With the passing of the Frank R. Lautenberg Chemical Safety for the 21st Century Act, the Toxic Substances Control Act was amended to require risk assessors to consider susceptible subpopulations when prioritizing compounds for risk assessment. While high-throughput consumer exposure models can be modified to account for some populations that can be considered susceptible (e.g., sensitive age groups), there are relatively few high-throughput models capable of addressing the chemical exposure scenarios encountered by workers (another susceptible group). Existing lower-throughput models (i.e., models that calculate the exposure for a single chemical over a single pathway and exposure scenario) are often contained in graphical user interfaces that make these models unamenable to incorporation with high-throughput models. Additionally, data collected across the US workforce measuring the amount of chemical to which various workers are exposed can be difficult to obtain.
In this month's Computational Toxicology Communities of Practice meeting, we will discuss adaptation of existing occupational exposure models, namely those contained within the Environmental Protection Agency (EPA) Chemical Screening Tool for Exposure and Environmental Releases (ChemSTEER) to meet high-throughput needs. The US Occupational Health and Safety Administration's Chemical Exposure Health Data provides a wealth of concentrations of chemicals measured in the workplace. While there are caveats to these data, with more than 1 million air samples over a 34 year span, this dataset provides one of the largest publicly available sources for occupational exposure measurements. In addition to describing efforts for collection and compilation of this data to a single data set, we will discuss how these data are used to develop statistical models which explore the presence and concentration of compounds in various industries.