School of Life Science and Biopharmaceutics, Shenyang Pharmaceutical University, Shenyang, China.
Key Laboratory of the Ministry of Health for Research on Quality and Standardization of Biotech Products, National Institutes for Food and Drug Control, China.
J Chromatogr B Analyt Technol Biomed Life Sci. 2024 Jul 1;1241:124167. doi: 10.1016/j.jchromb.2024.124167. Epub 2024 May 29.
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.
抗体药物偶联物（ADC）的开发和优化取决于增强的分析和生物分析特性，特别是在评估关键质量属性（CQA）方面。ADC 的效力在很大程度上取决于连接到单克隆抗体（mAb）的药物的平均数量，称为药物抗体比（DAR）。此外，药物负载分布（DLD）会影响 ADC 的治疗窗口，定义了在治疗疾病而不引起毒性作用的有效剂量范围。在 CQA 中，DAR 和 DLD 至关重要；控制它们对于确保制造一致性和产品质量至关重要。通常，使用疏水相互作用色谱（HIC）或反相液相色谱（RPLC）与紫外检测器来定量控制环境中的 DAR 和 DLD。最近，天然尺寸排阻色谱-质谱联用（nSEC-MS）证明了作为一种潜在的平台定量方法的潜力，可用于研究或早期临床前开发中各种半胱氨酸连接的 ADC 的 DAR 和 DLD 进行特征描述。在这项工作中，我们建立并评估了一种带有台式 LC-MS 平台的简化 nSEC-MS 工作流程，以定量监测不同化学类型和药物负载水平半胱氨酸连接的 ADC 的 DAR 和 DLD。此外，为了将此工作流程部署到 QC 环境中，在三个独立的实验室中进行了完整的方法验证，遵循了人用药物技术要求国际协调理事会（ICH）Q2（R1）指南。结果符合预定义的分析目标概况（ATP）和性能标准，包括特异性/选择性、准确性、精密度、线性、范围、定量/检测限和稳健性。最后，方法验证设计为其他潜在用于确定半胱氨酸连接 ADC 的 DAR 和 DLD 的 nSEC-MS 方法提供了参考。据我们所知，这项研究是首次报道用于检测 DAR 和 DLD 的 nSEC-MS 方法的系统验证。结果表明，协同验证的 nSEC-MS 工作流程适用于 ADC 质量控制、放行和稳定性测试中的 DAR 和 DLD 常规分析。
