PhysiBoSS

PhysiBoSS 2.0 integrates stochastic Boolean and agent-based modeling to simulate multiscale cancer dynamics by linking MaBoSS intracellular signaling with PhysiCell agent-based simulations to study molecular-to-tissue level processes and drug synergies.

Key Features:

• Integration with PhysiCell: Decouples PhysiCell agent-based cell simulations from internal Boolean models to link agent behavior with explicit intracellular models.
• Intracellular signaling (MaBoSS): Implements stochastic Boolean network simulation using MaBoSS to represent intracellular signaling dynamics.
• Decoupled, model-agnostic architecture: Provides a maintainable, decoupled design that permits substitution of user-defined intracellular models independent of the agent-based layer.
• Mechanistic ODE submodels: Incorporates mechanistic ordinary differential equation submodels for substrate internalization within cells.
• Drug synergy studies: Supports simulation of drug perturbations and combinatorial treatment scenarios to analyze potential drug synergies.

Scientific Applications:

• Multiscale cancer modeling: Simulates interactions across molecular, cellular, and tissue scales to investigate mechanisms of cancer progression.
• Therapeutic hypothesis generation: Enables perturbation of signaling networks and treatment conditions to generate hypotheses about drug combinations and therapeutic strategies.

Methodology:

Combines PhysiCell agent-based modeling with MaBoSS stochastic Boolean simulation in a decoupled architecture, incorporates mechanistic ODE submodels for substrate internalization, and supports simulation of drug perturbations for synergy analysis.