背景(考古学)
最优控制
补料分批培养
计算机科学
最大化
生化工程
控制变量
鉴定(生物学)
工艺工程
生物技术
生物系统
数学优化
生物
数学
工程类
食品科学
发酵
机器学习
古生物学
植物
作者
Surbhi Sharma,Jagadeesh Mahadevan,Lopamudra Giri,Kishalay Mitra
摘要
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.
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