Automated and Guided Workflows for Clinical Testing Using NGS Assays

在遗传实验室中处理样本的工作需要许多面向细节的步骤和丰富的知识。 个人和机构的知识。该过程的输出通常对患者的健康有显著影响。 结果和幸福。同时，该工作是重复性的，并且需要处理大量的测试卷 在医疗程序固有的时间压力下。尤其是下一代 越来越多地用于诊断罕见疾病的基于测序（NGS）的测试， 提供生殖遗传服务和进行新生儿遗传筛查。现有软件解决方案 已经采取措施使临床医生的总体工作更简单。尽管如此，这些努力并没有解决 对专家判断的依赖，以及完成一项 基因测试这种环境适合于工作流程自动化能力的应用。的关键获益 为临床用户提供以下服务： 1.最大限度地减少错误的可能性：工作流程自动化确保从 不被人注意通过压缩跟踪任务和执行任务的人员， 自动化使实验室避免了与实验室相关的深远且可能非常昂贵的费用 人员失误。 2.降低成本并提高产量：将内部沟通整合到工作流程中 平台减少了进行临床工作和保持合规性所需的开销。结果更 工作可以由相同的人员完成。 3.建立问责制和减少主观性：作为复杂的规则和制度知识 将实验室的每一个分析步骤编入工作流程，每个分析步骤都可以分配和归因于 单个实验室人员在减少系统外所做的选择量的同时， 结果的差异归因于操作者的主观性。 在这个项目中，我们将下一代测序的临床工作流程的所有元素结合在一起。这 包括检测单核苷酸变异和拷贝数变异，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库中， 仓库该项目还将涵盖使决策支持系统成为可能的信息学自动化 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。

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.