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 technical post, the team introduces admixr2, an R package that fits PK/PD models directly to aggregate published data, such as mean concentration-time profiles, standard deviations, and published model estimates, when individual patient data are unavailable because of privacy, access, or competitive constraints.
The post shows how admixr2 integrates with the familiar nlmixr2/rxode2 ini()/model() syntax to model digitized mean ± SD profiles from the literature, derive aggregate data from published NLME models for meta-analytic model-based analysis (MBMA), and combine multiple study summaries in a single joint fit.
Read the full post from the nlmixr2 blog: Fitting PK/PD models to published data with admixr2
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