Dataset for "Evaluating the utility of the Threshold of Toxicological Concern (TTC) and its exclusions in the biocompatibility assessment of extractable chemical substances from medical devices". This dataset is associated with the following publication: Patlewicz, G., M. Nelms, and D. Rua. Evaluating the utility of the Threshold of Toxicological Concern (TTC) and its exclusions in the biocompatibility assessment of extractable substances from medical devices. Computational Toxicology. Elsevier B.V., Amsterdam, NETHERLANDS, 24: 100246, (2022).

All of the code used to analyze and report the data as well as build confidence in the approach is available as a supplementary RMarkdown report, and a tool to derive PODBioactivity and PODRead-Across is available as an RShiny web-application. The data used in the workflow are either available on public databases or are included in the supplementary material to allow for reproducibility of results. The results and output of the workflow (i.e., chemical info, PODs, etc.) are provided in the supplementary material (available as a download from the journal article). This dataset is associated with the following publication: Beal, M., M. Gagne, S. Kulkarni, G. Patlewicz, R. Thomas, and T. Barton-Maclaren. Implementing in vitro Bioactivity Data to Modernize Priority Setting of Chemical Inventories. ALTEX. Society ALTEX Edition, Kuesnacht, SWITZERLAND, 39(1): 123-139, (2022).

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., W. Setzer, J. Davis, and J. Wambaugh. Evaluation and Calibration of High-Throughput Predictions of Chemical Distribution to Tissues. JOURNAL OF PHARMACOKINETICS AND PHARMACODYNAMICS. Springer, New York, NY, USA, 44(6): 549-565, (2017).

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., W. Setzer, J. Davis, and J. Wambaugh. Evaluation and Calibration of High-Throughput Predictions of Chemical Distribution to Tissues. JOURNAL OF PHARMACOKINETICS AND PHARMACODYNAMICS. Springer, New York, NY, USA, 44(6): 549-565, (2017).

We report on new, in vivo TK experiments in rats for 26 chemicals more commonly associated with non-therapeutic and/or unintentional exposure. These chemicals, and an additional 19 chemicals from previously published in vivo rat studies, were systematically analyzed to estimate relevant TK parameters (e.g., volume of distribution, elimination rate). Our analysis created a library of TK parameters for 38 chemicals for which rat-specific in vitro HTTK data were also available. This dataset is associated with the following publication: Wambaugh, J., M. Hughes, C. Ring, D. MacMillan, J. Ford, T. Fennell, S. Black, R. Snyder, N. Sipes, B. Wetmore, J. Westerhout, W. Setzer, R. Pearce, J. Simmons, and R. Thomas. Evaluating In Vitro-In Vivo Extrapolation of Toxicokinetics. TOXICOLOGICAL SCIENCES. Society of Toxicology, RESTON, VA, 163(1): 152-169, (2018).

We report on new, in vivo TK experiments in rats for 26 chemicals more commonly associated with non-therapeutic and/or unintentional exposure. These chemicals, and an additional 19 chemicals from previously published in vivo rat studies, were systematically analyzed to estimate relevant TK parameters (e.g., volume of distribution, elimination rate). Our analysis created a library of TK parameters for 38 chemicals for which rat-specific in vitro HTTK data were also available. This dataset is associated with the following publication: Wambaugh, J., M. Hughes, C. Ring, D. MacMillan, J. Ford, T. Fennell, S. Black, R. Snyder, N. Sipes, B. Wetmore, J. Westerhout, W. Setzer, R. Pearce, J. Simmons, and R. Thomas. Evaluating In Vitro-In Vivo Extrapolation of Toxicokinetics. TOXICOLOGICAL SCIENCES. Society of Toxicology, RESTON, VA, 163(1): 152-169, (2018).

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).

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).

Functions and data tables for simulation and statistical analysis of chemical toxicokinetics ("TK") as in Pearce et al. (2017) . Chemical-specific in vitro data have been obtained from relatively high throughput experiments. 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. 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).

Functions and data tables for simulation and statistical analysis of chemical toxicokinetics ("TK") as in Pearce et al. (2017) . Chemical-specific in vitro data have been obtained from relatively high throughput experiments. 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. 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).