Use the menu
Plot
to plot the PK profile, modify the PK model, the PK parameters, the dosage regimen and the design of the output.Use the menu
Table
to create and save a table with the concentration values.Use the menu
Codes
to display and download theSimulx
R code pkmodelCode.R automatically generated using the current settings, the ui.R and server.R files used for this application.
Select the administration route and the dosage regimen in the menu Administration:
- iv bolus, iv infusion, or oral administration,
- time of first dose,
- number of doses,
- interdose interval,
- amount.
- infusion time (only for infusion),
Select the parameterization in the menu Parameterization:
- rate constants (\(k\), \(k_{12}\), \(k_{21}\), \(k_{13}\), \(k_{31}\)),
- clearances (\(Cl\), \(Q_{2}\), \(V_{2}\), \(Q_{3}\), \(V_{3}\)),
Define the PK model in the menu Model:
- Define the absorption process for oral administration in the submenu 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 submenu Distribution:
- 1, 2 or 3 compartments
- volume of distribution \(V\)
- transfer rates constants \(k_{12}\) and \(k_{21}\) between compartments 1 and 2
- transfer rates constants \(k_{13}\) and \(k_{31}\) between compartments 1 and 3
- Define the elimination process in the submenu Elimination:
- linear or Michaelis Menten elimination process
- elimination rate constant \(k\), or
- Michaelis Menten parameters \(V_m\) and \(K_m\).
Define the output in the menu Output:
- 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,
- choose between linear and semi-log scale.
Model
Structural model:
1 compartment PK model with first order absorption and linear elimination.
parameters = (ka, V, Cl)
Statistical model:
- lognormal distributions on (ka, V, Cl)
- log(volume) = linear function of log(weight):
log(V_i) = log(V_pop) + beta log(w_i/70) + eta_(V,i)
- constant residual error: y = f + ae