Oncology Knowledge Rapid Alerts: Integrating biomarker-driven clinical decision support for therapy selection at point-of-care

肿瘤学知识快速警报：整合生物标志物驱动的临床决策支持，以在护理点选择治疗方法

• 批准号: 10526824
• 负责人: Christine M Micheel
• 金额: $ 45万
• 依托单位: VANDERBILT UNIVERSITY MEDICAL CENTER
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-19 至 2024-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10526824
• 关键词: Academic Medical Centers; Adjuvant; Adopted; Adoption; Algorithms; Bioinformatics; Biological Markers; Cancer Patient; Clinical; Clinical Oncology; DNA; Data; Data Store; Decision Making; Diagnostic; Drug Targeting; Electronic Health Record; Electronic Mail; Environment; Evolution; Foundations; Funding; Future; Genomics; Goals; Health care facility; Histology; Human; Information Resources; Institution; Knowledge; Laboratories; Malignant Neoplasms; Medicine; Methodology; Methods; Molecular; Molecular Profiling; Non-Small-Cell Lung Carcinoma; Oncologist; Oncology; Output; Patients; Persons; Pharmaceutical Preparations; Positioning Attribute; Readability; Reporting; Research; Resource Development; Retrieval; Running; Scanning; Selection for Treatments; Structure; System; Test Result; Testing; Therapeutic; Time; Vendor; Visit; Work; application programming interface; base; biomarker-driven; cancer cell; cancer genome; cancer therapy; cancer type; clinical care; clinical decision support; clinical development; data integration; data standards; data structure; electronic structure; genomic data; improved; infancy; innovation; knowledgebase; natural language; open source; point of care; precision oncology; prognostic; research clinical testing; standard of care; support tools; targeted treatment; tool; tumor; web app; web services

PROJECT SUMMARY/ABSTRACT Precision cancer medicine uses patient molecular test results to guide cancer therapy selection. An increasing number of cancer therapies are now targeted to specific molecular alterations, and tumor molecular testing is now standard of care. A significant obstacle in advancing precision cancer therapy is the rapid pace of change in this field—making it challenging for oncologists to stay up to date. The long-term goal of this project is to integrate clinical decision support (CDS) for precision cancer therapy selection directly into the electronic health record (EHR). Ultimately, we will create an integrated CDS solution within the EHR that includes best practice alerts to oncologists and integration of CDS into the molecular testing result report. The objective of this R21 is to develop a CDS algorithm to match molecular test results to targeted therapy assertions from a widely used precision oncology knowledgebase, deliver an open-source web service application programming interface (API) that can support vendor-agnostic integration with any EHR that uses the new genomic data standards, and provide proof-of-concept, point-of-care CDS in our local EHR environment. We will accomplish this through the following specific aims: Aim 1. Develop an open-source algorithm and API for computing and storing biomarker-driven CDS from the My Cancer Genome (MCG) knowledgebase. We will develop an algorithm that will compute targeted therapy options for a patient’s tumor histology and molecular profile from the data stored in the MCG knowledgebase. We will build a web service API that receives molecular testing data, calls the MCG knowledgebase, runs the CDS algorithm, and outputs the computed CDS in a format that can be stored for rapid retrieval and that is compatible with EHRs using the new genomic data standards. Aim 2. Develop methods for integration of biomarker-driven CDS into the EHR as human-readable statements. In this aim, we will build API functions to receive communications from the EHR when an oncologist views tumor test results, retrieve cached CDS, and send CDS to the EHR. Using non-small cell lung cancer as a proof-of-concept, our initial use cases will provide integration of CDS with the molecular results report and best practice alerts to oncologists. This project will provide tools to match patient molecular test results to appropriate targeted therapies. At the conclusion of this project, an oncologist will be able to view CDS when they access patient molecular results in the EHR. This point-of-care CDS will facilitate delivery of the right information to the right person at the right time to maximize impact on clinical care.

项目概要/摘要 精准癌症医学越来越多地利用患者分子检测结果来指导癌症治疗选择。 现在许多癌症疗法都针对特定的分子改变，并且肿瘤分子 检测现已成为护理标准，推进精准癌症治疗的一个重大障碍是快速的步伐。 该领域的变化使得肿瘤学家很难跟上这一领域的长期目标。 该项目旨在将精准癌症治疗选择的临床决策支持（CDS）直接整合到 最终，我们将在 EHR 中创建一个集成的 CDS 解决方案。 包括向肿瘤学家发出的最佳实践警报以及将 CDS 集成到分子检测结果中 该 R21 报告的目标是开发一种 CDS 算法，将分子测试结果与目标相匹配。 来自广泛使用的精准肿瘤学知识库的治疗断言，提供开源网络服务 应用程序编程接口 (API)，可以支持与任何使用 EHR 的供应商无关的集成 新的基因组数据标准，并在我们当地的 EHR 中提供概念验证、护理点 CDS 我们将通过以下具体目标来实现这一目标： 目标 1. 开发开源算法和 API，用于计算和存储生物标记驱动的 CDS 来自我的癌症基因组 (MCG) 知识库 我们将开发一种计算算法。 根据存储在数据库中的数据，针对患者的肿瘤组织学和分子谱提供靶向治疗方案 我们将构建一个 Web 服务 API，用于接收分子测试数据、调用 MCG。 知识库，运行 CDS 算法，并以可存储的格式输出计算出的 CDS 快速检索，并且与使用新基因组数据标准的 EHR 兼容。 目标 2. 开发将生物标记驱动的 CDS 集成到 EHR 中作为人类可读的方法 为此，我们将构建 API 函数，以便在出现异常情况时接收来自 EHR 的通信。 肿瘤学家使用非小细胞肺查看肿瘤测试结果、检索缓存的 CDS 并将 CDS 发送到 EHR。 癌症作为概念验证，我们的初始用例将提供 CDS 与分子结果的集成 向肿瘤学家报告和最佳实践警报。 该项目将提供工具将患者分子测试结果与适当的靶向治疗相匹配。 该项目结束后，肿瘤学家在访问患者分子结果时将能够查看 CDS 该 EHR 定点护理 CDS 将有助于将正确的信息传递给正确的人。 最大限度地影响临床护理的时间。