Cultivated meat (CM) presents a sustainable alternative to conventional animal agriculture. However, its projected benefits remain theoretical until bioprocesses can be successfully scaled from laboratory to industrial production. Traditional bioprocess scale-up relies on empirical correlations that inadequately capture the hydrodynamic heterogeneity inherent to large-scale bioreactors, creating critical bottlenecks for shear-sensitive CM cell types. Computational Fluid Dynamics (CFD) offers a mechanistic approach capable of spatiotemporally resolving flow parameters, including shear stress (τ), energy dissipation rate (ε), Kolmogorov length scale (η), and mixing time (θ), that can be directly translated to biological concerns of cell viability, oxygen supply, and mixing efficiency. This review evaluates CFD applications in CM bioprocessing, establishing connections between cellular requirements and quantifiable flow parameters. The theoretical foundations of CFD, including Reynolds-Averaged Navier-Stokes (RANS) equations and multiphase modelling frameworks for gas-liquid and solid-liquid interactions are examined. The analysis of published CFD-CM studies reveals a progressive evolution from preliminary flow characterization to hybrid CFD-cell growth kinetics modelling and CFD-guided rational scale-up strategies. Current research gaps are identified, including limited bioreactor diversity, an unexplored scale gap ranging from 20 to 2000 L, and insufficient biological validation. Experimental validation techniques for model credibility, critical challenges such as fluid property characterization and computational-biological timescale mismatch are pointed out. Finally, a staged roadmap is proposed, progressing from operating window definition through predictive growth modelling to digital twin-enabled real-time process control. This review provides researchers and engineers with a scheme for leveraging CFD as a rational tool to accelerate the upscaling of CM production.
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