An integrated computational and experimental approach to understanding the hemostatic response during treatment of bleeding

患有血友病或服用抗凝剂的人有出血的风险，但他们出血的地方不同。 了解这两种对止血系统的扰动是如何在不同的血管床上相互作用的 (VBS)将告知有关出血治疗的决定。出血是用止血剂治疗的，但 个体对这些药物的反应是高度不同的，这种差异背后的机制是 未知。止血是一个涉及复杂的凝血生化与血小板耦合的非线性过程 功能、VBS和包括血流在内的生物物理机制；它非常适合用集成的 计算和实验方法。这项研究的长期目标是发展数学 改善出血治疗的模型。总体目标是开发和验证数学 出血模型，将确定潜在的不同机制的止血前药物和 不同的电视节目。中心假设是全局敏感度分析(GSA)应用于机械论 出血的数学模型将阐明血小板、血管和 并预测经实验验证的止血反应。这一假设是基于 在申请者的实验室中使用这种方法产生的初步数据。其基本原理是 建议的定量方法和止血反应修饰剂的识别将结合在一起 为开发测试特定的和以前未识别的生物标志物的检测提供了基础。引导式 通过强大的初步数据，这一假设将在三个具体目标上得到检验：1)发展和完善 止血的数学模型，2)确定出血部位和出血之间的机制联系 原因，以及3)确定止血的修饰物，调节血友病A的止血前药物的反应。 目标1，现有模型将扩展到包括血小板和纤维蛋白动力学的基本特征和 用微流控分析进行了验证。在目标2中，将开发和纳入抗凝血剂的子模型 进入止血模型。将获得VB特性的实验测量结果。GSA将 确定止血反应中VB部位特异性变异的原因。在目标3中， 将开发止血前药物并将其纳入止血模型。GSA将确定以下原因 在治疗血友病A期间对它们的反应的变异性。该方法是创新的，因为(1) 将同时开发数学模型和实验分析，以迭代和优化信息 以及(2)抗凝剂和止血剂的新亚型将被添加到全面的 止血系统的模型，包括与凝血和流动相耦合的血小板、纤维蛋白和VB动力学。 这项拟议的研究具有重要意义，因为它有望(1)为场地- 血友病A中的特定出血和抗凝剂的使用，以及(2)提供基于机制的知识 有可能指导临床治疗出血的决定。

Individuals with hemophilia or taking anticoagulants are at risk for bleeding, but where they bleed is different. Understanding how these two types of perturbations to the hemostatic system interact in distinct vascular beds (VBs) will inform decisions about bleeding treatment. Bleeding is treated using prohemostatic agents, but individual responses to these agents are highly variable and the mechanisms underlying the variability are unknown. Hemostasis is a nonlinear process involving complex coagulation biochemistry coupled to platelet function, VBs, and biophysical mechanisms including blood flow; it is well suited for study with an integrated computational and experimental approach. The long-term goal of this research is to develop mathematical models that improve the treatment of bleeding. The overall objective is to develop and validate mathematical models of bleeding that will identify mechanisms underlying variable responses to prohemostatics and in different VBs. The central hypothesis is that global sensitivity analysis (GSA) applied to mechanistic mathematical models of bleeding will elucidate synergies and/or cooperation among platelet, vascular, and plasma components and predict experimentally-verified hemostatic responses. This hypothesis is based on preliminary data produced using exactly this approach in the applicants’ laboratories. The rationale is that the proposed quantitative methods and the identification of modifiers of the hemostatic response will together provide a foundation for developing assays that test for specific and previously unidentified biomarkers. Guided by strong preliminary data, this hypothesis will be tested in three specific aims: 1) Develop and refine mathematical models of hemostasis, 2) Determine the mechanistic link between bleeding site and bleeding cause, and 3) Identify modifiers of hemostasis that regulate responses to prohemostatics in hemophilia A. In Aim 1, existing models will be extended to include essential features of platelet and fibrin dynamics and validated with microfluidic assays. In Aim 2, submodels of anticoagulants will be developed and incorporated into the hemostasis models. Experimental measurements of VB characteristics will be acquired. GSA will identify the causes of VB site-specific variability in the hemostatic response. In Aim 3, submodels of prohemostatics will be developed and incorporated into the hemostasis models. GSA will identify the causes of variability in responses to them during treatment of hemophilia A. The approach is innovative because (1) the mathematical models and experimental assays will be developed in tandem to iteratively and optimally inform one another, and (2) novel submodels of anticoagulants and prohemostatics will be added to a comprehensive model of the hemostatic system that includes platelet, fibrin, and VB dynamics coupled to coagulation and flow. The proposed research is significant because it is expected to (1) provide mechanistic explanations for site- specific bleeding in hemophilia A and anticoagulant use, and (2) provide mechanism-based knowledge to potentially guide clinical decisions in the treatment of bleeding.