Community Benchmark of Centre-Based Multiscale Modelling Tools
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The emergence of virtual human twins (VHTs) in biomedical research has sparked interest in multiscale modelling frameworks, particularly in their application bridging cellular to tissue levels. Among the diverse array of multiscale modelling tools, centre-based agent-based models (ABMs) offer a promising approach due to their depiction of cells in 3D space, closely resembling biological reality. Despite the proliferation of ABM tools addressing various biomedical challenges, comprehensive and systematic comparisons among them have been lacking. This paper presents a community-driven benchmark initiative aimed at evaluating and comparing centre-based ABMs for biomedical applications, akin to successful efforts in other scientific domains such as the Critical Assessment of Protein Structure Prediction (CASP). Enlisting developers from leading tools like BioDynaMo, Chaste, PhysiCell, and TiSim, we devised a benchmark scope, defined metrics, and established reference datasets to ensure a meaningful and equitable evaluation. Unit tests targeting different solvers within these tools were designed, ranging from diffusion and mechanics to cell cycle simulations and growth scenarios. Results from these tests demonstrate varying tool performances in handling diffusion, mechanics, and cell cycle equations, emphasising the need for standardised benchmarks and interoperability. Discussions among the community underscore the necessity for defining gold standards, fostering interoperability, and drawing lessons from analogous benchmarking experiences. The outcomes, disseminated through a public platform in collaboration with OpenEBench, aim to catalyse advancements in computational biology, offering a comprehensive resource for tool evaluation and guiding future developments in cell-level simulations. This initiative endeavours to strengthen and expand the computational biology simulation community through continued dissemination and performance-oriented benchmarking efforts.
