Native size-exclusion chromatography-mass spectrometry (nSEC-MS) is an analytical methodology that is appropriate for accurately quantitating the drug-to-antibody ratio (DAR) on a wide variety of interchain cysteine-linked antibody-drug conjugates (ADCs), irrespective of chemotype. In the current preclinical environment, novel ADCs conjugated with unique drug-linkers need to progress toward the clinic as quickly as possible. Platform analytical approaches can reduce time-to-clinic because key process development and optimization activities can be decoupled from the development of bespoke, molecule-specific analytical methods. In this work, we assessed the potential of nSEC-MS as a platformable, quantitative DAR method. The nSEC-MS method was evaluated according to performance characteristics and parameters described in the ICH guideline Validation of Analytical Procedures: Text and Methodology Q2(R1). In order to comprehensively assess the accuracy and bias of nSEC-MS DAR quantitation, ADCs were generated using three different drug-linker chemotypes with DARs ranging from 2 to 8. These molecules were tested by hydrophobic interaction chromatography (HIC) and nSEC-MS, and DARs obtained from both methods were compared to assess the degree to which nSEC-MS quantitation aligned with the HIC release assay. Our results indicated that there is no bias introduced by nSEC-MS quantitation of DAR and that SEC-MS data can be bridged to HIC data without the need for a correction factor or offset. nSEC-MS was also found to be suitable for unbiased DAR quantitation in the other ADC chemotypes that were evaluated. Based on the totality of our work, we conclude that, used as intended, nSEC-MS is well suited for quantitating DAR on a variety of interchain cysteine-linked ADCs in an accurate, unbiased manner.

中文翻译：

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天然体积排阻色谱-质谱：适用于跨化学型和载药量范围的抗体-药物偶联物药物与抗体之比定量分析。

天然体积排阻色谱-质谱（nSEC-MS）是一种分析方法，适用于准确定量各种链间半胱氨酸连接的抗体-药物偶联物（ADC）上的药物与抗体的比率（DAR），不论化学类型如何。在当前的临床前环境中，与独特的药物连接物结合的新型ADC需要尽快进入临床。平台分析方法可以缩短开发时间，因为关键过程的开发和优化活动可以与定制的，分子特定的分析方法的开发脱钩。在这项工作中，我们评估了nSEC-MS作为一种可平台化的定量DAR方法的潜力。根据ICH准则分析程序验证：文本和方法Q2（R1）中描述的性能特征和参数，对nSEC-MS方法进行了评估。为了全面评估nSEC-MS DAR定量的准确性和偏倚，使用三种不同的药物连接物化学型生成了ADC，其DAR的范围为2至8。这些分子通过疏水相互作用色谱（HIC）和nSEC-MS进行了测试，比较从两种方法获得的DAR和DAR，以评估nSEC-MS定量与HIC释放测定相符的程度。我们的结果表明，DAR的nSEC-MS定量没有引入偏差，并且可以将SEC-MS数据桥接到HIC数据，而无需校正因子或偏移量。还发现，nSEC-MS也适用于所评估的其他ADC化学型中的无偏DAR定量。基于我们的全部工作，我们得出结论，按预期使用，nSEC-MS非常适合以准确，无偏的方式对各种链间半胱氨酸连接的ADC上的DAR进行定量。