Model-predicted effect of radial flux distribution on oxygen and glucose pericellular concentration in constructs cultured in axisymmetric radial-flow packed-bed bioreactors

Abstract

Radial flow packed-bed bioreactors (rPBBs) overcome the transport limitations of static and axial-flow perfusion bioreactors and enable development of clinical-scale bioengineered tissues. We developed criteria to design rPBBs with uniform medium radial flux distribution along bioreactor length ensuring uniform construct perfusion. We report a model-based analysis of the effect of non-uniform axial distribution of medium radial flux on pericellular concentration of oxygen and glucose. Albeit pseudo-homogeneous, the model predicts how medium flux, solutes transport and cellular consumption interact and determine the pericellular oxygen and glucose concentrations in the presence of pore transport resistance to design optimal axisymmetric rPBBs and enable control of pericellular environment. Thus, oxygen and glucose supply may match cell requirements as tissue matures. Flow and solute transport in bioreactor empty spaces and construct was described with Navier-Stokes and Darcy-Brinkman equations, and with convection–diffusion and convection–diffusion-reaction equations, respectively. Solute transport in construct accounted for Michaelian cellular consumption and bulk medium-to-cell surface oxygen transport resistance in terms of a transport-equivalent bed of Raschig rings. The effect of relevant dimensionless groups on pericellular and bulk solute concentrations was predicted under typical tissue engineering operation and evaluated against literature data for bone tissue engineering. Axial distribution of medium radial flux influenced the distribution of pericellular solutes concentration, more so at high cell metabolic activity. Increasing medium feed flow rates relieved non-uniform solute concentration distribution and decayed at cell surface for metabolic consumption, also starting from axially non-uniform radial flux distribution. Model predictions were obtained in runtimes compatible with on-line control strategies.