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利用原位拉曼光谱监测单克隆抗体培养过程:光谱选择性对校准模型及作为可靠过程分析技术工具用于工业生产的影响

Monitoring mAb cultivations with in-situ raman spectroscopy: The influence of spectral selectivity on calibration models and industrial use as reliable PAT tool.

作者信息

Santos Rafael M, Kessler Jean-Michel, Salou Patrick, Menezes Jose C, Peinado Antonio

机构信息

Institute for Biotechnology and Biosciences, Dept. BioEngineering IST, University of Lisbon, Av. Rovisco Pais 1, Lisbon, 1049-001, Portugal.

Novartis AG, Biologics, Basel, Basel-Stadt, CH 4002, Switzerland.

出版信息

Biotechnol Prog. 2018 May;34(3):659-670. doi: 10.1002/btpr.2635. Epub 2018 Apr 17.

DOI:10.1002/btpr.2635
PMID:29603907
Abstract

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 g L with 3 Latent Variables (LVs) and 0.19 g L (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 g L (4 LVs) and 0.29 g L (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. © 2018 American Institute of Chemical Engineers Biotechnol. Prog., 34:659-670, 2018.

摘要

拉曼光谱是一种适用于中国仓鼠卵巢细胞(CHO)培养的监测技术。然而,对于关键代谢物和培养特性的峰、谱带及区域归属,以及所生成校准的可解释性,目前还缺乏深入讨论。这种理解对于监测模型的长期预测能力以及促进符合监管指南的生命周期管理至关重要。进行了几次实验室规模的单克隆抗体哺乳动物补料分批培养,使用原位拉曼光谱进行过程状态估计和特性监测。目的是评估其作为过程分析技术(PAT)工具的用途,以检测残留葡萄糖和乳酸水平,了解它们的动态变化和相互转化,并最终估计关键的培养性能和产品质量特性。葡萄糖和乳酸模型分别使用3个潜变量(LVs)和0.19 g/L(2个LVs)的精度优化至0.31 g/L。谷氨酰胺和产物滴度模型不够特异和准确,尽管分别通过0.12 g/L(4个LVs)和0.29 g/L(5个LVs)的RMSEP获得了间接校准。本文提供了关于校准开发和优化方面大量工作的批判性讨论和详细信息。具体而言,考虑基于风险选择影响样品光谱的变异性来源,进行加标培养的设计实验,并使用先进的化学计量程序进行变量选择和模型交叉验证。提出了一种策略来评估拉曼光谱作为一种适用于工业用途的可靠PAT技术。© 2018美国化学工程师学会生物技术进展,34:659 - 670,2018。

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