Title : Physics-guided modelling for optimising cell alignment in lab-grown meat scaffolds
Abstract:
The development of lab-grown meat and engineered tissues for healthcare applications is constrained by the challenge of controlling cell organisation within three-dimensional structures. In particular, achieving aligned and functional tissue architecture remains difficult due to the complex interplay between mechanical forces and the cellular microenvironment, leading to inefficient trial-and-error design approaches.
This research presents a physics-driven computational modelling framework to optimise scaffold design and guide cellular organisation in engineered tissues. Building on the Contractile Network Dipole Orientation (CONDOR) model, the work integrates theoretical principles of mechanics and diffusion to predict how cells orient and organise in response to both structural and environmental cues. The model specifically identifies optimal positioning and structural configurations within scaffolds that promote aligned tissue growth.
By incorporating the interaction between mechanical forces and oxygen transport, the framework enables prediction of how cells adapt their orientation under physiologically relevant conditions. This is particularly relevant for thick tissue constructs, where oxygen gradients strongly influence cell viability and structural integrity. The modelling approach allows virtual testing of scaffold geometries and conditions, significantly reducing the need for experimental trial-and-error.
Experimental validation is conducted using stem-cell-derived tissue cultured in controlled environments, where scaffold structures and oxygen conditions are systematically varied. Quantitative imaging and analysis are used to compare predicted and observed cell alignment, enabling iterative refinement of the model.
The outcomes of this research provide a predictive design tool for engineering structured tissues with improved functionality. In the context of cultivated meat, the work enables the production of thicker, more realistic products with controlled texture and structure. In healthcare, the framework supports the design of engineered tissues for regenerative medicine and disease modelling.
By linking theoretical modelling with experimental validation, this research advances a scalable and efficient approach to tissue design, transforming current empirical methods into predictive, physics-based strategies.
