Create a minimalist model"

In campsismod: Generic Implementation of a PK/PD Model

EXPORT_PNG <- FALSE

Prerequisite

For this exercise, we'll need the campsismod package. This package can be loaded as follows:

library(campsismod)

Create a minimalist model in the Notepad++ editor

Assume a very simple 1-compartment PK model with first-order eliminate rate K. Say this parameter has a typical value of log(2)/12≈0.06 (where 12 is the elimination half life) and has 15% CV. Let's also initiate the central compartment to 1000.

This can be translated into the following CAMPSIS model (

xfun::embed_file('resources/campsis_npp_plugin.xml', text="download Notepad++ plugin for CAMPSIS")

):

Let's now create our theta.csv with our single parameter K as follows:

And finally, let's also create our omega.csv to include inter-individual variability on K:

This model can now be loaded by campsismod...

model <- read.campsis("resources/minimalist_model/")

Let's simulated this model in CAMPSIS:

library(campsis)
dataset <- Dataset(25) %>% add(Observations(seq(0,24,by=0.5)))
results <- model %>% simulate(dataset=dataset, seed=1)
spaghettiPlot(results, "A_CENTRAL")

ggplot2::ggsave(filename="resources/minimalist_example_sim1.png", width=7, height=3, dpi=100)

Create the same model programmatically

The same model can be created programmatically. First, let's create an empty CAMPSIS model.

model <- CampsisModel()

Then, let's define the equation of our model parameter K.

model <- model %>% add(Equation("K", "THETA_K*exp(ETA_K)"))

We can add an ordinary differential equation as follows:

model <- model %>% add(Ode("A_CENTRAL", "-K*A_CENTRAL"))

We can init the central compartment as well on the fly:

model <- model %>% add(InitialCondition(compartment=1, "1000"))

Finally, let's define our THETA_K and ETA_K:

model <- model %>% add(Theta("K", value=0.06))
model <- model %>% add(Omega("K", value=15, type="cv%"))

This model can simulated by CAMPSIS as well. Powerful, isn't it?

library(campsis)
dataset <- Dataset(25) %>% add(Observations(seq(0,24,by=0.5)))
results <- model %>% simulate(dataset=dataset, seed=2)
spaghettiPlot(results, "A_CENTRAL")

ggplot2::ggsave(filename="resources/minimalist_example_sim2.png", width=7, height=3, dpi=100)

campsismod documentation built on Oct. 12, 2023, 5:13 p.m.