Systems biology at the giga-scale: Large multiscale models of complex, heterogeneous multicellular systems br

Agent-based modelling has proven its usefulness in several biomedical projects by explaining and uncovering mechanisms in diseases. Nevertheless, the scenarios addressed in these models usually consider a small number of cells, lack cellspecific characterisation and dynamic interactions and have a simplistic environment description. Tools that enable scalable, real-sized simulations of biological systems that require complex setups are needed to have simulations closer to biomedical scenarios that can capture cell-to-cell heterogeneity and system-wide emerging properties. To deliver simulations at the giga-scale (109 cells), different tools have implemented technologies to run in high-performance computing clusters. We hereby review these efforts and detail the main areas of improvement the field needs to focus on to have simulations that are a step closer to having digital twins.

Automated summary

Agent-based modelling has been proven useful in biomedical projects, but current models suffer from limitations such as small scale, lack of cell-specific characterisation, and oversimplified environment description. Tools that allow scalable and real-sized simulations are needed to capture cell-to-cell heterogeneity and system-wide emerging properties in biomedical scenarios. Efforts have been made to implement technologies for simulations at the giga-scale, and improvement in key areas is necessary to achieve simulations closer to digital twins.