The bottleneck for real-time control and real-time release is the lack of product-specific in-line sensors or fast at-line methods suitable for model-based prediction of process outcome. There are multiple sensor-based parameters that help monitor a purification process, but which ones serve as predictors for protein concentration?
To answer this question, chromatography flow-through fractions were collected and analyzed for antibody concentration and osmolality, while UV280, 260, 214, pH and conductivity were measured on-line by the chromatography workstation. The root mean square error was used to assess the quality of a model-based prediction of protein quality.
This model showed that osmolality, alongside UV absorbance, is a valuable predictor for protein concentration.
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