A native SEC-MS workflow and validation for analyzing drug-to-antibody ratio and drug load distribution in cysteine-linked antibody-drug conjugates

关键质量属性 生物分析 生物制药 色谱法 工作流程 化学 设计质量 药品 计算机科学 药理学 医学 数据库 粒径 物理化学 生物 遗传学
作者
Gang Wu,Chuanfei Yu,Sicheng Yin,Jialiang Du,Yifan Zhang,Zhihao Fu,Lan Wang,Junzhi Wang
出处
期刊:Journal of Chromatography B [Elsevier BV]
卷期号:1241: 124167-124167 被引量:3
标识
DOI:10.1016/j.jchromb.2024.124167
摘要

The development and optimization of Antibody-Drug Conjugates (ADCs) hinge on enhanced analytical and bioanalytical characterization, particularly in assessing critical quality attributes (CQAs). The ADC's potency is largely determined by the average number of drugs attached to the monoclonal antibody (mAb), known as the drug-to-antibody ratio (DAR). Furthermore, the drug load distribution (DLD) influences the therapeutic window of the ADC, defining the range of dosages effective in treating diseases without causing toxic effects. Among CQAs, DAR and DLD are vital; their control is essential for ensuring manufacturing consistency and product quality. Typically, hydrophobic interaction chromatography (HIC) or reversed-phase liquid chromatography (RPLC) with UV detector have been used to quantitate DAR and DLD in quality control (QC) environment. Recently, Native size-exclusion chromatography-mass spectrometry (nSEC-MS) proves the potential as a platformable quantitative method for characterizing DAR and DLD across various cysteine-linked ADCs in research or early preclinical development. In this work, we established and assessed a streamlined nSEC-MS workflow with a benchtop LC–MS platform, to quantitatively monitor DAR and DLD of different chemotype and drug load level cysteine-linked ADCs. Moreover, to deploy this workflow in QC environment, complete method validation was conducted in three independent laboratories, adhering to the International Council for Harmonization of Technical Requirements for Pharmaceuticals for Human Use (ICH) Q2(R1) guidelines. The results met the predefined analytical target profile (ATP) and performance criteria, encompassing specificity/selectivity, accuracy, precision, linearity, range, quantification/detection limit, and robustness. Finally, the method validation design offers a reference for other nSEC-MS methods that are potentially used to determine the DAR and DLD on cysteine-linker ADCs. To the best of our knowledge, this study is the first reported systematic validation of the nSEC-MS method for detecting DAR and DLD. The results indicated that the co-validated nSEC-MS workflow is suitable for DAR and DLD routine analysis in ADC quality control, release, and stability testing.
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