httk (version 1.8)

calc_css: Find the steady state concentration and the day it is reached.

Description

This function finds the day a chemical comes within the specified range of the analytical steady state venous blood or plasma concentration(from calc_analytic_css) for the multiple compartment, three compartment, and one compartment models, the fraction of the true steady state value reached on that day, the maximum concentration, and the average concentration at the end of the simulation.

Usage

calc_css(parameters=NULL,chem.name=NULL,chem.cas=NULL,species="Human", f = .01,
         daily.dose=1, doses.per.day=3,days = 10,output.units = "uM",
         concentration='plasma',suppress.messages=F,model='pbtk',default.to.human=F,
         f.change=0.00001,adjusted.Funbound.plasma=T,regression=T,
         well.stirred.correction=T, restrictive.clearance=T,...)

Arguments

chem.name

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

chem.cas

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

f

Fractional distance from the final steady state concentration that the average concentration must come within to be considered at steady state.

parameters

Chemical parameters from parameterize_pbtk function, 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.

doses.per.day

Number of doses per day.

days

Initial number of days to run simulation that is multiplied on each iteration.

output.units

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

concentration

Desired concentration type, 'blood' or default 'plasma'.

suppress.messages

Whether or not to suppress messages.

model

Model used in calculation, 'pbtk' for the multiple compartment model,'3compartment' for the three compartment model, and '1compartment' for the one compartment model.

default.to.human

Substitutes missing animal values with human values if true (hepatic intrinsic clearance or fraction of unbound plasma).

f.change

Fractional change of daily steady state concentration reached to stop calculating.

adjusted.Funbound.plasma

Uses adjusted Funbound.plasma when set to TRUE along with partition coefficients calculated with this value.

regression

Whether or not to use the regressions in calculating partition coefficients.

well.stirred.correction

Uses correction in calculation of hepatic clearance for well-stirred model if TRUE for model 1compartment elimination rate. This assumes clearance relative to amount unbound in whole blood instead of plasma, but converted to use with plasma concentration.

restrictive.clearance

Protein binding not taken into account (set to 1) in liver clearance if FALSE.

...

Additional arguments passed to model solver (default of solve_pbtk).

Value

frac

Fraction of the true steady state concentration reached on the day steady state is reached.

max

The maximum concentration of the simulation.

avg

The average concentration on the final day of the simulation.

the.day

The day the average concentration comes within 100 * p percent of the true steady state concentration.

Examples

# NOT RUN {
calc_css(chem.name='Bisphenol-A',doses.per.day=5,f=.001,output.units='mg/L')
# }
# NOT RUN {
parms <- parameterize_3comp(chem.name='Bisphenol-A')
parms$Funbound.plasma <- .07
calc_css(parms,concentration='blood',model='3compartment')


library("ggplot2")
out <- solve_pbtk(chem.name = "Bisphenol A", days = 50, doses.per.day = 3)
plot.data <- as.data.frame(out)
css <- calc_analytic_css(chem.name = "Bisphenol A")
c.vs.t <- ggplot(plot.data,aes(time, Cplasma)) + geom_line() +
geom_hline(yintercept = css) + ylab("Plasma Concentration (uM)") +
xlab("Day") + theme(axis.text = element_text(size = 16), axis.title =
element_text(size = 16), plot.title = element_text(size = 17)) +
ggtitle("Bisphenol A")
print(c.vs.t)

days <- NULL
avg <- NULL
max <- NULL
for(this.cas in get_cheminfo()){
css.info <- calc_css(chem.cas = this.cas, doses.per.day = 1,suppress.messages=T)
days[[this.cas]] <- css.info[["the.day"]]
avg[[this.cas]] <- css.info[["avg"]]
max[[this.cas]] <- css.info[["max"]]
}
days.data <- as.data.frame(days)
hist <- ggplot(days.data, aes(days)) +
geom_histogram(fill = "blue", binwidth = 1/6) + scale_x_log10() +
ylab("Number of Chemicals") + xlab("Days") + theme(axis.text =
element_text(size = 16), axis.title = element_text(size = 16))
print(hist)
avg.max.data <- as.data.frame(cbind(avg, max))
avg.vs.max <- ggplot(avg.max.data, aes(avg, max)) + geom_point() +
geom_abline() + scale_x_log10() + scale_y_log10() +
xlab("Average Concentration at Steady State (uM)") +
ylab("Max Concentration at Steady State (uM)") +
theme(axis.text = element_text(size = 16),
axis.title = element_text(size = 16))
print(avg.vs.max)
# }