Towards anatomic scale agent-based modeling with a massively parallel spatially explicit general-purpose model of...

Area of Science:

• Computational biology
• Biomedical engineering
• Systems biology

Background:

• Integrating cellular mechanisms with clinical disease states is a major challenge in biomedical research.
• Histology remains crucial for disease diagnosis, but organ-level simulation is limited.
• High-performance computing (HPC) advancements enable larger, clinically relevant biological models.

Purpose of the Study:

• To develop a novel, massively parallel computational model for simulating intestinal diseases at an anatomic scale.
• To extend the existing SEGMEnT model to achieve cell-for-cell simulations.
• To demonstrate the model's utility by simulating ileal pouchitis.

Main Methods:

• Developed the Spatially Explicitly General-purpose Model of Enteric Tissue_HPC (SEGMEnT_HPC).
• Utilized high-performance computing (HPC) for massively parallel simulations.
• Created cell-for-cell anatomic scale simulations of the gut.

Main Results:

• Successfully extended the SEGMEnT model to SEGMEnT_HPC.
• Demonstrated the capability of SEGMEnT_HPC to simulate complex pathophysiological processes.
• Presented a simulation of ileal pouchitis pathogenesis.

Conclusions:

• SEGMEnT_HPC enables high-fidelity, multi-scale simulations of intestinal diseases.
• The model facilitates the integration of microscopic and organ-level data for therapeutic engineering.
• This approach holds promise for understanding and treating conditions like ileal pouchitis.