Implementing Big Data-Driven Precision Medicine for Improved Clinical Outcomes in East Asia

Abstract

Precision medicine is an emerging approach for disease treatment and prevention that takes into account individual variability in genes, environment, and lifestyle. Big data analytics enables the integration of massive amounts of biomedical data from genomic sequencing, electronic health records, imaging, etc. to understand disease and predict optimal therapies based on patient-specific parameters. Implementing big data-driven precision medicine holds great promise for improving clinical outcomes in East Asian populations through more targeted and personalized care. However, there are significant challenges that must be addressed around patient privacy, data sharing, clinical translation, and evaluation of utility. This article reviews the current landscape and future directions for applying big data analytics to enable precision medicine and improve patient outcomes in East Asia. Key focus areas include developing comprehensive biobanks, data integration frameworks, clinical decision support systems, and robust methods for validating utility. Addressing these areas in a coordinated, evidence-based manner will be critical to overcoming barriers and fully realizing the potential of big data-enabled precision medicine across East Asia.