Computational fluid dynamics based digital twins of fixed bed bioreactors validate scaling principles for recombinant adeno-associated virus gene therapy manufacturing.

Gene therapy using recombinant adeno-associated virus (rAAV) as delivery vehicles has garnered much interest in recent years. There are still significant gaps in our fundamental understanding of the manufacturing processes to deliver sufficient products. Manufacturing efforts of rAAV using HEK293 cells have commonly relied on fixed bed falling film bioreactors like the iCELLis®. We used computational fluid dynamics (CFD) to validate the operating conditions required for a predictive iCELLis® 500 scale-down model. The small-scale and at-scale systems have different flow paths causing validation of the corresponding agitation rates required to achieve the same linear flow through the fixed bed across scales to be non-trivial. Therefore, we used CFD to predict the theoretical scaling relationship. In addition, CFD could predict kLa differences between the two systems and the operating conditions required to match kLa between scales. We also confirmed that the location of DO control must be the same in both systems to achieve proper scaling. Experimental runs confirming the validity of the novel scale-down model showed that based on the modifications to the iCELLis® Nano system, we achieved similar DO, key metabolite, pH, and GC titer trends in both systems.

CFD-based bioreactor model with proportional-integral-derivative controller functionality for dissolved oxygen and pH.

A physics-based model for predicting cell culture fluid properties inside a stirred tank bioreactor with embedded PID controller logic is presented. The model evokes a time-accurate solution to the fluid velocity field and overall volumetric mass transfer coefficient, as well as the ongoing effects of interfacial mass transfer, species mixing, and aqueous chemical reactions. The modeled system also includes a direct coupling between process variables and system control variables via embedded controller logic. Satisfactory agreement is realized between the model prediction and measured bioreactor data in terms of the steady-state operating conditions and the response to setpoint changes. Simulation runtimes are suitable for industrial research and design timescales.

Modeling multiphase fluid flow, mass transfer, and chemical reactions in bioreactors using large-eddy simulation.

We present a transient large eddy simulation (LES) modeling approach for simulating the interlinked physics describing free surface hydrodynamics, multiphase mixing, reaction kinetics, and mass transport in bioreactor systems. Presented case-studies include non-reacting and reacting bioreactor systems, modeled through the inclusion of uniform reaction rates and more complex biochemical reactions described using Contois type kinetics. It is shown that the presence of reactions can result in a non-uniform spatially varying species concentration field, the magnitude and extent of which is directly related to the reaction rates and the underlying variations in the local volumetric mass transfer coefficient.

Combat Helmet Suspension System Stiffness Influences Linear Head Acceleration and White Matter Tissue Strains: Implications for Future Helmet Design.

Combat helmets are expected to protect the warfighter from a variety of blunt, blast, and ballistic threats. Their blunt impact performance is evaluated by measuring linear headform acceleration in drop tower tests, which may be indicative of skull fracture, but not necessarily brain injury. The current study leverages a blunt impact biomechanics model consisting of a head, neck, and helmet with a suspension system to predict how pad stiffness affects both (1) linear acceleration alone and (2) brain tissue response induced by both linear and rotational acceleration. The approach leverages diffusion tensor imaging information to estimate how pad stiffness influences white matter tissue strains, which may be representative of diffuse axonal injury. Simulation results demonstrate that a softer pad material reduces linear head accelerations for mild and moderate impact velocities, but a stiffer pad design minimizes linear head accelerations at high velocities. Conversely, white matter tract-oriented strains were found to be smallest with the softer pads at the severe impact velocity. The results demonstrate that the current helmet blunt impact testing standards' standalone measurement of linear acceleration does not always convey how the brain tissue responds to changes in helmet design. Consequently, future helmet testing should consider the brain's mechanical response when evaluating new designs.