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Changelog

pharmr.extra (development version)

  • update_parameters() now also accepts a raw nlmixr2FitCore / nlmixr2FitData object — useful when fitting outside run_nlme(). Both diagonal and off-diagonal omega elements are extracted and named per pharmpy’s IIV_X / IIV_X_IIV_Y convention, so block-omega covariances are now updated alongside variance terms (previously dropped).

  • run_nlme(), run_sim(), and create_vpc_data() now dispatch on the model engine. Pharmpy nlmixr-format models are routed through nlmixr2 / rxode2 directly (no pharmpy pyreadr dependency). NONMEM models still use the existing nmfe / PsN / pharmpy paths unchanged.

  • New control argument on run_nlme() is forwarded to nlmixr2::nlmixr2() (e.g. foceiControl()); ignored for NONMEM.

  • validate_model() now accepts nlmixr-format pharmpy models.

  • get_advan() / get_obs_compartment() return gracefully for non-NONMEM models instead of erroring on the missing control stream.

  • add_sir() now warns and no-ops for non-NONMEM models instead of silently doing nothing or aborting deep inside the covariance-record reader.

  • call_pharmpy_tool() now forwards esttool = "nlmixr" to pharmpy when a search tool (modelsearch, covsearch, iivsearch, ruvsearch, amd, bootstrap) is invoked with an nlmixr-format model. Pharmpy can drive these searches against nlmixr2 if the Python package pyreadr is installed and the system Rscript that pharmpy spawns has a working nlmixr2 / data.table install.

  • compare_nlme_runs() now detects the engine per run folder and loads nlmixr2 fits from the saved <id>.rds next to the run directory, so compare_nlme_runs() works for nlmixr2 runs too.

  • create_modelfit_info_table() is robust to fit objects reloaded from RDS whose pharmpy model attribute is no longer a live Python reference.

  • create_vpc_data() on an nlmixr fit now uses the fitted model’s parameter estimates (was silently falling back to the pre-fit initial estimates when only a fit was supplied), and restricts obs to observation rows so it matches the simulation row set.

  • run_nlme_nlmixr() now stashes an explicit data argument on the model so saved fits sim/VPC against the right dataset (previously the saved model still referenced the original model$dataset).

  • Initial CRAN submission.