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R Package "httk"

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

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, my_data, for all data on chemicals A, B, C, in R
my_data <- subset(get_cheminfo(info = "all"), Compound %in% c("A","B","C"))
  • Export data set, my_data, from R to csv file called my_data.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 (i.e. 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], and Colin Thomson [thomson.colin@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], Meredith Scherer [Scherer.Meredith@epa.gov], Celia Schacht [Schacht.Celia@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 [setzer.woodrow@epa.gov]

License

License: GPL-3 https://www.gnu.org/licenses/gpl-3.0.en.html

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Version

Install

install.packages('httk')

Monthly Downloads

835

Version

2.6.1

License

GPL-3

Maintainer

John Wambaugh

Last Published

May 1st, 2025

Functions in httk (2.6.1)

augment.table

Add a parameter value to the chem.physical_and_invitro.data table
available_rblood2plasma

Find the best available ratio of the blood to plasma concentration constant.
benchmark_httk

Assess the current performance of httk relative to historical benchmarks
armitage_eval

Evaluate the updated Armitage model
blood_weight

Predict blood mass.
armitage_input

Armitage et al. (2014) Model Inputs from Honda et al. (2019)
armitage_estimate_sarea

Estimate well surface area
blood_mass_correct

Find average blood masses by age.
aylward2014

Aylward et al. 2014
bmiage

CDC BMI-for-age charts
calc_analytic_css_pbtk

Calculate the analytic steady state plasma concentration for model pbtk.
brain_mass

Predict brain mass.
calc_analytic_css_3comp2

Calculate the analytic steady state concentration for model 3compartment
calc_analytic_css_1comp

Calculate the analytic steady state concentration for the one compartment model.
body_surface_area

Predict body surface area.
bone_mass_age

Predict bone mass
calc_analytic_css_3compss

Calculate the analytic steady state concentration for the three compartment steady-state model
calc_analytic_css_sumclearances

Calculate the steady state concentration for the sum of clearances steady-state model with exhalation
calc_analytic_css_3comp

Calculate the analytic steady state concentration for model 3compartment
calc_dow

Calculate the distribution coefficient
calc_hep_fu

Calculate the free chemical in the hepaitic clearance assay
calc_hep_clearance

Calculate the hepatic clearance.
calc_css

Find the steady state concentration and the day it is reached.
calc_half_life

Calculates the half-life for a one compartment model.
calc_hep_bioavailability

Calculate first pass heaptic metabolism
calc_fup_correction

Calculate the correction for lipid binding in plasma binding assay
calc_fetal_phys

Calculate maternal-fetal physiological parameters
calc_analytic_css

Calculate the analytic steady state plasma concentration.
calc_elimination_rate

Calculate the elimination rate for a one compartment model
calc_hepatic_clearance

Calculate the hepatic clearance (deprecated).
calc_ionization

Calculate the ionization.
calc_ma

Calculate the membrane affinity
calc_maternal_bw

Calculate maternal body weight
calc_fbio.oral

Functions for calculating the bioavaialble fractions from oral doses
calc_kair

Calculate air:matrix partition coefficients
calc_krbc2pu

Back-calculates the Red Blood Cell to Unbound Plasma Partition Coefficient
calc_mc_css

Distribution of chemical steady state concentration with uncertainty and variability
calc_vdist

Calculate the volume of distribution for a one compartment model.
calc_total_clearance

Calculate the total plasma clearance.
chem.physical_and_invitro.data

Physico-chemical properties and in vitro measurements for toxicokinetics
concentration_data_Linakis2020

Concentration data involved in Linakis 2020 vignette analysis.
ckd_epi_eq

CKD-EPI equation for GFR.
chem.invivo.PK.summary.data

Summary of published toxicokinetic time course experiments
convert_solve_x

convert_solve_x
convert_units

convert_units
calc_stats

Calculate toxicokinetic summary statistics (deprecated).
example.seem

SEEM Example Data We can grab SEEM daily intake rate predictions already in RData format from https://github.com/HumanExposure/SEEM3RPackage/tree/main/SEEM3/data Download the file Ring2018Preds.RData
calc_mc_oral_equiv

Calculate Monte Carlo Oral Equivalent Dose
cas_id_check

CAS number format check function
estimate_gfr_ped

Predict GFR in children.
example.toxcast

ToxCast Example Data The main page for the ToxCast data is here: https://www.epa.gov/comptox-tools/exploring-toxcast-data Most useful to us is a single file containing all the hits across all chemcials and assays: https://clowder.edap-cluster.com/datasets/6364026ee4b04f6bb1409eda?space=62bb560ee4b07abf29f88fef
get_gfr_category

Categorize kidney function by GFR.
check_model

Check for sufficient model parameters
estimate_hematocrit

Generate hematocrit values for a virtual population
export_pbtk_sbml

Export model to sbml.
export_pbtk_jarnac

Export model to jarnac.
calc_tkstats

Calculate toxicokinetic summary statistics.
get_physchem_param

Get physico-chemical parameters from chem.physical_and_invitro.data table
dawson2021

Dawson et al. 2021 data
create_mc_samples

Create a table of parameter values for Monte Carlo
gen_age_height_weight

Generate demographic parameters for a virtual population
fetalpcs

Fetal Partition Coefficients
get_fbio

Retrieve or calculate fraction of chemical absorbed from the gut
get_invitroPK_param

Retrieve species-specific in vitro data from chem.physical_and_invitro.data table
get_input_param_timeseries

Get timeseries containing the change of each of the input parameters.
get_rblood2plasma

Get ratio of the blood concentration to the plasma concentration.
get_lit_cheminfo

Get literature Chemical Information.
get_fup

Retrieve and parse fraction unbound in plasma
httk_chem_subset

HTTK data chemical subsetting function
honda.ivive

Return the assumptions used in Honda et al. 2019
calc_rblood2plasma

Calculate the constant ratio of the blood concentration to the plasma concentration.
calc_mc_tk

Conduct multiple TK simulations using Monte Carlo
chem.invivo.PK.aggregate.data

Parameter Estimates from Wambaugh et al. (2018)
chem.invivo.PK.data

Published toxicokinetic time course measurements
httkpop

httkpop: Virtual population generator for HTTK.
honda2023.data

Measured Caco-2 Apical-Basal Permeability Data
honda2023.qspr

Predicted Caco-2 Apical-Basal Permeabilities
in.list

Convenience Boolean (yes/no) functions to identify chemical membership in several key lists.
howgate

Howgate 2006
get_weight_class

Assign weight class (underweight, normal, overweight, obese)
httkpop_direct_resample_inner

Inner loop function called by httkpop_direct_resample.
httkpop_generate

Generate a virtual population for PBTK
hw_H

KDE bandwidth for residual variability in height/weight
get_wetmore_cheminfo

Get literature Chemical Information. (deprecated).
httkpop_mc

httk-pop: Correlated human physiological parameter Monte Carlo
gen_serum_creatinine

Generate serum creatinine values for a virtual population.
gen_height_weight

Generate heights and weights for a virtual population.
httkpop_direct_resample

Generate a virtual population by directly resampling the NHANES data.
get_cheminfo

Retrieve chemical information available from HTTK package
load_pradeep2020

Load CLint and Fup QSPR predictions predictions from Pradeep et al. 2020.
dtxsid_id_check

DTXSID number format check function
httkpop_virtual_indiv

Generate a virtual population by the virtual individuals method.
httkpop_biotophys_default

Convert HTTK-Pop-generated parameters to HTTK physiological parameters
get_clint

Retrieve and parse intrinsic hepatic clearance
is.httk

Convenience Boolean (yes/no) function to identify chemical membership and treatment within the httk project.
load_sipes2017

Load CLint and Fup QSPR predictions from Sipes et al 2017.
get_chem_id

Retrieve chemical identity from HTTK package
estimate_gfr

Predict GFR.
get_lit_oral_equiv

Get Literature Oral Equivalent Dose
list_models

List all available HTTK models
invitro_mc

Monte Carlo for in vitro toxicokinetic parameters including uncertainty and variability.
get_caco2

Retrieve in vitro measured Caco-2 membrane permeabilit
get_lit_css

Get literature Css
liver_mass_children

Predict liver mass for children
kapraun2019

Kapraun et al. 2019 data
kidney_mass_children

Predict kidney mass for children
mcnally_dt

Reference tissue masses and flows from tables in McNally et al. 2014.
load_dawson2021

Load CLint and Fup QSPR predictions from Dawson et al. 2021.
load_honda2023

Load Caco2 QSPR predictions from Honda et al. 2023
get_wetmore_oral_equiv

Get Literature Oral Equivalent Dose (deprecated).
get_wetmore_css

Get literature Css (deprecated).
hematocrit_infants

Predict hematocrit in infants under 1 year old.
httk-package

httk: High-Throughput Toxicokinetics
lung_mass_children

Predict lung mass for children
is_in_inclusive

Checks whether a value, or all values in a vector, is within inclusive limits
httk.performance

Historical Performance of R Package httk
hct_h

KDE bandwidths for residual variability in hematocrit
lump_tissues

Lump tissue parameters into model compartments
parameterize_fetal_pbtk

Parameterize_fetal_PBTK
onlyp

NHANES Exposure Data
parameterize_gas_pbtk

Parameters for a generic gas inhalation physiologically-based toxicokinetic model
pancreas_mass_children

Predict pancreas mass for children
parameterize_3comp

Parameters for a three-compartment toxicokinetic model (dynamic)
mecdt

Pre-processed NHANES data.
johnson

Johnson 2006
parameterize_3comp2

Parameters for a three-compartment toxicokinetic model (dynamic)
metabolism_data_Linakis2020

Metabolism data involved in Linakis 2020 vignette analysis.
pksim.pcs

Partition Coefficients from PK-Sim
monte_carlo

Monte Carlo for toxicokinetic model parameters
pradeep2020

Pradeep et al. 2020
parameterize_sumclearances

Parameters for a three-compartment model at steady-state with exhalation
parameterize_steadystate

Parameters for a three-compartment toxicokinetic model at steady-state
parameterize_pbtk

Parameters for a generic physiologically-based toxicokinetic model
pharma

DRUGS|NORMAN: Pharmaceutical List with EU, Swiss, US Consumption Data
scale_dosing

Scale mg/kg body weight doses according to body weight and units
r_left_censored_norm

Returns draws from a normal distribution with a lower censoring limit of lod (limit of detection)
reset_httk

Reset HTTK to Default Data Tables
parameterize_schmitt

Parameters for Schmitt's (2008) Tissue Partition Coefficient Method
propagate_invitrouv_pbtk

Propagates uncertainty and variability in in vitro HTTK data into PBPK model parameters
rfun

Randomly draws from a one-dimensional KDE
rmed0non0u95

Draw random numbers with LOD median but non-zero upper 95th percentile
pregnonpregaucs

AUCs for Pregnant and Non-Pregnant Women
physiology.data

Species-specific physiology parameters
predict_partitioning_schmitt

Predict partition coefficients using the method from Schmitt (2008).
set_httk_precision

set_httk_precision
parameterize_1tri_pbtk

Parameterize_1tri_PBTK
skeletal_muscle_mass

Predict skeletal muscle mass
scr_h

KDE bandwidths for residual variability in serum creatinine
parameterize_1comp

Parameters for a one compartment (empirical) toxicokinetic model
solve_1comp

Solve one compartment TK model
sipes2017

Sipes et al. 2017 data
pc.data

Partition Coefficient Data
pearce2017regression

Pearce et al. 2017 data
solve_1tri_pbtk

Solve_1tri_PBTK
solve_1comp_lifestage

Solve 1comp_lifestage model, which has time-dependent parameters
solve_3comp

Solve_3comp
skeletal_muscle_mass_children

Predict skeletal muscle mass for children
propagate_invitrouv_3comp

Propagates uncertainty and variability in in vitro HTTK data into three compartment model parameters
propagate_invitrouv_1comp

Propagates uncertainty and variability in in vitro HTTK data into one compartment model parameters
supptab1_Linakis2020

Supplementary output from Linakis 2020 vignette analysis.
spleen_mass_children

Predict spleen mass for children
solve_3comp2

Solve_3comp2
solve_full_pregnancy

Solve_full_pregnancy
solve_fetal_pbtk

Solve_fetal_PBTK
solve_model

Solve_model
skin_mass_bosgra

Predict skin mass
solve_gas_pbtk

solve_gas_pbtk
solve_3comp_lifestage

Solve the 3comp_lifestage model, which has time-dependent parameters
wambaugh2019

in vitro Toxicokinetic Data from Wambaugh et al. (2019)
wfl

WHO weight-for-length charts
well_param

Microtiter Plate Well Descriptions for Armitage et al. (2014) Model
wambaugh2019.nhanes

NHANES Chemical Intake Rates for chemicals in Wambaugh et al. (2019)
supptab2_Linakis2020

More supplementary output from Linakis 2020 vignette analysis.
wambaugh2019.seem3

ExpoCast SEEM3 Consensus Exposure Model Predictions for Chemical Intake Rates
thyroid.ac50s

ToxCast thyroid-related bioactivity data
wambaugh2019.raw

Raw Bayesian in vitro Toxicokinetic Data Analysis from Wambaugh et al. (2019)
truong25.seem3

SEEM3 Example Data for Truong et al. 2025
tissue_scale

Allometric scaling.
solve_pbtk

Solve_PBTK
wambaugh2019.tox21

Tox21 2015 Active Hit Calls (EPA)
tissue_masses_flows

Given a data.table describing a virtual population by the NHANES quantities, generates HTTK physiological parameters for each individual.
tissue.data

Tissue composition and species-specific physiology parameters
solve_pbtk_lifestage

Solve the pbtk_lifestage model, which has time-dependent parameters
wang2018

Wang et al. 2018 Wang et al. (2018) screened the blood of 75 pregnant women for the presence of environmental organic acids (EOAs) and identified mass spectral features corresponding to 453 chemical formulae of which 48 could be mapped to likely structures. Of the 48 with tentative structures the identity of six were confirmed with available chemical standards.
CAS.checksum

Test the check digit of a CAS number to confirm validity
age_draw_smooth

Draws ages from a smoothed distribution for a given gender/race combination
add_chemtable

Add a table of chemical information for use in making httk predictions.
apply_clint_adjustment

Correct the measured intrinsive hepatic clearance for fraction free
Frank2018invivo

Literature In Vivo Data on Doses Causing Neurological Effects
Tables.Rdata.stamp

A timestamp of table creation
Wetmore2012

Published toxicokinetic predictions based on in vitro data from Wetmore et al. 2012.
EPA.ref

Reference for EPA Physico-Chemical Data
apply_fup_adjustment

Correct the measured fraction unbound in plasma for lipid binding
Obach2008

Published Pharmacokinetic Parameters from Obach et al. 2008