build your PK model










[LONGITUDINAL]
input = {Tk0, V, k12, k21, k13, k31, Vm, Km}
          
EQUATION:
cc = pkmodel(Tk0, V, k12, k21, k13, k31, Vm, Km)
adm <- list(time = c(1,23,37,45), amount = c(1,0.5,2,0.3))

p <- list(name=c('Mtt', 'Ktr', 'ka', 'V', 'Vm', 'Km', 'p'), 
          value=c(5, 1, 0.5, 10, 1, 0.6, 0.5))
t <- seq(0, 80, by=0.1)

res <- pkmodel(t,adm,p)

pl=ggplot(data=res, aes(x=time, y=cc)) + geom_line(size=1) +
          xlab("time (h)") + ylab("concentration (mg/L)")
print(pl)

Build your PK model

Select the administration route and the dosage regimen in the tab administration:

  • iv bolus, iv infusion, or oral administration,
  • time of first dose, number of doses, interdose interval, infusion time (only for infusion), amount.

Define the PK model in the tab model:

  • Define the absorption process for oral administration in the tab absorption:

    • zero-order or first-order absorption process with the associated paramameters (duration of absorption \(Tk0\) or absorption rate constant \(ka\))
    • lag time \(Tlag\)
    • transit compartment model with mean transit time \(Mtt\) and number of transit compartments \(Ntr\) (only for first-order absorption)
  • Define the distribution process in the tab distribution: 1, 2 or 3 compartments

  • Define the eliination process in the tab elimination: linear or Michaelis Menten elimination process

Define the output in the tab outputs:

  • select the time range where the predicted concentration is computed, select the number of time points of the grid where the predicted concentration is computed.

Set some settings in the tab settings: line width, linear or semi-log scale.