httk : R Package for High-Throughput Toxicokinetics

• Published in: Journal of statistical software Vol. 79; no. 4; pp. 1 - 26
• Main Authors: Pearce, Robert G., Setzer, R. Woodrow, Strope, Cory L., Sipes, Nisha S., Wambaugh, John F.
• Format: Journal Article
• Language: English
• Published: United States Foundation for Open Access Statistics 17.07.2017
• Subjects: high-throughput; httk; pharmacokinetics; ToxCast; toxicokinetics; pharmacokinetics; toxicokinetics; httk; ToxCast; high-throughput
• ISSN: 1548-7660; 1548-7660
• DOI: 10.18637/jss.v079.i04

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 created four toxicokinetic models within the R software package . These models are designed to be parameterized using high-throughput data (plasma protein binding and hepatic clearance), as well as structure-derived physicochemical 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 data to make predictions for 553 chemicals in humans, rats, mice, dogs, and rabbits, including 94 pharmaceuticals and 415 ToxCast chemicals. For 67 of these chemicals, the package includes rat-specific data. This package is structured to be augmented with additional chemical data as they become available. Package enables the inclusion of toxicokinetics in the statistical analysis of chemicals undergoing high-throughput screening.