Original post on the nlmixr2 project blog is here.
The nlmixr2 Working Group continues to expand what open-source R tooling can support in pharmacometrics. In a new post, Matthew Fidler describes adaptive dosing in rxode2: decision logic inside the model({}) block that can push bolus, infusion, reset, and observation events while the solver is running.
That matters for protocols where the next dose depends on the trajectory so far — hold a cycle, cut a dose level, start a rescue infusion — which cannot be written into a fixed event table up front. The post walks through the Friberg myelosuppression model and a Taxotere-style dose-modification table, using sticky variables to remember dose level, days at grade 4, and when the next cycle is due.
Watch the 8-minute narrated walkthrough: https://youtu.be/kuQbzj5Hm4I
Read the full post from the nlmixr2 blog: Adaptive dosing in rxode2
Why nlmixr2?
The vision of nlmixr2 is to develop a R-based open-source nonlinear mixed-effects modeling software package that can compete with commercial pharmacometric tools and is suitable for regulatory submissions.
In short, the goal of nlmixr2 is to support easy and robust nonlinear mixed effects models in R.
Get involved in the nlmixr2 working group
The nlmixr2 working group is open to anyone interested in contributing to the project. You can get involved by:
Main repo: https://github.com/nlmixr2/nlmixr2
Issues: https://github.com/nlmixr2/nlmixr2/issues
Discussions: https://github.com/nlmixr2/nlmixr2/discussions