MONOLIX (MOdèles NOn LInéaires à effets miXtes)

NEW: MONOLIX 2.4-beta (release 2008-07-30)

MONOLIX is a free software dedicated to the analysis of non linear mixed effects models. The objective of this software is to perform:

1) Parameter estimation,
- computing the maximum likelihood estimator of the parameters, without any approximation of the model
- computing standard errors for the maximum likelihood estimator,

2) Model selection,
- comparing several models using some information criteria (AIC, BIC),
- testing hypotheses using the Likelihood Ratio Test.
- testing parameters using the Wald Test.

3) Goodness of fit plots,

4) Data simulation,

Several stochastic algorithms are used in MONOLIX: stochastic approximation of EM (SAEM), Importance Sampling, MCMC, Simulated Annealing... Theoretical properties of the proposed algorithms and practical applications were published in several papers.

Using C++ powered MEX files enables MONOLIX to manage complex ODE's defined models.

MLXTRAN is a "NMTRAN-like" interpretor for writing user defined models.

MONOLIX 2.4 is a MATLAB software. If you don't use MATLAB, you can download a stand-alone executable version of MONOLIX that does not require MATLAB (note that MLXTRAN can be used with this stand-alone version).

 

This software was developed by INRIA (with the valuable help of several members of the MONOLIX Group !).

Team: Marc Lavielle, Hector Mesa, Kaelig Chatel, Clive Canape, Jean-François Horn.

MONOLIX 2.4 was developed with the financial support of Johnson & Johnson Pharmaceutical Research & Development, a Division of Janssen Pharmaceutica N.V. This collaboration was initiated thanks to Vladimir Piotrovskij and his interest for Monolix and the SAEM algorithm.