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基于IgG1的单克隆抗体疗法的聚集动力学

Aggregation Kinetics for IgG1-Based Monoclonal Antibody Therapeutics.

作者信息

Singla A, Bansal R, Joshi Varsha, Rathore Anurag S

机构信息

Department of Chemical Engineering, Indian Institute of Technology, Hauz Khas, New Delhi, 110016, India.

出版信息

AAPS J. 2016 May;18(3):689-702. doi: 10.1208/s12248-016-9887-0. Epub 2016 Feb 22.

Abstract

Monoclonal antibodies (mAbs) as a class of therapeutic molecules are finding an increasing demand in the biotechnology industry for the treatment of diseases like cancer and multiple sclerosis. A key challenge associated to successful commercialization of mAbs is that from the various physical and chemical instabilities that are inherent to these molecules. Out of all probable instabilities, aggregation of mAbs has been a major problem that has been associated with a change in the protein structure and is a hurdle in various upstream and downstream processes. It can stimulate immune response causing protein misfolding having deleterious and harmful effects inside a cell. Also, the extra cost incurred to remove aggregated mAbs from the rest of the batch is huge. Size exclusion chromatography (SEC) is a major technique for characterizing aggregation in mAbs where change in the aggregates' size over time is estimated. The current project is an attempt to understand the rate and mechanism of formation of higher order oligomers when subjected to different environmental conditions such as buffer type, temperature, pH, and salt concentration. The results will be useful in avoiding the product exposure to conditions that can induce aggregation during upstream, downstream, and storage process. Extended Lumry-Eyring model (ELE), Lumry-Eyring Native Polymerization model (LENP), and Finke-Watzky model (F-W) have been employed in this work to fit the aggregation experimental data and results are compared to find the best fit model for mAb aggregation to connect the theoretical dots with the reality.

摘要

单克隆抗体(mAb)作为一类治疗性分子,在生物技术产业中对癌症和多发性硬化症等疾病的治疗需求日益增加。与单克隆抗体成功商业化相关的一个关键挑战在于这些分子固有的各种物理和化学不稳定性。在所有可能的不稳定性中,单克隆抗体的聚集一直是一个主要问题,它与蛋白质结构的变化有关,并且是各种上游和下游过程中的一个障碍。它会刺激免疫反应,导致蛋白质错误折叠,在细胞内产生有害影响。此外,从批次的其余部分中去除聚集的单克隆抗体所产生的额外成本巨大。尺寸排阻色谱法(SEC)是表征单克隆抗体聚集的主要技术,通过该技术可以估计聚集体大小随时间的变化。当前项目旨在了解在不同环境条件下,如缓冲液类型、温度、pH值和盐浓度,高阶寡聚体的形成速率和机制。这些结果将有助于避免产品在上下游及储存过程中暴露于可能诱导聚集的条件下。本研究采用扩展的Lumry-Eyring模型(ELE)、Lumry-Eyring天然聚合模型(LENP)和Finke-Watzky模型(F-W)来拟合聚集实验数据,并比较结果以找到最适合单克隆抗体聚集的模型,从而将理论与实际联系起来。

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