摘要：SummaryAgent-based models (ABMs) are a natural platform for capturing the multiple time and spatial scales in biological processes. However, these models are computationally expensive, especially when including molecular-level effects. The traditional approach to simulating this type of multiscale ABM is to solve a system of ordinary differential equations for the molecular events per cell. This significantly adds to the computational cost of simulations as the number of agents grows, which contributes to many ABMs being limited to around105cells. We propose an approach that requires the same computational time independent of the number of agents. This speeds up the entire simulation by orders of magnitude, allowing for more thorough explorations of ABMs with even larger numbers of agents. We use two systems to show that the new method strongly agrees with the traditionally used approach. This computational strategy can be applied to a wide range of biological investigations.Graphical abstractDisplay OmittedHighlights•Global method solves molecular dynamics in agent-based models of biological tissue•Speeds up simulations by orders of magnitude•Preserves spatial and temporal growth dynamics•Works with both spatial and phenotypic heterogeneityIn silico biology; Mathematical biosciences; Systems biology
