(84b) A Mechanistic Approach for Predicting Mass Transfer in Bioreactors
AIChE Annual Meeting
2021
2021 Annual Meeting
North American Mixing Forum
Computational Fluid Dynamics Simulations of Multiphase Mixing Processes
Tuesday, November 16, 2021 - 9:40am to 10:05am
The biomanufacturing processes that produce biologic drugs has become an extremely important area of
study within the pharmaceutical industry. Within such processes, the drug substance is typically produced
by living organisms within stirred tank bioreactors that require a continuous supply of sparged
oxygen. The overall oxygen transfer rate to the fluid is a nonlinear convolution of the gas bubble size distribution,
fluid properties, local fluid energy dissipation rates, and local dissolved oxygen concentrations.
The complexity of this process presents challenges to process scale-up and intensification. In this work,
we propose, implement, and validate a mechanistic transport model for predicting oxygen transfer rates
within stirred tank bioreactors. To begin, we describe the relevant conservation laws and key principles
from turbulence theory that govern mass transfer. Next, we present a physics-based modeling approach
for solving these equations in tandem and in real-time. We then systematically validate the model
against experimental data at operating scales ranging from 5 L to 2000 L. By running the algorithm on
graphics processing units (GPUs), the approach is shown to solve at timescales practical for industrial
application.
study within the pharmaceutical industry. Within such processes, the drug substance is typically produced
by living organisms within stirred tank bioreactors that require a continuous supply of sparged
oxygen. The overall oxygen transfer rate to the fluid is a nonlinear convolution of the gas bubble size distribution,
fluid properties, local fluid energy dissipation rates, and local dissolved oxygen concentrations.
The complexity of this process presents challenges to process scale-up and intensification. In this work,
we propose, implement, and validate a mechanistic transport model for predicting oxygen transfer rates
within stirred tank bioreactors. To begin, we describe the relevant conservation laws and key principles
from turbulence theory that govern mass transfer. Next, we present a physics-based modeling approach
for solving these equations in tandem and in real-time. We then systematically validate the model
against experimental data at operating scales ranging from 5 L to 2000 L. By running the algorithm on
graphics processing units (GPUs), the approach is shown to solve at timescales practical for industrial
application.
Reference:
Thomas, John A., et al. "A Mechanistic Approach for Predicting Mass Transfer in Bioreactors." Chemical Engineering Science (2021): 116538.