多克隆抗体
抗体
单克隆抗体
免疫原性
分析灵敏度
化学
表面等离子共振
分子生物学
免疫学
生物
医学
病理
材料科学
纳米颗粒
纳米技术
替代医学
作者
Christina Aniol-Nielsen,Henrik Toft–Hansen,Madeleine Dahlbäck,Claus Henrik Nielsen,Helene Solberg
标识
DOI:10.1016/j.jim.2021.113002
摘要
Highly sensitive assays for anti-drug antibodies (ADAs) are both a regulatory requirement and requisite for proper evaluation of the effects of immunogenicity on clinical efficacy and safety. Determination of ADA assay sensitivity depends on positive control antibodies to represent naturally occurring or treatment-induced ADA responses. An accurate determination of the proportion of drug-specific antibodies in these polyclonal positive control batches is critical for correct evaluation of assay sensitivity. Target purification of positive control antibodies is commonly applied but infers the risk to lose a proportion of the antibodies. This may lead to an incorrect estimate of the ADA assay sensitivity, especially if high-affinity antibodies are lost that may be representative of natural ADAs with clinical implication. The Surface Plasmon Resonance platform on the Biacore™ systems offers methods for real-time analysis of biomolecular interactions without introducing any modifications to the analysed material. Calibration-free concentration analysis (CFCA) is such an application for determination of the proportion of drug-specific antibodies, which allows direct determination of active antibody concentrations, as defined by the ligand, in a flow-based system. Here, we present a novel CFCA method for ADA quantification developed and validated using polyclonal positive control antibodies against endogenous human insulin, insulin degludec (Tresiba®) and turoctocog alfa (NovoEight®). We find that CFCA precisely and accurately measures concentrations of drug-specific IgG antibodies with a precision of ±10% and 90%-112% recovery of expected values of monoclonal positive control antibodies. Additionally, we have achieved a more accurate measure of the sensitivity of a cell-based bioassay for in vitro neutralising ADAs using the specific concentration determined with CFCA. Moreover, we effectively quantified serum anti-insulin antibodies in high-titre clinical samples from individuals with diabetes mellitus. This application extends the relevance of the CFCA technology to analysis of immunogenicity for accurate quantification of ADAs in both the polyclonal positive control and in clinical samples.
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