Import a Monolix/Simulx project

MonolixSuite applications are interconnected and projects can be exported/imported between different applications. This interconnection is guaranteed by using the same model syntax (mlxtran language) and the same dataset format.

There are two options to create a PKanalix project from a Monolix or Simulx project*

*Note: Import and export to PKanalix is available starting from the 2023 version. In the previous versions, you can only export a PKanalix project to Monolix.

Import a Monolix project to PKanalix

To import a Monolix project, open PKanalix application and in the home page select IMPORT FROM:

 

In PKanalix, it is possible to import only a Monolix project with its original dataset. When you select in the home screen IMPORT FROM > Monolix, then PKanalix will create a new, untitled, project with:

  • Dataset tagging and formatting steps if present as in the Monolix project.
  • Dataset filters if applied as in the Monolix project.
  • NCA settings: “administration type” set to intravenous or extravascular depending on the administration in a model selected in the Monolix project.
  • NCA settings: “observation ID to use” set to the first one alphabetically (if obsid are strings) or numerically (if obsid are integers).
  • NCA settings: default PKanalix settings for the integral method, treatment of BLQ values, parameters.
  • Acceptance criteria: not selected.
  • Bioequivalence: default PKanalix settings
  • CA model: set to the same structural model and the same mapping between observation ids and model outputs as in the Monolix project
  • CA initial parameter values: equal to the initial estimates of the Monolix project
  • CA parameters constraints: none for normally distributed parameters, positive for log-normally distributed parameters; bounded with limits imported from the Monolix project for logit-normally and probit-normally distributed parameters.
  • CA calculations settings: default PKanalix settings

After the import, you can save the PKanalix project as usual, edit it and run the analysis.

Remark: Importing a Monolix project to PKanalix is only with the original dataset used to create a Monolix project. Export from Monolix to PKanalix has more options. You can choose to import a Monolix project with its original dataset, vpc dataset or with individual fits dataset, see the next section. Import from Simulx is currently unavailable.

Export from Monolix to PKanalix

To export a Monolix project to PKanalix click EXPORT PROJECT TO in the top menu “Export”:

When you export a Monolix project, in the export pop-up window you can choose:

  • to which application you want to export your current project: PKanalix or Simulx: select “PKanalix”
  • which dataset you want to use in the export: original dataset, vpc dataset, individual fits dataset

By default, Monolix will copy all files, e.g. dataset and model, next to the new PKanalix project. To keep current location of these files, switch the toggle “Generated files next to project” off. Click the “EXPORT” button at the bottom to confirm. PKanalix application will open automatically with a predefined project called “untitled”. It will contain the same pre-defined elements as during the import, see the description above. If you selected export with vpc dataset or individual fits dataset, then Monolix creates a .csv files with vpc simulations or individual model predictions in the MonolixSuite data format. These dataset will be automatically loaded in the new PKanalix project.

Export with individual fits dataset

The .csv generated file contains model predictions on a fine time grid (specified in the Plots tasks settings in Monolix) obtained with different individual parameters:

  • popPred: model predictions with individual parameters corresponding to the population parameters estimated by Monolix and the impact of the individual covariates, but random effects set to zero. For instance,\( V_i = V_{pop} \times exp^{\beta_{V,WT}\times WT_i} \)
  • popPred_medianCOV: model predictions with individual parameters corresponding to the population parameters and the impact of the covariates using the population median for continuous covariates and reference category for categorical covariates, and random effects set to zero. For instance, \( V_i = V_{pop} \times exp^{\beta_{V,WT}\times WT_{med}} \)
  • indivPred_mode: [when EBEs task has run] model predictions with individual parameters corresponding to the EBEs (conditional mode) estimated by Monolix (as displayed in Monolix Results > Indiv. param > Cond. mode.). Tagged as OBSERVATION by default.
  • indivPred_mean: [when COND. DISTRIB. task has run] model predictions with individual parameters corresponding to the conditional mean estimated by Monolix (as displayed in in Monolix Results > Indiv. param > Cond. mean.)

The dataset contains also the individual design: doses, occasions, regressors, covariates.

Export with vpc dataset

The .csv generated dataset in the Monolix format constructed from the VPC simulations and individual design (doses, occasions, regressors, covariates)

  • rep: simulation replicate. Tagged as stratification categorical covariate
  • uid: unique id obtained by concatenation of “rep” and “id”. Tagged as ID by default.
  • time/timeAfterLastDose: observation times or times after last dose
  • doseid: administration id
  • y1/observation: simulated observation values. Default header is “y1” if a model has only one output, and “observation” in case of several outputs (obsid column is created automatically). Tagged automatically as OBSERVATION