Trustworthy Governance of Genomic and Health-Related Data: Lessons from Singapore

Abstract

Precision medicine (PM) is an approach to research and healthcare delivery driven by insights from linked genomic, epigenetic, clinical, behavioural, and environmental data. Data sharing for PM, especially between parties with divergent strategic and commercial interests, requires balancing competing values, creating a trusted data ecosystem, and maintaining social license. This paper integrates findings from normative bioethics and empirical research in Singapore to discern recommendations for guidance on the ethical governance of genomic and health data. We distil findings from mixed methods research in Singapore and map these onto Kalkman et al.’s themes and principles for data sharing. Based on our normative and empirical analyses, we argue that the values of public benefit, fairness, accountability, and transparency are critical for maintaining social license for PM in Singapore. Consent is important but insufficient to secure public trust or support for data sharing if these other normative values are not achieved. Contrary to assertions in much of the existing bioethics literature on genomic and health data sharing, we found that different consent options (such as specific versus broad consent) had little impact on social license for data sharing. Our analysis provides empirically grounded, contextually appropriate, responsive normative guidance for trustworthy data governance in Singapore. While our findings are specific to Singapore's cultural and institutional context, our methodological approach and the relative de-emphasis of individual consent models offer important insights for other jurisdictions developing PM programs, particularly in non-Western settings where collective values may take precedence over individual autonomy.