Automated and Guided Workflows for Clinical Testing Using NGS Assays

使用 NGS 检测进行临床测试的自动化和引导式工作流程

• 批准号: 9894817
• 负责人: Andreas Scherer
• 金额: $ 64.97万
• 依托单位: GOLDEN HELIX, INC.
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-03-15 至 2021-02-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9894817
• 关键词: Accountability; Adopted; Adoption; Algorithms; American; Appropriateness Review; Automation; Benchmarking; Bioinformatics; Biological Assay; Classification; Clinical; Clinical Laboratory Improvement Amendments; Clinical assessments; Collaborations; Communication; Competence; Complex; Complex Analysis; Computer software; Copy Number Polymorphism; Data; Data Sources; Decision Support Systems; Dependence; Detection; Development; Diagnosis; Elements; Ensure; Environment; Future; Genetic; Genetic Screening; Genetic Services; Genomics; Government; Guidelines; Hand; Hereditary Disease; Human Resources; Individual; Industry; Industry Standard; Informatics; Inherited; Institution; Judgment; Knowledge; Laboratories; Malignant Neoplasms; Medical; Medical Genetics; Mutation; Newborn Infant; Nucleotides; Outcome; Output; Patient-Focused Outcomes; Patients; Personal Satisfaction; Phase; Positioning Attribute; Privatization; Procedures; Process; Rare Diseases; Reporting; Resources; Risk Assessment; Running; Sampling; Single Nucleotide Polymorphism; Small Business Innovation Research Grant; Source; Specialist; System; Talents; Testing; Time; Training; Variant; Work; analysis pipeline; base; blind; cost; data hosting; data integration; data warehouse; design; disease diagnosis; genetic association; genetic testing; genetic variant; genomic data; genomic variation; improved; in silico; medical schools; molecular pathology; next generation sequencing; precision medicine; pressure; prototype; reproductive; research clinical testing; secondary analysis; success; testing services; tool; tumor; web app

The work done in a genetic laboratory to process a sample requires many detailed-oriented steps and a wealth of individual and institutional knowledge. The output of this process often has a significant impact on a patient’s outcome and wellbeing. At the same time, the work is repetitive and requires the handling of large test volumes under the time pressures inherent in medical procedures. This is particularly the case with next-generation sequencing (NGS) based tests, which are increasingly used to diagnose rare diseases, analyze mutation profiles of tumors, offer reproductive genetic services and perform newborn genetic screening. Existing software solution in this space have taken steps to make the overall work for a clinician simpler. Still, the efforts have not addressed the dependency on expert judgment and the following of detailed and often complex procedures to complete a genetic test. This environment lends itself to the application of workflow automation capabilities. The key benefits for the clinical users are the following: 1. Minimizing the potential for error: Workflow automation ensures essential and necessary tasks from going unnoticed. With tasks and the personnel that perform them being compressively tracked, workflow automation saves labs from far reaching and potentially very costly expenses associated with lab personnel errors. 2. Reducing costs and increasing throughput: Integrating internal communication into the workflow platform reduces the overhead required to conduct clinical work and stay compliant. The result is more work can be done with the same personnel. 3. Creating accountability and reducing subjectivity: As the complex rules and institutional knowledge of a laboratory gets codified into a workflow, every analytical step can be assigned and attributed to individual lab personnel while reducing the amount of choices made outside the system also reduces variance of outcomes attributed to operator subjectivity. In this project, we bring all elements of the clinical workflow for next-generation sequencing together. This includes the detection of single nucleotide variations and copy number variations, the annotation and clinical assessment of those variants, the storing of the finalized report and all associated data in a genetic data warehouse. This project will also cover the automation of the informatics that enable a decision support system capable of implementing variant classification guidelines such as those by the American College of Medical Genetics, Association of Molecular Pathology and other leading industry bodies.

基因实验室处理样本的工作需要许多详细的步骤和丰富的资源 个人和机构知识的输出通常会对患者的健康产生重大影响。 同时，这项工作是重复性的，需要处理大量的测试。 在医疗程序固有的时间压力下，下一代的情况尤其如此。 基于测序 (NGS) 的测试越来越多地用于诊断罕见疾病、分析突变谱 肿瘤，提供生殖遗传服务并进行新生儿遗传筛查。 在这个领域已经采取了一些措施来简化临床医生的整体工作，但这些努力尚未得到解决。 依赖专家判断以及遵循详细且往往复杂的程序来完成 该环境适合于工作流程自动化功能的应用。 对于临床用户来说，有以下几点： 1. 最大限度地减少出错的可能性：工作流程自动化确保了基本和必要的任务 通过对任务和执行任务的人员进行压缩跟踪，工作流程会被忽视。 自动化使实验室免于与实验室相关的深远且可能非常昂贵的费用 人员失误。 2. 降低成本并提高吞吐量：将内部通信集成到工作流程中 平台减少了进行临床工作和保持合规性所需的开销。 工作可以由相同的人员完成。 3. 建立问责制并减少主观性：由于复杂的规则和制度知识 实验室的工作流程被编入工作流程中，每个分析步骤都可以分配并归因于 个别实验室人员在减少系统外部选择数量的同时也减少了 归因于操作员主观性的结果差异。 在这个项目中，我们将下一代测序的临床工作流程的所有要素整合在一起。 包括单核苷酸变异和拷贝数变异的检测、注释和临床 评估这些变异，将最终报告和所有相关数据存储在遗传数据中 该项目还将涵盖支持决策支持系统的信息学自动化。 能够实施变异分类指南，例如美国医学院的指南 遗传学、分子病理学协会和其他领先的行业机构。