Computational fluid dynamics enables predictable scale-up of perfusion bioreactors for microvessel production

Abstract

Scaling up microvessel culture systems is essential for producing clinically relevant vascularized tissues, yet conventional microphysiological platforms offer limited insight into how to maintain flow conditions during scale-up. Here, we present a computational—experimental framework using computational fluid dynamics (CFD) to guide the design and scaling of microvessel bioreactors. Interstitial flow (IF) distributions were predicted in two perfusion-based platforms—a permeable well-plate insert and a rhomboidal microfluidic chamber—across multiple scaling factors and hydrostatic pressures. CFD identified IF ranges conducive to microvessel network formation and quantified how geometry and pressure modulate the flow field. IF-preserving scale-up in permeable well-plate inserts generated microvessel networks with consistent morphology metrics across a more than 30-fold increase in culture volume. In microfluidic rhomboidal chambers, regions with distinct CFD-predicted IF velocity fields showed significant differences in average lumen diameter and total vessel length per area under otherwise matched experimental conditions, supporting an association between local IF environment and regional morphology. Together, these results show that CFD can predict and compare IF environments during scale-up, that preserving IF conditions during scale-up can result in similar morphology metrics, and that IF distributions inside a device can correlate with regional network morphology.