Combined Biomarker and EMR Data for Heterogeneous Treatment Effects and Surrogate Endpoints in Sepsis

脓毒症异质治疗效果和替代终点的生物标志物和 EMR 数据相结合

• 批准号: 10603924
• 负责人: Bobby Reddy
• 金额: $ 116.16万
• 依托单位: PRENOSIS, INC.
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-06-01 至 2025-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10603924
• 关键词: Adrenal Cortex Hormones; Aftercare; Award; Biological Markers; Clinical; Clinical Data; Clinical Trials; Computerized Medical Record; Data; Data Set; Diagnostic; Ensure; Euclidean Space; Frustration; Grant; Health; Heterogeneity; Hospitals; Hour; Housing; Immune response; Individual; Infection; Intervention; Length of Stay; Location; Machine Learning; Maps; Measurement; Measures; Methods; Modeling; National Institute of General Medical Sciences; Outcome; Patient-Focused Outcomes; Patients; Plasma; Principal Investigator; Sampling; Sepsis; Series; Serum; Site; Steroids; Subgroup; Surrogate Endpoint; Syndrome; Techniques; Testing; Time; Work; biobank; clinical decision support; clinical trial recruitment; clinically relevant; coronavirus disease; demographics; drug development; effective therapy; follow-up; improved; interest; mortality; novel; patient biomarkers; patient subsets; product development; programs; protein biomarkers; response; septic patients; treatment effect; two-dimensional

Principal Investigator/Program Director (Last, first, middle): Reddy, Jr., Bobby Project Summary: Sepsis is a poorly understood clinical syndrome characterized by dysregulated host response to infection. The complexity and heterogeneity of the host response has frustrated attempts at developing effective treatments. In partnership with 6 U.S. hospitals, Prenosis amassed NOSIS, one of the world’s largest datasets and biobanks that combines biomarker and clinical data for patients suspected of infection, housing over 60,000 plasma or serum samples from over 12,000 patients. We also curated a dataset of dense time-series data from each patient’s Electronic Medical Record (EMR), including demographics, vitals, lab results, interventions, outcomes, and many other parameters. In this project, Prenosis will build upon previous work to conduct targeted analyses of the individual treatment effects of corticosteroids on septic patient outcomes. Using propensity score matching on patient baseline data (their biomarker/EMR profile at the time they were suspected of serious infection), we have identified 1,350 pairs of treatment and control patients whose samples have already been collected and stored in the biobank. We will leverage our existing pipeline to measure the 40 core biomarkers on 8,100 samples for these 2,700 patients: the pre-treatment sample closest to the time at which the treatment patient received steroids, the sample closest to 24 hours after the treatment patient received steroids, and the patients’ final samples to understand how treatment impacted biomarker profile and how these changes are associated with clinical outcomes of interest. These data and analyses will serve as the basis for at least three immediately commercializable products. First, elucidating which patients are likely to benefit or suffer from treatment with corticosteroids will improve diagnostic and clinical decision support products that are deployable within Prenosis’ existing ImmunixTM platform. Second, this will demonstrate the NOSIS dataset is a powerful platform for predictive enrichment of clinical trials. Estimating individual treatment effects in NOSIS identifies the optimal patient subpopulations to be recruited for clinical trials, which would otherwise fail. Third, understanding treatment effects on biomarker profile and corresponding association with clinical outcomes will establish the NOSIS host response profile as effective surrogate endpoints for clinical trials.

首席研究员/计划主任（最后，第一，中间）：小雷迪，鲍比 项目摘要： 败血症是一种鲜为人知的临床综合征，其特征是宿主对感染的反应失调。这 宿主反应的复杂性和异质性挫败了开发有效治疗的尝试。 与6家美国医院合作，Prenosis积聚了Nosis，这是世界上最大的数据集和生物库之一 结合了涉嫌感染的患者的生物标志物和临床数据，住房超过60,000个血浆或 来自12,000多名患者的血清样品。我们还从每个 患者的电子病历（EMR），包括人口统计，生命力，实验室结果，干预措施，结果， 以及许多其他参数。 在这个项目中，培养病将基于以前的工作以进行针对性的分析 皮质类固醇对化脓性患者结局的影响。在患者基线数据上使用倾向分数匹配 （当时他们的生物标志物/EMR曲线被怀疑严重感染），我们已经确定了1,350对 的治疗和对照患者的样本已经收集并存储在生物库中。我们将 利用我们现有的管道来测量这2700名患者的8,100个样品的40个核心生物标志物： 预处理样本最接近治疗患者接受类固醇的时间，最接近的样本 治疗后24小时接受立体定向，以及患者的最终样本，以了解如何了解 治疗影响了生物标志物的概况，以及这些变化与感兴趣的临床结果如何相关。 这些数据和分析将作为至少三个立即商业化产品的基础。第一的， 阐明哪些患者可能受益或接受皮质类固醇治疗将改善诊断 以及可在Prenosis现有的ImmunixTM平台中部署的临床决策支持产品。第二， 这将证明NOSIS数据集是临床试验预测酶的强大平台。 估计NOSIS中的个体治疗效果确定要招募的最佳患者亚群 临床试验，否则会失败。第三，了解治疗对生物标志物概况的影响和 与临床结果的相应关联将确定Nosis宿主反应曲线有效 临床试验的替代端点。