nlmixr2 3.0 is here nlmixr2 3.0 has been released and most of the related packages in the nlmixr2 ecosystem have been updated as well. Since there were a few non-backward compatible changes and breaking changes, the version has been bumped from 2 to 3. Most code will run the same, but because of the breaking change, we changed the major version. The big changes are: Non abi binary linkages between every package.
One of the things that can be useful from time to time is to calculate different PK parameters based on whatever parameters you have estimated. There is a great function, calc_derived() in pmxTools that allows this calculation of the derived parameters (by my collaborators Justin Wilkins and Bill Denney). I think this is an underrated function that can help many people with typical calculations. rxode2 has the same type of function, which can be helpful to test the linCmt() functions, rxDerived().
This month, I will talk about about a new iteration of mu-referencing in nlmixr2, which I call mu2. What is mu referencing in nlmixr2 mu-referencing is combining a fixed effect, random effect and possibly a covariate in the form: [ \theta_\mathsf{pop}+\eta_\mathsf{individual}+\theta_\mathsf{covariate}\times \mathsf{DataCovariate} ] Often they are placed in exponentials for these to be log-normally distributed like: [ \exp\left(\theta_\mathsf{pop}+\eta_\mathsf{individual}+\theta_\mathsf{covariate}\times \mathsf{DataCovariate}\right) ] In optimization routines like saem, these are switched out with a single parameter during optimization classically called (\phi) in both NONMEM and Monolix.
Both nlmixr2 and rxode2 have been updated, the below describes all the nlmixr2 related packages (maintained by the nlmixr2 team). Most of items in this release are bug fixes. One of the changes will make random number generation platform independent. Unfortunately, this means simulations from within rxode2/nlmixr2 will have different numbers drawn from random distributions but I think platform independence is important enough to push this change through. Versions of new packages nlmixr2 2.
One of the exciting new features of the recent rxode2 is user functions. This allows you to define your own R functions for use in nlmixr2 or rxode2. This new feature can really help make your code more concise by reusing custom transformations or apply more complex routines. This can call R functions directly, but at a cost – single threaded and slower execution. However, you can reduce the cost by converting the R functions to C automatically with rxFun().