Soft‐sensors application for automated feeding control in high‐throughput mammalian cell cultures

Abstract

The ever‐increasing demand for biopharmaceuticals has created the need for improving the overall productivity of culture processes. One such operational concept that is considered is fed‐batch operations as opposed to batch operations. However, optimal fed‐batch operations require complete knowledge of the cell culture to optimize the culture conditions and the nutrients feeding. For example, when using high‐throughput small‐scale bioreactors to test multiple clones that do not behave the same, depletion or overfeeding of some key components can occur if the feeding strategy is not individually optimized. Over the recent years, various solutions for real‐time measuring of the main cell culture metabolites have been proposed. Still, the complexity in the implementation of these techniques has limited their use. Soft‐sensors present an opportunity to overcome these limitations by indirectly estimating these variables in real‐time. This manuscript details the development of a new soft‐sensor‐based fed‐batch strategy to maintain substrate concentration (glucose and glutamine) at optimal levels in small‐scale multiparallel Chinese Hamster Ovary Cells cultures. Two alternatives to the standard feeding strategy were tested: an OUR soft‐sensor‐based strategy for glucose and glutamine (Strategy 1) and a dual OUR for glutamine and CO2/alkali addition for glucose soft‐sensor strategy (Strategy 2). The results demonstrated the applicability of the OUR soft‐sensor‐based strategy to optimize glucose and glutamine feedings, which yielded a 21% increase in final viable cell density (VCD) and a 31% in erythropoietin titer compared with the reference one. However, CO2/alkali addition soft‐sensor suffered from insufficient data to relate alkali addition with glucose consumption. As a result, the culture was overfed with glucose resulting in a 4% increase on final VCD, but a 9% decrease in final titer compared with the Reference Strategy.

Bioprocess Development and Bioreactor Scale-Up for the Production of Recombinant Lentiviral Viral Vectors in HEK293 Suspension Cell Culture

“…The main drawback however is the sensitivity of the precipitation process to pH or agitation force [36]. Furthermore, calcium phosphate co-precipitation usually requires the presence of animal-derived components in the medium such as serum or albumin [37,38] that is frowned upon by regulators. In comparison, the transfection efficacy of cationic lipids has been reported to be similar to or even better than calcium precipitation [39] or polyethylenimine (PEI) [40,41].…”

A Fermentation State Marker Rule Design Task in Metabolic Engineering

“…Logical marker rule can be interpreted also as a kind of soft sensor [25,26] where the meaning of the marker rule is derived from genome scale metabolic model optimization and has a mechanistic interpretation in contrast to soft sensors. There is also some similarity to biomarkers in medicine that could be sensed to identify cells' state [27].…”