MS02 - MFBM-14

Multicellular Agent-Based Modelling - The OpenVT Project (Part 2)

Monday, July 14 at 3:50pm

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Note: this minisymposia has multiple sessions. The other sessions are: Part-1, and Part-3.

James Osborne (University of Melbourne), James Glazier (Indiana University) Yi Jiang (Georgia State University)

Description:

Multicellular simulations have become indispensable in understanding complex biological phenomena, from tissue development to disease progression. But the diversity in simulation methods - from agent-based models, lattice-free models, stochastic particle simulations, etc - poses challenges in reproducibility, modularity, reusability, and integration within multi-scale simulation. This minisymposia aims to present the variety of multicellular simulations being used by the community along with the efforts to make these simulations replicable and reproducible. Through a series of scientific presentations, we will demonstrate the need for standardization, and the importance of sharing and reusing models. The minisymposia is broken up into three parts; Parts 1 and 2: Modelling Biological Systems 1 and 2. Part 3: Reproducibility and Standards. Parts 1 and 2 of the Minisymposia (Modelling Biological Systems 1 and 2) contain a series of scientifically focused talks to demonstrate the variety of modelling techniques and applications being used in multicellular simulations. These talks have a scientific focus however each talk will have 5 minutes dedicated to model specification/reproducibility/comparison. Part 3 of the Minisymposia (Reproducibility and Standards) contains a series of talks on the current efforts in reproducibility and standards for multicellular simulations including a report on the OpenVT Satellite meeting reproducibility challenge.

Claire Miller

Auckland Bioengineering Institute, NEW ZEALAND

"Multicellular modelling of endometrial cell invasion in endometriosis lesion onset"

Endometriosis is a chronic gynaecological condition that is estimated to affect 1 in 9 people with a uterus. The disease is characterised by the presence of cells similar to those that line the uterus (endometrial cells) growing as lesions outside the uterus, such as in the lining of the pelvis. It is hypothesised that the disease originates from menstrual debris entering the pelvic region via the fallopian tubes. The endometrial cells in this menstrual debris then breach the epithelial layer lining the pelvis and form lesions that intrude into the lower layers of the tissue. Very little is understood about the conditions required for endometriosis onset. The endometrial cell invasion behaviour has been hypothesised to be a result of dysfunctions in the immune system, the invading endometrial cells, the breached epithelial layer, or any combination of these. In this talk I will present a multicellular agent-based model for endometrial cell invasion of an epithelial monolayer. Using this model, I will explore several of the hypotheses around disease onset, such as those related to cell proliferation and adhesion, and assess the level to which they promote endometrial cell invasion.

Paul Macklin

Indiana University, USA

"Intuitive code-free tissue modeling in the cloud with PhysiCell"

Agent-based models (ABMs) simulate individual cells as they move and interact in a virtualized tissue microenvironment (TME). When developing an ABM for a complex multicellular system, a scientist must define diffusible chemical substrates (e.g., oxygen and signaling factors), cell types, and functional relationships between cell behaviors and the chemical and physical signals in the simulated tissue environment. To date, creating an ABM requires scientists to encode these relationships–the “rules” of the cell agents–by hand: first as qualitative statements, then as mathematics, and finally as custom-written simulation code. As a result, ABMs take substantial time to develop and debug, and their code is neither interpretable nor reusable. In this talk, we describe a new (recently published), intuitive cell behavior grammar that writes ABM rules with human-interpretable language (e.g., “IL6 increases migration speed”), and directly and uniquely transforms these interpretable statements into mathematics and model code at run-time without need for hand coding. We also show a graphical studio (PhysiCell Studio) that allows scientist users to rapidly create, explore, and refine these code-free models on the desktop or in the cloud. We show examples from cancer hypoxia, immunology, neurodevelopment, and combination cancer treatments. Beyond the reference implementation in the PhysiCell ABM framework, the modeling grammar could provide a basis for model annotation and exchange between open source simulation toolkits, including “virtual cell templates” (digital cell lines) that bundle a cell type with base behavioral parameter values and cell rules written in this grammar.

Steve Runser

ETH Zurich, SWITZERLAND

"PolyHoop & SimuCell3D: Efficient and Versatile Tissue Simulations in 2D and 3D"

Accurate simulation of epithelial tissue dynamics requires models that capture complex, polarized cell shapes with high spatial resolution. Previous approaches were hampered by high computational cost or lacked essential biological detail. To overcome these challenges, we developed two powerful new computational frameworks for simulating epithelial tissues in 2D and 3D. PolyHoop [Vetter, Runser & Iber, Comput. Phys. Commun. 299, 109128 (2024)] models cell membranes as closed flexible hoops in 2D, incorporating intra- and intercellular forces and topological events such as cell division and fusion. SimuCell3D [Runser, Vetter & Iber, Nat. Comput. Sci.] extends this approach to 3D, using triangulated surfaces to represent membranes, nuclei, and extracellular matrices, with an algorithm that automatically polarizes cells. Both tools are highly efficient, enabling simulations of hundreds of thousands of deformable epithelial cells with unprecedented spatial fidelity. In this talk, I will demonstrate how these models reproduce key epithelial features and support applications including cancer growth, cell migration, and tissue stratification dynamics.

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Annual Meeting for the Society for Mathematical Biology, 2025.