Modeling of filtration processes—Microfiltration and depth filtration for harvest of a therapeutic protein expressed in pichia pastoris at constant pressure

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Abstract

Filtration steps are ubiquitous in biotech processes due to the simplicity of operation, ease of scalability and the myriad of operations that they can be used for. Microfiltration, depth filtration, ultrafiltration and diafiltration are some of the most commonly used biotech unit operations. For clean feed streams, when fouling is minimal, scaling of these unit operations is performed linearly based on the filter area per unit volume of feed stream. However, for cases when considerable fouling occurs, such as the case of harvesting a therapeutic product expressed in Pichia pastoris, linear scaling may not be possible and current industrial practices involve use of 20–30% excess filter area over and above the calculated filter area to account for the uncertainty in scaling. In view of the fact that filters used for harvest are likely to have a very limited lifetime, this oversizing of the filters can add considerable cost of goods for the manufacturer. Modeling offers a way out of this conundrum. In this paper, we examine feasibility of using the various proposed models for filtration of a therapeutic product expressed in Pichia pastoris at constant pressure. It is observed that none of the individual models yield a satisfactory fit of the data, thus indicating that more than one fouling mechanism is at work. Filters with smaller pores were found to undergo fouling via complete pore blocking followed by cake filtration. On the other hand, filters with larger pores were found to undergo fouling via intermediate pore blocking followed by cake filtration. The proposed approach can be used for more accurate sizing of microfilters and depth filters.

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Sampath, M., Shukla, A., & Rathore, A. S. (2014). Modeling of filtration processes—Microfiltration and depth filtration for harvest of a therapeutic protein expressed in pichia pastoris at constant pressure. Bioengineering, 1(4), 260–277. https://doi.org/10.3390/bioengineering1040260

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