Monolix

Monolix is a software platform for nonlinear mixed-effects modeling used in pharmacometrics to analyze population pharmacokinetic and pharmacodynamic data. It is designed to estimate typical parameter values for a population, quantify between-subject and within-subject variability, and support model-based decision making in drug development and regulatory submissions. Monolix was developed by the French software company Lixoft and is a core component of the MonolixSuite.

Models are specified in a dedicated modeling language that describes the structural PK/PD model, random effects, and residual error structure. The platform uses the SAEM (stochastic approximation expectation-maximization) algorithm for parameter estimation, which is well-suited for complex nonlinear models and sparse data. It supports covariate effects, between-subject and between-occasion variability, and various residual error models. It also provides features to handle data issues common in pharmacometrics, such as below-quantification-limit observations.

Monolix integrates with Simulx for forward simulation of concentration-time profiles under different dosing regimens and covariate scenarios, enabling trial design, dose optimization, and forecasting. The suite includes tools for model evaluation and diagnostics, such as visual predictive checks, goodness-of-fit plots, and likelihood-based model comparison. It supports data import from standard formats and outputs results in publication-ready reports and tables.

Monolix is used by pharmaceutical and biotechnical companies, researchers, and regulatory agencies to perform population PK/PD analyses, perform covariate analyses, and support dose selection and risk assessment across discovery, development, and regulatory submissions.