Welcome
Why nlmixr?
The goal of nlmixr, or more accurately nlmixr2, is to support easy and robust nonlinear mixed effects models (NLMEMs) in R.
NLMEMs are used to help identify and explain the relationships between drug exposure, safety, and efficacy and the differences among population subgroups. Most often, they are built using longitudinal PK and pharmacodynamic (PD) data collected during clinical studies. These models characterize the relationships between dose, exposure and biomarker and/or clinical endpoint response over time, variability between individuals and groups, residual variability, and uncertainty.
NLMEM development in the pharmaceutical space is dominated by a small number of proprietary, commercial software tools. Although this kind of approach to software has some advantages, adopting an open-source, open-science paradigm also has benefits - third-party auditing or adjustments are possible, and the precise model-fitting methodology employed can be determined by anyone with the time and energy to review the source code. We see nlmixr2 being especially useful in being able to integrate into the rich R ecosystem, and it is well suited for use in scripted, literate-programming workflows of the kind flourishing in the R ecosystem by means of packages such as knitr and rmarkdown.
The nlmixr2 blog
nlmixr2save: fits you can read, runs you don't repeat
Watch on YouTube If you are at ACoP 2026 (October 11-14, National Harbor, Maryland), come find the nlmixr2save poster. This post covers the same material, with code you can run. nlmixr2save is on CRAN and version 0.2.0 is out now: install.packages("nlmixr2save") Two problems Problem 1: Fits you can’t open later. Nonlinear mixed-effects models can take minutes to weeks to fit. Once one is done, you want to keep it. The usual way is saveRDS(), but that ties the result to R’s binary format and to how nlmixr2 stored the fit internally.
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