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Using Computational Fluid Dynamics And Optical Sensor Technology To Scale Cell Culture Platforms, Mandar Makwana Jan 2023

Using Computational Fluid Dynamics And Optical Sensor Technology To Scale Cell Culture Platforms, Mandar Makwana

KGI Theses and Dissertations

Different cell culture vessels ranging from micro scale to laboratory scale to commercial scale play critical role in upstream process development for biologics manufacturing. Based on the mode of operation, cell culture vessels have different hydrodynamic environments, making it challenging to scale. Integrated approaches using computational tools supported by experimental studies can overcome these challenges. Computational Fluid Dynamics (CFD) is one such tool that can simulate hydrodynamics within the cell culture vessels and can provide insights at macro and micro-scale. Accuracy of a CFD model significantly depends on the fluid model and assumptions. Traditionally, simple two-equation fluid models were developed …


Modeling Residence Time Distribution Of Chromatographic Perfusion Resin For Large Biopharmaceutical Molecules: A Computational Fluid Dynamic Study, Kevin Vehar Dec 2020

Modeling Residence Time Distribution Of Chromatographic Perfusion Resin For Large Biopharmaceutical Molecules: A Computational Fluid Dynamic Study, Kevin Vehar

KGI Theses and Dissertations

The need for production processes of large biotherapeutic particles, such as virus-based particles and extracellular vesicles, has risen due to increased demand in the development of vaccinations, gene therapies, and cancer treatments. Liquid chromatography plays a significant role in the purification process and is routinely used with therapeutic protein production. However, performance with larger macromolecules is often inconsistent, and parameter estimation for process development can be extremely time- and resource-intensive. This thesis aimed to utilize advances in computational fluid dynamic (CFD) modeling to generate a first-principle model of the chromatographic process while minimizing model parameter estimation's physical resource demand. Specifically, …