Yang Yun, Rao Romesh, Valliere-Douglass John, Tremintin Guillaume
Bruker Scientific, LLC., 101 Daggett Drive, San Jose, CA, USA.
Analytical Sciences, Seagen Inc., 21823 30th Drive S.E., Bothell, WA, USA.
J Chromatogr B Analyt Technol Biomed Life Sci. 2024 Mar 1;1235:124007. doi: 10.1016/j.jchromb.2024.124007. Epub 2024 Jan 8.
Antibody drug conjugates (ADCs) are an increasingly important therapeutic class of molecules for the treatment of cancer. Average drug-to-antibody ratio (DAR) and drug-load distribution are critical quality attributes of ADCs with the potential to impact efficacy and toxicity of the molecule and need to be analytically characterized and understood. Several platform methods including hydrophobic interaction chromatography (HIC) and native size-exclusion chromatography-mass spectrometry (nSEC-MS) have been developed for that purpose; however, each presents some limitations. In this work, we assessed a new sample preparation and buffer exchange platform coupled with high-resolution mass spectrometry for characterizing the drug-load and distribution of several cysteine-linked ADCs conjugated with a variety of chemotypes. Several criteria were evaluated during the optimization of the buffer exchange-mass spectrometry system performance and the data generated with the system were compared with results from nSEC-MS and HIC. The results indicated that the platform enables automated and high throughput quantitative DAR characterization for antibody-drug conjugates with high reproducibility and offers several key advantages over existing approaches that are used for chemotype-agnostic ADC characterization.
抗体药物偶联物（ADCs）是治疗癌症的一类日益重要的治疗性分子。平均药物与抗体比率（DAR）和药物负载分布是ADCs的关键质量属性，可能会影响分子的疗效和毒性，需要进行分析表征和理解。为此已经开发了几种平台方法，包括疏水相互作用色谱法（HIC）和天然尺寸排阻色谱-质谱法（nSEC-MS）；然而，每种方法都存在一些局限性。在这项工作中，我们评估了一种新的样品制备和缓冲液交换平台，该平台与高分辨率质谱联用，用于表征与多种化学类型偶联的几种半胱氨酸连接的ADCs的药物负载和分布。在优化缓冲液交换-质谱系统性能期间评估了几个标准，并将该系统生成的数据与nSEC-MS和HIC的结果进行了比较。结果表明，该平台能够以高重现性对抗体药物偶联物进行自动化和高通量定量DAR表征，并且相对于用于与化学类型无关的ADCs表征的现有方法具有几个关键优势。
