B Cell Repertoire Molecular Platform for Antibody Drug Discovery

用于抗体药物发现的 B 细胞库分子平台

• 批准号: 8756836
• 负责人: David Scott Johnson
• 金额: $ 24.91万
• 依托单位: GIGAGEN, INC.
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-08-01 至 2015-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8756836
• 关键词: Affinity; Antibodies; Applications Grants; B cell repertoire; B lymphocyte immortalization; B-Lymphocytes; Bioinformatics; Biological Products; Blood; Cancer Patient; Capital; Cells; Clinical; Computing Methodologies; Contracts; Cost Savings; DNA Library; DNA Sequence; Data; Detection; Development; Diagnostic; Disease; Drug Industry; Elderly; Epidermal Growth Factor Receptor; Evolution; Failure; Fertilization in Vitro; Future; Generations; Genomics; Human; Immune; Immune system; Immunoglobulin Fragments; Institutes; Laboratories; Lead; Licensing; Life; Light; Malignant Neoplasms; Malignant neoplasm of pancreas; Mammalian Cell; Marketing; Methods; Metric; Microfluidics; Molecular; Molecular Analysis; Monoclonal Antibodies; Mus; National Cancer Institute; Phage Display; Pharmaceutical Preparations; Pharmacologic Substance; Phase; Phase I Clinical Trials; Productivity; Research; Services; Small Business Innovation Research Grant; Staging; Surface; Surveys; System; Technology; Testing; Therapeutic; Therapeutic Agents; Therapeutic antibodies; Tube; United States Food and Drug Administration; United States National Institutes of Health; Work; biological research; cell immortalization; clinical efficacy; cost; cytokine; drug discovery; human monoclonal antibodies; immunogenicity; improved; in vivo; innovation; medical specialties; new technology; novel therapeutics; oncology; oncology service; primary outcome; programs; public health relevance; research and development; screening

DESCRIPTION (provided by applicant): Specific Aim of this Innovative Molecular Analysis Technologies (IMAT) SBIR Phase I grant proposal is to show the feasibility of a high-throughput molecular technology for discovery of monoclonal antibody (mAb) drugs for oncology from human B cell repertoires. Drug companies spend up to $5 billion to produce a single FDA-approved monoclonal antibody, or mAb (DiMasi & Grabowski, 2007; Nelson et al., 2010). High mAb development cost is at least partly due to the high failure rate of candidates. A technology that improves mAb selection by just 10% before entering clinical development could save the drug industry ~$400 million per FDA- approved mAb. Immune systems are "test tubes" that constantly select for antibodies with strong potential as drugs. GigaLink" will be a research service for drug discovery programs that leverages these antibody selection test tubes. In mouse systems, our technology could eventually replace B cell immortalization. In human systems, our technology could eventually replace phage display. Antibody fragments identified in our DNA libraries will be easily modified into mAbs, because they are fully human, are already known to express on the surface of B cells, and have already shown positive selection in vivo. In Phase I we will integrate our current molecular and bioinformatic methods with mammalian expression and affinity screening. The project will focus on antibody fragments against epidermal growth factor receptor (EGFR), because many anti-EGFR biologics are available to help us test our system. Though we focus on EGFR, the primary outcome of this project is platform development - ideal for the IMAT program at the National Cancer Institute (NCI). We will accomplish the Specific Aim by performing the following tasks: (i) Optimize mammalian expression and affinity screening using known anti-EGFR antibody fragments; (ii) Implement computational methods for quantitatively integrating genomic and affinity data; and (iii) Screen pancreatic cancer patient B cells for anti-EGFR antibody fragments. To be successful, we must achieve the following metrics: (i) Recover >80% of known anti-EGFR antibody fragments by mammalian expression and affinity screening (power=0.8, ¿=0.05); and (ii) Use germline divergence rates and affinity screening to discover no less than ten anti-EGFR antibody fragments with affinity constant (Kaff)<10-7 and significant sequence evolution rates (power=0.8,¿=0.05). In Phase II, we will focus on laboratory and computational methods for affinity maturation of fully human monoclonal antibodies from GigaLink" antibody fragments. Once Phase II is complete, GigaGen will compete directly with mAb discovery services such as Morphosys and Adimab. Future grant applications will focus on oncology targets for discovery and development of GigaGen-proprietary drugs for pancreatic cancer targets (Dodson et al., 2011), but this will only be possible once the current IMAT project has been completed.

描述（由申请人提供）：本创新分子分析技术 (IMAT) SBIR 第一阶段拨款提案的具体目标是展示高通量分子技术从人类 B 细胞库中发现用于肿瘤学的单克隆抗体 (mAb) 药物的可行性。制药公司花费高达 50 亿美元来生产 FDA 批准的单克隆抗体或 mAb（DiMasi & Grabowski，2007；Nelson 等人，2010）。高单克隆抗体开发成本至少部分是由于候选药物的高失败率。在进入临床开发之前将 mAb 选择仅提高 10% 的技术可为制药行业节省约 4 亿美元 FDA 批准的 mAb。免疫系统是“试管”，不断选择具有强大药物潜力的抗体。 GigaLink”将成为利用这些抗体选择试管的药物发现项目的研究服务。在小鼠系统中，我们的技术最终可以取代 B 细胞永生化。在人体系统中，我们的技术最终可以取代噬菌体展示。在我们的 DNA 文库中识别的抗体片段将很容易修改为 mAb，因为它们是完全人类的，已知在 B 细胞表面表达，并且已经在体内表现出正选择。在第一阶段，我们将整合我们的抗体片段。 当前的分子和生物信息方法与哺乳动物表达和亲和力筛选。该项目将重点关注针对表皮生长因子受体 (EGFR) 的抗体片段，因为许多抗 EGFR 生物制剂可帮助我们测试我们的系统。尽管我们专注于 EGFR，但该项目的主要成果是平台开发 - 非常适合国家癌症研究所 (NCI) 的 IMAT 项目。我们将通过执行以下操作来实现具体目标 任务： (i) 使用已知的抗 EGFR 抗体片段优化哺乳动物表达和亲和力筛选； (ii) 实施定量整合基因组和亲和力数据的计算方法； (iii) 筛选胰腺癌患者 B 细胞中的抗 EGFR 抗体片段。为了取得成功，我们必须实现以下指标： (i) 通过哺乳动物表达和亲和力回收 >80% 的已知抗 EGFR 抗体片段 筛选（功效=0.8，¿=0.05）； (ii)利用种系分化率和亲和力筛选发现不少于10个亲和常数(Kaff)<10-7且具有显着序列进化率(power=0.8,k=0.05)的抗EGFR抗体片段。在第二阶段，我们将重点关注全人单克隆抗体亲和力成熟的实验室和计算方法 GigaLink”抗体片段。一旦第二阶段完成，GigaGen 将直接与 Morphosys 和 Adimab 等 mAb 发现服务公司竞争。未来的拨款申请将集中于肿瘤学目标，以发现和开发用于胰腺癌目标的 GigaGen 专有药物（Dodson 等，2011），但这只有在当前 IMAT 项目完成后才有可能实现。