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PhysiCell: An open source physics-based cell simulator for 3-D multicellular systems.

Ahmadreza Ghaffarizadeh1, Randy Heiland2, Samuel H Friedman1,3

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Summary
This summary is machine-generated.

PhysiCell is an open-source simulator for studying multicellular systems. It models cell behaviors and microenvironments, enabling research into cancer and other complex biological processes.

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Area of Science:

  • Computational Biology
  • Biophysics
  • Systems Biology

Background:

  • Understanding multicellular systems requires simulating cell behaviors like movement, growth, division, interaction, and death.
  • Tissue-scale dynamics arise from complex interactions between numerous cells and their microenvironment.
  • A virtual laboratory is needed to simulate both the cellular players and the biochemical microenvironment stage.

Purpose of the Study:

  • To introduce PhysiCell, an open-source, physics-based, agent-based multicellular simulator.
  • To provide a platform for studying interacting cells within dynamic tissue microenvironments.
  • To demonstrate the simulator's capabilities in modeling various biological phenomena.

Main Methods:

  • PhysiCell employs a multi-substrate biotransport solver to link cell phenotypes with diffusing substrates and signaling factors.
  • It incorporates biologically-driven sub-models for cell cycling, apoptosis, necrosis, volume changes, mechanics, and motility.
  • The simulator is implemented in C++ with minimal dependencies, parallelized with OpenMP for scalable performance.

Main Results:

  • PhysiCell enables simulations of up to 10^5-10^6 cells on standard workstations, with linear scaling.
  • Demonstrated simulations include tumor spheroids and ductal carcinoma in situ (DCIS), analyzing necrotic core biomechanics, 3-D geometry, and stochasticity.
  • Examples showcase stochastic motility, multi-type cell interactions, and applications in synthetic systems, cancer heterogeneity, and immunology.

Conclusions:

  • PhysiCell is a powerful and extensible multicellular systems simulator.
  • It offers a robust platform for replicating results and advancing research in various biological fields.
  • The open-source nature and ongoing development ensure continued improvements and broader accessibility.