A web-based platform to support team-based genome diagnostics

一个基于网络的平台，支持基于团队的基因组诊断

• 批准号: 10482593
• 负责人: Alistair Ward
• 金额: $ 29.89万
• 依托单位: FRAMESHIFT LABS, INC.
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-07-14 至 2023-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10482593
• 关键词: Address; Adopted; Architecture; Back; Clinic; Collaborations; Communication; Communication Methods; Communities; Complex; Computer software; Computing Methodologies; Custom; Data; Data Files; Data Store; Development; Diagnosis; Diagnostic; Disease; Education; Effectiveness; Electronic Mail; Ensure; Evaluation; Family; Gene Order; Genes; Genetic; Genetic Risk; Genome; Genomic medicine; Genomics; Goals; Health Insurance Portability and Accountability Act; Hybrids; Industry Standard; Knowledge; Location; Mediating; Medical; Metadata; Methodology; Methods; Mosaicism; National Human Genome Research Institute; Neonatal Intensive Care Units; Online Systems; Patients; Personal Computers; Persons; Pharmacology; Phenotype; Physicians; Procedures; Process; Rare Diseases; Role; Secure; Security; Software Tools; Speed; Testing; Time; Training; Universities; Utah; Variant; Visual; Visualization; Work; application programming interface; base; bioinformatics pipeline; clinical care; clinical diagnostics; clinical research site; cloud storage; consumer product; critically ill newborn; data management; data sharing; data visualization; design; distributed data; exome; file format; genetic analysis; genetic counselor; genetic variant; genome sequencing; improved; individual patient; interactive tool; interest; literacy; meetings; member; personalized care; precision medicine; programs; scale up; skills; tool; web-based tool; whole genome

Summary/Abstract Genomic sequencing is rapidly becoming a standard tool in diagnosing complex diagnostic cases, especially in critically ill newborns, and patients suffering from rare diseases. Current programs focused on addressing these cases utilise a team-based approach to identify, interpret and evaluate a patient’s genetic variants. These diverse teams include bioinformaticians, medical geneticists, genetic counselors, and physicians among others, and encompass a wide range of expertise, skills, and literacy with computational methods. The complexity of evaluating a genetic variant’s role in causing a patient’s specific set of phenotypes requires the expertise and unique knowledge of all members of the team, and efficient methods of communication to support rapid, asynchronous analysis of all potentially interesting observations. Currently, team members perform analyses based on their own expertise, and rely on email communication, and regular in-person meetings to integrate the knowledge of the team. This process is very time-intensive, and inefficient, especially when previously undiagnosed cases are reviewed, and critical case information is hidden in myriad email threads, presentations etc. This proposal brings together a highly popular tool for rapid visual analysis of genetic variants with a commercial data management solution to provide a tool set to support team-based genomic medicine. Our gene.iobio tool performs real-time analysis of a patient’s genome in an easy-to-use web-based application, ensuring all team members can efficiently contribute their expertise in the diagnostic process. This tool will be expanded with critica features, and brought up to a commercial standard of deployment to ensure it can deliver on its potential in a reliable and repeatable manner. Our Mosaic tool provides HIPAA-compliant access to distributed data, role-based authentication, as well as comprehensive visualization, and communication features. This tool will also be expanded with functionality to support integration with gene.iobio, as well as collaboration features designed to support this community. By improving the features of both of these tools; providing analysis versioning; developing a deep API based integration between them; and ensuring the combined package is fast, reliable and robust, we will deliver a software product that is currently absent in the market; one that will improve collaboration on cases, save significant amounts of time for all team members, and ultimately use these efficiency gains to ensure that genomic medicine can be scaled up to serve more patients moving forwards. We will deploy this package in our own rapid NICU sequencing program, and UDN clinical site to evaluate and refine the product.

总结/摘要 基因组测序正在迅速成为诊断复杂诊断病例的标准工具，特别是在 危重新生儿和罕见病患者。目前的方案侧重于解决 这些个案均采用团队合作的方法，以鉴定，解释及评估病人的基因变异。 这些不同的团队包括生物信息学家，医学遗传学家，遗传咨询师和医生， 其他人，并涵盖了广泛的专业知识，技能和识字与计算方法。的 评估遗传变异在导致患者特定表型集合中的作用的复杂性需要 团队所有成员的专业知识和独特知识，以及有效的沟通方法， 支持对所有可能感兴趣的观测进行快速、异步分析。目前，团队成员 根据自己的专业知识进行分析，并依靠电子邮件通信和定期面对面进行分析 会议以整合团队的知识。这个过程非常耗时，而且效率低下，特别是 当审查以前未诊断的病例时，关键病例信息隐藏在无数的电子邮件中， 这个建议汇集了一个非常流行的工具，用于快速可视化分析， 基因变异与商业数据管理解决方案，以提供一套工具，支持基于团队的 基因组医学我们的gene.iobio工具以易于使用的方式对患者的基因组进行实时分析。 基于Web的应用程序，确保所有团队成员都可以有效地贡献他们的专业知识， 过程该工具将扩展Critica功能，并达到商业标准， 部署，以确保它能够以可靠和可重复的方式发挥其潜力。我们的马赛克工具 提供对分布式数据的符合HIPAA的访问、基于角色的身份验证以及全面的 可视化和通信功能。该工具还将扩展功能，以支持 与gene.iobio的集成，以及旨在支持该社区的协作功能。通过改善 这两种工具的功能;提供分析版本控制;开发基于深度API的集成 他们之间;并确保组合包是快速，可靠和强大的，我们将提供一个软件 目前市场上没有的产品;一个将改善案例协作，节省大量 所有团队成员的时间，并最终使用这些效率收益，以确保基因组 医学可以扩大规模，为更多的患者提供服务。我们将在我们自己的 快速NICU测序程序和UDN临床站点来评估和改进产品。