Viral transduction is a main route for gene transfer to producer cells in biomanufacturing. Designing a transduction-based biomanufacturing process poses significant challenges, due to the complex dynamics of viral infection and virus-host interaction. This article introduces a software toolkit composed of a multiscale model and an efficient numeric technique that can be leveraged for determining genetic and process designs that optimize transduction-based biomanufacturing platforms. Viral transduction and propagation for up to two viruses simultaneously can be simulated through the model, considering viruses in either lytic or lysogenic stage, during batch, perfusion, or continuous operation. The model estimates the distribution of the viral genome(s) copy number in the cell population, which is an indicator of transduction efficiency and viral genome stability. The infection age distribution of the infected cells is also calculated, indicating how many cells are in an infection stage compatible with recombinant product expression and/or with viral amplification. The model can also consider the presence in the system of defective interfering particles, which can severely compromise the productivity of biomanufacturing processes. Model benchmarking and validation are demonstrated for case studies on the baculovirus expression vector system and influenza A propagation in suspension cultures.

中文翻译：

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生物制造中病毒转导和传播的有效模拟

病毒转导是生物制造中将基因转移至生产细胞的主要途径。由于病毒感染和病毒与宿主相互作用的复杂动力学，设计基于转导的生物制造过程面临着巨大的挑战。本文介绍了一个由多尺度模型和高效数值技术组成的软件工具包，可用于确定优化基于转导的生物制造平台的遗传和工艺设计。考虑到分批、灌注或连续操作期间处于裂解或溶原阶段的病毒，可以通过该模型同时模拟最多两种病毒的病毒转导和繁殖。该模型估计细胞群中病毒基因组拷贝数的分布，这是转导效率和病毒基因组稳定性的指标。还计算了受感染细胞的感染年龄分布，表明有多少细胞处于与重组产物表达和/或病毒扩增相容的感染阶段。该模型还可以考虑系统中存在的有缺陷的干扰颗粒，这可能会严重影响生物制造过程的生产率。模型基准测试和验证针对杆状病毒表达载体系统和悬浮培养中甲型流感传播的案例研究进行了论证。