Tumor Exposomics: A New Paradigm for Individualized Continuous Exposure Monitoring

Abstract

Exposomics provides a systems‐level framework to characterize the environmental exposures experienced across the life course and their biological consequences, offering critical insights into tumor initiation and precision prevention. Advances in sensing technologies, intelligent materials, and data science now enable continuous acquisition of external exposures alongside endogenous molecular and phenotypic responses. In this emerging paradigm, exposure is conceptualized not as an isolated variable statistically associated with disease, but as a temporally structured driver embedded within multiscale biological processes. By integrating multimodal monitoring with AI‐enabled causal modeling, exposomics moves cancer risk assessment beyond population averages toward individualized, dynamically updated exposure‐informed risk assessment. This Perspective highlights key technological directions in external‐internal monitoring integration, intelligent sensing ecosystems, and causal data fusion, and outlines a translational framework aimed at supporting precision cancer prevention and early risk management.