The Great Lakes PrecISE Partnership

五大湖 PrecISE 合作伙伴关系

基本信息

批准号：
9979943
负责人：
Loren C Denlinger
金额：
$ 38.41万
依托单位：
UNIVERSITY OF WISCONSIN-MADISON
依托单位国家：
美国
项目类别：
财政年份：
2017
资助国家：
美国
起止时间：
2017-09-23 至 2023-06-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9979943
关键词：
Adherence Affect Air Antibodies Asthma Biological Markers Blinded Blood C-reactive protein Clinical Trials Design Community Healthcare Community Practice Data Development Disease Disease Progression Dose Evaluation FDA approved Fc Receptor Free Will Frequencies Guidelines HIV Heterogeneity Illinois Image Impairment Interleukin 6 Receptor Interleukin-5 Interleukin-6 Intervention Investigation Malignant Neoplasms Measures Methods Molecular Monitor Morbidity - disease rate Muscarinic Antagonists Oncology Outcome Participant Pathogenesis Patients Pharmacopoeias Phenotype Plasma Population Population Heterogeneity Prediction of Response to Therapy Predictive Value Prevention Probability Process Protocols documentation Public Health Pulmonary Function Test/Forced Expiratory Volume 1 Randomized Research Research Personnel Risk Risk Factors Sampling Severities Sputum Standardization Symptoms Testing Therapeutic Therapeutic Intervention Translational Research Treatment Efficacy Urine Validation Vision Wisconsin X-Ray Computed Tomography asthma exacerbation base chest computed tomography comorbidity design disease phenotype effective therapy eosinophil eosinophilic inflammation flexibility health care settings heart rate variability high risk indexing innovation multidisciplinary oxidant stress patient population patient subsets personalized medicine precision medicine predictive tools programs randomized placebo-controlled clinical trial respiratory success targeted treatment therapeutic development treatment duration treatment guidelines treatment response trial design

项目摘要

Abstract: The lack of data to inform treatment guidelines in patients with severe asthma remains a major unmet need. Our vision is to develop a personalized medicine approach for the treatment of severe asthma, directed at its pathogenesis and ultimately translatable to the community health care setting for implementation. Because traditional clinical trial designs are inefficient for diseases with multiple phenotypes, our central hypothesis is that the application of an adaptive trial design will identify subtypes of severe asthma that will be most responsive to precise interventions. The scientific rationale for this proposal includes recent data showing that elevated blood eosinophils, maximum FEV1 reversal, and plasma IL-6 concentrations are risk factors for frequent exacerbations which are a major component of severe asthma. Each of these phenotypes has precise interventions that are FDA approved for asthma or other diseases, namely anti-IL-5 antibodies, long acting muscarinic antagonists, and anti-IL6 receptor antibodies. We propose the following Specific Aims to test this hypothesis: 1) To determine the impact of phenotype-directed interventions on the frequency of asthma exacerbations using a sequential Bayesian adaptive clinical trial design, stratified by blood eosinophils, maximum FEV1 reversal, and plasma IL-6 concentrations; and 2) To validate the predictive value of monitoring biomarkers assessed at baseline and after three months of treatment. These biomarkers include sputum eosinophils, heart rate variability, C-reactive protein levels, air trapping and other imaging metrics assessed by low dose chest CT scan, and measures of airway oxidant stress. Our team of multi-disciplinary investigators and translational science clinicians in the Great Lakes PrecISE Partnership has access to a diverse population of patients with severe asthma from Wisconsin and Northern Illinois which will enable us to be a very active partner in this collaborative network. We expect to rapidly identify patient subsets that benefit from therapies not currently considered as part of the asthma pharmacopoeia. The efficient assessment of these biomarkers and precise treatments would not be possible without this departure from the typical therapeutic development process.

抽象的：缺乏为严重哮喘患者的治疗指南提供信息的数据仍然是一个主要的未满足需求。我们的愿景是开发一种个性化医学方法来治疗严重哮喘发病机理，最终可以翻译成社区医疗保健设置以实施。因为传统的临床试验设计对于具有多种表型的疾病效率低下，我们的中心假设是适应性试验设计的应用将识别出最大的严重哮喘的亚型对精确的干预措施做出反应。该提案的科学原理包括最近的数据表明血液嗜酸性粒细胞升高，最大FEV1逆转和血浆IL-6浓度是危险因素频繁加重，这是严重哮喘的主要组成部分。这些表型中的每一个都有精确的 FDA批准用于哮喘或其他疾病的干预措施，即抗IL-5抗体，长期行动毒蕈碱拮抗剂和抗IL6受体抗体。我们提出以下具体目的来测试这一点假设：1）确定表型定向干预措施对哮喘频率的影响使用顺序贝叶斯自适应临床试验设计，由血液嗜酸性粒细胞分层的加重，最大FEV1反转和血浆IL-6浓度； 2）验证监视的预测值生物标志物在基线和三个月的治疗后进行了评估。这些生物标志物包括痰嗜酸性粒细胞，心率变异性，C反应蛋白水平，空气捕获和其他由低剂量的胸部CT扫描和气道氧化应激的测量。我们的多学科研究人员团队大湖区的转化科学临床医生精确合作伙伴关系可以接触到多样化的人群威斯康星州和伊利诺伊州北部严重哮喘的患者将使我们成为非常活跃的患者该协作网络的合作伙伴。我们希望迅速识别受益于疗法的患者子集目前尚未被视为哮喘药典的一部分。对这些生物标志物的有效评估如果没有这种偏离典型的治疗性发展，则不可能进行精确治疗过程。