Improved Risk Assessment through the integration of toxicokinetic modelling to connect external exposure to internal dose: the case of persistent chemicals

摘要

Biomonitoring data has many advantages for exposure assessment since it represents an integration of exposure from all sources and routes, takes into account the accumulation of the chemical in the body and represents direct measurements of the dose of the chemical substance that is really taken up from the environment (internal dose). Although the availability of human biomonitoring data can greatly improve the risk assessment especially for persistent chemicals, their interpretation often remains their main weakness because of the inability to identify the different sources of exposure, their relative contribution to the total exposure or to interpret it in terms of individual behaviors. Consequently, biomonitoring data needs to be linked with external exposure for interpretation through the integration of toxicokinetic modelling. The objective of this work is thus to propose a method which makes it possible to combine all the information available to assess the exposure and to link external and internal exposure using relevant toxicokinetic models and integrating inter and intra individual variability when possible. Two case studies were conducted: dioxins with dioxin-like PCBs and cadmium. Focusing on cadmium, concentration in the urine of the French population from French Nutrition and Health Survey (ENNS) were used. Dietary and smoking habits recorded in the ENNS study were combined with contamination levels in food and cigarettes to assess individual exposures. A physiologically based toxicokinetic (PBTK) model was used in a Bayesian population model to link this external exposure with the measured urinary concentrations. In this model, the level of the past exposure was corrected thanks to a scaling function which account for a trend in the French dietary exposure. It resulted in a modelling which was able to explain the current urinary concentrations measured in the French population through current and past exposure levels. Risk related to cadmium exposure in the general French population was then assessed from external and internal critical values corresponding to kidney effects. This work illustrates how the combination of different data in a population modelling can improve risk assessment for persistent chemical. It does not aim to convince that all this data are needed to evaluate the risk but rather to investigate what can be learned when combining all the data.