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:

  • Scalable: Capable of simulating at least 500,000 cells on modern quad-core desktops.
  • Physics-based: Cells are not constrained by lattice positions, but instead move according to biomechanical forces. Cells change fluid and solid (biomass) volumes according to physical processes.
  • Calibration to digital cell lines: We will be able to read MultiCellDS-formatted digital cell lines to initialize cell phenotypes and their sensitivities to the microenvironment.
  • Calibration by snapshots: Reading in a simulation snapshot (or in the future, a properly-annotated experimental/clinical image) will arrange cells and configure the tissues.
  • Realistic cell cycle: Cells go through G0/G1, S, G2, and M phases, along with realistic rates of volumetric growth.
  • Realistic apoptosis: Apoptotic cell death includes volume loss rates and adhesive changes to mimic experimental observations.
  • Realistic necrosis: Necrotic cell death includes volume loss rates and adhesive changes to mimic early cell swelling, lysis, pyknosis, calcification (where appropriate, such as ductal carcinoma in situ), and other in vivo observations.
  • Microenvironment coupling: Cell cycle progression, apoptosis, and necrosis are all microenvironment-dependent. We use BioFVM for the microenvironment modeling.
  • Heterogeneity: Cells choose their phenotypic parameters according to the ranges indicated in their digital cell lines. If heterogeneity has been experimentally recorded, it will be reproduced in the cells.
  • Open source and cross-platform compatible: Use standard, compliant C++ (targeting GCC and Intel C++ Compiler) with minimal external dependencies.
  • Iterative progress: The first release will focus on getting good performance with reasonable accuracy; later releases will improve accuracy, increase performance, and add new capabilities.