Strategy for mixture risk assessment using European human biomonitoring data: lessons learned from applications to pesticides, per- and polyfluoroalkyl substances and metal(loid)s

Abstract

Humans are exposed daily to mixtures of chemicals from multiple sources and routes, including diet and the environment. These combined exposures may cause adverse health effects that are not adequately captured by conventional substance-by-substance risk assessment, due to the inherent complexity of assessing combined risks. To address this gap, the Partnership for the Assessment of Risks from Chemicals (PARC) Real-life Mixtures project aims to consolidate scientific knowledge regarding mixture risk assessment (MRA). In synergy with ongoing activities of European agencies and other initiatives, this project developed a strategy to perform MRA using human biomonitoring (HBM) data. The approach consists of five steps: (1) prioritisation of chemical mixtures of interest for human health to guide case-study selection; (2) collection and organisation of the data required for MRA, including exposure, hazard, and toxicokinetic information; (3) development of methods for conducting MRA using HBM data; (4) implementation of these methods within the Monte Carlo Risk Assessment (MCRA) toolbox; and (5) application of the strategy to prioritised case studies. Three chemical families and four associated adverse health outcomes were selected based on the results of PARC priority process: pesticides affecting the nervous system, per- and polyfluoroalkyl substances (PFAS) affecting the immune system, and metal(loid)s affecting kidney function and neurodevelopment. HBM data from studies conducted across Europe and Greenland were harmonised using the HBM data toolkit. Hazard and toxicokinetic data were compiled to derive internal toxicological values suitable for MRA. The MRA was then performed in a harmonised way for each case study using the MCRA toolbox. The strategy developed within the PARC Real-life Mixtures project provides a proof-of-concept for conducting HBM-based MRA and for informing policymakers. Future research will focus on reducing uncertainties and expanding the approach to additional chemicals with common health endpoints and co-exposure. © 2026 The Author(s).