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List of known bugs

The list of known bugs in every version of MonolixSuite can be found in the release notes of the next version.

We list below the known bugs in MonolixSuite 2023R1 (they will be fixed in the next version). The 2023R1 version of Monolix can be downloaded here.


  • The lixoft folder inside temp is not deleted after installation.


  • In the Documentation tab, the tutorials section can be empty (due to issues with the host server).

Data set

  • For specific projects, the warning message about ignored columns in external treatment file of data formatting appeared each time we save the project.
  • If an ID has only censored data, when navigating through IDs in the selection panel of stratify and reaching this ID, Monolix freezes then shuts down.
  • The case “two different regressor values at the same time for the same id” is not always properly detected, although it should trigger an error at dataset load. When importing this Monolix project in Simulx, the regressor element is not created withotu any error message.

Model and Tasks

  • [Statistical Model] Modalities of categorical covariates are not properly updated in the statistical model if some of them are removed by filtering the dataset.
  • [Check initial estimates] For parameters set as “fixed”, autoinit also optimizes their value even if the value shown in the GUI did not change.
  • [Structural Model] It is possible to set a model not compatible with the data, and an error is raised without preventing the action. This can lead to a crash if setting a single event TTE model with a repeated event dataset.
  • [Scenario] After making a change to the model, the “Plots” task is disabled, to avoid generating plots that are not consistent with project settings. The bug is that the “plots” task gets re-enabled after changing number of simulations setting even if if should stay disabled.
  • [convergence assessment] After running the convergence assessment on a linux machine, the project does not reopen on a windows machine and the error ” “” is not a valid assessment type” appears. It is due to different Qt versions between linux and windows. A possible workaround is to run the convergence on linux with the 2021 version.

Plots & Reporting

  • [Charts Data] When exporting VPC Charts Data, when the “corrected prediction” option is selected, the outputted percentiles are prediction-corrected but not the observations
  • When generating a default report without results, Monolix gives an error instead of generating a report with observed data.
  • When generating a default report with invalid results, Monolix generates report with observed data without giving an error.
  • If the axes in bivariate data viewer have been modified (to select which observation goes on which axis), default report generation can get frozen.
  • [VPC] When splitting the VPC by a covariates containing special characters in the categories names, the outlier area is drawn from the middle of the prediction intervals to the empirical percentiles instead of from the border of the prediction interval to the empirical percentiles.
  • [Observed data] numbers in Information box are based on all ids from the dataset, and not all ids in the Observed data plot (ie if there are ids without data in this plot they are still counted)
  • [Observed data TTE] If at least one individual in a time-to-event dataset has two observations (even 0) at the same time, the survival estimate (Kaplan-Meier curve) is not adjusted to take into account the right-censoring events (dropouts).
  • [Observed data TTE] Events occurring at the first time in the dataset (usually 0) were missing from the Kaplan-Meier curve.
  • [Observations versus predictions] When several Obs Id are present, the “90% prediction interval” and “outlier proportion” are calculated using the error model of one of the Obs id for all others Obs id.
  • [VPC] “prediction correction” option is not taken into account when generating a report

Export from Datxplore

  • After exporting a datxplore project with filters to Monolix, filters were enabled with display issues (whereas they should be disabled), and data formatting tab had some display issues.


  • Mapping arguments are not taken into account in newProject(). You need to use setMapping() instead.
  • plotVpc() in case of TTE data and plot split by covariate leads to a wrong plot with incorrect empirical KM curve
  • plotVpc() in case of continuous data: red areas have an incorrect shape in log-scale