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Traces matter: Targeted optimization of monoclonal antibody N-glycosylation based on/by implementing automated high-throughput trace element screening.
Biotechnology Progress ( IF 2.5 ) Pub Date : 2020-06-25 , DOI: 10.1002/btpr.3042
Sven Markert 1 , Stephanie Torkler 2 , Katharina Hohmann 2 , Oliver Popp 2
Affiliation  

The use of high‐throughput systems in cell culture process optimization offers various opportunities in biopharmaceutical process development. Here we describe the potential for acceleration and enhancement of product quality optimization and de novo bioprocess design regarding monoclonal antibody N‐glycosylation by using an iterative statistical Design of Experiments (DoE) strategy based on our automated microtiter plate‐based system for suspension cell culture. In our example, the combination of an initial screening of trace metal building blocks with a comprehensive DoE‐based screening of 13 different trace elemental ions at three concentration levels in one run revealed most effective levers for N‐glycan processing and biomass formation. Obtained results served to evaluate optimal concentration ranges and the right supplementation timing of relevant trace elements at shake flask and 2 L bioreactor scale. This setup identified manganese, copper, zinc, and iron as major factors. Manganese and copper acted as inverse key players in N‐glycosylation, showing a positive effect of manganese and a negative effect of copper on glycan maturation in a zinc‐dependent manner. Zinc and iron similarly improved cell growth and biomass formation. These findings allowed determining optimal concentration ranges for all four trace elements to establish control on desired product quality attributes regarding premature afucosylated and mature galactosylated glycan species. Our results demonstrates the power of combining robotics with DoE screening to enhance product quality optimization and to improve process understanding, thus, enabling targeted product quality control.

中文翻译:

痕量物质:基于/通过实施自动化高通量痕量元素筛选,有针对性地优化单克隆抗体 N-糖基化。

在细胞培养工艺优化中使用高通量系统为生物制药工艺开发提供了各种机会。在这里,我们描述了通过使用基于我们的基于自动化微量滴定板的悬浮细胞培养系统的迭代统计实验设计 (DoE) 策略,加速和增强关于单克隆抗体 N-糖基化的产品质量优化和从头生物工艺设计的潜力。在我们的示例中,将微量金属构建块的初始筛选与基于 DoE 的全面筛选在三个浓度水平下的 13 种不同微量元素离子的一次运行相结合,揭示了 N-聚糖加工和生物质形成的最有效杠杆。获得的结果用于评估摇瓶和 2 L 生物反应器规模的相关微量元素的最佳浓度范围和正确的补充时间。该设置将锰、铜、锌和铁确定为主要因素。锰和铜在 N-糖基化中起反向关键作用,显示锰的积极作用和铜的消极影响以锌依赖性方式对聚糖成熟。锌和铁同样改善细胞生长和生物量形成。这些发现允许确定所有四种微量元素的最佳浓度范围,以建立对有关过早无岩藻糖基化和成熟半乳糖基化聚糖种类的所需产品质量属性的控制。
更新日期:2020-06-25
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