Sun Zhiyuan, Ji Qinqin, Evans Adam R, Lewis Michael J, Mo Jingjie, Hu Ping
Large Molecules Analytical Development, BioTherapeutics Development, Janssen Research & Development, LLC, Malvern, PA, 19355, USA.
Biologicals. 2019 Sep;61:44-51. doi: 10.1016/j.biologicals.2019.07.003. Epub 2019 Aug 7.
Monitoring cell culture metabolites, including media components and cellular byproducts, during bio manufacturing is critical for gaining insights into cell growth, productivity and product quality. Historically, cell culture metabolite analysis was a complicated process requiring several orthogonal methods to cover the large number of metabolites with diverse properties over wide concentration ranges. These off-line analyses are time consuming and not suitable for real time bioreactor monitoring. In this study, we present a high-throughput LC-MS method with a 17-min cycle time that is capable of simultaneously monitoring 93 cell culture metabolites, including amino acids, nucleic acids, vitamins, sugars and others. This method has high precision and accuracy and has been successfully applied to the daily profiling of bioreactors and raw material qualification. Information obtained in these studies has been used to identify limiting amino acids during production, which guided adjustments to the feed strategy that prevented the potential misincorporation of amino acids. This type of metabolite profiling can be further utilized to build predictive process models for adaptive feedback control and pave the road for continuous manufacturing and real-time release testing.
在生物制造过程中监测细胞培养代谢物，包括培养基成分和细胞副产物，对于深入了解细胞生长、生产力和产品质量至关重要。从历史上看，细胞培养代谢物分析是一个复杂的过程，需要几种正交方法来覆盖大量具有不同性质、浓度范围广泛的代谢物。这些离线分析耗时且不适用于实时生物反应器监测。在本研究中，我们提出了一种高通量液相色谱 - 质谱方法，其循环时间为17分钟，能够同时监测93种细胞培养代谢物，包括氨基酸、核酸、维生素、糖类等。该方法具有高精度和准确性，并已成功应用于生物反应器的日常分析和原材料鉴定。这些研究中获得的信息已用于识别生产过程中的限制性氨基酸，从而指导对进料策略的调整，防止氨基酸的潜在错误掺入。这种代谢物分析类型可进一步用于构建预测过程模型，以实现自适应反馈控制，并为连续制造和实时放行检测铺平道路。
