Bioreactors & mixing tanks are the workhorse of the biopharmaceutical industry. It is therefore imperative that both mixing and various gas-liquid interactions in these systems should be well understood and characterized. To help reduce experimentation and provide an in-silico modeling platform for accelerated troubleshooting, design assessment and optimization of process technology transfers, we have developed Computational Fluid Dynamics (CFD)-based modeling frameworks called Mixing Analysis Toolkit (MAT) and Eulerian Multiphase Bioreactor (EMBER) model.<br/>MAT is based on single phase turbulent computational fluid dynamics (CFD) methods and computes several important performance parameters for both Newtonian and Non-Newtonian fluids in both batch and flow process conditions. EMBER is an Eulerian-Eulerian multiphase turbulence model coupled with a population balance model (PBM) to predict kLa (mass transfer coefficients).We have successfully used MAT and EMBER for tech transfer, root-cause analysis, risk mitigation, and design assessments during commercial operations at Amgen.<br/>In this presentation, we will showcase MAT and EMBER models and discuss few examples were these models were used to compute mixing performance, estimate mass transfer coefficient (kLa), and develop an information-rich in-silico design space for optimizing scale-up/scale-down strategies during process technology transfer. Both MAT & EMBER provides a sound and rigorous framework for early integration in process development activities in order to provide significant opportunities for in-silico process understanding, performance optimization and quality assurance. These models are enabling process engineers and scientists to tackle some of the challenges associated with process technology transfers, increase agility and gain speed.

MAT & EMBER: CFD modeling framework for optimizing mixing and aeration-agitation strategies in mixing tanks and bioreactors

255th National Meeting (2018)

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