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Stochastic Modeling of Tissue Injury, Edema and Targeted Drug Delivery

组织损伤、水肿和靶向药物输送的随机模型

基本信息

批准号：
10252849
负责人：
ARIF MASUD
金额：
$ 19万
依托单位：
UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN
依托单位国家：
美国
项目类别：
财政年份：
2019
资助国家：
美国
起止时间：
2019-09-20 至 2024-05-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10252849
关键词：
Accounting Acute Adhesions Arteries Biocompatible Materials Biological Availability Biology Blood Vessels Blood flow Calibration Clinical Collaborations Coupled Coupling Data Development Diffuse Dimensions Dose Drug Carriers Drug Delivery Systems Drug Experimentation Drug Targeting Drug Transport Edema Engineering Ensure Equation Formulation Geometry Goals Guidelines Health Image In Vitro Interphase Kinetics Laboratories Lead Mathematical Biology Mathematics Measurement Medicine Methods Microfluidics Modeling Movement Nature Navier-Stokes equations Outcomes Research Particle Size Patient Care Pharmaceutical Preparations Play Principal Investigator Property Risk Role Shapes Source Statistical Data Interpretation Stochastic Processes System Technology Tissue Model Tissues Training Activity Uncertainty Validation Variant base biological systems computer code design drug efficacy experimental study improved in vitro testing in vivo injured innovation limb ischemia mathematical model migration mouse model nanosized next generation novel particle programs simulation spatiotemporal stem success targeted delivery tissue injury vascular injury viscoelasticity

项目摘要

Program Director/Principal Investigator (Last, First, Middle): Masud, Arif Targeted drug delivery using a nano-sized carrier is a multi-faceted problem that aims at achieving maximum efficacy with minimum dose of medicine. This problem gets compounded in biological systems due to their inherent uncertainty and spatiotemporal inhomogeneity. The sources of uncertainty are both aleatory and epistemic, stemming from natural variability, information uncertainty, and modeling approximations at multiple levels. Information uncertainty arises from sparse and imprecise data on hydrodynamic effects and drug transport via blood flow, propensity of the targeted tissue to absorb the drug, clinical measurement and imaging data .,processing errors, and qualitative information. Model uncertainty arises due to unknown model parameters, model form assumptions, and solution approximation errors. Unlike deterministic analysis typically employed in engineered systems, modeling and analysis methods for biological systems need to be grounded in stochastic methods and associated robust numerical formulations. These models can then be employed to carry out simulation-based statistical analysis of the effect of the various combinations of the modeled parameters thereby establishing risk informed decision guidelines. We hypothesize that size and shape of drug carriers play a significant role in increasing the number of drug carriers reaching targeted, injured tissue and, in turn, drugs available for treatments. A mathematical framework for stochastic models and associated computer code will be developed to simulate an ischemic vascular injury and subsequent edema in perivascular tissue and optimize geometry of drug carriers with minimal trials-and-error. We will examine the hypothesis by validating the developed mathematical model with drug carriers both in vitro and in vivo with a two-pronged approach. We will develop a variational framework for coupling stochastic PDEs for drug delivery and reduce dimensionality of the stochastic system via a novel fine-scale modeling concept. The mathematical framework will be validated via experimentation of drug carrier transport to targeted tissue using in vitro microfluidic and in vivo mouse models of the acute limb ischemia. The in vivo mouse model will generate data for the development of the mathematical model and for its calibration and validation. The new method and the computer codes will be applied to optimize adhesion and transendothelial migration of drug carriers to a target vascular wall, accounting for optimal particle size and shape. These studies will be of direct relevance to improving quality of patient care and health.

项目负责人/主要研究者（最后，第一，中间）：Masud，Arif 使用纳米尺寸载体的靶向药物递送是一个多方面的问题，其旨在实现以最小的药物剂量获得最大的疗效。这个问题在生物系统中变得更加复杂由于其固有的不确定性和时空不均匀性。不确定性的来源有两个偶然性和认识性，源于自然变异性、信息不确定性和建模多层次的近似。信息的不确定性来自以下方面的稀疏和不精确的数据：流体动力学效应和通过血流的药物运输，靶组织吸收药物的倾向，药物、临床测量和成像数据。处理错误和定性信息。模型由于模型参数、模型形式假设和解的近似未知，会产生不确定性错误.与工程系统中通常采用的确定性分析不同，建模和分析生物系统的方法需要建立在随机方法和相关的鲁棒性基础上。数值公式然后，这些模型可以用于进行基于模拟的统计分析。分析建模参数的各种组合的影响，从而确定风险知情决策指南。我们推测，药物载体的大小和形状在增加细胞数量方面起着重要作用。药物载体到达靶向的、受损的组织，并且反过来，药物可用于治疗。数学随机模型的框架和相关的计算机代码将被开发，以模拟缺血性血管损伤和随后的血管周围组织水肿，并优化药物载体的几何形状，最少的试错我们将通过验证开发的数学模型来检验假设与药物载体在体外和体内双管齐下的方法。我们将开发一种变分的用于药物递送的耦合随机偏微分方程的框架和降低随机偏微分方程的维数系统通过一个新的精细尺度建模的概念。数学框架将通过以下方式进行验证：使用体外微流体和体内小鼠的药物载体转运到靶组织的实验急性肢体缺血模型。体内小鼠模型将产生用于开发数学模型及其校准和验证。新的方法和计算机代码将是应用于优化药物载体对靶血管壁的粘附和跨内皮迁移，考虑到最佳的颗粒尺寸和形状。这些研究将与提高质量直接相关病人的护理和健康。