httk (version 2.7.0)

calc_analytic_css: Calculate the analytic steady state plasma concentration.

Description

This function calculates the analytic steady state plasma or venous blood concentrations as a result of infusion dosing for the three compartment and multiple compartment PBTK models.

Usage

calc_analytic_css(
  chem.name = NULL,
  chem.cas = NULL,
  dtxsid = NULL,
  parameters = NULL,
  species = "human",
  daily.dose = NULL,
  dose = 1,
  dose.units = "mg/kg/day",
  route = "oral",
  output.units = "uM",
  model = "pbtk",
  concentration = "plasma",
  suppress.messages = FALSE,
  tissue = NULL,
  bioactive.free.invivo = FALSE,
  IVIVE = NULL,
  parameterize.args.list = list(),
  ...
)

Value

Steady state plasma concentration in specified units

Arguments

chem.name

Either the chemical name, CAS number, or the parameters must be specified.

chem.cas

Either the chemical name, CAS number, or the parameters 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

parameters

Chemical parameters from parameterize_pbtk (for model = 'pbtk'), parameterize_3comp (for model = '3compartment), parameterize_1comp(for model = '1compartment') or parameterize_steadystate (for model = '3compartmentss'), overrides chem.name and chem.cas.

species

Species desired (either "Rat", "Rabbit", "Dog", "Mouse", or default "Human").

daily.dose

Total daily dose, mg/kg BW.

dose

The amount of chemial to which the individual is exposed.

dose.units

The units associated with the dose received.

route

Route of exposure (either "oral", "iv", or "inhalation" default "oral").

output.units

Units for returned concentrations, defaults to uM (specify units = "uM") but can also be mg/L.

model

Model used in calculation,'gas_pbtk' for the gas pbtk model, 'pbtk' for the multiple compartment model, '3compartment' for the three compartment model, '3compartmentss' for the three compartment steady state model, and '1compartment' for one compartment model.

concentration

Desired concentration type: 'blood','tissue', or default 'plasma'. In the case that the concentration is for plasma, selecting "blood" will use the blood:plasma ratio to estimate blood concentration. In the case that the argument 'tissue' specifies a particular tissue of the body, concentration defaults to 'tissue' -- that is, the concentration in the If cocentration is set to 'blood' or 'plasma' and 'tissue' specifies a specific tissue then the value returned is for the plasma or blood in that specific tissue.

suppress.messages

Whether or not the output message is suppressed.

tissue

Desired steady state tissue concentration. Default is of NULL typically gives whole body plasma concentration.

bioactive.free.invivo

If FALSE (default), then the total concentration is treated as bioactive in vivo. If TRUE, the the unbound (free) plasma concentration is treated as bioactive in vivo. Only works with tissue = NULL in current implementation.

IVIVE

Honda et al. (2019) identified four plausible sets of assumptions for in vitro-in vivo extrapolation (IVIVE) assumptions. Argument may be set to "Honda1" through "Honda4". If used, this function overwrites the tissue, restrictive.clearance, and bioactive.free.invivo arguments. See Details below for more information.

parameterize.args.list

List of arguments passed to model's associated parameterization function, including default.to.human, adjusted.Funbound.plasma, regression, and minimum.Funbound.plasma. The default.to.human argument substitutes missing animal values with human values if true, adjusted.Funbound.plasma returns adjusted Funbound.plasma when set to TRUE along with parition coefficients calculated with this value, regression indicates whether or not to use the regressions in calculating partition coefficients, and minimum.Funbound.plasma is the value to which Monte Carlo draws less than this value are set (default is 0.0001 -- half the lowest measured Fup in our dataset).

...

Additional parameters passed to parameterize function if parameters is NULL.

parameterize.args

Additional parameters passed to parameterize function if parameters is NULL.

Author

Robert Pearce, John Wambaugh, Greg Honda, Miyuki Breen

Details

Concentrations are calculated for the specifed model with constant oral infusion dosing. All tissues other than gut, liver, and lung are the product of the steady state plasma concentration and the tissue to plasma partition coefficient.

Only four sets of IVIVE assumptions that performed well in Honda et al. (2019) are currently included in honda.ivive: "Honda1" through "Honda4". The use of max (peak) concentration can not be currently be calculated with calc_analytic_css. The httk default settings correspond to "Honda3":

	In Vivo Conc.	Metabolic Clearance	Bioactive Chemical Conc. In Vivo	TK Statistic Used*	Bioactive Chemical Conc. In Vitro
Honda1	Veinous (Plasma)	Restrictive	Free	Mean Conc. In Vivo	Free Conc. In Vitro
Honda2	Veinous	Restrictive	Free	Mean Conc. In Vivo	Nominal Conc. In Vitro
Honda3	Veinous	Restrictive	Total	Mean Conc. In Vivo	Nominal Conc. In Vitro
Honda4	Target Tissue	Non-restrictive	Total	Mean Conc. In Vivo	Nominal Conc. In Vitro

"Honda1" uses plasma concentration, restrictive clearance, and treats the unbound invivo concentration as bioactive. For IVIVE, any input nominal concentration in vitro should be converted to cfree.invitro using armitage_eval, otherwise performance will be the same as "Honda2".

References

honda2019usinghttk

See Also

calc_css

Examples

calc_analytic_css(chem.name='Bisphenol-A',output.units='mg/L',
                 model='3compartment',concentration='blood')

# \donttest{
# Test that the underlying PK models give the same answers:
calc_analytic_css(chem.cas="15972-60-8")
calc_analytic_css(chem.cas="15972-60-8",model="1compartment")
calc_analytic_css(chem.cas="15972-60-8",model="pbtk")
calc_analytic_css(chem.cas="15972-60-8",model="3compartment")

calc_analytic_css(chem.name='Bisphenol-A',tissue='liver',species='rabbit',
                 parameterize.args.list = list(
                                default.to.human=TRUE,
                                adjusted.Funbound.plasma=TRUE,
                                regression=TRUE,
                                minimum.Funbound.plasma=1e-4),daily.dose=2)

calc_analytic_css(chem.name="bisphenol a",model="1compartment")

calc_analytic_css(chem.cas="80-05-7",model="3compartmentss")

params <- parameterize_pbtk(chem.cas="80-05-7") 

calc_analytic_css(parameters=params,model="pbtk")

# Try various chemicals with differing parameter sources/issues:
calc_analytic_css(chem.name="Betaxolol")
calc_analytic_css(chem.name="Tacrine",model="pbtk")
calc_analytic_css(chem.name="Dicofol",model="1compartment")
calc_analytic_css(chem.name="Diflubenzuron",model="3compartment")
calc_analytic_css(chem.name="Theobromine",model="3compartmentss")

# permutations on steady-state for the 1compartment model
calc_analytic_css(chem.name="bisphenol a",
                  model="1compartment")
calc_analytic_css(chem.cas="80-05-7",
                  model="1compartment")
calc_analytic_css(parameters=parameterize_1comp(chem.cas="80-05-7"),
                  model="1compartment")
calc_analytic_css(chem.cas="80-05-7",
                  model="1compartment",
                  tissue="liver")
calc_analytic_css(chem.cas="80-05-7",
                  model="1compartment",
                  tissue="brain")

# permutations on steady-state for the 3compartment model
calc_analytic_css(chem.cas="80-05-7",
                  model="3compartment")
calc_analytic_css(parameters=parameterize_3comp(chem.cas="80-05-7"),
                  model="3compartment")
calc_analytic_css(chem.name="bisphenol a",
                  model="3compartment",
                  tissue="liver")
calc_analytic_css(chem.name="bisphenol a",
                  model="3compartment",
                  tissue="brain")

# permurtations on steady-state for the pbtk model:
calc_analytic_css(chem.cas="80-05-7",
                  model="pbtk")
calc_analytic_css(parameters=parameterize_pbtk(chem.cas="80-05-7"),
                  model="pbtk")
calc_analytic_css(chem.name="bisphenol a",
                  model="pbtk",
                  tissue="liver")
calc_analytic_css(chem.name="bisphenol a",
                  model="pbtk",
                  tissue="brain")

# Test oral absorption functionality:
# By default we now include calculation of Fabs and Fgut (always had Fhep):
calc_analytic_css(chem.name="bisphenol a",
                  model="pbtk")
# Therefore if we set Fabs = Fgut = 1 with keetit100=TRUE, we should get a
# higher predicted plasma steady-state concentration:
calc_analytic_css(chem.name="bisphenol a",
                  model="pbtk",
                  Caco2.options=list(keepit100=TRUE))
# }