Nonlinear Mixed Effects Models in Population PK/PD, Extra Support Functions.

nlmixr2extra

The goal of nlmixr2extra is to provide the tools to help with common pharmacometric tasks with nlmixr2 models like bootstrapping, covariate selection etc.

Installation

You can install the development version of nlmixr2extra from GitHub with:

# install.packages("remotes")
remotes::install_github("nlmixr2/nlmixr2data")
remotes::install_github("nlmixr2/lotri")
remotes::install_github("nlmixr2/rxode2")
remotes::install_github("nlmixr2/nlmixr2est")
remotes::install_github("nlmixr2/nlmixr2extra")

Example of a bootstrapFit()

This is a basic example of bootstrapping provided by this package

library(nlmixr2est)
#> Loading required package: nlmixr2data
library(nlmixr2extra)
# basic example code
# The basic model consists of an ini block that has initial estimates
one.compartment <- function() {
  ini({
    tka <- 0.45; label("Absorption rate, Ka")
    tcl <- 1; label("Clearance, Cl")
    tv <- 3.45; label("Central volumne, V")
    eta.ka ~ 0.6
    eta.cl ~ 0.3
    eta.v ~ 0.1
    add.sd <- 0.7; label("Additive residual error")
  })
  # and a model block with the error specification and model specification
  model({
    ka <- exp(tka + eta.ka)
    cl <- exp(tcl + eta.cl)
    v <- exp(tv + eta.v)
    d/dt(depot) = -ka * depot
    d/dt(center) = ka * depot - cl / v * center
    cp = center / v
    cp ~ add(add.sd)
  })
}

# The fit is performed by the function nlmixr/nlmixr2 specifying the model, data
# and estimate (in a real estimate, nBurn and nEm would be much higher.)
fit <- nlmixr2(one.compartment, theo_sd,  est="saem", saemControl(print=0, nBurn = 10, nEm = 20))
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#> → loading into symengine environment...
#> → pruning branches (`if`/`else`) of saem model...
#> ✔ done
#> → finding duplicate expressions in saem model...
#> [====|====|====|====|====|====|====|====|====|====] 0:00:00
#> → optimizing duplicate expressions in saem model...
#> [====|====|====|====|====|====|====|====|====|====] 0:00:00
#> ✔ done
#> using C compiler: 'gcc.exe (GCC) 13.2.0'
#> ℹ calculate uninformed etas
#> ℹ done
#> rxode2 3.0.2 using 8 threads (see ?getRxThreads)
#>   no cache: create with `rxCreateCache()`
#> 
#> Attaching package: 'rxode2'
#> The following objects are masked from 'package:nlmixr2est':
#> 
#>     boxCox, yeoJohnson
#> Calculating covariance matrix
#> → loading into symengine environment...
#> → pruning branches (`if`/`else`) of saem model...
#> ✔ done
#> → finding duplicate expressions in saem predOnly model 0...
#> → finding duplicate expressions in saem predOnly model 1...
#> → optimizing duplicate expressions in saem predOnly model 1...
#> → finding duplicate expressions in saem predOnly model 2...
#> ✔ done
#> using C compiler: 'gcc.exe (GCC) 13.2.0'
#> → Calculating residuals/tables
#> ✔ done
#> → compress origData in nlmixr2 object, save 5952
#> → compress phiM in nlmixr2 object, save 3712
#> → compress parHistData in nlmixr2 object, save 2456
#> → compress saem0 in nlmixr2 object, save 27920

# In a real bootstrap, nboot would be much higher.
fit2 <- suppressMessages(bootstrapFit(fit, nboot = 5))
fit2