A B C D E F G H I J K L M N O P R S T W
httk-package | High-Throughput Toxicokinetics |
httkpop-package | httkpop: Virtual population generator for HTTK. |
add_chemtable | Add a table of chemical information for use in making httk predictions. |
age_dist_smooth | Smoothed age distributions by race and gender. |
age_draw_smooth | Draws ages from a smoothed distribution for a given gender/race combination |
armitage_estimate_sarea | Estimate well surface area |
armitage_eval | Evaluate the updated Armitage model |
armitage_input | Armitage et al. (2014) Model Inputs from Honda et al. (2019) |
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. |
Aylward2014 | Aylward et al. 2014 |
aylward2014 | Aylward et al. 2014 |
blood_mass_correct | Find average blood masses by age. |
blood_weight | Predict blood mass. |
bmiage | CDC BMI-for-age charts |
body_surface_area | Predict body surface area. |
bone_mass_age | Predict bone mass |
brain_mass | Predict brain mass. |
calc_analytic_css | Calculate the analytic steady state plasma concentration. |
calc_analytic_css_1comp | Calculate the analytic steady state concentration for the one compartment model. |
calc_analytic_css_3comp | Calculate the analytic steady state concentration for model 3comp |
calc_analytic_css_3compss | Calculate the analytic steady state concentration for the three compartment steady-state model |
calc_analytic_css_pbtk | Calculate the analytic steady state plasma concentration for model pbtk. |
calc_css | Find the steady state concentration and the day it is reached. |
calc_elimination_rate | Calculate the elimination rate for a one compartment model. |
calc_fetal_phys | Calculate maternal-fetal physiological parameters |
calc_half_life | Calculates the half-life for a one compartment model. |
calc_hepatic_clearance | Calculate the hepatic clearance (deprecated). |
calc_hep_bioavailability | Calculate first pass metabolism |
calc_hep_clearance | Calculate the hepatic clearance. |
calc_hep_fu | Calculate the free chemical in the hepaitic clearance assay |
calc_ionization | Calculate the ionization. |
calc_krbc2pu | Back-calculates the Red Blood Cell to Unbound Plasma Partition Coefficient |
calc_maternal_bw | Calculate maternal body weight |
calc_mc_css | Find the monte carlo steady state concentration. |
calc_mc_oral_equiv | Calculate Monte Carlo Oral Equivalent Dose |
calc_mc_tk | Conduct multiple TK simulations using Monte Carlo |
calc_rblood2plasma | Calculate the constant ratio of the blood concentration to the plasma concentration. |
calc_stats | Calculate toxicokinetic summary statistics (deprecated). |
calc_tkstats | Calculate toxicokinetic summary statistics. |
calc_total_clearance | Calculate the total plasma clearance. |
calc_vdist | Calculate the volume of distribution for a one compartment model. |
CAS.checksum | Test the check digit of a CAS number to confirm validity |
chem.invivo.PK.aggregate.data | Parameter Estimates from Wambaugh et al. (2018) |
chem.invivo.PK.data | Published toxicokinetic time course measurements |
chem.invivo.PK.summary.data | Summary of published toxicokinetic time course experiments |
chem.lists | Chemical membership in different research projects |
chem.physical_and_invitro.data | Physico-chemical properties and in vitro measurements for toxicokinetics |
ckd_epi_eq | CKD-EPI equation for GFR. |
concentration_data_Linakis2020 | Concentration data involved in Linakis 2020 vignette analysis. |
convert_httkpop_1comp | Converts HTTK-Pop physiology into parameters relevant to the one compartment model |
convert_solve_x | convert_solve_x |
convert_units | convert_units |
create_mc_samples | Create a data table of draws of parameter values for Monte Carlo |
Dawson2021 | Dawson et al. 2021 data |
dawson2021 | Dawson et al. 2021 data |
EPA.ref | Reference for EPA Physico-Chemical Data |
estimate_gfr | Predict GFR. |
estimate_gfr_ped | Predict GFR in children. |
estimate_hematocrit | Predict hematocrit using smoothing spline. |
export_pbtk_jarnac | Export model to jarnac. |
export_pbtk_sbml | Export model to sbml. |
fetalPCs | Fetal Partition Coefficients |
fetalpcs | Fetal Partition Coefficients |
Frank2018invivo | Literature In Vivo Data on Doses Causing Neurological Effects |
gen_age_height_weight | Generate ages, heights, and weights for a virtual population using the virtual-individuals method. |
gen_height_weight | Generate heights and weights for a virtual population. |
gen_serum_creatinine | Predict GFR. |
get_cheminfo | Retrieve chemical information from HTTK package |
get_chem_id | Retrieve chemical identity from HTTK package |
get_gfr_category | Categorize kidney function by GFR. |
get_invitroPK_param | Retrieve data from chem.physical_and_invitro.data table |
get_lit_cheminfo | Get literature Chemical Information. |
get_lit_css | Get literature Css |
get_lit_oral_equiv | Get Literature Oral Equivalent Dose |
get_physchem_param | Get physico-chemical parameters from chem.physical_and_invitro.data |
get_rblood2plasma | Get ratio of the blood concentration to the plasma concentration. |
get_weight_class | Given vectors of age, BMI, recumbent length, weight, and gender, categorizes weight classes using CDC and WHO categories. |
hematocrit_infants | Predict hematocrit in infants under 1 year old. |
honda.ivive | Return the assumptions used in Honda et al. 2019 |
howgate | Howgate 2006 |
httk | High-Throughput Toxicokinetics |
httkpop | httkpop: Virtual population generator for HTTK. |
httkpop_biotophys_default | Convert HTTK-Pop-generated parameters to HTTK physiological parameters |
httkpop_direct_resample | Generate a virtual population by directly resampling the NHANES data. |
httkpop_direct_resample_inner | Inner loop function called by 'httkpop_direct_resample'. |
httkpop_generate | Generate a virtual population |
httkpop_mc | Converts the HTTK-Pop population data table to a table of the parameters needed by HTTK, for a specific chemical. |
httkpop_virtual_indiv | Generate a virtual population by the virtual individuals method. |
in.list | Convenience Boolean (yes/no) functions to identify chemical membership in several key lists. |
invitro_mc | Draw in vitro TK parameters including uncertainty and variability. |
is.expocast | Convenience Boolean (yes/no) functions to identify chemical membership in several key lists. |
is.httk | Convenience Boolean (yes/no) function to identify chemical membership and treatment within the httk project. |
is.nhanes | Convenience Boolean (yes/no) functions to identify chemical membership in several key lists. |
is.nhanes.blood.analyte | Convenience Boolean (yes/no) functions to identify chemical membership in several key lists. |
is.nhanes.blood.parent | Convenience Boolean (yes/no) functions to identify chemical membership in several key lists. |
is.nhanes.serum.analyte | Convenience Boolean (yes/no) functions to identify chemical membership in several key lists. |
is.nhanes.serum.parent | Convenience Boolean (yes/no) functions to identify chemical membership in several key lists. |
is.nhanes.urine.analyte | Convenience Boolean (yes/no) functions to identify chemical membership in several key lists. |
is.nhanes.urine.parent | Convenience Boolean (yes/no) functions to identify chemical membership in several key lists. |
is.pharma | Convenience Boolean (yes/no) functions to identify chemical membership in several key lists. |
is.tox21 | Convenience Boolean (yes/no) functions to identify chemical membership in several key lists. |
is.toxcast | Convenience Boolean (yes/no) functions to identify chemical membership in several key lists. |
is_in_inclusive | Checks whether a value, or all values in a vector, is within inclusive limits |
johnson | Johnson 2006 |
Kapraun2019 | Kapraun et al. 2019 data |
kapraun2019 | Kapraun et al. 2019 data |
kidney_mass_children | Predict kidney mass for children |
liver_mass_children | Predict liver mass for children |
load_dawson2021 | Load data from Dawson et al. 2021. |
load_pradeep2020 | Load data from Pradeep et al. 2020. |
load_sipes2017 | Load data from Sipes et al 2017. |
lump_tissues | Lump tissue parameters |
lung_mass_children | Predict lung mass for children |
mcnally_dt | Reference tissue masses and flows from tables in McNally et al. 2014. |
metabolism_data_Linakis2020 | Metabolism data involved in Linakis 2020 vignette analysis. |
monte_carlo | Monte Carlo for pharmacokinetic models |
nhanes_mec_svy | Pre-processed NHANES data. |
Obach2008 | Published Pharmacokinetic Parameters from Obach et al. 2008 |
onlyp | NHANES Exposure Data |
pancreas_mass_children | Predict pancreas mass for children |
parameterize_1comp | Parameterize_1comp |
parameterize_3comp | Parameterize_3comp |
parameterize_fetal_pbtk | Parameterize_fetal_PBTK |
parameterize_gas_pbtk | Parameterize_gas_pbtk |
parameterize_pbtk | Parameterize_PBTK |
parameterize_schmitt | Get the Parameters for Schmitt's Tissue Partition Coefficient Method |
parameterize_steadystate | Parameterize_SteadyState |
pc.data | Partition Coefficient Data |
Pearce2017Regression | Pearce et al. 2017 data |
pearce2017regression | Pearce et al. 2017 data |
pharma | DRUGS|NORMAN: Pharmaceutical List with EU, Swiss, US Consumption Data |
physiology.data | Species-specific physiology parameters |
pksim.pcs | Partition Coefficients from PK-Sim |
Pradeep2020 | Pradeep et al. 2020 |
pradeep2020 | Pradeep et al. 2020 |
predict_partitioning_schmitt | Predict partition coefficients using the method from Schmitt (2008). |
pregnonpregaucs | AUCs for Pregnant and Non-Pregnant Women |
propagate_invitrouv_1comp | Propagates uncertainty and variability in in vitro HTTK data into one compartment model parameters |
propagate_invitrouv_3comp | Propagates uncertainty and variability in in vitro HTTK data into three compartment model parameters |
propagate_invitrouv_pbtk | Propagates uncertainty and variability in in vitro HTTK data into PBPK model parameters |
reset_httk | Reset HTTK to Default Data Tables |
rfun | Randomly draws from a one-dimensional KDE |
r_left_censored_norm | Returns draws from a normal distribution with a lower censoring limit of lod (limit of detection) |
scale_dosing | Scale mg/kg body weight doses according to body weight and units |
set_httk_precision | set_httk_precision |
Sipes2017 | Sipes et al. 2017 data |
sipes2017 | Sipes et al. 2017 data |
skeletal_muscle_mass | Predict skeletal muscle mass |
skeletal_muscle_mass_children | Predict skeletal muscle mass for children |
skin_mass_bosgra | Predict skin mass |
solve_1comp | Solve one compartment TK model |
solve_3comp | Solve_3comp |
solve_fetal_pbtk | Solve_fetal_PBTK |
solve_gas_pbtk | solve_gas_pbtk |
solve_model | Solve_model |
solve_pbtk | Solve_PBTK |
spleen_mass_children | Predict spleen mass for children |
spline_heightweight | Smoothing splines for log height vs. age and log body weight vs. age, along with 2-D KDE residuals, by race and gender. |
spline_hematocrit | Smoothing splines for log hematocrit vs. age in months, and KDE residuals, by race and gender. |
spline_serumcreat | Smoothing splines for log serum creatinine vs. age in months, along with KDE residuals, by race and gender. |
supptab1_Linakis2020 | Supplementary output from Linakis 2020 vignette analysis. |
supptab2_Linakis2020 | More supplementary output from Linakis 2020 vignette analysis. |
Tables.Rdata.stamp | A timestamp of table creation |
tissue.data | Tissue composition and species-specific physiology parameters |
tissue_masses_flows | Given a data.table describing a virtual population by the NHANES quantities, generates HTTK physiological parameters for each individual. |
tissue_scale | Allometric scaling. |
wambaugh2019 | in vitro Toxicokinetic Data from Wambaugh et al. (2019) |
wambaugh2019.nhanes | NHANES Chemical Intake Rates for chemicals in Wambaugh et al. (2019) |
wambaugh2019.raw | Raw Bayesian in vitro Toxicokinetic Data Analysis from Wambaugh et al. (2019) |
wambaugh2019.seem3 | ExpoCast SEEM3 Consensus Exposure Model Predictions for Chemical Intake Rates |
wambaugh2019.tox21 | Tox21 2015 Active Hit Calls (EPA) |
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. |
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. |
well_param | Microtiter Plate Well Descriptions for Armitage et al. (2014) Model |
Wetmore.data | Published toxicokinetic predictions based on in vitro data |
Wetmore2012 | Published toxicokinetic predictions based on in vitro data from Wetmore et al. 2012. |
wfl | WHO weight-for-length charts |