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首页> 外文期刊>Biotechnology Progress >Monitoring mAb cultivations with in-situ raman spectroscopy: The influence of spectral selectivity on calibration models and industrial use as reliable PAT tool
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Monitoring mAb cultivations with in-situ raman spectroscopy: The influence of spectral selectivity on calibration models and industrial use as reliable PAT tool

机译:用原位拉曼光谱监测MAB培养:光谱选择性对校准模型的影响和工业用途可靠的PAT工具

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摘要

Raman spectroscopy is a suitable monitoring technique for CHO cultivations. However, a thorough discussion of peaks, bands, and region assignments to key metabolites and culture attributes, and the interpretability of produced calibrations is scarce. That understanding is vital for the long-term predictive ability of monitoring models, and to facilitate lifecycle management that comply with regulatory guidelines. Several fed-batch lab-scale mAb mammalian cultivations were carried out, with in situ Raman spectroscopy used for process state estimation and attribute monitoring. The goal was to evaluate its use as a process analytical technology (PAT) tool to detect residual glucose and lactate levels, understand their dynamics and interconversion, and eventually estimate key performance culture and product quality attributes. Glucose and lactate models were optimized up to 0.31 gL(-1) with 3 Latent Variables (LVs) and 0.19 gL(-1) (2 LVs) accuracy, respectively. Glutamine and product titer models, were not specific and accurate enough, even though indirect calibrations were obtained with a RMSEP of 0.12 gL(-1) (4 LVs) and 0.29 gL(-1) (5 LVs), respectively. A critical discussion and details about the extensive work done in calibration development and optimization are provided. Namely, considering a risk-based selection of variability sources impacting sample spectra, executing designed experiments with spiked cultivations, and using advanced chemometric procedures for variable selection and model cross validation. A strategy is presented to evaluation Raman spectroscopy as a reliable PAT technology fit-for industrial use. (c) 2018 American Institute of Chemical Engineers Biotechnol. Prog., 34:659-670, 2018
机译:拉曼光谱是CHO培养的合适监测技术。然而,对关键代谢物和文化属性的峰,乐队和区域分配的彻底讨论,以及产生校准的可解释性是稀缺的。这种理解对于监测模型的长期预测能力至关重要,并促进符合监管指南的生命周期管理。进行了几种美联储批次实验室规模的MAB哺乳动物培养,以原位拉曼光谱用于处理状态估计和属性监测。目标是评估其用作过程分析技术(PAT)工具,以检测残留的葡萄糖和乳酸水平,了解它们的动态和互联,最终估计关键性能文化和产品质量属性。葡萄糖和乳酸模型可分别优化高达0.31G1(-1),分别具有3个潜变量(LV)和0.19GL(-1)(2 LV)精度。谷氨酰胺和产品滴度模型,即使使用0.12G1(4LV)和0.29G1(5LV)的RMSEP获得间接校准,也不足够精确。提供了关于校准开发和优化的广泛工作的关键讨论和细节。即,考虑到基于风险的可变性源的选择,影响样本光谱,用尖刺的栽培执行设计的实验,并使用先进的化学计量程序进行可变选择和模型交叉验证。提出了一种评估拉曼光谱作为适合工业用途的可靠的PAT技术。 (c)2018美国化学工程师学院Biotechnol。 Prog。,34:659-670,2018

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