4.5 Article

Current landscape of personalized medicine adoption and implementation in Southeast Asia

期刊

BMC MEDICAL GENOMICS
卷 11, 期 -, 页码 -

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BMC
DOI: 10.1186/s12920-018-0420-4

关键词

Personalized medicine; Pharmacogenomics; Implementation; Southeast Asia

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BackgroundThe emergence of personalized medicine (PM) has raised some tensions in healthcare systems. PM is expensive and health budgets are constrained - efficient healthcare delivery is therefore critical. Notwithstanding the cost, many countries have started to adopt this novel technology, including resource-limited Southeast Asia (SEA) countries. This study aimed to describe the status of PM adoption in SEA, highlight the challenges and to propose strategies for future development.MethodsThe study included scopingreview and key stakeholder interviews in four focus countries - Indonesia, Malaysia, Singapore, and Thailand. The current landscape of PM adoption was evaluated based on an assessment framework of six key themes - healthcare system, governance, access, awareness, implementation, and data. Six PM programs were evaluated for their financing and implementation mechanisms.ResultsThe findings revealed SEA has progressed in adopting PM especially Singapore and Thailand. A regional pharmacogenomics research network has been established. However, PM policies and programs vary significantly. As most PM programs are champion-driven and the available funding is limited, the current PM distribution has the potential to widen existing health disparities. Low PM awareness in the society and the absence of political support with financial investment are fundamental barriers. There is a clear need to broaden opportunities for critical discourse about PM especially for policymakers. Multi-stakeholder, multi-country strategies need to be prioritized in order to leverage resources and expertise.ConclusionsAdopting PM remains in its infancy in SEA. To achieve an effective PM adoption, it is imperative to balance equity issues across diverse populations while improving efficiency in healthcare.

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