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PhysiCell: an Open Source Physics-Based Cell Simulator for 3-D Multicellular Systems

View ORCID ProfileAhmadreza Ghaffarizadeh, View ORCID ProfileRandy Heiland, View ORCID ProfileSamuel H. Friedman, View ORCID ProfileShannon M Mumenthaler, View ORCID ProfilePaul Macklin
doi: https://doi.org/10.1101/088773
Ahmadreza Ghaffarizadeh
3formerly Lawrence J. Ellison Institute for Transformative Medicine
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Randy Heiland
1Intelligent Systems Engineering, Indiana University, Bloomington, IN 47408, USA
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Samuel H. Friedman
3formerly Lawrence J. Ellison Institute for Transformative Medicine
4Opto-Knowledge Systems, Inc., Torrance, CA 90502, USA
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Shannon M Mumenthaler
2Lawrence J. Ellison Institute for Transformative Medicine, University of Southern California, Los Angeles, CA 90033, USA
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Paul Macklin
1Intelligent Systems Engineering, Indiana University, Bloomington, IN 47408, USA
3formerly Lawrence J. Ellison Institute for Transformative Medicine
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Abstract

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—physics-based multicellular simulator—is an open source agent-based simulator that provides both the stage and the players for studying many interacting cells in dynamic tissue microenvironments. It builds upon a multi-substrate biotransport solver to link cell phenotype to multiple diffusing substrates and signaling factors. It includes biologically-driven sub-models for cell cycling, apoptosis, necrosis, solid and fluid volume changes, mechanics, and motility “out of the box.” The C++ code has minimal dependencies, making it simple to maintain and deploy across platforms. PhysiCell has been parallelized with OpenMP, and its performance scales linearly with the number of cells. Simulations up to 105-106 cells are feasible on quad-core desktop workstations; larger simulations are attainable on single HPC compute nodes.

We demonstrate PhysiCell by simulating the impact of necrotic core biomechanics, 3-D geometry, and stochasticity on the dynamics of hanging drop tumor spheroids and ductal carcinoma in situ (DCIS) of the breast. We demonstrate stochastic motility, chemical and contact-based interaction of multiple cell types, and the extensibility of PhysiCell with examples in synthetic multicellular systems (a “cellular cargo delivery” system, with application to anti-cancer treatments), cancer heterogeneity, and cancer immunology. PhysiCell is a powerful multicellular systems simulator that will be continually improved with new capabilities and performance improvements. It also represents a significant independent code base for replicating results from other simulation platforms. The PhysiCell source code, examples, documentation, and support are available under the BSD license at http://PhysiCell.MathCancer.org and http://PhysiCell.sf.net.

Author Summary This paper introduces PhysiCell: an open source, agent-based modeling framework for 3-D multicellular simulations. It includes a standard library of sub-models for cell fluid and solid volume changes, cycle progression, apoptosis, necrosis, mechanics, and motility. PhysiCell is directly coupled to a biotransport solver to simulate many diffusing substrates and cell-secreted signals. Each cell can dynamically update its phenotype based on its microenvironmental conditions. Users can customize or replace the included sub-models.

PhysiCell runs on a variety of platforms (Linux, OSX, and Windows) with few software dependencies. Its computational cost scales linearly in the number of cells. It is feasible to simulate 500,000 cells on quad-core desktop workstations, and millions of cells on single HPC compute nodes. We demonstrate PhysiCell by simulating the impact of necrotic core biomechanics, 3-D geometry, and stochasticity on hanging drop tumor spheroids (HDS) and ductal carcinoma in situ (DCIS) of the breast. We demonstrate contact- and chemokine-based interactions among multiple cell types with examples in synthetic multicellular bioengineering, cancer heterogeneity, and cancer immunology.

We developed PhysiCell to help the scientific community tackle multicellular systems biology problems involving many interacting cells in multi-substrate microenvironments. PhysiCell is also an independent, cross-platform codebase for replicating results from other simulators.

Footnotes

  • ↵* Paul.Macklin{at}MathCancer.org

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Posted December 21, 2017.
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PhysiCell: an Open Source Physics-Based Cell Simulator for 3-D Multicellular Systems
Ahmadreza Ghaffarizadeh, Randy Heiland, Samuel H. Friedman, Shannon M Mumenthaler, Paul Macklin
bioRxiv 088773; doi: https://doi.org/10.1101/088773
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PhysiCell: an Open Source Physics-Based Cell Simulator for 3-D Multicellular Systems
Ahmadreza Ghaffarizadeh, Randy Heiland, Samuel H. Friedman, Shannon M Mumenthaler, Paul Macklin
bioRxiv 088773; doi: https://doi.org/10.1101/088773

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