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HTTK: R Package for High-Throughput Toxicokinetics
Citation:
Pearce, R., Woodrow Setzer, C. Strope, N. Sipes, AND J. Wambaugh. HTTK: R Package for High-Throughput Toxicokinetics. Journal of Statistical Software. American Statistical Association, Alexandria, VA, 79(4):1-26, (2017).
Impact/Purpose:
• Agency Research Drivers - The Frank R. Lautenberg Chemical Safety for the 21st Century Act directs the Agency to consider exposure when prioritizing chemicals for risk evaluations. To meet this Congressional mandate, the EPA needs methods to estimate levels of environmental chemicals and predict internal concentrations in humans following exposure. • Science Challenge – Use of high-throughput assays for Agency regulatory decisions is limited by uncertainties in estimating exposure dose. To address this limitation, data and tools are necessary to compare exposure model predictions with bioactive concentrations from high-throughput bioassays. • Research Approach – This research refined previous methods to extrapolate from in vitro data to human exposures, with a focus on replacing the constant infusion exposure route with more realistic human exposure pathways. The research developed new high throughput PBPK models and methods for characterizing uncertainty of these models for risk estimation. • Results – We have implemented four toxicokinetic models within a new R software package, httk. These models are designed to be parameterized using high-throughput in vitro data, as well as structure-derived physico-chemical properties and species-specific physiological data. The package can currently use human in vitro data to make predictions for 391 chemicals in humans, rats, mice, dogs, and rabbits, including 76 pharmaceuticals and 282 ToxCast chemicals • Anticipated Impact/Expected use – The tools and methods developed allow extrapolation of data on the toxicokinetics for environmental chemicals. These approaches enable exposure estimations for thousands of chemicals, addressing a critical Agency need for pre-prioritization under Frank R. Lautenberg Chemical Safety for the 21st Century Act.
Description:
Thousands of chemicals have been profiled by high-throughput screening programs such as ToxCast and Tox21; these chemicals are tested in part because most of them have limited or no data on hazard, exposure, or toxicokinetics. Toxicokinetic models aid in predicting tissue concentrations resulting from chemical exposure, and a "reverse dosimetry" approach can be used to predict exposure doses sufficient to cause tissue concentrations that have been identified as bioactive by high-throughput screening. We have implemented four toxicokinetic models within a new R software package, httk. These models are designed to be parameterized using high-throughput in vitro data (the fraction of chemical unbound to plasma and the hepatic clearance), as well as structure-derived physico-chemical properties and species-specific physiological data. The package contains tools for Monte Carlo sampling and reverse dosimetry along with functions for the analysis of concentration vs. time simulations. The package can currently use human in vitro data to make predictions for 391 chemicals in humans, rats, mice, dogs, and rabbits, including 76 pharmaceuticals and 282 ToxCast chemicals. For 65 of these chemicals the package includes rat-specific in vitro data. This package is structured to be augmented with additional chemical data as they become available. httk enables the inclusion of toxicokinetics in the statistical analysis of chemicals undergoing high-throughput screening.
