Office of Biostatistics and Epidemiology, Center for Biologics Evaluation and Research, US FDA, 10903 New Hampshire Ave, Silver Spring, 20993, Maryland, USA.
Office of Tissues and Advanced Therapy, Center for Biologics Evaluation and Research, US FDA, 10903 New Hampshire Ave, Silver Spring, 20993, Maryland, USA.
AAPS J. 2019 Aug 2;21(5):96. doi: 10.1208/s12248-019-0368-0.
Most immune responses to biotherapeutic proteins involve the development of anti-drug antibodies (ADAs). New drugs must undergo immunogenicity assessments to identify potential risks at early stages in the drug development process. This immune response is T cell-dependent. Ex vivo assays that monitor T cell proliferation often are used to assess immunogenicity risk. Such assays can be expensive and time-consuming to carry out. Furthermore, T cell proliferation requires presentation of the immunogenic epitope by major histocompatibility complex class II (MHCII) proteins on antigen-presenting cells. The MHC proteins are the most diverse in the human genome. Thus, obtaining cells from subjects that reflect the distribution of the different MHCII proteins in the human population can be challenging. The allelic frequencies of MHCII proteins differ among subpopulations, and understanding the potential immunogenicity risks would thus require generation of datasets for specific subpopulations involving complex subject recruitment. We developed TCPro, a computational tool that predicts the temporal dynamics of T cell counts in common ex vivo assays for drug immunogenicity. Using TCPro, we can test virtual pools of subjects based on MHCII frequencies and estimate immunogenicity risks for different populations. It also provides rapid and inexpensive initial screens for new biotherapeutics and can be used to determine the potential immunogenicity risk of new sequences introduced while bioengineering proteins. We validated TCPro using an experimental immunogenicity dataset, making predictions on the population-based immunogenicity risk of 15 protein-based biotherapeutics. Immunogenicity rankings generated using TCPro are consistent with the reported clinical experience with these therapeutics.
大多数针对生物治疗蛋白的免疫反应涉及到抗药物抗体(ADA)的产生。新药必须进行免疫原性评估,以在药物开发过程的早期阶段识别潜在风险。这种免疫反应是 T 细胞依赖性的。体外试验,监测 T 细胞增殖,常用于评估免疫原性风险。这些试验可能既昂贵又耗时。此外,T 细胞增殖需要主要组织相容性复合体 II 类(MHCII)蛋白在抗原呈递细胞上呈递免疫原性表位。MHC 蛋白在人类基因组中是最多样化的。因此,从反映人类群体中不同 MHCII 蛋白分布的受试者中获得细胞可能具有挑战性。MHCII 蛋白的等位基因频率在亚群中存在差异,因此,了解潜在的免疫原性风险需要为涉及复杂受试者招募的特定亚群生成数据集。我们开发了 TCPro,这是一种预测常见药物免疫原性体外试验中 T 细胞计数时间动态的计算工具。使用 TCPro,我们可以根据 MHCII 频率测试虚拟受试者群体,并估计不同人群的免疫原性风险。它还可以为新的生物治疗药物提供快速且经济实惠的初始筛选,并可用于确定在蛋白质工程中引入新序列的潜在免疫原性风险。我们使用实验免疫原性数据集验证了 TCPro,对 15 种基于蛋白质的生物治疗药物的基于人群的免疫原性风险进行了预测。TCPro 生成的免疫原性排名与这些治疗药物的临床报告经验一致。