The global political economy of stem cell therapies is characterised by an established biomedical hegemony of expertise, governance and values in collision with an increasingly informed health consumer demand able to define and pursue its own interest. How does the hegemony then deal with the challenge from the consumer market and what does this tell us about its modus operandi? In developing a theoretical framework to answer these questions, the paper begins with an analysis of the nature of the hegemony of biomedical innovation in general, its close relationship with the research funding market, the current political modes of consumer incorporation, and the ideological role performed by bioethics as legitimating agency. Secondly, taking the case of stem cell innovation, it explores the hegemonic challenge posed by consumer demand working through the global practice based market of medical innovation, the response of the national and international institutions of science and their reassertion of the values of the orthodox model, and the supporting contribution of bioethics. Finally, the paper addresses the tensions within the hegemonic model of stem cell innovation between the key roles and values of scientist and clinician, the exacerbation of these tensions by the increasingly visible demands of health consumers, and the emergence of political compromise.
Computational brain models use machine learning algorithms and statistical models to harness big data for delivering disease-specific diagnosis or prognosis for individuals. They are intended to support clinical decision making and are widely available. However, their translation into clinical practice remains weak despite efforts to improve implementation such as through training clinicians and clinical staff in their use and benefits. In this paper, we argue that it is necessary to go beyond existing implementation efforts to understand and meaningfully integrate the clinician's perspective and tacit knowledge for This is an Accepted Manuscript of an article published by Taylor & Francis in Interdisciplinary Science Reviews 2 translating computational brain models in neurological practice. The empirical research draws on our collective seven-year engagement with the Human Brain Project as researchers of its 'Ethics and Society' subproject and includes analysis of published and grey literature, participant observation at workshops and conferences, and interviews with data scientists, neuroscientists, and neurologists in the UK and Europe developing computational tools for neurology.Our findings show that building trust in the relationships between clinicians and researchers (modelers, data scientists) through meaningful upstream collaboration, greater model transparency and integration of tacit knowledge play a salient role in translation processes with meaningful benefit for patients.
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