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生物过程监测中细胞活力在线测定的传感器与技术

Sensors and Techniques for On-Line Determination of Cell Viability in Bioprocess Monitoring.

作者信息

Rösner Laura S, Walter Franziska, Ude Christian, John Gernot T, Beutel Sascha

机构信息

Institute for Technical Chemistry, Leibniz University of Hanover, 30167 Hannover, Germany.

PreSens Precision Sensing GmbH, Am BioPark 11, 93053 Regensburg, Germany.

出版信息

Bioengineering (Basel). 2022 Dec 3;9(12):762. doi: 10.3390/bioengineering9120762.

Abstract

In recent years, the bioprocessing industry has experienced significant growth and is increasingly emerging as an important economic sector. Here, efficient process management and constant control of cellular growth are essential. Good product quality and yield can only be guaranteed with high cell density and high viability. Whereas the on-line measurement of physical and chemical process parameters has been common practice for many years, the on-line determination of viability remains a challenge and few commercial on-line measurement methods have been developed to date for determining viability in industrial bioprocesses. Thus, numerous studies have recently been conducted to develop sensors for on-line viability estimation, especially in the field of optical spectroscopic sensors, which will be the focus of this review. Spectroscopic sensors are versatile, on-line and mostly non-invasive. Especially in combination with bioinformatic data analysis, they offer great potential for industrial application. Known as soft sensors, they usually enable simultaneous estimation of multiple biological variables besides viability to be obtained from the same set of measurement data. However, the majority of the presented sensors are still in the research stage, and only a few are already commercially available.

摘要

近年来,生物加工行业经历了显著增长,并日益成为一个重要的经济部门。在此,高效的过程管理和对细胞生长的持续控制至关重要。只有在高细胞密度和高活力的情况下,才能保证良好的产品质量和产量。虽然物理和化学过程参数的在线测量多年来一直是常规做法,但活力的在线测定仍然是一个挑战,迄今为止,很少有商业在线测量方法被开发用于工业生物过程中活力的测定。因此,最近进行了大量研究以开发用于在线活力估计的传感器,特别是在光学光谱传感器领域,这将是本综述的重点。光谱传感器具有通用性、在线性且大多是非侵入性的。特别是与生物信息数据分析相结合时,它们在工业应用中具有巨大潜力。作为软传感器,它们通常能够从同一组测量数据中除了活力之外同时估计多个生物变量。然而,所展示的大多数传感器仍处于研究阶段,只有少数已经商业化。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b6ce/9774925/492e230496b2/bioengineering-09-00762-g001.jpg

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