Advancing next-generation sequencing for optimization of rAAV production

推进下一代测序以优化 rAAV 生产

• 批准号: 10820589
• 负责人: Susanna L Lamers
• 金额: $ 29.59万
• 依托单位: BIOINFOEXPERTS
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-25 至 2024-09-24
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10820589
• 关键词: Advancing; next; generation; sequencing; optimization

1 BioInfoExperts develops pathogen-associated next-generation sequencing (NGS) analytics and software for a 2 growing number of industries that require genome characterization. In the proposed SBIR Phase I project, we 3 will develop NGS analytics for the recombinant adeno-associated viruses (rAAVs) manufacturing industry; in 4 Phase II, we will incorporate the NGS analytics into a a software-as-a-service (SaaS) where customers (rAAV 5 manufacturers) can access results from customized analytical pipelines designed explicitly for their processes. 6 There are >200 rAAV products in clinical trials and three FDA-approved rAAV-mediated gene therapies already 7 in the market. As the industry expands, the FDA is demanding more rigorous rAAV manufacturing quality control 8 (QC) methods to ensure patient safety. In fact, both the FDA and the Dark Horse Consulting group, an advisory 9 committee for the rAAV industry, have recommended NGS for rAAV QC; however, the methods for NGS 10 evaluation of rAAV data have not yet matured to the point where they are accurate or high throughput enough 11 for widespread adoption. NGS from rAAV is notoriously difficult to process, due in part to the production 12 processes and genomic structure of rAAV, combined with limitations of the sequencing platforms such as high 13 error rate, bias towards short reads, and potential for generating chimeric reads. With decades of pathogen- 14 related bioinformatics experience and a successful software-as-as-service business model, BIE plans to 15 aggressively enter this competitive market, and systematically address the issues associated with rAAV NGS 16 data. We will collaborate with Lacerta Therapeutics, a company with long experience with rAAV capsid 17 technology and scalable manufacturing platforms. In Phase I, we will assess the reliability, consistency, and 18 accuracy of NGS for quantifying production-induced mutations in rAAV vector DNA. We will generate sequence 19 data from encapsidated DNA of a self-complementary (sc)AAV vector produced in two different systems (human 20 and insect cell line). In Specific Aim 1, we will use single genome amplification (SGA) followed by Sanger 21 sequencing to generate highly accurate near-full length genomes (NFLG) of the vector DNA, which will enable 22 precise quantification of the actual production-induced mutation rate. In Specific Aim 2, we will generate data on 23 three NGS platforms: Oxford Nanopore, Pacific Bioscience Single Molecule Real Time, and Illumina. We will use 24 several different approaches for error-correction, including combining data from two or more sequencing 25 platforms, and compare results to the known mutations as identified through SGA. Our goal is to develop a 26 bioinformatics pipeline that leverages the power and efficiency of NGS while attaining the level of accuracy of 27 SGA for identifying true production induced mutations. In Phase II, we will continue to address other AAV NGS 28 quality control issues and build our SaaS in the cloud, where we will be able to quickly scale and innovate as 29 needed.

1 BioInfoExperts 开发病原体相关的下一代测序 (NGS) 分析和软件，用于 2 越来越多的行业需要基因组表征。在拟议的 SBIR 第一阶段项目中，我们 3 将为重组腺相关病毒 (rAAV) 制造行业开发 NGS 分析；在 4 第二阶段，我们将把 NGS 分析整合到软件即服务 (SaaS) 中，客户 (rAAV 5 个制造商）可以访问专门为其流程设计的定制分析管道的结果。 6 已有超过 200 种 rAAV 产品处于临床试验阶段，并且 FDA 已批准三种 rAAV 介导的基因疗法 市场上有7个。随着行业的扩张，FDA 要求更严格的 rAAV 生产质量控制 8（QC）方法确保患者安全。事实上，FDA 和黑马咨询集团都提供咨询服务 rAAV 行业的 9 个委员会推荐 NGS 用于 rAAV QC；然而，NGS 方法 10 rAAV 数据的评估尚未成熟到准确或足够高通量的程度 11 供广泛采用。众所周知，rAAV 的 NGS 很难处理，部分原因在于生产过程 rAAV的12个过程和基因组结构，结合测序平台的局限性，例如高 13 错误率、短读取的偏差以及生成嵌合读取的可能性。数十年的病原体- 14 项相关生物信息学经验和成功的软件即服务商业模式，BIE 计划 15 积极进入这个竞争激烈的市场，并系统地解决与 rAAV NGS 相关的问题 16个数据。我们将与 Lacerta Therapeutics 合作，该公司在 rAAV 衣壳方面拥有长期经验 17 种技术和可扩展的制造平台。在第一阶段，我们将评估可靠性、一致性和 18 NGS 用于量化 rAAV 载体 DNA 中生产诱导的突变的准确性。我们将生成序列 19 数据来自两个不同系统（人类）中产生的自互补 (sc)AAV 载体的衣壳 DNA 20和昆虫细胞系）。在具体目标 1 中，我们将使用单基因组扩增 (SGA)，然后使用 Sanger 21 测序以生成载体 DNA 的高度准确的近全长基因组 (NFLG)，这将使 22 精确量化实际生产诱发的突变率。在具体目标 2 中，我们将生成以下数据 23 三个 NGS 平台：Oxford Nanopore、Pacific Bioscience Single Molecule Real Time 和 Illumina。我们将使用 24 几种不同的纠错方法，包括组合来自两个或多个测序的数据 25 个平台，并将结果与​​通过 SGA 识别的已知突变进行比较。我们的目标是开发一个 26 个生物信息学管道，利用 NGS 的强大功能和效率，同时达到 27 SGA 用于识别真正的生产诱导突变。在第二阶段，我们将继续解决其他 AAV NGS 问题 28 个质量控制问题并在云中构建我们的 SaaS，我们将能够在云中快速扩展和创新 需要 29 个。