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.
nonmem2rx/babelmixr2 I am really excited to announce that the nlmixr2 team has released a new version of babelmixr2 and a new package nonmem2rx that allows you to convert NONMEM to rxode2 or even a nlmixr2 object. To install, simply upgrade babelmixr2 with: install.packages(c("nonmem2rx", "babelmixr2")) What you can do with nonmem2rx/babelmixr2 You can do many useful tasks directly converting between nlmixr2 and NONMEM models; you can: Convert a NONMEM model to a rxode2 model
As with NONMEM, it is important to be able to compare nlmixr2 to industry standard software like Monolix. With that , in mind, I am proud to announce the first nlmixr2 to Monolix translator in babelmixr2. As with NONMEM, while this has been done before, the method whereby we are converting between the two is novel and has some surprising advantages. How to use Monolix with nlmixr2 To use Monolix in nlmixr, you do not need to change your data or your nlmixr2 dataset.
I remember attending a virtual ACoP where Tim Waterhouse said “This person is so convincing that the could sell NONMEM to a nlmixr developer”. I was in the wrong meeting so I laughed and connected to the correct meeting. While he is correct, I don’t really want to purchase a NONMEM license, and I would think that individual pharmacometricians are the same: they don’t want to buy a personal license for the software they use at work (although CROs might be different here).