This investigation was broken down into three interrelated steps: data collection, model building, and model evaluation. R software (v. 3.5.1) with the httk package (v. 1.9) was used for data organization, analysis, and visualization. All models and data associated with this manuscript are available in httk vX. This dataset is associated with the following publication: Linakis, M., R. Sayre, R. Pearce, M.A. Sfeir, N. Sipes, H. Pangburn, J. Gearhart, and J. Wambaugh. Development and Evaluation of a High Throughput Inhalation Model for Organic Chemicals. Journal of Exposure Science and Environmental Epidemiology. Nature Publishing Group, London, UK, 30(5): 866-877, (2020).

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).

An effort was made to derive new inhalation TTC values using the EPA’s Toxicity Values database, ToxValDB. A total of 4703 substances captured in ToxValDB were assigned into their respective TTC categories using the Kroes module within the Toxtree software tool and custom profilers developed in Nelms et al (2019) and Patlewicz et al (2018). For the substances assigned into the 3 Cramer classes, the 5th percentiles were calculated from the empirical cumulative distributions of No observed (adverse) effect level (concentration) values. The 5th percentiles were converted to their respective TTC values and compared with published values reported by Escher et al (2010) and Carthew et al (2009). The TTC values derived from ToxValDB were orders of magnitude more conservative, further Cramer classification was not found to be effective at discriminating potencies. This dataset is associated with the following publication: Nelms, M., and G. Patlewicz. Derivation of New Threshold of Toxicological Concern Values for Exposure via Inhalation for Environmentally-Relevant Chemicals. Frontiers in Toxicology. Frontiers, Lausanne, SWITZERLAND, 2: 580347, (2020).

An effort was made to derive new inhalation TTC values using the EPA’s Toxicity Values database, ToxValDB. A total of 4703 substances captured in ToxValDB were assigned into their respective TTC categories using the Kroes module within the Toxtree software tool and custom profilers developed in Nelms et al (2019) and Patlewicz et al (2018). For the substances assigned into the 3 Cramer classes, the 5th percentiles were calculated from the empirical cumulative distributions of No observed (adverse) effect level (concentration) values. The 5th percentiles were converted to their respective TTC values and compared with published values reported by Escher et al (2010) and Carthew et al (2009). The TTC values derived from ToxValDB were orders of magnitude more conservative, further Cramer classification was not found to be effective at discriminating potencies. This dataset is associated with the following publication: Nelms, M., and G. Patlewicz. Derivation of New Threshold of Toxicological Concern Values for Exposure via Inhalation for Environmentally-Relevant Chemicals. Frontiers in Toxicology. Frontiers, Lausanne, SWITZERLAND, 2: 580347, (2020).

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: Ring, C., R. Pearce, W. Setzer, B. Wetmore, and J. Wambaugh. (Environment International) Refining high-throughput prioritization of environmental chemicals to include inter-individual variability across subpopulations. ENVIRONMENT INTERNATIONAL. Elsevier Science Ltd, New York, NY, USA, 106: 105-118, (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: Ring, C., R. Pearce, W. Setzer, B. Wetmore, and J. Wambaugh. (Environment International) Refining high-throughput prioritization of environmental chemicals to include inter-individual variability across subpopulations. ENVIRONMENT INTERNATIONAL. Elsevier Science Ltd, New York, NY, USA, 106: 105-118, (2017).

This dataset includes all data used to derive final figures and tables for paper to be submitted to the journal Inhalation Toxicology. Each tab is labeled with the name of the figure or table. This dataset is associated with the following publication: Vance, S., Y.H. Kim, I. George, J. Dye, W. Williams, M. Schladweiler, M. Gilmour, I. Jaspers, and S. Gavett. Contributions of Particulate and Gas Phases of Simulated Burn Pit Smoke Exposures to Impairment of Respiratory Function in Mice. INHALATION TOXICOLOGY. Informa Healthcare USA, New York, NY, USA, 35(5-6): 129-138, (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).

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).