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R Package “httk”

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

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

Description

Pre-made models that can be rapidly tailored to various chemicals andspecies using chemical-specific in vitro data and physiologicalinformation. These tools allow incorporation of chemical toxicokinetics(“TK”) and in vitro-in vivo extrapolation (“IVIVE”) into bioinformatics,as described byPearceet al. (2017). Chemical-specific in vitro data characterizingtoxicokinetics have been obtained from relatively high-throughputexperiments. The chemical-independent (“generic”) physiologically-based(“PBTK”) and empirical (for example, one compartment) “TK” modelsincluded here can be parameterized with in vitro data or in silicopredictions which are provided for thousands of chemicals, multipleexposure routes, and various species. High throughput toxicokinetics(“HTTK”) is the combination of in vitro data and generic models. Weestablish the expected accuracy of HTTK for chemicals without in vivodata through statistical evaluation of HTTK predictions for chemicalswhere in vivo data do exist. The models are systems of ordinarydifferential equations that are developed in MCSim and solved usingcompiled (C-based) code for speed. A Monte Carlo sampler is included forsimulating human biological variability (Ring et al.,2017) and propagating parameter uncertainty (Wambaugh et al., 2019).Empirically calibrated methods are included for predicting tissue:plasmapartition coefficients and volume of distribution (Pearce et al.,2017). These functions and data provide a set of tools for usingIVIVE to convert concentrations from high-throughput screeningexperiments (for example, Tox21, ToxCast) to real-world exposures viareverse dosimetry (also known as “RTK”) (Wetmore et al.,2015).

Chemical Insights

UL Research Institutes’ Chemical Insights Research Institute(ULRI-CIRI) is an independent, non-profit research organization(501(c)(3)) dedicated to advancing the understanding of chemicalexposures and their impacts on human health. Building on UL’s 130-yearlegacy in safety science, we are committed to producing peer-reviewed,open-access research that serves as a trusted resource for the publicand scientific community. CIRI develops data and tools that adhere tothe FAIR principlesWilkinson et al. 2016:Findable, Accessible, Interoperable, and Reusable. Our mission is toprovide trustworthy, scientifically grounded predictions of chemicalbehavior.

We emphasize rigorous scientific peer review, and best practices insoftware development and engineering: 1. Wherever possible, we integrateexisting, peer-reviewed data and tools. 2. When creating new data ormethods, we submit them to external peer review to ensure quality andcredibility. 3. We try to make our research open-source where possible,and use continuous integration and testing to ensure high-qualitysoftware

Our goal is to inform standards, support evidence-baseddecision-making, and protect public health. We are passionate aboutadvancing scientific discovery and applying it to real-world healthchallenges.

Visit theULRIChemical Insights website for more information and our latestresearch updates.

Getting Started

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

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

Dependencies

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 fromsoftware like Word or Outlook you may need to replace the quotationmarks that curve toward each other with ones typed by the keyboard.

Installing R package “httk”

Adapted fromBreen etal. (2021)

install.packages("httk")

Load the HTTK data, models, and functions

library(httk)
packageVersion("httk")

Examples

get_cheminfo()
get_cheminfo(info = "all", median.only=TRUE)
"80-05-7" %in% get_cheminfo()
subset(get_cheminfo(info = "all"), Compound %in% c("A","B","C"))
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")
calc_tkstats(chem.cas = "34256-82-1",species = "rat")calc_tkstats(chem.cas = "962-58-3", species = "rat")
solve_pbtk(chem.name = "bisphenol a", plots = TRUE)
my_data <- subset(get_cheminfo(info = "all"), Compound %in% c("A","B","C"))
write.csv(my_data, file = "my_data.csv")

User Notes

Help

help(httk)
help(package = httk)
vignette(package = "httk")
vignette("IntroToHTTK")

Authors

Principal Investigator

John Wambaugh [wambaugh.research@gmail.com]

EPA Lead Developer

Caroline Ring [Ring.Caroline@epa.gov]

Model Authors andFunction Developers

Robert Pearce, Sarah Davidson-Fritz [DavidsonFritz.Sarah@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], and CeliaSchacht [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, GilbertoPadilla Mercado [PadillaMercado.Gilberto@epa.gov], Katie Paul Friedman[Katie.PaulFriedman@UL.org], Nathan Pollesch [pollesch.nathan@epa.gov],Meredith Scherer [Scherer.Meredith@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], and Lily Whipple

Statistical Expertise

Woodrow Setzer

Disclaimer

This software/application was initially developed by the U.S.Environmental Protection Agency (USEPA). No warranty expressed orimplied is made regarding the accuracy or utility of the system, norshall the act of distribution constitute any such warranty. The USEPAhas relinquished control of the information and no longer hasresponsibility to protect the integrity, confidentiality or availabilityof the information. Any reference to specific commercial products,processes, or services by service mark, trademark, manufacturer, orotherwise, does not constitute or imply their endorsement,recommendation or favoring by the USEPA.


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