babelmixr2 and PopED

New babelmixr2 integrates PopED. I am excited to announce today a new version of babelmixr2 has been released that streamlines creating fast, efficient PopED databases for optimal design. With the babelmixr2 package you can: Import your NONMEM model to rxode2/nlmixr2 format using nonmem2rx Import your Monolix model to rxode2/nlmixr2 using monolix2rx Use your existing nlmixr2 model or create your own rxode2/nlmixr2 model With it in the nlmixr2 format, you can then quickly do optimal design

monolix2rx

monolix2rx has been released on CRAN. I am excited to announce that as part of the nlmixr2 3.0 series of releases, you now have a way to import a Monolix model into rxode2/nlmixr2. This is similar to how you can import the output of nonmem into a rxode2 model with nonmem2rx. I am also in the process of releasing a bug-fix revision now. Key notes in importing models to rxode2 and nlmixr2 There are a few things to note in any conversion from monolix to rxode2 and nlmixr2:

nlmixr2 3.0

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.

rxode2 calculating derived PK model parameters

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().

nlmixr2/rxode2 mu referencing 2.0

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.