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确定最佳的培养基流量、细胞密度和氧气流量,以最大限度地提高昆虫细胞-杆状病毒悬浮培养体系中的病毒产量。

Identification of optimal flow rate for culture media, cell density, and oxygen toward maximization of virus production in a fed-batch baculovirus-insect cell system.

机构信息

Department of Chemical Engineering, Indian Institute of Technology, Hyderabad, Telangana, India.

出版信息

Biotechnol Bioeng. 2023 Dec;120(12):3529-3542. doi: 10.1002/bit.28558. Epub 2023 Sep 25.

Abstract

In recent times, it has been realized that novel vaccines are required to combat emerging disease outbreaks, and faster optimization is required to respond to global vaccine demands. Although, fed-batch operations offer better productivity, experiment-based optimization of a new fed-batch process remains expensive and time-consuming. In this context, we propose a novel computational framework that can be used for process optimization and control of a fed-batch baculovirus-insect cell system. Since the baculovirus expression vector system (BEVS) is known to be widely used platforms for recombinant protein/vaccine production, we chose this system to demonstrate the identification of optimal profile. Toward this, first, we constructed a mathematical model that captures the time course of cell and virus growth in a baculovirus-insect cell system. Second, the proposed model was used for numerical analysis to determine the optimal operating profiles of control variables such as culture media, cell density, and oxygen based on a multiobjective optimal control formulation. Third, a detailed comparison between batch and fed-batch culture was perfromed along with a comparison between various alternatives of fed-batch operation. Finally, we demonstrate that a model-based quantification of controlled feed addition in fed-batch culture is capable of providing better productivity as compared to a batch culture. The proposed framework can be utilized for the estimation of optimal operating regions of different control variables to achieve maximum infected cell density and virus yield while minimizing the substrate/media, uninfected cell, and oxygen consumption.

摘要

近年来,人们已经意识到需要新型疫苗来应对新出现的疾病爆发,并且需要更快地优化来满足全球对疫苗的需求。尽管分批补料操作可以提供更好的生产力,但基于实验的新型分批补料过程的优化仍然昂贵且耗时。在这种情况下,我们提出了一种新的计算框架,可用于优化和控制分批补料杆状病毒-昆虫细胞系统。由于杆状病毒表达载体系统 (BEVS) 被广泛认为是用于重组蛋白/疫苗生产的平台,因此我们选择了该系统来展示最佳方案的确定。为此,首先,我们构建了一个数学模型来捕获杆状病毒-昆虫细胞系统中细胞和病毒生长的时间过程。其次,根据多目标最优控制公式,使用所提出的模型进行数值分析,以确定控制变量(如培养基、细胞密度和氧气)的最佳操作方案。第三,对分批培养和分批补料培养进行了详细比较,并对分批补料操作的各种替代方案进行了比较。最后,我们证明了与分批培养相比,基于模型的定量控制补料在分批补料培养中能够提供更好的生产力。该框架可用于估计不同控制变量的最佳操作区域,以实现最大感染细胞密度和病毒产量,同时最小化基质/培养基、未感染细胞和氧气消耗。

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