Integrating human exposome data into next-generation risk assessment: a systematic framework to infer real-life exposure levels and prioritize chemical compounds for testing

Exposome research and next-generation risk assessment (NGRA) share the goal of improving the human relevance of chemical safety evaluations, yet practical integration remains limited. We developed a flexible framework that combines human biomonitoring (HBM) data, exposome datasets, and exposure modeling results with chemical property, toxicity, and bioactivity information to support NGRA and chemical prioritization. The framework comprises three modules: a curated human exposome database, model-based exposure estimates, and toxicity/bioactivity data integration. Its application was demonstrated in two case studies. Case study 1 focused on organ-specific carcinogens, prioritizing candidate hepatocarcinogens. Case study 2 adopted an exposure-driven approach, highlighting compounds frequently detected in biomonitoring programs across populations. The framework generated quantitative ranges of compound concentrations in biological samples, predicted blood concentrations, and external intake values, which can be compared with in vitro toxicity benchmarks such as half-maximal activity concentration (AC50). Results show that incorporating human exposure data substantially influences chemical prioritization. This framework provides a practical pathway for embedding exposome data into NGRA workflows, thereby strengthening human-relevant risk assessments and informing future chemical safety evaluations.