Section: New Software and Platforms

Carcinom

Computer-Assisted Research about Cancer growth and INsights on Oncological Mechanisms

Keywords: Cancer - Regression - Tumor growth

Scientific Description: This software is primarily designed to perform a modeling analysis of tumor growth kinetics. Given a data set of longitudinal measurements of tumor size in a population, it fits multiple models of tumor growth (either user-defined or selected from a library of classical models), computes goodness-of-fit statistical metrics, identifies the parameters of the models and estimates associated standard errors. Fits of the data can be performed either individual per individual or using a population approach (nonlinear mixed-effects).

Functional Description: Software for modeling and fitting tumor growth kinetics. Given a data set of longitudinal measurements of tumor size in a population, it fits multiple models of tumor growth (either user-defined or selected from a library of classical models), computes goodness-of-fit statistical metrics, identifies the parameters of the models and estimates associated standard errors. Fits of the data can be performed either on an individual basis or using a population approach (nonlinear mixed-effects).

Graphical and statistical tools of use when analyzing growth curves are also included.

News Of The Year: Submission to the French agency of software protection (APP). Development of a python module for interaction with Monolix.

• Participants: Simon Evain, Vivien Pianet and Cristina Vaghi

• Partner: Roswell Park Comprehensive Cancer Center

• Contact: Sébastien Benzekry

• Publication: Classical Mathematical Models for Description and Forecast of Experimental Tumor Growth

• URL: https://team.inria.fr/monc/software/