Successful Clinical Response In Pneumonia Therapy (SCRIPT) Systems Biology Center

肺炎治疗 (SCRIPT) 系统生物学中心成功的临床反应

基本信息

批准号：
10551461
负责人：
RICHARD G WUNDERINK
金额：
$ 250.61万
依托单位：
NORTHWESTERN UNIVERSITY AT CHICAGO
依托单位国家：
美国
项目类别：
财政年份：
2018
资助国家：
美国
起止时间：
2018-01-17 至 2027-12-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10551461
关键词：
2019-nCoV Admission activity Alveolar Bioinformatics Blood specimen Bronchoalveolar Lavage COVID-19 COVID-19 pandemic COVID-19 pneumonia Caring Cessation of life Clinical Clinical Data Clinical Trials Collaborations Complex Critical Illness Curettage procedure DNA Data Data Set Databases Direct Costs Disease model Distal Dose Drug Kinetics Enrollment Epidemiology Etiology Evaluation Flow Cytometry Funding Generations Grant Hospitals Immune response Inbred Mouse Infection Intervention Intubation Investigational Therapies Klebsiella Laboratories Lead Lung Lung Transplantation Mechanical ventilation Metagenomics Modeling Modification Morbidity - disease rate Multiomic Data Names Nasopharynx Nature Nose Nosocomial pneumonia Outcome Pathogenesis Patient Care Patients Pharmacodynamics Phase Phase II Clinical Trials Pneumonia Procedures Pseudomonas aeruginosa Publishing Research Personnel Respiratory Mucosa Risk Sampling Space Models Staphylococcus aureus Systems Biology Technology Testing Therapeutic Time United States Validation Viral Work clinical care clinical phenotype clinically actionable co-infection cohort community acquired pneumonia data management high dimensionality humanized mouse improved influenza epidemic inhibitor innovation longitudinal analysis microbial microbiome microbiome therapeutics molecular modeling mortality mouse model multidimensional data multiple omics novel therapeutics participant enrollment pathogen pharmacologic phenome pneumonia model pneumonia treatment predictive modeling randomized trial response seasonal influenza severe COVID-19 single-cell RNA sequencing superinfection therapeutic target translational impact treatment response ventilation ventilator-associated pneumonia

项目摘要

PROJECT SUMMARY/ABSTRACT – Overall Pneumonia, including both community-acquired pneumonia (CAP) and hospital-acquired/ventilator-associated pneumonia (HAP/VAP), causes almost 80% of deaths from infections in the US. As evidenced by the ongoing COVID-19 pandemic, severe pneumonia represents an important cause of morbidity and mortality. Our U19 Systems Biology Center, Successful Clinical Response In Pneumonia Therapy (SCRIPT), which we rename Super-SCRIPT (SCRIPT2) for this renewal, leverages bronchoalveolar lavage (BAL), nasal curettage, and blood sampling paired with cutting-edge multi-omics technologies—including multiparameter flow cytometry, single- cell RNA-sequencing, deep pathogen sequencing, DNA metagenomics, and deep clinical phenotyping—to develop models of pneumonia pathogenesis. In SCRIPT, we generated a detailed systems biology model of SARS-CoV-2 pathobiology that supported a novel therapy for severe SARS-CoV-2 pneumonia that was efficacious in a phase II clinical trial. In SCRIPT2, we will determine whether models generated using high- dimension longitudinal data describing the host response, pathogen, microbiome, and clinical phenome in patients with severe CAP (Project 1) and HAP/VAP (Project 2) can predict favorable or unfavorable clinical transitions over the course of a pneumonia episode. We test the hypothesis that multi-omics inputs will create actionable models that identify favorable and unfavorable clinical transitions/outcomes for both severe CAP and severe HAP/VAP. Aim 1/Project 1. To generate actionable models to improve the clinical course of patients with severe CAP using multi-omics analysis of longitudinal samples from the distal lung and nasopharynx. Aim 2/Project 2. To generate actionable models to improve the clinical course of patients with severe HAP/VAP using a multi-omics analysis of longitudinal samples from the distal lung. Three scientific cores support the projects. The Technology Core developed cutting edge multi-omics approaches for the analysis of bronchoalveolar lavage samples collected as part of clinical care. The Data Management and Bioinformatics Core weaves together clinical data extracted from our own EHR and those from other centers. The Modeling Core works seamlessly with the Projects and Cores to integrate, validate and iteratively improve latent space models of disease. Clinician scholars who provide direct care to patients with pneumonia lead or contribute to each project and core, enhancing the translational impact of our findings.

项目摘要/摘要 - 总体肺炎，包括社区获得的肺炎（CAP）和与医院相关的/呼吸机相关肺炎（HAP/VAP）导致美国感染的死亡中近80％。正如正在进行的 COVID-19大流行，严重的肺炎代表了发病率和死亡率的重要原因。我们的U19 系统生物学中心，肺炎治疗（脚本）的成功临床反应，我们将其重命名 Super-Script（Script2），用于此更新，利用支气管肺泡灌洗（BAL），鼻刮和血液采样与尖端的多词技术 - 包括多参数流式细胞仪，单个细胞RNA测序，深层病原体测序，DNA宏基因组学和深临床表型 - 开发肺炎发病机理的模型。在脚本中，我们生成了一个详细的系统生物学模型 SARS-COV-2病理生物学支持了一种新型的严重SARS-COV-2肺炎疗法在Script2中，我们将确定是否使用高级生成模型描述宿主反应，病原体，微生物组和临床现象的维度纵向数据严重CAP（项目1）和HAP/VAP（项目2）的患者可以预测有利或不利的临床在肺炎发作过程中过渡。我们检验了多摩尼克输入的假设创建可行的模型，以识别两者的有利且不利的临床转变/结果严重的帽子和严重的HAP/VAP。目标1/项目1。生成可行的模型以改善严重患者的临床过程使用来自圆盘肺和鼻咽的纵向样品的多摩学分析。目标2/项目2。生成可行的模型以改善严重患者的临床过程使用来自圆盘肺的纵向样品的多摩学分析HAP/VAP。三个科学核心支持这些项目。技术核心开发了尖端多摩斯分析作为临床护理一部分收集的支气管肺泡灌洗样品的方法。数据管理和生物信息学核心编织从我们自己的EHR中提取的临床数据以及其他中心。建模核心与项目和核心无缝合作，以集成，验证和迭代地改善疾病的潜在空间模型。为患者提供直接护理的临床医生肺炎带领或为每个项目和核心做出贡献，从而增强了我们发现的翻译影响。