# Bridging the gap between individual-based and continuum models of growing cell populations

## TL;DR

This paper establishes a formal link between individual-based stochastic models and continuum PDE models for growing cell populations, showing that the latter can be derived from the former and that simulations align well.

## Contribution

It introduces a simple stochastic individual-based model and demonstrates how nonlinear PDEs for cell growth can be derived from it, bridging a gap in modeling approaches.

## Key findings

- Derivation of PDEs from the individual-based model
- Qualitative and quantitative agreement between models
- Emergence of complex patterns from simple rules

## Abstract

Continuum models for the spatial dynamics of growing cell populations have been widely used to investigate the mechanisms underpinning tissue development and tumour invasion. These models consist of nonlinear partial differential equations that describe the evolution of cellular densities in response to pressure gradients generated by population growth. Little prior work has explored the relation between such continuum models and related single-cell-based models. We present here a simple stochastic individual-based model for the spatial dynamics of multicellular systems whereby cells undergo pressure-driven movement and pressure-dependent proliferation.We show that nonlinear partial differential equations commonly used to model the spatial dynamics of growing cell populations can be formally derived from the branching random walk that underlies our discrete model. Moreover, we carry out a systematic comparison between the individual-based model and its continuum counterparts, both in the case of one single cell population and in the case of multiple cell populations with different biophysical properties. The outcomes of our comparative study demonstrate that the results of computational simulations of the individual-based model faithfully mirror the qualitative and quantitative properties of the solutions to the corresponding nonlinear partial differential equations. Ultimately, these results illustrate how the simple rules governing the dynamics of single cells in our individual-based model can lead to the emergence of complex spatial patterns of population growth observed in continuum models.