结合
抗体-药物偶联物
抗体
子类
连接器
共轭体系
化学
半胱氨酸
药品
免疫球蛋白G
单克隆抗体
药理学
体内
生物物理学
免疫学
生物化学
医学
生物
数学
计算机科学
聚合物
酶
有机化学
生物技术
数学分析
操作系统
作者
Amita Datta‐Mannan,Hiuwan Choi,David J. Stokell,Jason X. Tang,Anthony Murphy,A.D. Wrobleski,Yu Feng
出处
期刊:Aaps Journal
[Springer Nature]
日期:2018-09-25
卷期号:20 (6)
被引量:15
标识
DOI:10.1208/s12248-018-0263-0
摘要
Among the numerous antibody-drug conjugate (ADC) clinical candidates, one of the most prevalent types utilizes the interchain cysteines in antibodies to conjugate auristatin via a maleimide-containing linker. In this class of ADCs, there are a paucity of systematic studies characterizing how IgG subclass influences the biophysical properties and in vivo pharmacokinetics of the ADC molecules. In the current investigation, we studied cysteine-conjugated ADCs using a model system consisting of human IgG1, IgG2, and IgG4 antibodies with the same variable region. Our findings identified some unforeseen differences among the three ADCs. Drug conjugation profiling by LC-MS revealed that 50% of inter heavy-light chain disulfide bonds are disrupted to conjugate drugs in IgG1 antibody while only 10% in IgG2 antibody and 20% in IgG4 antibody. The solution behavior of the ADCs was interrogated in concentrating experiments and diffusion interaction parameter measurements. We found that drug conjugation affected the solution property of the three antibodies differently, with the IgG2-based ADC having the most increased propensity to aggregate. Rat PK studies using a sensitive LC-MS-based bioanalytical method showed that the IgG1-based ADC has poor peripheral linker-payload stability while the IgG2- and IgG4-based ADCs are stable. The conjugate stability of the IgG2-based ADC was further confirmed in a cynomolgus monkey PK study. Overall, the IgG2-based ADC exhibited the best PK/conjugate stability but also the most deterioration in stability among the three ADCs. Our findings provide important information and present multifactorial considerations for the selection of IgG subclass during ADC drug discovery when employing stochastic cysteine conjugation.
科研通智能强力驱动
Strongly Powered by AbleSci AI