Mathematical Modeling of Inflammation in ARDS

ARDS 炎症的数学模型

基本信息

批准号：
7923836
负责人：
YORAM VODOVOTZ
金额：
$ 43.95万
依托单位：
UNIVERSITY OF PITTSBURGH AT PITTSBURGH
依托单位国家：
美国
项目类别：
财政年份：
2008
资助国家：
美国
起止时间：
2008-09-01 至 2011-08-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/7923836
关键词：
Acute Address Adult Respiratory Distress Syndrome Algorithms Animal Experiments Animal Model Animals Anti-Inflammatory Agents Anti-inflammatory Biochemical Biological Process Blood COL-3 Cells Cessation of life Choking Chronic Clinical Clinical Trials Complex Computer Simulation Controlled Clinical Trials Critical Pathways Data Development Diabetic Foot Ulcer Diagnostic Disease Disease Progression Drug Industry Elastases FDA approved Failure Family suidae Free Radicals Functional disorder Funding Funding Mechanisms Future Gelatinase A Gelatinase B Goals Grant Health Care Costs Hemorrhagic Shock High Performance Computing Human Impaired wound healing Indium Individual Industry Inflammation Inflammation Mediators Inflammatory Inflammatory Response Injury Institutes Intervention Ischemia Leukocytes Lilly brand of drotrecogin alfa activated Literature Lung Marketing Mediator of activation protein Medical Metabolic Pathway Modeling Molecular Morbidity - disease rate Multiple Organ Failure Mus National Heart, Lung, and Blood Institute Nature Organ Outcome Pathogenesis Pathologic Patients Peptide Hydrolases Pharmaceutical Preparations Physiological Placebo Control Population Process Randomized Randomized Clinical Trials Rattus Recording of previous events Reperfusion Therapy Research Research Personnel Resources Secure Sepsis Sepsis Syndrome Septic Shock Shock Simulate Small Business Technology Transfer Research Solutions System Systemic infection Systems Biology TNFRSF5 gene Testing Tetracyclines Therapeutic Therapeutic Agents Tissues Training Translating Translational Research Trauma Treatment outcome United States United States National Institutes of Health Universities Validation Variant Work abstracting antimicrobial drug base clinical decision-making cytokine effective therapy experience improved insight knockout gene mathematical model mortality neutrophil novel novel therapeutics pre-clinical preclinical study preconditioning prevent research study response simulation symptom management therapeutic target tool translational study treatment strategy

项目摘要

DESCRIPTION (provided by applicant): Trauma and systemic infection elicit an acute inflammatory response. Inflammation involves complex interactions among leukocytes, their products (cytokines, free radicals, and proteases), and the tissue damage/dysfunction that ensues. This multiple organ dysfunction often manifests as septic shock and severe lung dysfunction, referred to collectively as the acute respiratory distress syndrome (ARDS), and contributes to the 215,000 annual deaths in the U.S. from sepsis. The complexity of this process has stymied the progress towards immunomodulatory ARDS therapeutics. We have developed a mathematical model of these elements in order to unravel this complex interplay in various settings of acute inflammation, and have calibrated distinct variants of this model with data from mice, rats, swine, and humans (University of Pittsburgh Inflammatory Analyte/Modeling Component). Our modeling platform has been used to gain both basic and translational insights, the latter including simulated (in silico) clinical trials. In conjunction with these efforts, we developed a sepsis + gut ischemia/reperfusion (Sepsis+I/R) porcine model that mimics the pathogenesis of human septic shock and ARDS (Upstate Medical University ARDS Animal Model Component). We hypothesize that mathematical analysis of the complex biochemical and physiologic data generated in our Sepsis+I/R model will enable us to isolate key therapeutic targets and to test novel therapeutics; one such agent is the modified tetracycline COL-3. Our Specific Aims are: 1) to develop a robust mathematical model describing Sepsis+I/R- induced shock and ARDS in swine, its pathologic consequences, and possible therapies, 2) to utilize COL-3 as a tool to further calibrate the mathematical model and 3) to demonstrate that NE, MMP-2 and MMP-9 are critical components in Sepsis+I/R-induced septic shock and ARDS pathogenesis. Our calibrated mathematical model will be used to conduct in silico clinical trials and establish a platform for the rational development of novel ARDS therapeutics. The in silico trials will be validated in animal experiments. The proposed translational studies will develop a robust mathematical model capable of describing the complex pathogenesis of sepsis-induced ARDS and identify target molecules whose modulation would significantly improve clinical outcome. Sepsis and septic shock are responsible for more that 215,000 deaths in the United States per year with an annual healthcare cost of over $16 billion dollars. Due to the complexity of sepsis pathogenesis, it has been exceedingly difficult to develop drugs that will reduce this high mortality. In the proposed study, we will analyze the mechanisms of sepsis mortality with a sophisticated mechanistic, partially-calibrated mathematical model that will be able to identify molecular "choke points" that if blocked will arrest the progression of this disease and significantly reduce sepsis-induced morbidity and mortality. (End of Abstract)

描述（由申请人提供）：创伤和全身感染引起急性炎症反应。炎症涉及白细胞及其产物（细胞因子、自由基和蛋白酶）之间复杂的相互作用，以及随之而来的组织损伤/功能障碍。这种多器官功能障碍通常表现为脓毒性休克和严重肺功能障碍，统称为急性呼吸窘迫综合征 (ARDS)，导致美国每年有 215,000 人死于脓毒症。这一过程的复杂性阻碍了免疫调节 ARDS 治疗的进展。我们开发了这些元素的数学模型，以便揭示各种急性炎症中复杂的相互作用，并使用来自小鼠、大鼠、猪和人类的数据校准了该模型的不同变体（匹兹堡大学炎症分析/建模）成分）。我们的建模平台已用于获得基本和转化见解，后者包括模拟（计算机）临床试验。结合这些努力，我们开发了脓毒症 + 肠道缺血/再灌注 (Sepsis+I/R) 猪模型，模拟人类脓毒性休克和 ARDS（北部医科大学 ARDS 动物模型组件）的发病机制。我们假设，对脓毒症 + I/R 模型中生成的复杂生化和生理数据进行数学分析将使我们能够分离关键治疗靶点并测试新疗法；其中一种药物是改良的四环素 COL-3。我们的具体目标是：1) 开发一个强大的数学模型，描述猪脓毒症+I/R 引起的休克和 ARDS、其病理后果和可能的治疗方法，2) 利用 COL-3 作为工具来进一步校准数学模型模型和 3) 证明 NE、MMP-2 和 MMP-9 是脓毒症 + I/R 诱导的感染性休克和 ARDS 发病机制的关键组成部分。我们校准的数学模型将用于进行计算机临床试验，并为合理开发新型 ARDS 疗法建立平台。计算机模拟试验将在动物实验中得到验证。拟议的转化研究将开发一个强大的数学模型，能够描述脓毒症引起的 ARDS 的复杂发病机制，并确定其调节将显着改善临床结果的靶分子。在美国，败血症和败血性休克每年导致超过 215,000 人死亡，每年的医疗费用超过 160 亿美元。由于脓毒症发病机制的复杂性，开发降低这种高死亡率的药物非常困难。在拟议的研究中，我们将通过复杂的机械、部分校准的数学模型来分析脓毒症死亡率的机制，该模型将能够识别分子“阻塞点”，如果阻断这些点，将阻止这种疾病的进展并显着减少脓毒症引起的死亡发病率和死亡率。（摘要完）

项目成果

期刊论文数量（1）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

An agent-based model of inflammation and fibrosis following particulate exposure in the lung.

DOI：
10.1016/j.mbs.2011.03.005
发表时间：
2011-06
期刊：
Mathematical biosciences
影响因子：
4.3
作者：
Brown BN;Price IM;Toapanta FR;DeAlmeida DR;Wiley CA;Ross TM;Oury TD;Vodovotz Y
通讯作者：
Vodovotz Y