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Probabilistic Aggregate Exposure Modelling for a Broad Spectrum Antimicrobial in Personal Cleansing Products


Realistic estimates of chemical aggregate exposure are needed to ensure consumer safety and satisfy the requirements of regulators. In most cases, aggregate exposure is estimated simply by adding deterministic exposures from all product types containing the chemical. However, this summation will result in an unrealistically-conservative estimate since individuals vary in their patterns of product use, and it is very unlikely that consumers use high levels of all products at the same time. As aggregate exposure estimates could be used to calculate acceptable “safe levels” and conduct risk assessments for chemicals, methods are needed to produce realistic exposure estimations.


A probabilistic aggregate exposure model was developed to estimate consumer exposure in Europe and North America to a hypothetical broad spectrum biocide, from a range of rinse off personal cleansing products. It incorporates large habits and practices surveys, from industry/cosmetic trade associations, containing data on frequency of use, amount, co-use along with market share, and combines these data at the level of the individual based on subject demographics (gender, age, ethnicity) to realistically calculate exposure. Results: When the antimicrobial was assumed present in five rinse off products (Shampoo: 2% and other products: 0.5%), the average daily applied exposure (amount applied to the skin) was estimated at 1.65 mg/kg/day for the average person and 3.79 mg/kg/day for the 95th percentile consumer. This probabilistic modelling offers significant exposure refinement versus deterministic aggregate summation methods.


This probabilistic aggregate exposure model provides robust data that can be used in the human safety assessment of multiple rinse-off technologies (e.g., shampoo, bar soap, body wash, liquid hand soap) containing the biocide. In addition, this model may be used in other situations where refined exposure assessment is required to support a chemical risk assessment.

Authors: Tozer Sarah, J F Nash, and E.J. Daly

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