Generic physiologically-based pharmacokinetic (PBPK) models were used to explore how saturable absorption or clearance can influence the shape of the internal to external concentration (IEC) relationship. The models were used for hypothetical chemicals to show how differences in kinetic parameters can impact the shape of an IEC relationship; and the models for styrene and caffeine were used to explore how exposure route, frequency, and duration impact the IEC relationships in rat and human exposures. We also analyzed available plasma concentration data for 2,4-dichlorophenoxyacetic acid (data from Saghir et al. 2013; https://doi.org/10.1093/toxsci/kft212) to demonstrate how a PBPK modeling approach can be an alternative to common statistical methods for analyzing dose proportionality. These files contain the model code and utilized parameters for each of these case studies as well as a link to the publicly available dataset from Saghir et al. 2013 (https://doi.org/10.1093/toxsci/kft212). Citation information for this dataset can be found in Data.gov's References section.

Estimates of ionization equilibrium constants (i.e., pKa) were analyzed for 8,132 pharmaceuticals and 24,281 other compounds to which humans might be exposed in the environment. Results revealed broad differences in the ionization of pharmaceutical chemicals and chemicals with either near-field (in the home) or far-field sources. Probability distributions corresponding to ionizable atom types (IATs) were then used to analyze the sensitivity of predicted Vdss on predicted pKa using Monte Carlo methods. 8 of the 22 compounds were predicted to be ionizable. For 5 of the 8 the predictions based upon ionization are significantly different from what would be predicted for a neutral compound. For all but one (foramsulfuron), the probability distribution of predicted Vdss generated by IAT sensitivity analysis spans both the neutral prediction and the prediction using ionization. This dataset is associated with the following publication: Strope, C., K. Mansouri, H. Clewell, J. Rabinowitz, C. Stevens, and J. Wambaugh. High-Throughput in-silico prediction of ionization equilibria for pharmacokinetic modeling. SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM, NETHERLANDS, 615: 150-160, (2018).

The dataset includes source code that was used to perform analyses described in the manuscript "Evaluating Impact of Anatomical and Physiological Variability on Human Equivalent Doses Using PBPK Models" by Schacht et al.

General aggregate PFOS and PFOA exposure estimates are based on reported summary statistics from concentration studies by media, i.e. into indoor air, outdoor air, food, water, dust and soil, and published contact rates. These values were entered into a first-order PK model to estimate PFOS and PFOA blood serum concentrations. which were then compared measured concentrations reported by the 2013-2014 National Health and Nutrition Examination Survey (NHANES) measured concentrations. These methods are an expansion of the process taken by two previous studies, which predicted body burden from aggregate route intakes for PFOA and for PFOS, respectively. This dataset is associated with the following publication: East, A., P. Egeghy, E. Hubal, R. Slover, and D. Vallero. Computational estimates of daily aggregate exposure to PFOA/PFOS from 2011 to 2017 using a basic intake model. Journal of Exposure Science and Environmental Epidemiology. Nature Publishing Group, London, UK, 33: 56-68, (2023).

httk: High-Throughput Toxicokinetics Functions and data tables for simulation and statistical analysis of chemical toxicokinetics ("TK") using data obtained from relatively high throughput, in vitro studies. Both physiologically-based ("PBTK") and empirical (e.g., one compartment) "TK" models can be parameterized for several hundred chemicals and multiple species. These models are solved efficiently, often using compiled (C-based) code. A Monte Carlo sampler is included for simulating biological variability and measurement limitations. Functions are also provided for exporting "PBTK" models to "SBML" and "JARNAC" for use with other simulation software. These functions and data provide a set of tools for in vitro-in vivo extrapolation ("IVIVE") of high throughput screening data (e.g., ToxCast) to real-world exposures via reverse dosimetry (also known as "RTK"). This dataset is associated with the following publication: Pearce , R., C. Strope , W. Setzer , N. Sipes , and J. Wambaugh. (Journal of Statistical Software) HTTK: R Package for High-Throughput Toxicokinetics. Journal of Statistical Software. American Statistical Association, Alexandria, VA, USA, 79(4): 1-26, (2017).

Contains values from pbpk models for each study on n-butanol effects. This dataset is associated with the following publication: Segal, D., A. Bale, L. Phillips, A. Sasso, P. Schlosser, C. Starkey, and S. Makris. Issues in Assessing the Health Risks of n-Butanol. JOURNAL OF APPLIED TOXICOLOGY. John Wiley & Sons, Ltd., Indianapolis, IN, USA, 40(1): 72-86, (2020).

This data set includes source code files and associated data files that implement a pharmacokinetic (PK) model for lipophilic persistent environmental chemicals (LPECs) that can be used to simulate various exposure scenarios involving pregnant and nursing maternal animals and offspring. The model is described in a manuscript entitled "A Generic Pharmacokinetic Model for Mother-to-Offspring Transfer of Lipophilic Persistent Environmental Chemicals" by Kapraun et al.

Dataset for "Incorporating human exposure information in a weight of evidence approach to inform design of repeated dose animal studies". This dataset is associated with the following publication: Lowe, K., J. Dawson, K. Phillips, J. Minucci, J. Wambaugh, H. Qian, T. Ramanarayanan, P. Egeghy, B. Ingle, R. Brunner, E. Mendez, M. Embry, and C. Tan. Incorporating human exposure information in a weight of evidence approach to inform design of repeated dose animal studies. REGULATORY TOXICOLOGY AND PHARMACOLOGY. Elsevier Science Ltd, New York, NY, USA, 127: 105073, (2021).

The files and .R scripts here are provided to aid in understanding and reproduction of the analyses in the submitted paper, "Examining the Utility of In Vitro Bioactivity as a Protective Point of Departure: A Case Study." The scripts in the .R folder reference source files in the other folders. This dataset is associated with the following publication: Friedman, K., M. Gagne, L. Loo, P. Karamertzanis, T. Netzeva, T. Sobanski, J. Franzosa, A. Richard, R. Lougee, A. Gissi, J.J. Lee, M. Angrish, J. Dorne, S. Foster, K. Raffaele, T. Bahadori, M. Gwinn, J. Lambert, M. Whelan, M. Rasenberg, T. Barton-Maclaren, and R. Thomas. Utility of In Vitro Bioactivity as a Lower Bound Estimate of In Vivo Adverse Effect Levels and in Risk-Based Prioritization. TOXICOLOGICAL SCIENCES. Society of Toxicology, RESTON, VA, 173(1): 202-225, (2020).