Development of automated metabolite control using mid-infrared probe for bioprocesses and vaccine manufacturing.

IF 3.2 4区 生物学 Q2 BIOTECHNOLOGY & APPLIED MICROBIOLOGY
Jennifer Reid, Manjit Haer, Airong Chen, Calvin Adams, Yu Chen Lin, Jim Cronin, Zhou Yu, Marina Kirkitadze, Tao Yuan
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引用次数: 0

Abstract

Automation of metabolite control in fermenters is fundamental to develop vaccine manufacturing processes more quickly and robustly. We created an end-to-end process analytical technology and quality by design-focused process by replacing manual control of metabolites during the development of fed-batch bioprocesses with a system that is highly adaptable and automation-enabled. Mid-infrared spectroscopy with an attenuated total reflectance probe in-line, and simple linear regression using the Beer-Lambert Law, were developed to quantitate key metabolites (glucose and glutamate) from spectral data that measured complex media during fermentation. This data was digitally connected to a process information management system, to enable continuous control of feed pumps with proportional-integral-derivative controllers that maintained nutrient levels throughout fed-batch stirred-tank fermenter processes. Continuous metabolite data from mid-infrared spectra of cultures in stirred-tank reactors enabled feedback loops and control of the feed pumps in pharmaceutical development laboratories. This improved process control of nutrient levels by 20-fold and the drug substance yield by an order of magnitude. Furthermore, the method is adaptable to other systems and enables soft sensing, such as the consumption rate of metabolites. The ability to develop quantitative metabolite templates quickly and simply for changing bioprocesses was instrumental for project acceleration and heightened process control and automation.

One-sentence summary: Intelligent digital control systems using continuous in-line metabolite data enabled end-to-end automation of fed-batch processes in stirred-tank reactors.

利用中红外探头开发用于生物工艺和疫苗生产的自动代谢物控制。
发酵罐中代谢物控制的自动化是更快速、更稳健地开发疫苗生产工艺的基础。我们创建了一个以端到端过程分析技术(PAT)和质量源于设计(QbD)为重点的流程,用一个具有高度适应性和自动化功能的系统取代了在开发喂料批次生物工艺过程中对代谢物的人工控制。利用在线衰减全反射探头和使用比尔-朗伯定律的简单线性回归,开发出了中红外(MIR)光谱法,以便从测量发酵过程中复杂培养基的光谱数据中量化关键代谢物(葡萄糖和谷氨酸)。这些数据以数字方式连接到过程信息管理系统(PIMS),以便利用比例-积分-派生(PID)控制器对进料泵进行连续控制,从而在整个喂料批次搅拌罐发酵过程中保持营养水平。从搅拌罐反应器中培养物的中红外光谱中获得的连续代谢物数据实现了反馈回路,并控制了制药开发实验室中的进料泵。这将营养水平的过程控制提高了 20 倍,药物产量提高了一个数量级。此外,该方法还可适用于其他系统,实现软传感,如代谢物的消耗率。能够快速、简单地开发出定量代谢物模板,以适应不断变化的生物工艺,这对于加快项目进度、提高工艺控制和自动化水平至关重要。
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来源期刊
Journal of Industrial Microbiology & Biotechnology
Journal of Industrial Microbiology & Biotechnology 工程技术-生物工程与应用微生物
CiteScore
7.70
自引率
0.00%
发文量
25
审稿时长
3 months
期刊介绍: The Journal of Industrial Microbiology and Biotechnology is an international journal which publishes papers describing original research, short communications, and critical reviews in the fields of biotechnology, fermentation and cell culture, biocatalysis, environmental microbiology, natural products discovery and biosynthesis, marine natural products, metabolic engineering, genomics, bioinformatics, food microbiology, and other areas of applied microbiology
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