Release Notes MonolixSuite2020R1

MonolixSuite 2020R1 Release Notes
October 2020

The document is the release notes for MonolixSuite2020R1 and contains the new software description, most of the evolution of the software along with the data set and Mlxtran management.

Global display


* The global display of all softwares has been improved.
* We propose the possibility to have a dark theme
* One can change the size for numerical values
* One can change the font size
* The preferences are accessible even if a project is not loaded
* One can change the number of significant digits displayed in the interface
* There is a specific visual theme for each software

Data set

There was a large evolution of the data set for the 2020 version.


* First of all, we propose the possibility to filter a data set. Thus, we propose the following actions: select a line, remove a line, select an ID, and remove an ID based on any condition with respect to the columns in the data set. In addition, it is possible to make the union and the intersection of these filters. It will also be possible to create the complementary filter of a proposed one. Finally, it is possible to have several filters in a row.
* Addition of a STRATIFICATION CONTINUOUS COVARIATE and STRATIFICATION CATEGORICAL COVARIATE column types in order to have covariates (either continuous or categorical) that will be available in the plots but not in the covariates available in the statistical model of Monolix.
* Creation of the Additional covariate tab in the data. The user can add covariates based on the information of the data set. The number of observations (per observation ID), the number of doses, the dose regimen, first dose amount, …are accessible. The user can also rename them.
* The data displayed after acceptation of the data set are the interpreted data
* it is possible not to display the ignored columns



* A tumor growth inhibition model library was added
* The display of the models of the libraries is much faster
* There is a search engine in the model libraries for faster and simplified access
* There is a now button to clear the library filters
* The TTE library was updated to be also written with a proportional hazard



* The data viewer has been replaced by a plot Observed data, representing only the observation with respect to time. When there are several outputs, several observed data plots are created and a bivariate viewer is created.
* It is possible to choose between hovering and keeping the doses always visible in the observed data
* All the covariates are now already preallocated for stratification.
* The mean and the standard deviation of a group can be displayed. The bins are configured and computed with the same method as in the rest of the software.
* It is possible to display the values of the mean and the sd either as a tooltip or as a label.
* It is possible to group the plots by outcome or by chart type.


Monolix Interface

Data tab
* cf Data set

Structural model tab

* cf Mlxtran

Initial estimates tab

* The calculation and display is much faster
* The “discretization” was renamed “grid size” and the value by default is now 250.
* The Increment button was removed
* It is possible to have several references and highlight one of the references
* It is possible to change the appearance of the reference curves (pattern of dashes and gaps)
* It is possible to restore the initial values
* it is possible toggle the settings

Statistical model and tasks tab

* The vertical scroll bar is now for each section
* It is possible to close the Task part and the the Observation model task
* The formula button have been moved to make it clearer

Comment tab

* The comment tab is now displayed with another icon
* The preview with markdown formatting is visible only upon selection

Export Menu

* It is possible to export your Monolix project directly to Simulx
* It is possible to export the VPC data

Monolix calculation engine

Population parameter estimation

* The algorithm was optimized when there are several levels of variability but not on all levels

Conditional distribution

* We added a parameter maxNbIteraions in the conditional distribution tasks to limit the number of iterations. A warning is provided if this number is achieved

Fisher Information Matrix calculation

* The algorithm was updated for the stochastic approximation for cases when there is low variability on some parameters.


* The tests were updated to better take the correlated covariates into account: the correlations between the covariates in the model and the parameters are now tested with a linear regression on the averages over the replicates, and a t-test on the betas estimated in the regression to check whether they are significantly different from 0. This test is also used in COSSAC.

Monolix plots

Observed data chart

* cf Datxplore

Correlation of the random effects chart

* The decorrelated random effects are now well exported.

Monolix Connectors

* The connector computeChartsData was updated to allow the export of the VPC
* The following connectors have been added: applyFilter, createFilter, editFilter, exportData, fillFixedEffectsByAutiInit, getTests.

Bug fix:
* In Initial estimates, the horizontal scroll bar was missing
* In Initial estimates, beta coefficients for categorical covariates with more than 2 categories appeared in blue even when fixed instead of red
* Bayesian estimation was not applied on parameters without variability



* It is possible to define a reference project and then have all the objective functions values in comparison to the reference project
* It is possible to remove subdirectories

Bug fix:
* For discrete/tte projects, the icon for the standard error with linearization was wrong
* The setting for number of exploratory iterations with exploratory autostop disabled was not well displayed
* Instability of the software when loading several projects at the same time from a subfolder was corrected


Simulx has been deeply updated to have a new user interface. Notice that Mlxplore is now embedded in Simulx
Simulx provides the possibility to define a new project from scratch, import a project from Monolix, and define any element for the simulation (model, occasions, population parameters, individual parameters, covariates, treatments, outputs, and regressors). Notice that all these elements can be defined manually, imported by a Monolix project, and imported from an external file. All the definition of these elements are in a “Definition” tab.
This Simulx project can be saved and reloaded.
There is an exploration tab where the user can explore in real-time several different treatments, parameters, … In real-time means the calculations are performed directly and very fastly. This tab is close to the Mlxplore functionalities. Notice that it is possible to change the treatment (amount, starting time, …)
There is also a simulation tab where you can define the desired simulations in terms of number of individuals, parameters, covariates, treatments, outputs. One can define elements that are shared and the one that are specific to each group.
Outcome and endpoint are also available so the user can perform the trial and have its endpoint as a results.
All the results come with a “Results” tab where all the numerical parameters are defined and a “Plots” tab with all the graphical outputs. The plots are highly customizable as all the plots from the other applications.



* Data: cf Data set
* The user can now define the units of the concentration, the amount, the volume, and time. The units are also displayed in the plots and in the results files.
* It is possible to define several partial AUC
* It is possible to define which parameter to compute in the NCA analysis
* It is possible to define which parameters are defined by default in the analys in the preferences
* Information with the number of points and R2 are now displayed in the check lamda_z plot
* It is possible to hide the settings of the check lambda_z
* In the NCA plots, only the selected parameters are displayed, and the list of parameters selected by default can be changed in Preferences
* In the NCA results, it is possible to filter the summary to take only the values corresponding to some acceptance criteria
* In the NCA results, it is possible to split the summary by a defined categorical covariate.

Jonathan CHAUVINRelease Notes MonolixSuite2020R1