NOTE: nlmixr
is curently archived on CRAN. You can also use nlmixr2
which is on CRAN currenty. See http://nlmixr2.org or https://github.com/nlmixr2/nlmixr2
nlmixr
is an R package for fitting general dynamic models,
pharmacokinetic (PK) models and pharmacokinetic-pharmacodynamic (PKPD)
models in particular, with either individual data or population
data. The nlme and SAEM estimation routines can be accessed using a
universal user interface (UUI), that provides universal model and
parameter definition syntax and results in a fit object that can be
used as input into the Xpose
package. Running nlmixr using the UUI
is described in this vignette.
Under the hood nlmixr
has five main modules:
dynmodel()
and its mcmc cousindynmodel.mcmc()
for nonlinear dynamic models of individual data;nlme_lin_cmpt()
for one to three linear compartment models of population data with first order absorption, or i.v. bolus, or i.v. infusion using the nlme algorithm;nlme_ode()
for general dynamic models defined by ordinary differential equations (ODEs) of population data using the nlme algorithm;saem_fit
for general dynamic models defined by ordinary differential equations (ODEs) of population data by the Stochastic Approximation Expectation-Maximization (SAEM) algorithm;gnlmm
for generalized non-linear mixed-models (possibly defined by ordinary differential equations) of population data by the adaptive Gaussian quadrature algorithm.
A few utilities to facilitate population model building are also included in nlmixr
.
Documentation can be found at https://nlmixrdevelopment.github.io/nlmixr/, and we maintain a comprehensive and ever-growing guide to using nlmixr
at our bookdown site.
More examples and the associated data files are available at https://github.com/nlmixrdevelopment/nlmixr/tree/master/vignettes.
We recommend you have a look at RxODE
, the engine upon which nlmixr
depends, as well as xpose.nlmixr
, which provides a link to the seminal nonlinear mixed-effects model diagnostics package xpose
, and shinyMixR
, which provides a means to build a project-centric workflow around nlmixr from the R command line and from a streamlined shiny
front-end application. Members of the nlmixr team also contribute to the ggPMX
, xgxr
and pmxTools
packages. For PKPD modeling (with ODE and dosing history) with
Stan, check out Yuan Xiong's package PMXStan
.
When on CRAN, you can install the released version of nlmixr from CRAN with:
install.packages("nlmixr")
And the development version from GitHub with:
# install.packages("devtools")
devtools::install_github("nlmixrdevelopment/nlmixr")