What's new in MonolixSuite 2023
  • Less programming for you and more time to explore models and results thanks to a user-friendly environment with a modern graphical interface design, intuitive workflow, clear display of settings and results, and interactive data visualization.

  • Fast and efficient model development using built-in libraries with more than 30 thousand editable models, automatic algorithms for initialization, advanced model building tools, and a full set of interactive diagnostic tools.

  • Confidence and reliable convergence for all types of data, sparse data sets, and complex models thanks to the innovative implementation of the SAEM algorithm.

Very easy to use with the GUI

Designed for ease of use with a modern, user-friendly graphical interface. Simple and intuitive workflow means less programming for you and more focus on exploring models and pharmacology.

Advanced statistical methodologies

Lixoft, in collaboration with Inria, pioneered the implementation of the SAEM algorithm. Reliable convergence for all types of data and innovative automatic model building tools are a centerpiece in population modeling provided by Monolix.

Automated generation of diagnostic plots

Automatic generation of a full set of diagnostic plots gives immediate feedback, while the interactive features assure to make the most of the analysis. In only a few clicks you create the VPC, split it by any patient subgroup, adjust axis settings, and export it to a report.

Increased productivity and quality

Efficient C++ solver package, standardized model language Mlxtran, built-in model libraries, integrated automatic tools and interoperability across other applications in the Suite all contribute to better productivity and quality or the results.

03. Monolix WHAT & HOW
Novel Approaches

Support of all relevant data types and statistical features for population modeling

For all cases, the right statistical methodology has been developed to properly handle modeling and parameter estimation processes. Monolix covers:

  • Continuous, categorical, count and time to event data (or any combination)
  • Mixture models and mixtures of models
  • Inter-occasion variability with any number of levels
  • Normal, lognormal, logit, probit and user defined distributions for the individual parameters
  • Proper handling of BLQ data
  • Effect of covariates (continuous and categorical) and correlations
  • and more

Mlxtran, model libraries, mlxEditor and Sycomore

Mlxtran – a human readable language designed for custom-build models; a simple, yet powerful, suitable for simple as well as complex systems Pharmacology models.

Built-in Monolix libraries – fully documented, open-source libraries with more then 30000 models, from PK, PKPD, count/categorical/time-to-event, to TMDD, parent-metabolite and tumor growth. Analytical solutions, which are implemented for a large class of models, together with the automatic initialization procedures available for any model assure the highest performance of parameter estimation.

mlxEditor – advanced text editor, integrated with Monolix and equipped with a dedicated syntax check for the Mlxtran language.

Sycomore – interconnected application for systematic and visual management of Monolix projects and direct models’ comparison.

Outputs and plots

All results are displayed in sortable and formatted tables easy to copy in any document and exported in the result folder in an R-compatible format. Interactive diagnostic plots are also automatically generated for straightforward interpretation of the results.

R API to automate your process

All steps performed in Monolix can be run from R with the LixoftConnectors package. What you have done once intuitively in the interface for a specific project can be generalized to a script automating the process for any other dataset and model.

Comprehensive documentation and examples

Great care has been taken to provide the user with a comprehensive Monolix documentation that includes methodology, software manuals and tutorials.
A wide collection of examples that include models and data can be used as templates to start your own project.

A lot of online material (feature of the weeks, webinars, …) on our Lixoft University page.

Monolix has been widely used by pharmaceutical companies and smaller biotech, as well as universities and research institutes, government agencies, hospitals, and non-profit organizations.
Some of the routine applications include:

  • data visualization and interactive exploration with personalized charts options and stratification
  • development of NLME models that include population characteristics and variability between and within individuals
  • tests of modeling hypotheses with more than 30 000 models divided in several built-in libraries
  • parameter estimation by SAEM algorithm for all types of data, with proper handling of preclinical, sparse, multidose and censored data
  • analysis of effects of covariates using diagnostic plots, statistical tests, and automatic model building tools
  • support for preclinical, clinical trials and treatment individualization
  • conduct population modeling for tumor growth, QSP, C-QTc



Global interoperability

Extended interoperability with export between all MonolixSuite applications. In addition to the exports/imports already available, it is now possible to:

  • Export a PKanalix CA run to Simulx to predict PK for new dosing regimens.
  • Export simulations from Simulx, and individual fits or VPC simulations from Monolix, to PKanalix for NCA analysis.

Report generation

Automatic generation of a report from the GUI with result tables and plots:

  • Default report: default results tables and plots with settings, stratification and preferences customized by a user in the GUI.
  • Custom report: full customization of tables and plots.
  • Reports templates

Global display

  • Custom axis limits for Observed data and VPC plots.
  • Multiple trendlines (mean and standard error) for different covariate groups in one chart for Observed data plot.
  • Coefficient of variation
  • Feedback on the software directly from the GUI

Data formatting

A data formatting module, integrated in the GUI, to adapt a dataset to the Monolix input format.

  • Merging of several observation types
  • Add censoring information
  • Definition of a treatment
  • Adding additional columns from an external file



04. Monolix EXPERTS
Meet The Experts

How do I move forward from here?

Request for a demo with Monolix to support internal research projects and regulatory interactions.