mattfidler/campsismod

Generic implementation of a drug model in pharmacometrics

campsismod

Installation

Install the latest stable release using devtools:

devtools::install_github("Calvagone/campsismod")

Basic examples

Load example from model library

Load 2-compartment PK model from built-in model library:

library(campsismod)
model <- model_library$advan4_trans4

Write CAMPSIS model

model %>% write(file="path_to_model_folder")

list.files("path_to_model_folder")
#> [1] "model.campsis" "omega.csv"     "sigma.csv"     "theta.csv"

Read and show CAMPSIS model

model <- read.campsis(file="path_to_model_folder")
show(model)
#> [MAIN]
#> KA=THETA_KA*exp(ETA_KA)
#> CL=THETA_CL*exp(ETA_CL)
#> V2=THETA_V2*exp(ETA_V2)
#> V3=THETA_V3*exp(ETA_V3)
#> Q=THETA_Q*exp(ETA_Q)
#> S2=V2
#> 
#> [ODE]
#> d/dt(A_DEPOT)=-KA*A_DEPOT
#> d/dt(A_CENTRAL)=KA*A_DEPOT + Q*A_PERIPHERAL/V3 + (-CL/V2 - Q/V2)*A_CENTRAL
#> d/dt(A_PERIPHERAL)=-Q*A_PERIPHERAL/V3 + Q*A_CENTRAL/V2
#> d/dt(A_OUTPUT)=CL*A_CENTRAL/V2
#> F=A_CENTRAL/S2
#> 
#> [ERROR]
#> CP=F
#> OBS_CP=CP*(EPS_PROP + 1)
#> Y=OBS_CP
#> 
#> 
#> THETA's:
#>   name index value   fix
#> 1   KA     1     1 FALSE
#> 2   CL     2     5 FALSE
#> 3   V2     3    80 FALSE
#> 4   V3     4    20 FALSE
#> 5    Q     5     4 FALSE
#> OMEGA's:
#>   name index index2 value   fix type same
#> 1   KA     1      1 0.025 FALSE  var   NA
#> 2   CL     2      2 0.025 FALSE  var   NA
#> 3   V2     3      3 0.025 FALSE  var   NA
#> 4   V3     4      4 0.025 FALSE  var   NA
#> 5    Q     5      5 0.025 FALSE  var   NA
#> SIGMA's:
#>   name index index2 value   fix type
#> 1 PROP     1      1 0.025 FALSE  var
#> No variance-covariance matrix
#> 
#> Compartments:
#> A_DEPOT (CMT=1)
#> A_CENTRAL (CMT=2)
#> A_PERIPHERAL (CMT=3)
#> A_OUTPUT (CMT=4)

Simulate with RxODE or mrgsolve

library(campsis)

dataset <- Dataset(5) %>%
  add(Bolus(time=0, amount=1000, ii=12, addl=2)) %>%
  add(Observations(times=0:36))

rxode <- model %>% simulate(dataset=dataset, dest="RxODE", seed=1)
mrgsolve <- model %>% simulate(dataset=dataset, dest="mrgsolve", seed=1)

spaghettiPlot(rxode, "CP")

spaghettiPlot(mrgsolve, "CP")