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Fluorescence-Based Soft Sensor for at Situ Monitoring of Chinese Hamster Ovary Cell Cultures

机译:基于荧光的软传感器用于中国仓鼠卵巢细胞培养的原位监测

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摘要

Multi-wavelength fluorescence spectroscopy was investigated as a potential tool for use in monitoring key process variables that include: viable and dead cells, recombinant protein, glucose, and ammonia concentrations for Chinese hamster ovary (CHO) cells during cultivation. For the purpose of calibrating the fluorescence-based empirical model, cells were grown in batch mode with different initial glucose and glutamine concentrations. Spectrofluorometer settings were optimized to ensure reproducibility and accuracy of the acquired spectra. With the purpose of gaining qualitative insight into the evolution of the spectra, the trajectories of individual fluorophore peaks were studied during the cultivation process. Spectral changes related to biomass and secreted proteins were investigated by comparing the spectra at various stages during the downstream processing. A partial least square regression(PLSR) was used to formulate empirical models that related the input data set, i.e., the fluorescence excitation–emission matrix, to the actual state of the system including viable cell and dead cells and recombinant protein, glucose, and ammonia concentrations. The models exhibited accurate prediction ability for the process variables of interest.
机译:研究人员将多波长荧光光谱法用作监测关键过程变量的潜在工具,这些关键过程变量包括:中国仓鼠卵巢(CHO)细胞在培养过程中的存活和死亡细胞,重组蛋白,葡萄糖和氨浓度。为了校准基于荧光的经验模型,以不同的初始葡萄糖和谷氨酰胺浓度以批处理模式生长细胞。优化了荧光分光光度计的设置,以确保所采集光谱的重现性和准确性。为了获得对光谱演变的定性见解,在培养过程中研究了各个荧光团峰的轨迹。通过比较下游加工过程中各个阶段的光谱,研究了与生物量和分泌蛋白有关的光谱变化。使用偏最小二乘回归(PLSR)来建立将输入数据集(即荧光激发-发射矩阵)与系统的实际状态(包括活细胞和死细胞以及重组蛋白,葡萄糖和氨浓度。这些模型对目标过程变量具有准确的预测能力。

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