parameterize_sumclearances {httk} | R Documentation |
Parameters for a three-compartment model at steady-state with exhalation
Description
This function initializes the parameters needed in the functions
calc_mc_css
, calc_mc_oral_equiv
, and
calc_analytic_css
for the three
compartment steady state model ('3compartmentss') as used in
Rotroff et al. (2010), Wetmore et al. (2012), Wetmore et al. (2015), and
elsewhere. By assuming that enough time has passed to reach steady-state, we
eliminate the need for tissue-specific parititon coefficients because we
assume all tissues have come to equilibrium with the unbound concentration
in plasma. However, we still use chemical properties to predict the
blood:plasma ratio for estimating first-pass hepatic metabolism for oral
exposures.
Usage
parameterize_sumclearances(
chem.cas = NULL,
chem.name = NULL,
dtxsid = NULL,
species = "Human",
clint.pvalue.threshold = 0.05,
default.to.human = FALSE,
physchem.exclude = TRUE,
class.exclude = TRUE,
force.human.clint.fup = FALSE,
adjusted.Funbound.plasma = TRUE,
adjusted.Clint = TRUE,
restrictive.clearance = TRUE,
fup.lod.default = 0.005,
suppress.messages = FALSE,
minimum.Funbound.plasma = 1e-04,
Caco2.options = NULL,
...
)
Arguments
chem.cas |
Chemical Abstract Services Registry Number (CAS-RN) – the chemical must be identified by either CAS, name, or DTXISD |
chem.name |
Chemical name (spaces and capitalization ignored) – the chemical must be identified by either CAS, name, or DTXISD |
dtxsid |
EPA's DSSTox Structure ID (https://comptox.epa.gov/dashboard) – the chemical must be identified by either CAS, name, or DTXSIDs |
species |
Species desired (either "Rat", "Rabbit", "Dog", "Mouse", or default "Human"). |
clint.pvalue.threshold |
Hepatic clearances with clearance assays having p-values greater than the threshold are set to zero. |
default.to.human |
Substitutes missing species-specific values with human values if TRUE (default is FALSE). |
physchem.exclude |
Exclude chemicals on the basis of physico-chemical properties (currently only Henry's law constant) as specified by the relevant modelinfo_[MODEL] file (default TRUE). |
class.exclude |
Exclude chemical classes identified as outside of domain of applicability by relevant modelinfo_[MODEL] file (default TRUE). |
force.human.clint.fup |
Uses human hepatic intrinsic clearance and fraction of unbound plasma in calculation of partition coefficients for rats if true. |
adjusted.Funbound.plasma |
Uses Pearce et al. (2017) lipid binding adjustment for Funbound.plasma (which impacts partition coefficients) when set to TRUE (Default). |
adjusted.Clint |
Uses Kilford et al. (2008) hepatocyte incubation binding adjustment for Clint when set to TRUE (Default). |
restrictive.clearance |
In calculating hepatic.bioavailability, protein binding is not taken into account (set to 1) in liver clearance if FALSE. |
fup.lod.default |
Default value used for fraction of unbound plasma for chemicals where measured value was below the limit of detection. Default value is 0.0005. |
suppress.messages |
Whether or not the output message is suppressed. |
minimum.Funbound.plasma |
Monte Carlo draws less than this value are set equal to this value (default is 0.0001 – half the lowest measured Fup in our dataset). |
Caco2.options |
A list of options to use when working with Caco2 apical
to basolateral data |
... |
Other parameters |
Details
We model systemic oral bioavailability as
Fbio=Fabs*Fgut*Fhep.
Fhep
is estimated from in vitro TK data using
calc_hep_bioavailability
.
If Fbio
has been measured in vivo and is found in
table chem.physical_and_invitro.data
then we set
Fabs*Fgut
to the measured value divided by
Fhep
Otherwise, if Caco2 membrane permeability data or predictions
are available Fabs is estimated
using calc_fabs.oral
.
Intrinsic hepatic metabolism is used to very roughly estimate
Fgut
using calc_fgut.oral
.
Per- and polyfluoroalkyl substances (PFAS) are excluded by default because the transporters that often drive PFAS toxicokinetics are not included in this model. However, PFAS chemicals can be included with the argument "class.exclude = FALSE".
Value
Clint |
Hepatic Intrinsic Clearance, uL/min/10^6 cells. |
Fabsgut |
Fraction of the oral dose absorbed and surviving gut metabolism, that is, the fraction of the dose that enters the gutlumen. |
Funbound.plasma |
Fraction of plasma that is not bound. |
Qtotal.liverc |
Flow rate of blood exiting the liver, L/h/kg BW^3/4. |
Qgfrc |
Glomerular Filtration Rate, L/h/kg BW^3/4, volume of fluid filtered from kidney and excreted. |
BW |
Body Weight, kg |
MW |
Molecular Weight, g/mol |
million.cells.per.gliver |
Millions cells per gram of liver tissue. |
Vliverc |
Volume of the liver per kg body weight, L/kg BW. |
liver.density |
Liver tissue density, kg/L. |
Fhep.assay.correction |
The fraction of chemical unbound in hepatocyte assay using the method of Kilford et al. (2008) |
hepatic.bioavailability |
Fraction of dose remaining after first pass clearance, calculated from the corrected well-stirred model. |
Author(s)
John Wambaugh
References
Pearce RG, Setzer RW, Strope CL, Wambaugh JF, Sipes NS (2017). “Httk: R package for high-throughput toxicokinetics.” Journal of Statistical Software, 79(4), 1. doi:10.18637/jss.v079.i04.
Kilford PJ, Gertz M, Houston JB, Galetin A (2008). “Hepatocellular binding of drugs: correction for unbound fraction in hepatocyte incubations using microsomal binding or drug lipophilicity data.” Drug Metabolism and Disposition, 36(7), 1194–1197. doi:10.1124/dmd.108.020834.
Wambaugh JF, Schacht CM, Ring CL (2025). “A Simple Physiologically Based Toxicokinetic Model for Multi-Route In Vitro–In Vivo Extrapolation.” Environmental Science & Technology Letters, 12(3), 261–268. doi:10.1021/acs.estlett.4c00967.
Rotroff DM, Wetmore BA, Dix DJ, Ferguson SS, Clewell HJ, Houck KA, LeCluyse EL, Andersen ME, Judson RS, Smith CM, others (2010). “Incorporating human dosimetry and exposure into high-throughput in vitro toxicity screening.” Toxicological Sciences, 117(2), 348–358. doi:10.1093/toxsci/kfq220.
Wetmore BA, Wambaugh JF, Ferguson SS, Sochaski MA, Rotroff DM, Freeman K, Clewell III HJ, Dix DJ, Andersen ME, Houck KA, others (2012). “Integration of dosimetry, exposure, and high-throughput screening data in chemical toxicity assessment.” Toxicological Sciences, 125(1), 157–174. doi:10.1093/toxsci/kfr254.
Wetmore BA, Wambaugh JF, Allen B, Ferguson SS, Sochaski MA, Setzer RW, Houck KA, Strope CL, Cantwell K, Judson RS, others (2015). “Incorporating high-throughput exposure predictions with dosimetry-adjusted in vitro bioactivity to inform chemical toxicity testing.” Toxicological Sciences, 148(1), 121–136. doi:10.1093/toxsci/kfv171.
See Also
Examples
parameters <- parameterize_steadystate(chem.name='Bisphenol-A',species='Rat')
parameters <- parameterize_steadystate(chem.cas='80-05-7')