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Vascular Drug Delivery - Supplement for Equipment

Vascular Drug Delivery - Supplement for Equipment
血管给药-设备补充
批准号:
9025113
负责人:
Elazer R Edelman
金额:
$11.05万
依托单位国家:
美国
项目类别:
财政年份:
1994
资助国家:
美国
项目状态:
已结题
起止时间:
1994-08-01 至 2016-09-14

项目摘要

项目成果

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中文摘要
翻译
描述(由申请人提供):血管内机械干预和局部血管药物输送(LVDD)影响血管愈合,但在不同患者之间存在差异。器械的设计、配方和部署影响但不能严格预测临床反应。由此产生了两个影响。首先,修复生物学本质上是可变的,临床结果永远无法预测。第二,反应变异性可以分类,但取决于更接近的生理力量,如果确定,可以更好地定义手术成功和预测不良事件。我们接受后一种观点,即尺寸和解剖参数可以说明手术的成功,但只有在大范围内,几乎没有歧视,血管操作的生理后果是表现的最强预测因素。在我们过去资助的工作的指导下,目前的提案检验了诱导的血流模式和药物分布是血管干预生物反应的近似驱动因素的假设,并且可以更好地预测干预在动物和现在在人类中的治疗结果。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来表征动物系统血管干预后的修复和血流中断,并建立了定量框架来预测LVDD的药物动力学和动力学。我们通过将这些资源应用于更受控制的动物模型、计算机模型和人类临床数据来扩展这项工作。三个具体目标将:(1)定义复杂干预的传统描述符的局限性,无论其多么精确;(2)在复杂的动物模型中开发和验证预测现实环境中近壁流动模式和药物分布的计算模型,并提供统计工具来确定这些力相对于程序变量的预测作用;(3)调查所确定的变量是否能预测人类的临床结果。创新存在于我们使用的工具,我们分析的数据,我们采取的方法,工作的含义以及具有合作传统的跨学科研究小组的集合中。OCT成像量化原位生物效应,以相同的方式提供动物和人类支架血管几何形状的高分辨率图像。内部计算机算法提取程序几何图形,创建生理流动中断和药物分布的三维计算模型。MALDI证实了当地交付后的药物分配。动物实验使用定制的药物输送装置,以便在体内精确控制复杂的介入程序。访问大学医院广泛的临床图像OCT数据库为临床验证提供了丰富的测试平台。在数据具有多层次、纵向和空间结构的情况下,统计创新将准确地描述支架特性、流量和药物分布对生物学结果的影响。这些经验教训可以扩展我们对基本血管生物学、支架和其他组合装置、组织或病理条件的局部药物输送的理解。
英文摘要
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.
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