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在生物制药开发过程中糖基化预测和控制的先进策略:迈向工业 4.0 的途径。

Advanced strategies in glycosylation prediction and control during biopharmaceutical development: Avenues toward industry 4.0.

机构信息

Department of Chemical Engineering, Institute of Chemical Technology, Mumbai, India.

Symphonytech Biologics Private Limited, Pune, India.

出版信息

Biotechnol Prog. 2022 Sep;38(5):e3283. doi: 10.1002/btpr.3283. Epub 2022 Jul 12.

Abstract

Glycosylation has been shown to define the safety and efficacy of biopharmaceuticals, thus classified as a critical quality attribute. However, controlling glycan heterogeneity has always been a major challenge owing to the multivariate factors that govern the glycosylation process. Conventional approaches for controlling glycosylation such as gene editing and metabolic control have succeeded in obtaining desired glycan profiles in accordance with the Quality by Design paradigm. Nonetheless, the development of smart algorithms and omics-enabled complete cell characterization has made it possible to predict glycan profiles beforehand, and manipulate process variables accordingly. This review thus discusses the various approaches available for control and prediction of glycosylation in biopharmaceuticals. Further, the futuristic goal of integrating such technologies is discussed in order to attain an automated and digitized continuous bioprocess for control of glycosylation. Given, control of a process as complex as glycosylation requires intense monitoring intervention, we examine the current technologies that enable automation. Finally, we discuss the challenges and the technological gap that currently limits incorporation of an automated process in routine bio-manufacturing, with a glimpse into the economic bearing.

摘要

糖基化已被证明可定义生物制药的安全性和疗效,因此被归类为关键质量属性。然而,由于控制糖基化过程的多种因素,控制聚糖异质性一直是一个主要挑战。传统的控制糖基化的方法,如基因编辑和代谢控制,已经成功地按照质量源于设计的原则获得了所需的聚糖谱。然而,智能算法和组学驱动的完整细胞表征的发展使得可以预先预测聚糖谱,并相应地操纵工艺变量。因此,本综述讨论了控制和预测生物制药中糖基化的各种方法。此外,还讨论了将这些技术集成的未来目标,以便实现自动化和数字化的连续生物过程来控制糖基化。鉴于像糖基化这样复杂的过程需要进行密集的监测干预,我们研究了能够实现自动化的当前技术。最后,我们讨论了当前限制自动化过程纳入常规生物制造的挑战和技术差距,并展望了经济影响。

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