Model-based optimization of antibody galactosylation in CHO cell culture
Model-based optimization of antibody galactosylation in CHO cell culture
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DOI：
10.1002/bit.26960
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发表时间：
2019-07-01
影响因子：
3.8
通讯作者：
Kontoravdi, Cleo
中科院分区：
文献类型：
--
作者：
Kotidis, Pavlos;Jedrzejewski, Philip;Kontoravdi, Cleo
从产品安全性和批次间一致性的角度来看，对抗体治疗剂的聚糖部分的快速控制是非常期望的。提高抗体生产率的策略可能会损害质量，而改善糖型分布的干预措施可能会对细胞生长和生产率产生不利影响。因此，工艺设计需要考虑在保持细胞健康和生产力同时提高抗体质量之间的权衡。在这项工作中，我们提出了一个建模平台，量化糖基化前体喂养-特别是半乳糖和尿苷-对细胞生长，代谢以及抗体生产力和糖型分布的影响。该平台已使用初始训练数据集进行了参数化，相对于糖型分布，其准确度为+/- 5%。然后将其用于设计优化的补料策略，与对照相比，该策略将上清液中半乳糖基化抗体的最终浓度提高超过90%，而不损害活细胞密度或最终抗体滴度的积分。这项工作支持实施质量设计，以实现更高性能的生物工艺。
Exerting control over the glycan moieties of antibody therapeutics is highly desirable from a product safety and batch-to-batch consistency perspective. Strategies to improve antibody productivity may compromise quality, while interventions for improving glycoform distribution can adversely affect cell growth and productivity. Process design therefore needs to consider the trade-off between preserving cellular health and productivity while enhancing antibody quality. In this work, we present a modeling platform that quantifies the impact of glycosylation precursor feeding - specifically that of galactose and uridine - on cellular growth, metabolism as well as antibody productivity and glycoform distribution. The platform has been parameterized using an initial training data set yielding an accuracy of +/- 5% with respect to glycoform distribution. It was then used to design an optimized feeding strategy that enhances the final concentration of galactosylated antibody in the supernatant by over 90% compared with the control without compromising the integral of viable cell density or final antibody titer. This work supports the implementation of Quality by Design towards higher-performing bioprocesses.