Light-based 3D printing enables the fabrication of biological scaffolds with high precision, versatility and biocompatibility, particularly the cell-laden scaffolds with architecturally complex geometric features. However, many bioprinted tissue scaffolds suffer from low cell viability due to insufficient oxygen and nutrient supply, which is heavily influenced by scaffold structure and cultivation conditions. Current practice relies mainly on resource-intensive trial-and-error methods to optimize scaffolds’ structures and cultivation parameters. In this study, we developed a comprehensive multi-physics model integrating fluid dynamics, oxygen mass transfer, cell oxygen consumption, and cell growth processes to capture cell growth behaviors in scaffolds, establishing a robust theoretical foundation for scaffold structure optimization. The modeling results showed that a large number of parameters, such as system inlet flow rate, geometric feature size, cell parameters, and material properties, significantly impact oxygen concentration and cell growth within the scaffold. A two-step optimization strategy is proposed in this paper and was applied to obtain optimal geometric parameters of channeled scaffolds to demonstrate the model’s effectiveness for scaffold optimization. The model can be employed for scaffolds with arbitrary shapes and various materials, facilitating the optimal design of sophisticated scaffolds for more advanced tissue engineering.
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