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

Description

This function implements the method from Schmitt (2008) in predicting the tissue to unbound plasma partition coefficients for the tissues contained in the tissue.data table.

Usage

predict_partitioning_schmitt(
  chem.name = NULL,
  chem.cas = NULL,
  dtxsid = NULL,
  species = "Human",
  model = "pbtk",
  default.to.human = FALSE,
  parameters = NULL,
  alpha = 0.001,
  adjusted.Funbound.plasma = TRUE,
  regression = TRUE,
  regression.list = c("brain", "adipose", "gut", "heart", "kidney", "liver", "lung",
    "muscle", "skin", "spleen", "bone"),
  tissues = NULL,
  minimum.Funbound.plasma = 1e-04,
  suppress.messages = FALSE
)

Value

Returns tissue to unbound plasma partition coefficients for each tissue.

Arguments

chem.name: Either the chemical name or the CAS number must be specified.
chem.cas: Either the chemical name or the CAS number must be specified.
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").
model: Model for which partition coefficients are neeeded (for example, "pbtk", "3compartment")
default.to.human: Substitutes missing animal values with human values if true (hepatic intrinsic clearance or fraction of unbound plasma).
parameters: Chemical parameters from parameterize_schmitt overrides chem.name, dtxsid, and chem.cas.
alpha: Ratio of Distribution coefficient D of totally charged species and that of the neutral form
adjusted.Funbound.plasma: Whether or not to use Funbound.plasma adjustment.
regression: Whether or not to use the regressions. Regressions are used by default.
regression.list: Tissues to use regressions on.
tissues: Vector of desired partition coefficients. Returns all by default.
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).
suppress.messages: Whether or not the output message is suppressed.

Author

Robert Pearce

Details

A separate regression is used when adjusted.Funbound.plasma is FALSE.

A regression is used for membrane affinity when not provided. The regressions for correcting each tissue are performed on tissue plasma partition coefficients (Ktissue2pu * Funbound.plasma) calculated with the corrected Funbound.plasma value and divided by this value to get Ktissue2pu. Thus the regressions should be used with the corrected Funbound.plasma.

The red blood cell regression can be used but is not by default because of the span of the data used, reducing confidence in the regression for higher and lower predicted values.

Human tissue volumes are used for species other than Rat.

References

Schmitt, Walter. "General approach for the calculation of tissue to plasma partition coefficients." Toxicology in Vitro 22.2 (2008): 457-467.

Birnbaum, L., et al. "Physiological parameter values for PBPK models." International Life Sciences Institute, Risk Science Institute, Washington, DC (1994).

Pearce, Robert G., et al. "Evaluation and calibration of high-throughput predictions of chemical distribution to tissues." Journal of pharmacokinetics and pharmacodynamics 44.6 (2017): 549-565.

Yun, Y. E., and A. N. Edginton. "Correlation-based prediction of tissue-to-plasma partition coefficients using readily available input parameters." Xenobiotica 43.10 (2013): 839-852.

Examples

Run this code


predict_partitioning_schmitt(chem.name='ibuprofen',regression=FALSE)

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