Rational Integration of clinical SEquencing (RISE)

Rise项目摘要 临床基因组测序的出现，以识别有严重疾病风险的患者 量身定做的治疗方法有望极大地改善健康结果，并提供 精准医疗输送基金会。然而，即使作为实验室方法 执行测序变得非常高效，不确定最佳的宽度 以及排序的经济价值以及关于个人应该 被测试是更广泛使用的关键障碍。随着我们迅速接近一个 廉价的排序，量化和优化经济和 基因组定制护理的临床价值是必要的。为了合理地整合 排序(RISE)项目，我们建议开发一个离散事件仿真(DES)来 评估前瞻性获取的平均临床疗效和成本效益 对不同患者群体的数据进行排序。模拟将利用 基于文献的临床结果比率、成本和效用的估计，结合 临床外显子组和药物基因组实施计划数据描述如何 结果被返回并在临床护理中做出反应。第一个目标是开发一种 了解驱动因素的概念框架和计算基础架构 基因组筛选的经济价值。第二个目标将从外部验证这一增长 使用真实世界使用数据的模型。第三个目标将评估以下项目的成本效益 基因组筛选方案，确定价值的关键驱动因素并提供研究优先事项 在基因组筛选中。

RISE Project Summary The advent of clinical genome sequencing to identify patients at risk for serious diseases and to tailor treatments promises to greatly improve health outcomes and provide a foundation for the delivery of Precision Medicine. However, even as laboratory methods to perform sequencing become highly efficient, uncertainty around the optimal breadth and economic value of sequencing as well as ambiguity around which individuals should be tested presents a critical barrier to wider use. As we rapidly approach an era of inexpensive sequencing, new approaches to quantify and optimize the economic and clinical value of genome-tailored care are needed. For the Rational Integration of Sequencing (RISE) project, we propose to develop a Discrete Event Simulation (DES) to estimate the average clinical efficacy and cost-effectiveness of prospectively acquiring sequence data across a diverse patient population. The simulation will leverage literature-based estimates of clinical outcome rates, costs, and utilities combined with clinical exome and pharmocogenomic implementation program data describing how results are returned and reacted to within clinical care. The first Aim will develop a conceptual framework and computational infrastructure to understand the drivers of economic value in genomic screening. The second Aim will externally validate the RISE model using real-world use data. The third Aim will assess the cost effectiveness of genomic screening scenarios, identify key drivers of value and inform research priorities in genomic screening.