RESUMO
Mandates that require the estimation of exposure and human health risk posed by large numbers of chemicals present regulatory managers with a significant challenge. Although these issues have been around for some time, the estimation of human exposure to chemicals from use of products in the workplace and by the consumer has been generally hindered by the lack of good tools. Logically and in the interest of cost-effective resource allocation and regulation one would typically and naturally first attempt to rank-order or prioritize the chemicals according to the human exposure potential that each might pose. We have developed an approach and systematic modeling construct that accomplishes this critical task by providing a quantitative estimate of human exposure for as many as several hundred chemicals initially; however, it could ultimately do this for any number of regulated chemicals starting only with the identity (Chemical Abstract Service number) for each chemical under consideration. These exposure estimates can then be readily linked to toxicological benchmarks for each item to estimate and rank the human health risk for the chemicals under consideration in a "worst things first" listing. This modeling construct, entitled Complex Exposure Tool (ComET) was developed by The LifeLine Group as a proof of concept under the sponsorship of Health Canada. ComET considers multiple routes of exposure, multiple subpopulations and different possible durations of exposure. A beta-version of ComET was issued and demonstrated in which users can change the assumptions in the model and see the impacts of these changes and the quality of information as they relate to the predicted exposure potential. We have advanced the operational elements of ComET into a tool entitled the Chemical Exposure Priority Setting Tool (CEPST) designed to provide quantitative estimation of the exposure potential of large groups of chemicals with little data and possibly multiple exposure scenarios. A basic feature of this tool is the utilization of an internally consistent approach and assumptions that are completely transparent. It uses publicly available information as critical input and is specifically designed to be continually reviewed, refined, expanded and updated using scientific peer review and stakeholder input.