High throughput toxicokinetic (HTTK) modeling of inhalation exposures
presentationposted on 22.09.2021, 19:18 by John Wambaugh, Matthew Linakis, Marina V. Evans, Kristin Isaacs, Risa Sayre, Christopher Grulke, Robert Pearce, Mark Sfeir, Miyuki Breen, Nisha Sipes, Heather Pangburn, Jeffery M. Gearhart
The inhalation route is important for both occupational and general population chemical 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 and integrates both in vitro data and toxicokinetic models. We have recently added models for inhalation of both gases and aerosols. The structures of these inhalation models are refactored from previous models to allow for parameterization with in vitro toxicokinetic data. Because the models are generic, their expected 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, resulting blood and/or plasma concentrations of 41 volatile organic chemicals were modeled across 142 exposure scenarios and compared to published data. The slope of the regression line of best fit between log-transformed simulated and observed measured plasma and/or blood concentrations was 0.47 with an r2= 0.45 and a log-scale Root Mean Square Error (RMSE) 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 volatile compounds, enabling comparison of estimates of bioactive in vivo doses with estimates of chemical exposures. These approaches have the potential to integrate in vitro toxicity data for air pollutants into chemical risk evaluations.
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