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High Throughput Toxicokinetic (HTTK) Modeling of Inhalation Exposures
Citation:
Wambaugh, J., M. Linakis, M. Evans, K. Isaacs, R. Sayre, Chris Grulke, R. Pearce, Mark A. Sfeir, M. Breen, N. Sipes, H. Pangburn, AND J. Gearhart. High Throughput Toxicokinetic (HTTK) Modeling of Inhalation Exposures. American Chemical Society Annual Meeting, Virtual, California, August 17 - 20, 2020. https://doi.org/10.23645/epacomptox.16663450
Impact/Purpose:
The is an presentation for the ACS annual meeting in San Francisco, CA. The session is on "Modernization of Inhalation Assessments".This session seeks to bring together new knowledge on various components of human health and exposure assessments, including: exposure assessment, inhalation dosimetry modeling, aggregate exposure and adverse outcome pathways, in vitro to in vivo extrapolation (IVIVE), source to outcome characterization, risk assessment, and mitigation approaches. Presentations describing original research, novel risk assessments approaches, and cases studies which address these and related topics are encouraged.
Description:
The inhalation route of chemical exposure is important for both occupational and general population exposures. Unfortunately, in vivo data describing chemical toxicokinetics (that is, absorption, distribution, metabolism, and excretion) are typically unavailable for the chemicals in commerce and the environment. “High throughput toxicokinetic methods” (HTTK) combine relatively rapid in vitro measurements of toxicokinetics with generic mathematical models that make use of the in vitro data and physico-chemical properties. We present “httk”, our HTTK software tool that includes both in vitro data and generic models. We have added generic models for inhalation exposures including both gas and aerosol chemical forms. The structures of these inhalation models have been developed from previous models but refactored to allow for parameterization with in vitro toxicokinetic data. Because the models are generic, their performance for chemicals lacking in vivo data can be estimated based on chemicals that have in vivo data available. The inhalation models have been statistically evaluated using EPA’s Concentration vs. Time toxicokinetics database (CvTdb). For the gas model, 142 exposure scenarios across 41 volatile organic chemicals were modeled and compared to published data. The slope of the regression line of best fit between log-transformed simulated and observed combined measured plasma and blood concentrations was 0.47 with an r2= 0.45 and a Root Mean Square Error (RMSE) of direct comparison between the log-transformed simulated and observed values of 1.10. Additionally, log-transformed maximum concentration (Cmax) and area under the curve (AUC) values were compared, resulting in direct comparison RMSEs of 0.47 and 0.49 respectively. HTTK inhalation models allow for in vitro-in vivo extrapolation of in vitro data on volatile compounds, enabling comparison of estimates of bioactive in vivo doses and chemical exposures. These approaches have the potential to integrate in vitro toxicity data for air pollutants into chemical risk evaluations.
URLs/Downloads:
DOI: High Throughput Toxicokinetic (HTTK) Modeling of Inhalation Exposures
ACS2020-WAMBAUGH-HTTKINHALATION.PDF (PDF, NA pp, 5272.01 KB, about PDF)