化学
生物制药
结合
关键质量属性
工作流程
药物发现
抗体-药物偶联物
色谱法
计算生物学
抗体
单克隆抗体
计算机科学
生物化学
数据库
生物技术
数学分析
数学
物理化学
粒径
免疫学
生物
作者
Armelle Martelet,Valérie Garrigue,Zoe Zhang,Bruno Genêt,András Guttman
标识
DOI:10.1016/j.jpba.2021.114094
摘要
Antibody–drug conjugates (ADCs) represent an important class of new biopharmaceutical modalities. ADCs are highly complex and heterogeneous molecules, potentially containing numerous product-related structures, that can contribute to the quality, efficacy and safety of the product. To keep up with product life cycle related changes, wide-range and targeted characterization of product quality attributes (PQA) are of high demand. Multi-attribute methods (MAM) can screen numerous PQAs in a parallel fashion including product properties as well as product and process-related impurities. MAM is usually based on a bottom-up approach relying on the enzymatic digestion of the protein into peptides prior to mass spectrometry (MS). However, this processing workflow can result in considerable information loss, such as the drug distribution profile of an antibody-drug conjugate. Therefore, complementary MAM approaches, based on subunit and intact mass analyses, are necessary approaches offering the advantage of product identity confirmation, quantification of the different conjugated species and monitoring the drug-to-antibody ratio at the same time. In this work we introduce a high throughput MS based attribute tracking method for ADC characterization at the intact and subunit levels by simultaneously monitoring multiple PQAs. The workflow includes sample preparation and MS instrument suitability testing for heterogeneous lysine-linked ADCs, software solutions for routine PQAs tracking, method repeatability and an easy data review fitting perfectly into high throughput analyses. As methionine oxidation is one of the modifications that should be closely monitored at any step of process development, an important application to oxidative stress evaluation using forced degradation demonstrated the applicability of the workflow.
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