httk: R Package for High-Throughput Toxicokinetics

Robert G. Pearce, R. Woodrow Setzer, Cory L. Strope, Nisha S. Sipes, John F. Wambaugh.
Journal of Statistical Software (2017) DOI: https://doi.org/10.18637/jss.v079.i04 PMID: Not available

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Abstract

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 httk. These models are designed to be parameterized using high-throughput in vitro 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 in vitro 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 in vitro data. This package is structured to be augmented with additional chemical data as they become available. Package httk enables the inclusion of toxicokinetics in the statistical analysis of chemicals undergoing high-throughput screening.

Figures

Figure 1. Models (A) 1compartment, (B) 3compartment, and (C) pbtk.

In order to preserve mass-balance, Q_rest is defined as the difference between Q_cardiac and the flow to the liver, kidney, and gut. Variable names are defined in Table 1.

Figure 1 (85 KB)

Figure 2. C_ss at 3 doses per day, 1 mg/kg BW/day.

Figure 2 (76 KB)

Figure 3. Days to steady state histogram.

Figure 3 (47 KB)

Figure 4. Average vs. maximum concentration at steady state for 1 dose per day, 1 mg/kg BW/day.

Figure 4 (83 KB)

Figure 5. Sampling distribution of zoxomide Css from the model pbtk.

Figure 5 (63 KB)

Tables

Table 1. List of abbreviations.

Table 1 (79 KB)

Table 2. Model parameter and prediction comparison.

*Partition coefficients are needed in calculating V_dist . Clearances and f_ub are needed in calculating k_elim.

Table 2 (112 KB)

Table 3. List of data tables in the package.

In Ring et al. (2017), a series of tables for generating populations based on variation in human physiology were added. They are described in that manuscript and vignettes.

Table 3 (124 KB)

Table 4. List of functions in the package – Part I.

Models are described in Table 2. Parameters are defined in Table 1. Jarnac and SBML are external languages for systems biology models.

Table 4 (117 KB)

Table 5. List of functions in the package – Part II.