Workshop Report 31

Modelling Total Exposure to Chemicals in Multiple Sources

For the purposes of the ECETOC task force work, Exposure assessment is defined as “Exposure to a chemical from multiple sources and pathways, entering via different routes”. Aggregate exposure assessment is becoming a consideration in safety assessments in some sectors, whereas in other consumer product categories, it is less frequently considered as products may not be frequently used together. However, for chemicals that are ubiquitous, consumer exposure may even come from multiple sources (foods, consumer products) and via multiple routes. Aggregate exposure should be estimated using a tiered approach (Delmaar and van Engelen, 2006; Meek et al., 2011) which begins with a conservative deterministic


estimation of exposure and evolves, as needed, to a more refined person-orientated probabilistic approach. Such high tier assessments of aggregate exposure can help to accurately represent the relative exposure sources. Dr Tozer shared examples of higher tier exposure estimates, including zinc pyrithione (a preservative) (Tozer et al., 2015); vitamin A, and aluminium. These examples demonstrated that, for high tier assessments across domains, there is a need for access to population input data and tools including products from multiple domains. Currently available subject-orientated tools tend to be domain specific. Probabilistic aggregate exposure modeling, conducted at the level of individuals in the population, provides realistic estimates of exposure to ingredients present in multiple products & foods. Anonymised data sharing on product composition is a clear need. Other consumer product categories need to be better explored (i.e. the frequency that products are used) in order to increase understanding on when different consumer products are used together.

In the discussion that followed, it was concluded that there is a need for confidence in the data, tools and models. It was recommended that this could be achieved through a verification mechanism of their “fit for purpose”. In the occupational setting, some best practice guidance exists to ensure exposure data quality – and this could potentially be adapted and extrapolated to consumer exposure settings. An internationally recognised rating system to evaluate the quality of data would enable the evaluation of quality data. Transparency is a pre-requisite for confidence in data and mechanisms to achieve this should be established.