Clinical Immunology, Amgen Inc., One Amgen Center Drive, 30E-3-C, Thousand Oaks, California, 91320, USA.
AAPS J. 2013 Oct;15(4):1160-7. doi: 10.1208/s12248-013-9523-1. Epub 2013 Aug 30.
Immunogenicity assessment of fully human monoclonal antibody-based biotherapeutics requires sensitive and specific ligand binding assays. One of the components of specificity is the depletion of signal by a relevant biotherapeutic that is commonly based on an arbitrary depletion criterion of inhibition of the original response or reduction of the signal below the screening assay cut point (ACP). Hence, there is a need to develop a statistically derived physiologically relevant specificity criterion. We illustrate an optimization approach to determine the concentration of biotherapeutic required for the specificity evaluation. Naïve donor sample sets with and without circulating drug and antitherapeutic/drug antibody (ADA) were prepared. Next, a depletion cut point (DCP) using naïve and ADA-containing donor sets with the optimized biotherapeutic concentration was evaluated. A statistically derived design of experiment was used to establish a validated DCP. A reliable DCP requires naïve (no ADA) donors treated only with an optimized concentration of biotherapeutic. The additional DCPs generated using two distinct concentrations of ADA-spiked sample sets led to a physiologically irrelevant criterion that was not necessarily representative of real-time samples. This increased the risk of false positives or negatives. In this study, well-defined bioanalytical and statistical methods were employed to validate a DCP to confirm the presence of biotherapeutic specific ADA in human serum samples. A physiologically relevant and effective strategy to confirm specificity in immune reactive samples, especially those that are close to the ACP, is proposed through this study.
基于完全人源单克隆抗体的生物治疗药物的免疫原性评估需要敏感和特异性的配体结合分析。特异性的一个组成部分是相关生物治疗药物的信号耗竭,这通常基于抑制原始反应或信号降低到筛选分析截止点(ACP)以下的任意耗竭标准。因此,需要开发一种基于统计学的生理相关特异性标准。我们举例说明了一种优化方法,用于确定用于特异性评估的生物治疗药物所需的浓度。制备了含有和不含有循环药物和抗治疗药物/药物抗体(ADA)的天然供体样本集。接下来,使用优化的生物治疗药物浓度的天然和 ADA 含量供体集评估了耗竭截止点(DCP)。使用基于统计学的实验设计来建立验证 DCP。可靠的 DCP 需要天然(无 ADA)供体,仅用优化浓度的生物治疗药物处理。使用两个不同浓度的 ADA 加标样本集生成的其他 DCP 导致了不切实际的生理标准,不一定代表实时样本。这增加了假阳性或假阴性的风险。在这项研究中,采用了明确的生物分析和统计方法来验证 DCP,以确认人血清样本中存在生物治疗药物特异性 ADA。通过这项研究提出了一种在免疫反应性样本中确认特异性的生理相关且有效的策略,特别是那些接近 ACP 的样本。