ABMACT: Agent Based Model for Adaptive Cancer Therapy

This repository contains the code and data for the ABMACT model, an agent-based model for simulating adaptive cancer therapy. The model is implemented in Python and uses various libraries for numerical computations and data visualization.

The primary framework for ABM simulation is Mesa. Detailed documentation of Mesa can be found at https://mesa.readthedocs.io/stable/getting_started.html

Mesa: ter Hoeven, E., Kwakkel, J., Hess, V., Pike, T., Wang, B., rht, & Kazil, J. (2025). Mesa 3: Agent-based modeling with Python in 2025. Journal of Open Source Software, 10(107), 7668. https://doi.org/10.21105/joss.07668

Setup

1. Install required packages by running bash setup.sh
2. Download data from ABMACT-data from Zenodo at: in to data/ folder. This includes data for generating figures for lymphoma and glioblastoma mouse model, benchmarking with ODE, and sensitivity analysis.

Run Simulations

1. conda activate ABMACT
2. Modify parameter file in params/ folder as needed.
3. Modify arguments in run.sh as needed (e.g., runname, paramfile, etc.).
4. bash run.sh
5. Output will be saved in the output/{runname} folder.

More advanced options:

• Modify step length, function parameters, and other simulation settings in cell agent and TME object in model/.