Matching genotypes with personalized therapies: Development of a decision support infrastructure to augment the value of precision medicine

项目概要 尽管精准肿瘤学取得了进展，但临床医生通常面临着数量庞大、种类繁多的后续治疗： 世代测序和分子数据经常被直观地处理以支持高风险 决定。总体而言，目前有助于下一代序列数据解释的可用资源 受到手动执行、复杂、耗时且容易出错的基因查询的限制，最终 缺乏以可扩展的方式优先考虑新兴疗法的必要信息。重要的是， 由于缺乏先进的分析工具，基因组与临床数据的整合受到严重阻碍 将基因组靶标与分子驱动疗法相匹配。这些障碍，加上健康差异， 扩大呈指数级增长的药物开发领域与实际效益之间的差距 癌症患者。 拟议研究的总体目标是将临床与计算精确肿瘤学联系起来 能够在基因组定义的群体中做出临床决策。我们建议开发精准肿瘤学 决策支持框架，用于自动化、可扩展且精确匹配可操作的下一代 靶向治疗的测序结果。然后我们将在几个临床中测试其临床效用和价值 约翰霍普金斯大学分子肿瘤委员会内的机构，在约翰霍普金斯大学合作社区医疗 中心以及两项正在进行的针对乳腺癌女性的临床试验。增强普遍性 我们的分析工具包超越了我们当地的学术环境，我们设计了该平台的架构 这样就可以从多个来源摄取和协调下一代序列数据， 实施通用数据模型，将临床要素映射到标准化术语和杠杆作用 集成自然语言处理来生成可操作的突变靶向治疗对。这些 属性为该工具包在医疗保健领域的潜在广泛使用和实施奠定了基础 我们当地学术环境之外的环境。 尽管在肿瘤分析的高级诊断方面取得了重大进展，但坚实的支柱 缺乏支持卫生保健系统内部和跨卫生保健系统实际实施的支持。底层的 拟议研究的前提是它将引发跨机构的真实世界基因组数据分析 倡议和基因型驱动的临床试验将有益于卫生系统和患者。值得注意的是， 我们的精准肿瘤学决策支持平台将加强精准肿瘤学的实施 不易获得临床基因组学内部专业知识的机构。我们设想这 简化的自动化和可扩展流程将改善护理、提高患者治疗效果并定义国家标准 如何为个体患者选择和定制治疗方法的标准。

Project Summary Despite the progress made in precision oncology, clinicians typically face a vast volume and variety of next- generation sequencing and molecular data that is frequently intuitively processed to support high-stakes decisions. Overall, currently available resources that assist with next-generation sequence data interpretation are limited by manually performed, complex, time-consuming, and error-prone gene queries and ultimately lack the necessary information for prioritizing emerging therapies in a scalable manner. Importantly, the integration of genomic with clinical data has been severely hampered by the lack of advanced analytical tools that match genomic targets with molecularly-driven therapies. These barriers, together with health disparities, widen the gap between an exponentially increasing drug development field and the actual benefits for patients with cancer. The overarching goal of the proposed research is to link clinical with computational precision oncology and enable clinical decision-making in genomically defined groups. We propose to develop a precision oncology decision support framework for automated, scalable, and precise matching of actionable next-generation sequencing findings with targeted therapies. We will then test its clinical utility and value in the several clinical settings within the Johns Hopkins Molecular Tumor Board, in Johns Hopkins partnering community medical centers as well within two ongoing clinical trials for women with breast cancer. To enhance the generalizability of our analytical toolkit past our local academic environment, we have designed the platform's architecture such that it allows for ingestion and harmonization of next-generation sequence data from multiple sources, implements a common data model to map clinical elements to standardized terminologies and leverages ensemble natural language processing to generate actionable mutation-targeted therapy pairs. These attributes provide the foundation for the toolkit's potential widespread use and implementation in health care settings outside our local academic environment. While significant advances have been made in advanced diagnostics for tumor profiling, a solid backbone that supports the practical implementation within and across health care systems is lacking. The underlying premise of the proposed research is that it will ignite cross-institutional real-world genomic data analysis initiatives and genotype-driven clinical trials that will be beneficial for health systems and patients. Notably, our precision oncology decision support platform will enhance the implementation of precision oncology at institutions that do not readily have access to in-house expertise in clinical genomics. We envision that this streamlined automatic and scalable process will improve care, enhance patient outcomes and define national standards in how treatments are selected and tailored to individual patients.