Git Repository for R Package "httk"

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This R package provides data and models for predicting toxicokinetics (chemical absorption, distribution, metabolism, and excretion by the body). The models are design to be parameterized with chemical-specific in vitro (animal free) measurements. The predictions can be used for traditional dosimetry as well as in vivo-in vitro extrapolation (IVIVE) of in vitro bioactivity testing data (for example, ToxCast). See Breen et al. (2021) for a recent review.

This repository is for reporting bugs and contributing enhancements. Installable files, documentation, and other information can be obtained from https://cran.r-project.org/package=httk.

Description

Pre-made models that can be rapidly tailored to various chemicals and species using chemical-specific in vitro data and physiological information. These tools allow incorporation of chemical toxicokinetics ("TK") and in vitro-in vivo extrapolation ("IVIVE") into bioinformatics, as described by Pearce et al. (2017). Chemical-specific in vitro data characterizing toxicokinetics have been obtained from relatively high-throughput experiments. The chemical-independent ("generic") physiologically-based ("PBTK") and empirical (for example, one compartment) "TK" models included here can be parameterized with in vitro data or in silico predictions which are provided for thousands of chemicals, multiple exposure routes, and various species. High throughput toxicokinetics ("HTTK") is the combination of in vitro data and generic models. We establish the expected accuracy of HTTK for chemicals without in vivo data through statistical evaluation of HTTK predictions for chemicals where in vivo data do exist. The models are systems of ordinary differential equations that are developed in MCSim and solved using compiled (C-based) code for speed. A Monte Carlo sampler is included for simulating human biological variability (Ring et al., 2017) and propagating parameter uncertainty (Wambaugh et al., 2019). Empirically calibrated methods are included for predicting tissue:plasma partition coefficients and volume of distribution (Pearce et al., 2017). These functions and data provide a set of tools for using IVIVE to convert concentrations from high-throughput screening experiments (for example, Tox21, ToxCast) to real-world exposures via reverse dosimetry (also known as "RTK") (Wetmore et al., 2015).

Getting Started

For an introduction to R, see Irizarry (2022) "Introduction to Data Science": http://rafalab.dfci.harvard.edu/dsbook/getting-started.html

For an introduction to toxicokinetics, with examples in "httk", see Ring (2021) in the "TAME Toolkit": https://uncsrp.github.io/Data-Analysis-Training-Modules/toxicokinetic-modeling.html

Dependencies

• Users will need the freely available R statistical computing language: https://www.r-project.org/
• Users will likely want a development environment like RStudio: https://posit.co/download/rstudio-desktop/
• If you get the message "Error in library(X) : there is no package called 'X'" then you will need to install that package: install.packages("X") Or, if using RStudio, look for Install Packages under Tools tab.
• Note that R does not recognize fancy versions of quotation marks ,$~$,$~$, or$~$. If you are cutting and pasting from software like Word or Outlook you may need to replace the quotation marks that curve toward each other with ones typed by the keyboard.

Installing R package "httk"

Adapted from Breen et al. (2021)

• Getting Started with R Package httk from the R command line install.packages("httk") Load the HTTK data, models, and functions library(httk)
• Check what version you are using packageVersion("httk")

Examples

• List all CAS numbers for all chemicals with sufficient data to run httk get_cheminfo()
• List all information (If median.only=FALSE you will get medians, lower 95th, and upper 95th for Fup, plus p-value for Clint, separated by commans, when those statistics are available. Older data only have means for Clint and Fup.): get_cheminfo(info = "all", median.only=TRUE)
• Is a chemical with a specified CAS number available? "80-05-7" %in% get_cheminfo()
• All data on chemicals A, B, C (You need to specify the names instead of "A","B","C"...) subset(get_cheminfo(info = "all"), Compound %in% c("A","B","C"))
• Administrated equivalent dose (mg/kg BW/day) to produce 0.1 uM plasma concentration, 0.95 quantile, for a specified CAS number and species calc_mc_oral_equiv(0.1,chem.cas = "34256-82-1",species = "human") calc_mc_oral_equiv(0.1,chem.cas = "99-71-8", species = "human")
• Calculate the mean, AUC, and peak concentrations for a simulated study (28-day daily dose, by default) for a specified CAS number and species calc_tkstats(chem.cas = "34256-82-1",species = "rat") calc_tkstats(chem.cas = "962-58-3", species = "rat")
• Using the PBTK solver for a specified chem name solve_pbtk(chem.name = "bisphenol a", plots = TRUE)
• Create data set, mydata, for all data on chemicals A, B, C, in R ``` mydata <- subset(get_cheminfo(info = "all"), Compound %in% c("A","B","C")) ```

• Export data set, mydata, from R to csv file called mydata.csv in the current working directory write.csv(my_data, file = "my_data.csv")

  User Notes

• When using the CAS number as a unique chemical identifier with 'httk' functions it is best to type these numbers directly (that is, by hand) into the console, script, Rmarkdown, etc. to avoid unnecessary error messages. Webpages, word documents, and other sources of these CAS numbers may use a different character encoding that does not match those used in the 'httk' data sources.

Help

• Getting help with R Package httk help(httk)
• You can go straight to the index: help(package = httk)
• List all vignettes for httk vignette(package = "httk")
• Displays the vignette for a specified vignette vignette("IntroToHTTK")

Authors

Principal Investigator

John Wambaugh [wambaugh.john@epa.gov]

Lead Software Engineer

Sarah Davidson Fritz [DavidsonFritz.Sarah@epa.gov]

Model Authors and Function Developers

Robert Pearce, Caroline Ring [Ring.Caroline@epa.gov], Greg Honda [honda.gregory@epa.gov], Mark Sfeir, Matt Linakis [MLINAKIS@ramboll.com], Dustin Kapraun [kapraun.dustin@epa.gov], Kimberly Truong [truong.kimberly@epa.gov], Colin Thomson [thomson.colin@epa.gov], Annabel Meade [aemeade7@gmail.com], Meredith Scherer [Scherer.Meredith@epa.gov], and Celia Schacht [Schacht.Celia@epa.gov]

Bug-Fixes Vignette edits, and Parameter Values

Todor Antonijevic [tantonijevic@toxstrategies.com], Miyuki Breen, Shannon Bell [Shannon.bell@inotivco.com], Xiaoqing Chang [Xiaoqing.chang@inotivco.com], Jimena Davis, Elaina Kenyon [kenyon.elaina@epa.gov], Gilberto Padilla Mercado [PadillaMercado.Gilberto@epa.gov], Katie Paul Friedman [Paul-Friedman.Katie@epa.gov], Nathan Pollesch [pollesch.nathan@epa.gov], Noelle Sinski [Noelle.Sinski@icf.com], Nisha Sipes [sipes.nisha@epa.gov], James Sluka [jsluka@indiana.edu],
Caroline Stevens [Stevens.Caroline@epa.gov] Barbara Wetmore [wetmore.barbara@epa.gov], Lily Whipple

Statistical Expertise

Woodrow Setzer

License

License: MIT https://github.com/USEPA/CompTox-ExpoCast-httk/httk/LICENSE.md

Disclaimer

This software/application was developed by the U.S. Environmental Protection Agency (USEPA). No warranty expressed or implied is made regarding the accuracy or utility of the system, nor shall the act of distribution constitute any such warranty. The USEPA has relinquished control of the information and no longer has responsibility to protect the integrity, confidentiality or availability of the information. Any reference to specific commercial products, processes, or services by service mark, trademark, manufacturer, or otherwise, does not constitute or imply their endorsement, recommendation or favoring by the USEPA. The USEPA seal and logo shall not be used in any manner to imply endorsement of any commercial product or activity by the USEPA or the United States Government.