PhD Dissertation Defense – Mandar Narayan Makwana – “Using computational fluid dynamics and optical sensor technology to scale cell culture platforms”

Please join us for PhD Student, Mandar Narayan Makwana’s PhD Dissertation Defense.

Cell culture vessels range from a micro scale to lab and eventually to a commercial scale vessel. Based on the mode of operation, cell culture vessels have different hydrodynamic environments, making it challenging to scale. Computational Fluid Dynamics (CFD) is one such tool that can simulate the hydrodynamics and provide insights at macro and micro-scale. Accuracy of a CFD model significantly depend on the fluid model and assumptions. Traditionally, simple two-equation fluid models were developed to solve for simple 2D flows. Unfortunately, these models are known to overpredict hydrodynamic variables such as shear and strain rates in 3D complex flows such as swirling and stirring which occurs in these cell culture vessels.   

The cost and ease of operation makes shaken vessels a perfect candidate for a high throughput process development platform. In this study, we use complex fluid models to simulate mixing of deep wells, shake flasks and bioreactor and establish scalability between these systems. Scalability criteria were estimated from CFD models and were validated with experimental data using non-invasive optical sensors. Finally, the robustness of scalability strategy was also validated using cell culture runs with different processes and cell lines.

Date: Friday, April 14, 2023

Time: 12:00–1:00 p.m. (and via Zoom)

Location: 121 Building ­– 1111 Classroom