parameterize_schmitt {httk} | R Documentation |
Parameters for Schmitt's (2008) Tissue Partition Coefficient Method
Description
This function provides the necessary parameters to run
predict_partitioning_schmitt
, excluding the data in table
tissue.data
. The model is based on the
Schmitt (2008) (doi:10.1016/j.tiv.2007.09.010)
method for predicting tissue:plasma partition coefficients as modified by
Pearce et al. (2017) (doi:10.1007/s10928-017-9548-7).
The modifications include approaches adapted from
Peyret et al. (2010) (doi:10.1016/j.taap.2010.09.010).
Usage
parameterize_schmitt(
chem.cas = NULL,
chem.name = NULL,
dtxsid = NULL,
parameters = NULL,
species = "Human",
default.to.human = FALSE,
force.human.fup = FALSE,
adjusted.Funbound.plasma = TRUE,
suppress.messages = FALSE,
class.exclude = TRUE,
minimum.Funbound.plasma = 1e-04,
pfas.calibration = TRUE
)
Arguments
chem.cas |
Chemical Abstract Services Registry Number (CAS-RN) – if parameters is not specified then the chemical must be identified by either CAS, name, or DTXISD |
chem.name |
Chemical name (spaces and capitalization ignored) – if parameters is not specified then the chemical must be identified by either CAS, name, or DTXISD |
dtxsid |
EPA's DSSTox Structure ID (https://comptox.epa.gov/dashboard) – if parameters is not specified then the chemical must be identified by either CAS, name, or DTXSIDs |
parameters |
Chemcial and physiological description parameters needed to run the Schmitt et al. (2008) model |
species |
Species desired (either "Rat", "Rabbit", "Dog", "Mouse", or default "Human"). |
default.to.human |
Substitutes missing fraction of unbound plasma with human values if true. |
force.human.fup |
Returns human fraction of unbound plasma in calculation for rats if true. When species is specified as rabbit, dog, or mouse, the human unbound fraction is substituted. |
adjusted.Funbound.plasma |
Uses Pearce et al. (2017) lipid binding adjustment for Funbound.plasma (which impacts partition coefficients) when set to TRUE (Default). |
suppress.messages |
Whether or not the output message is suppressed. |
class.exclude |
Exclude chemical classes identified as outside of domain of applicability by relevant modelinfo_[MODEL] file (default TRUE). |
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). |
pfas.calibration |
Whether MA for chemicals in class PFAS should be increased using the regression to the Droge (2019) dataset. |
Value
Funbound.plasma |
Unbound fraction in plasma, adjusted for lipid binding according to Pearce et al. (2017) |
unadjusted.Funbound.plasma |
measured unbound fraction in plasma (0.005 if below limit of detection) |
Pow |
octanol:water partition coefficient (not log transformed) |
pKa_Donor |
compound H dissociation equilibrium constant(s) |
pKa_Accept |
compound H association equilibrium constant(s) |
MA |
phospholipid:water distribution coefficient, membrane affinity |
Fprotein.plasma |
protein fraction in plasma |
plasma.pH |
pH of the plasma |
Author(s)
Robert Pearce and 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.
Schmitt W (2008). “General approach for the calculation of tissue to plasma partition coefficients.” Toxicology in vitro, 22(2), 457–467. doi:10.1016/j.tiv.2007.09.010.
Schmitt W (2008). “Corrigendum to:'General approach for the calculation of tissue to plasma partition coefficients'[Toxicology in Vitro 22 (2008) 457–467].” Toxicology in Vitro, 22(6), 1666. doi:10.1016/j.tiv.2008.04.020.
Pearce RG, Setzer RW, Davis JL, Wambaugh JF (2017). “Evaluation and calibration of high-throughput predictions of chemical distribution to tissues.” Journal of pharmacokinetics and pharmacodynamics, 44, 549–565. doi:10.1007/s10928-017-9548-7.
Peyret T, Poulin P, Krishnan K (2010). “A unified algorithm for predicting partition coefficients for PBPK modeling of drugs and environmental chemicals.” Toxicology and applied pharmacology, 249(3), 197–207. doi:10.1016/j.taap.2010.09.010.
See Also
Examples
library(httk)
# Create a list of parameters (that you can potentially change):
p <- parameterize_schmitt(chem.name="bisphenola")
# Predict the partition coefficients using a list of parameters:
PCs <- predict_partitioning_schmitt(parameters = p)
# Lump the tissues into the compartments for model "pbtk":
lump_tissues(PCs)
# Lump the tissues into a single volume of distribution
calc_vdist(parameters=c(p, PCs))