Vascular Drug Delivery

血管药物输送

基本信息

批准号：
8664866
负责人：
Elazer R Edelman
金额：
$ 53.91万
依托单位：
MASSACHUSETTS INSTITUTE OF TECHNOLOGY
依托单位国家：
美国
项目类别：
财政年份：
1994
资助国家：
美国
起止时间：
1994-08-01 至 2016-05-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8664866
关键词：
Adverse event Affect Anatomy Angiography Animal Experiments Animal Model Animals Arteries Beds Binding Biological Biological Models Biology Blood Vessels Characteristics Clinical Clinical Data Clinical Trials Collaborations Complex Computational algorithm Computer Simulation Computers Control Animal Coronary Coronary artery Custom Data Data Analyses Data Set Databases Descriptor Device Designs Devices Discrimination Drug Delivery Systems Drug Formulations Drug Kinetics Event Family suidae Funding Geometry Grant Healed Histology Housing Human Image Imaging technology Implant In Situ Individual Intervention Kinetics Lead Learning Lesion Link Measurement Measures Mechanics Mediator of activation protein Modeling Optical Coherence Tomography Outcome Pathologic Patients Pattern Performance Pharmaceutical Preparations Physiological Positioning Attribute Procedures Relative (related person)Research Personnel Resolution Resources Risk Role Sirolimus Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization Stents Structure Surface System Techniques Testing Therapeutic Thrombosis Time Tissues University Hospitals Validation Variant Work clinical effect drug distribution experience follow-up healing human data implantation in vivo innovation insight local drug delivery novel repaired response stressor success three-dimensional modeling tissue repair tool

项目摘要

DESCRIPTION (provided by applicant): Endovascular mechanical interventions and local vascular drug delivery (LVDD) affect vascular healing but differently across patients. Device design, formulation and deployment influence but do not strictly predict, clinical response. Two implications emerge. The first is that repair biology is inherently variable and clinical outcomes can never be predicted. The second is that response variability can be categorized but depends on more proximate physiological forces, which, if identified, can allow better definition of procedural success and prediction of adverse events. We embrace the latter view, that dimensional and anatomic parameters can speak to procedural success but only over a wide range and with little discrimination, and it is physiologic consequences of vascular manipulation that are the strongest predictors of performance. Guided by our past funded work, the current proposal examines the hypothesis that induced patterns of flow and drug distribution are the proximate drivers of biological response to vascular interventions, and can better predict the therapeutic consequences of interventions in animals and now in humans as well. In past cycles we created analytical, immunohistochemical and imaging technologies to characterize repair and flow disruptions after vascular intervention in animal systems, and a quantitative framework to predict pharmaco-kinetics and -dynamics of LVDD. We extend this work by using these resources in more controlled animal models, in silico models and with human clinical data. Three specific aims will: (1) define the limits of traditional descriptors of complex interventions no matter how precise, (2) develop and validate computational models that predict near-wall flow patterns and drug distributions in real-world settings in complex animal models and provide statistical tools to determine predictive roles of these forces relative to procedural variables alone, and (3) investigate whether the variables determined predict clinical outcomes in humans. Innovation exists in the tools we employ, data we analyze, approach we take, implications of the work and assembly of a pandisciplinary group of investigators with a legacy of collaboration. OCT imaging quantifies biologic effect in situ, providing high-resolution images of stent-vessel geometry in animals and humans in an identical manner. In-house computer algorithms extract procedural geometries, which create 3D computational models of physiological flow disruption and drug distribution. MALDI corroborates drug distribution after local delivery. Animal experiments use custom-made drug delivery devices to allow precise control in defining complex interventional procedures in vivo. Access to the University Hospital's extensive OCT databank of clinical images offers a rich test bed for clinical validation. Statisticl innovation will accurately describe the effects of stent characteristics, flow, and drug distributin on biological outcomes in a setting where the data have multilevel, longitudinal, and spatial structure. The lessons learned may extend our understanding of basic vascular biology, local drug delivery in stents and other combination devices, tissues, or pathologic conditions.

描述（由申请人提供）：血管内机械干预措施和局部血管药物递送（LVDD）会影响血管愈合，但在患者之间有所不同。设备设计，配方和部署影响，但不能严格预测临床反应。出现了两个含义。首先是修复生物学本质上是可变的，并且永远无法预测临床结果。第二是可以对响应变异性进行分类，但取决于更接近的生理力，如果确定，可以更好地定义程序成功和不良事件的预测。我们接受了后一种观点，即维度和解剖参数可以说明程序上的成功，但只有在很大程度上且几乎没有歧视，这是血管操作的生理后果，是性能的最强预测指标。在我们过去的资助工作的指导下，当前的提案研究了诱导的流动和药物分布模式是生物学对血管干预的近端驱动因素，并且可以更好地预测动物和现在的人类干预措施的治疗后果。在过去的周期中，我们创建了分析，免疫组织化学和成像技术，以表征动物系统血管干预后的修复和流动中断，以及一个定量框架，以预测LVDD的药物 - 运动型和 - 动力学。我们通过在更受控的动物模型，计算机模型和人类临床数据中使用这些资源来扩展这项工作。三个具体目的将：（1）定义复杂干预措施的传统描述的限制，无论多么精确，（2）在复杂动物模型中预测现实环境中近处理流动模式和药物分布的计算模型，并提供统计工具，并提供统计工具以确定这些力相对于单独的程序性变量，以及（3）是否在临床上确定了临床的统计学作用。创新存在于我们采用的工具，我们分析的数据，我们采用的方法，对合作遗产的统治研究人员的工作和组装的含义。 OCT成像量化了原位的生物学效应，以相同的方式提供了动物和人类的支架 - 老子几何形状的高分辨率图像。内部计算机算法提取程序几何形状，从而创建了生理流动破坏和药物分布的3D计算模型。 Maldi在局部分娩后证实了药物分布。动物实验使用定制的药物输送设备，以在体内定义复杂的介入程序中精确控制。访问大学医院广泛的OCT临床图像数据库提供了丰富的测试床，用于临床验证。统计学创新将准确描述支架特性，流量和药物分布素对数据具有多级，纵向和空间结构的环境中的生物学结果的影响。所学的经验教训可能会扩展我们对基本血管生物学，支架和其他组合装置，组织或病理状况的局部药物输送的理解。