HBM4EU - Deliverable Report D 5.5: Human biomonitoring in risk assessment: 2nd set of examples on the use of HBM in risk assessments of HBM4EU priority chemicals

Abstract

The aim of this work was to exemplify the inclusion of human biomonitoring (HBM) data in risk assessment (RA) and health impact assessment (HIA) strategies. RA was performed for six compound groups on HBM4EU’s first list of priority substances: anilines, cadmium/chromium, flame retardants, PAHs, PFAS and phthalates. In addition, burden of disease (BoD) calculations were made for cadmium. The general approach used included: 1) identification of an existing RA for the substance, 2) identification of possible existing biological limit or guidance values or biological equivalents (BEs), or if lacking, existing health based limit values for external exposure, 3) identification of relevant biomonitoring data to be used in the RA, 4) in case no existing biological limit or guidance values or BEs existed, identification of approaches for reverse/forward calculation, including the use of PBPK modelling or calculation of BE values based on one-compartment modelling, 5) RA or BoD calculation based on HBM data, 6) analysing the benefits and challenges of using HBM data in RA compared to the use of external exposure data. The overall result of the work was that HBM can be included in RA even when relatively few data are available, and its inclusion generally benefits the RA. Several methods exist, and a tiered approach is suggested, based on the amount and quality of data available. The recommended 1st tier method is a one-compartment modelling based derivation of BE values or reverse calculation of external exposure based on biomarker levels. This approach is simple and rough, and uses only very basic parameters. However, in many cases this approach can be considered sufficient, especially when conservative assumptions have been used for the FUE, and the calculated RCRs remain well below 1, indicating a low risk. Also, in cases in which risk assessment using this approach supports the RA made based on external exposure estimates, it is often a sufficient approach. Nevertheless, in some cases e.g. where the RCR is close to 1, a more detailed approach may be needed to refine the RA. For the 2nd tier, PBPK modelling is recommended. For the most robust, 3rd tier approach, measured data on correlations between external exposure and internal doses from well controlled studies would be needed. Certain cases were identified where inclusion of HBM would be particularly important for performing RA: for compounds, for which several exposure routes may contribute to the body burden and the health effects, as HBM reflects the total body burden, and cumulative compounds. For cumulative compounds, HBM could also be useful for hazard assessment in addition to exposure assessment. One of the major challenges for the inclusion of HBM into RA is the often limited data available on toxicokinetics. In addition, in some cases, there is an urgent need for more specific biomarkers or more sensitive analytic methods than currently available. It should be noted that these risk assessments were performed purely to determine how HBM data can contribute to the risk assessment of chemicals, and they have no regulatory implications. Overall for the substances on the HBM4EU’s first list of priority substances, more HBM data are needed. This work is ongoing in WP8, and the RAs presented here will be updated when new data become available.