Session Introduction: Precision Medicine: Integrating Large-Scale Data and Intermediate Phenotypes for Understanding Health and Treating Disease

Abstract

The field of precision medicine has undergone rapid development over the past three decades, driven by advances in high-throughput molecular profiling, large-scale electronic health data, and computational modeling. The central objective is to refine disease risk prediction, diagnosis, and treatment strategies by incorporating genetic, molecular, environmental, and clinical information into individualized care. However, the effective integration of these heterogeneous data sources presents substantial analytical challenges. The 2026 Precision Medicine session of the Pacific Symposium on Biocomputing (PSB) highlights computational methods that bridge large-scale biological data and intermediate phenotypes, emphasizing approaches that advance mechanistic understanding, risk prediction, and clinical utility. The contributions span multi-modal risk modeling, biomarker discovery, and causal inference frameworks, demonstrating the breadth and depth of research in computational precision medicine.

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