Policy strategies for personalising medicine "in the data moment". Issue 3 (September 2020) - Rajam, Neethu
Highlights: A comparison of current personalized health care policies for data driven strategies. Role of intellectual property rights, proprietary information, transparency and GDPR in the era of data oriented technologies and AI. Legal and technological challenges for the development of data driven technologies. The need for policy oriented strategies such as self-regulation and co-regulation in building great capacity for the functioning of data driven research particularly in the context of PM. Abstract: Objective: 'Data' is relevant in evolving value-based healthcare that involves machine learning and artificial intelligence-based technologies which are increasingly changing the landscape of personalised medicine (PM). However, a lack in adequate data for decision making may lead to new forms of health inequalities spite of the advancement in the technological front. There exists a dearth in alignment between incentive structures for innovation and policy measures for collective action and data transparency. Against this background, this article identifies the legal challenges for a data-driven PM in Europe. Transparency, data protection and Intellectual property rights (IP) are major legal challenges for data-oriented personalised research in Europe. Consequently, there is a need for restructuring public policy strategies in the interest of patients. Method: Legal dogmatic analysis of structural inefficiencies within interrelated legal paradigm over data that limits a functional development of a data-driven PM. Result: Engaging in the data movement in personalised health care calls for special attention to strategic tools such as co-regulation and self-regulation that bridge the gap in law and practice.