UBC Theses and Dissertations
Computational modeling and performance characterization of an acoustic cell concentration and washing device Sabour, Niki
The success and clinical approval of CAR T-cell therapy has stimulated the development of manufacturing process technologies tailored for the needs of these new cell therapies. Cell concentration and washing is the most common unit operation such that it is crucial to perform this in a reliable and robust manner, with high yields. Acoustic cell separation provides a non-fouling filter alternative by trapping cells in a gentle ultrasonic standing wave. This innovative technology has the advantages of being operable in a closed system without cell losses to the much larger surfaces of conventional filters or in cylindrical centrifuges. However, the acoustic energy dissipation into heat causes temperature increases that need to be well understood and constrained to harmless ranges. Computational fluid dynamic models of the device energy sources and sinks were developed and investigated, including the effects of air cooling and different ultrasound power inputs. The internal temperature distributions showed that air cooling near the ultrasound source effectively cooled the device in the range acoustic power inputs were used. Thus, with the input power below 7 W at 3 mL/min flows, the temperature did not exceed 37˚C and so should not harm the cells. Within these constraints, design of experiment and modeling methods were used to maximize the separation yields as a function of the cell concentration, acoustic power and flow rate. This was applied to washing a freezing medium from Jurkat cells. A flow rate of 4 mL/min and input power of 3.8 W maximized the washed cell recovery at input cell concentration of 7x106 cell/mL, with the possibility of increasing the flow rate up to 7 mL/min without compromising the separation efficiency. This study highlights the applicability of this technology for cell separation and washing as well as the value of systematic engineering analysis to understand and maximize the performance of devices for cell therapy processing.
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