Operationalising the exposome across environmental, consumer and industrial chemicals for public-health protection

Abstract

Purpose:

To demonstrate how the exposome can deliver decision-grade, life-course evidence across a broad chemical universe – encompassing environmental contaminants, consumer-product ingredients and industrial chemicals – and to show how this evidence translates into prevention targets and policy.

Methods:

Building on developments and results of past and running exposome and chemical risk assessment projects (HEALS, ICARUS, URBANOME, PARC, ENVESOME), we propose a comprehensive methodological pipeline that integrates: (i) generic lifelong PBPK/PBBK models to translate multi-route, multi-chemical exposures (inhalation, ingestion, dermal) into internal dosimetry across developmental stages; parameterisation leverages QSAR/read-across, Bayesian calibration to human biomonitoring, and mixture kinetics. (ii) Human-centred exposure modelling that fuses wearables and indoor/outdoor multimedia fate with agent-based activity and product-use profiles, capturing microenvironments (home, work, transport) and socio-spatial heterogeneity. (iii) High-resolution mass spectrometry (suspect screening and non-target analysis), effect-directed assays, adductomics and multiomics readouts mapped to AOP networks to connect external dose with early biological effects. (iv) Causal mixture analytics (e.g., g-methods, BKMR, WQS) and target-trial emulation under compute-to-data/federated learning to respect governance of sensitive health and product data. (v) Decision engines that run intervention scenarios (safe and sustainable chemical innovation, substitution, reformulation, procurement, ventilation/filtration, dietary shifts) and rank options by attributable risk, benefit-cost and equity.

Results:

Across European cohorts and cities, the pipeline resolves contributions from persistent and semi-volatile organics (PFAS, phthalates, bisphenols, flame retardants), pesticides, solvents, metals, indoor emissions and air pollutants, alongside chemical mixtures arising from food, drinking water, dust and personal-care products. It quantifies window-specific vulnerabilities (preconception, pregnancy, infancy, adolescence), sex-specific differences, and high-impact microenvironments. Federated analyses enable cross-site generalisation and full bias/calibration audits without centralising personal or proprietary data. Scenario tests show that targeted chemical substitution and in-door-environment controls often deliver larger near-term health gains than uniform ambient measures, while combined strategies maximise equity by reducing exposures in disadvantaged groups. Outputs include decision-grade internal-dose and effect-biomarker metrics, mixture-aware hazard indices and auditable uncertainty bounds suitable for regulatory uptake.

Conclusions:

The exposome becomes operational for regulators and public-health agencies when mechanistic dosimetry, discovery-oriented analytics and data-proximate causal inference are implemented under Good Exposome Practices and EHDS-aligned governance. Priorities include mixture-ready PBPK libraries, standardised reporting/validation, routine compute-to-data for confidential datasets, and embedding exposome metrics into prevention targets for vulnerable populations – turning complex chemical realities into tractable, actionable and equitable protection.