Antibody Disulfide Bond Reduction and Recovery during Biopharmaceutical Process Development - A Review

生物制药 二硫键 根本原因 过程(计算) 新产品开发 生化工程 还原(数学) 计算机科学 纳米技术 风险分析(工程) 业务 组合化学 化学 工程类 运营管理 材料科学 生物技术 生物化学 数学 操作系统 营销 生物 几何学
作者
Tingwei Ren,Zhijun Tan,Vivekh Ehamparanathan,Angela Lewandowski,Sanchayita Ghose,Zheng Jian Li
出处
期刊:Authorea - Authorea
标识
DOI:10.22541/au.160838215.55110778/v1
摘要

Disulfide bond reduction has been a challenging issue in antibody manufacturing, as it leads to reduced product purity, failed product specifications and more importantly, impacting drug safety and efficacy. Scientists across industry have been examining the root causes and developing mitigation strategies to address the challenge. In recent years, with the development of high-titer mammalian cell culture processes to meet the rapidly growing demand for antibody biopharmaceuticals, disulfide bond reduction has been observed more frequently. Thus, it is necessary to continue evolving the disulfide reduction mitigation strategy and development of novel approaches to achieve high product quality. Additionally, in recent years as more complex molecules emerge such as bispecific and trispecific antibodies, the molecular heterogeneity due to incomplete formation of the interchain disulfide bonds becomes a more imperative issue. Given the disulfide reduction challenges that our industry are facing, in this review, we provide a comprehensive contemporary scientific insight into the root cause analysis of disulfide reduction during process development of antibody therapeutics, mitigation strategies and recovery based on our expertise in commercial and clinical manufacturing of biologics. First, this paper intended to highlight different aspects of the root cause for disulfide reduction. Secondly, to provide a broader understanding of the disulfide bond reduction in downstream process, this paper discussed disulfide bond reduction impact to product stability and process performance, analytical methods for detection and characterization, process control strategies and their manufacturing implementation. In addition, brief perspectives on development of future mitigation strategies will also be reviewed, including platform alignment, mitigation strategy application for bi- and tri-specific antibodies and using machine learning to identify molecule susceptibility of disulfide bond reduction. The data in this review are originated from both the published papers and our internal development work.

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