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Osmolality is a predictor for model-based real-time monitoring of concentration in protein chromatography

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The bottleneck for real time control and real time release is 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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