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Invariant set theory for predicting failure of antibiotic cycling

This repository contains the computation of invariant sets for switched linear systems, with applications to a model for bacteria evolution of resistance to antibiotics. It also contains the solutions of a network-based nonlinear model for bacteria dynamics population.

The nonlinear model is based on bug:drug interactions, which provide a mutation network based on collateral effects among the antibiotics used, namely collateral sensitivity, cross-resistance, and insensitivity. This mutation network connects with a series of differential equations that estimate the rate of change of the total bacteria population. The model used to describe the total population is given by a nonlinear switching system, where the drug used serves as a control measure for the population.

For further details, please refer to: https://www.biorxiv.org/content/10.1101/2024.02.06.579227v1.abstract

Table of Contents

  1. Installation
  2. Contact
  3. Cite

Installation

Before using this project, please ensure you have the following installed:

Matlab MPT3 toolbox for working with polytope sets (Polyhedron function) Installation Steps Matlab Installation: If you haven't already, install Matlab on your system. You can obtain Matlab from MathWorks.

MPT3 Toolbox Installation: After installing Matlab, download and install the MPT3 toolbox. The MPT3 toolbox is required for working with polytope sets, specifically for utilizing the Polyhedron function.

Contact

Alejandro Anderson: [email protected] Esteban Hernandez Vargas: [email protected]

Cite

Cite the corresponding tool as follows: A. Anderson, M. W. Kinahan, A. H. Gonzalez, K. Udekwu, E. A. Hernandez-Vargas. Invariant set theory for predicting failure of antibiotic cycling, Infectious Disease Modelling, 2025.

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This code helps to employ set-control theory to predict potential failure of antibiotic cycling.

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  • MATLAB 100.0%