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实时预测抗体捕获过程的数量和纯度

时间:2019-04-04 来源:未知 编辑:梦想论文 阅读:



Abstract
Regulatory recommendations for quality by design instead of quality by testing raised increasing interest in new sensor technologies. We have developed an online monitoring system for downstream processes, which is based on an array of online detectors. Besides the standard detectors (UV, pH, conductivity), our chromatographic workstation was equipped with a fluorescence and a mid?infrared spectrometer, a light scattering and a refractive index detector. The combination of these sensors enabled the prediction of specific protein concentration and various purity attributes such as high molecular weight impurities, DNA and HCP content during the elution phase of a chromatographic antibody capture process. Prediction models solely based on online signals were set up providing real?time predictions. No mechanistic models or information about the chromatographic runs were used. These predictions allow online pooling decisions replacing time and labor?intensive laboratory measurements. Different process variations such as changes in the column load or elution buffer were introduced to test the predictive power of the models. Extrapolation of the models worked well when the column load was changed, whereas model adjustment is necessary when the elution conditions are changed considerably.

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