research and through the framework of “solidarity” as developed by Prainsack and Buyx (2011, 2013). The analysis presented in this chapter is sympathetic to the concept of solidarity as the basis for a governance model for biomedical “Big Data” research. However there are some limitations to the solidarity model and it is argued here that a presumption of solidarity may presume too much. The principle of solidarity is very evident within the history of rare disease patient activism but this has evolved alongside other practices, characterised here as “the patient voice” which demands a more collaborative approach to the governance of research. The collaborative approach is one which allows the patient voice to be heard and respected thereby giving research participants an opportunity to be able to negotiate the conditions of participation in research. The chapter concludes with some reflections upon the future challenges for biomedical “Big Data” governance.
This chapter, published in the book “The Ethics of Biomedical Big Data” (2016), was written by Simon Woods from the Policy Ethics and Life Sciences Research Centre at the Newcastle University. He describes rare disease research as a classical example of Big Data, which requires collaborative effort and data sharing between scientists across countries. The chapter explores the social and ethical challenges of biomedical “Big Data” with a focus on two case studies of contemporary rare disease research and through the “solidarity” framework. The author emphasizes the benefits of the solidarity concept; however, he also discusses its limitations.
In his book chapter, Simon Woods mentions RD-Connect as an important exemplar of a project where solidarity meets the patient voice. He describes the collaboration between RD-Connect and EURORDIS, one of the leading organisations for the patient voice within Europe. RD-Connect addresses the ethical issues by incorporating the Rare Disease Patient and Ethics Council (RD-PEC), which responds to ethical, social and participatory issues within RD-Connect and provides an open forum for question with an ethical focus. Finally, the Patient Advisory Council (PAC) of RD-Connect ensures that the opinion of the patient community reaches the highest level of management within the project. This collaborative approach allowed for developing important policies within the project, such as policies on data sharing and consent, in a participatory way.