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Mathematical modeling as a tool to improve influenza vaccine production processes

机译：数学建模作为改善流感疫苗生产过程的工具

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Cell culture-based production of influenza vaccines is emerging as a promising alternative to conventional production in embryonated chicken eggs. Development and establishment of high-yield producer cell lines represents a major challenge to manufacture sufficient amounts of low-cost vaccines. One possible option to optimize vaccine production is to manipulate the expression of host cell factors relevant for virus replication. Lentiviral transduction is a gene editing method that allows to modify the expression of single or multiple host cell genes. However, due to different copy numbers and integration sites of the gene constructs the expression level shows a large cell-to-cell variability within the cell population. In this study, we will investigate the impact of genetic modifications on virus yield with the help of a structured population balance model. Therein, cell-to-cell variability is represented in terms of distributed kinetic parameter sets obtained after bootstrapping for five cell lines overexpressing a single gene. Moreover, we evaluate four different strategies to predict distributed parameter sets for cell lines overexpressing multiple genes based on the parameter distributions of the underlying single gene modifications. Furthermore, we will apply the most suitable prediction strategy to find a combination of gene modifications that leads to the highest virus productivity.
机译：基于细胞培养的流感疫苗的生产正在成为有前景的有雏鸡卵常规生产的替代方法。高产量生产细胞系的开发和建立是制造足够数量的低成本疫苗的主要挑战。优化疫苗生产的一种可能选择是操纵与病毒复制相关的宿主细胞因子的表达。慢病毒转导是一种基因编辑方法，可修改单个或多个宿主细胞基因的表达。然而，由于基因构建体的不同拷贝数和整合位点，表达水平在细胞群体内显示出很大的细胞间差异。在这项研究中，我们将借助结构化的人口平衡模型研究基因修饰对病毒产量的影响。其中，细胞之间的变异性是通过自举五种过表达单个基因的细胞系后获得的分布动力学参数集来表示的。此外，我们评估了四种不同的策略来预测基于潜在的单个基因修饰的参数分布的过表达多个基因的细胞系的分布式参数集。此外，我们将应用最合适的预测策略来找到可导致最高病毒生产率的基因修饰组合。

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