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Tuesday, Mar 7th, 2017
2017 Macklin Lab speaking schedule: Members of Paul Macklin’s lab are speaking at the following events: Feb. 28, 2017:┬áPaul Macklin, at the NCI PSON-CSBC Mathematical Oncology Meeting Open source tools and resources ... [read more]

Friday, Sep 9th, 2016
Coarse-graining discrete cell cycle models: Introduction One observation that often goes underappreciated in computational biology discussions is that a computational model is often a model of a model of a model ... [read more]

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PhysiCell: an open source physics-based cell simulator

Download the latest version (1.0.0)


Many multicellular systems problems can only be understood by studying how cells move, grow, divide, interact, and die. Tissue-scale dynamics emerge from systems of many interacting cells as they respond to and influence their microenvironment. The ideal "virtual laboratory" for such multicellular systems simulates both the biochemical microenvironment (the "stage") and many mechanically and biochemically interacting cells (the "players" upon the stage). PhysiCell was developed to work in concert with BioFVM to fill this role as a virtual laboratory.

Project goals

PhysiCell aims to provide a robust, scalable code for simulating large systems of cells in 3-D tissues on standard desktop computers. Among our design goals:

What's New Back to top

September 27, 2016: We submitted PhysiCell to PLoS Computational Biology as a software article. As part of that submission, PhysiCell is now available as open source, under the BSD license.

Method, accuracy, and performance Back to top

PhysiCell extends the agent-based model from Macklin et al. (2012) to 3D, with improved sub-models for cell volume regulation, cell cycling, apoptosis, and necrosis. It uses cross-platform compatible C++ (tested on OSX, Linux, and Windows), and it has been parallelized using OpenMP. More details will be available once the method is fully published.

Computational cost scales linearly with the number of simulated cells, and we have tested all the major software components for numerical accuracy and convergence. Simulations up to 1 million cells are feasible on a modern Intel i7 processor with 16-32 GB of system memory. Larger simulations are feasible on HPC compute nodes.

Back to top

We'll post some updated examples once PhysiCell ispublished. In the meantime, please enjoy this early simulation test of a 3-D hanging-drop tumor spheroid.

Licensing and disclaimers Back to top

PhysiCell is licensed under the (3-Clause) BSD License. It is GPL v2 and v3 compatible, and suitable for commercial use in many circumstances.

PhysiCell is an academic/scientific code, and it should not be used as the basis for individual medical decisions. (That's what peer review, clinical trials, and FDA oversight are for!) Always consult your physician when making medical decisions.

Downloads Back to top


PhysiCell is available for download at SourceForge. Each download includes a tutorial and code examples.

Most recent versions

Version Release Date Download link
1.0.0 12 September 2016 []
Notes: First public release


PhysiCell Method Paper:
Ghaffarizadeh et al. (2017, in review) published the original version of PhysiCell. It is under review and revision at PLoS Computational Biology.
bioRxiv preprint:
PhysiCell Method Paper: Supplementary Materials
The supplementary materials to Ghaffarizadeh et al. (2017, in review) includes more information on the underlying algorithms, reference parameter values, and extensive testing results.
A user tutorial is included with every PhysiCell download.

Support Back to top

For support, please contact Paul Macklin.

If you plan to use PhysiCell in a grant proposal, please consider including Paul Macklin as a Co-I or consultant for more dedicated support.

Development Roadmap Back to top

More soon.

How to Cite PhysiCell Back to top

PhysiCell is under review and revision at PLoS Computational Biology. For now, please reference our bioRxiv preprint:

We built our model using PhysiCell (Version 1.0.0). [1]

[1] A. Ghaffarizadeh, S.H. Friedman, S.M. Mumenthaler, and P. Macklin, PhysiCell: an Open Source Physics-Based Cell Simulator for 3-D Multicellular Systems, bioRxiv 088773, 2016. DOI: 10.1101/088773.

We will update this citation information once PhysiCell has been accepted for publication.

You can also cite an earlier (2-D) version of the model by our 2012 paper in the Journal of Theoretical Biology:

P. Macklin, M.E. Edgerton, A.M. Thompson, and V. Cristini. Patient-calibrated agent-based modelling of ductal carcinoma in situ (DCIS): From microscopic measurements to macroscopic predictions of clinical progression. J. Theor. Biol. 301:122-40, 2012. DOI: 10.1016/j.jtbi.2012.02.002.

Some Publications and Projects that cite PhysiCell

Nothing just yet. :-)

Additional topics Back to top

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