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.

计划总监/首席研究员（最后，第一，中间）：Masud，Arif 使用纳米大小载体的有针对性药物输送是一个多方面的问题，旨在实现最低剂量的药物最大疗效。这个问题在生物系统中变得更加复杂由于它们固有的不确定性和时空不均匀性。不确定性的来源都是源自自然变异性，信息不确定性和建模多个级别的近似值。信息不确定性来自稀疏和不精确的数据流体动力效应和通过血流传输的药物，靶向组织的倾向以吸收药物，临床测量和成像数据，处理错误和定性信息。模型由于未知模型参数，模型形式假设和解决方案近似而产生不确定性错误。与通常在工程系统中使用的确定性分析不同，建模和分析生物系统的方法需要以随机方法和相关的鲁棒为基础数值公式。然后可以使用这些模型进行基于模拟的统计分析建模参数的各种组合的影响，从而建立风险知情的决策指南。我们假设药物携带者的大小和形状在增加数量吸毒者到达有针对性的，受伤的组织，进而可用于治疗的药物。数学将开发用于随机模型和相关计算机代码的框架以模拟缺血性血管损伤和随后的血管周组织水肿，并优化药物载体的几何形状最小的试验和错误。我们将通过验证开发的数学模型来检查假设在体外和体内使用药物载体，采用两种良好的方法。我们将开发一个变种用于耦合随机PDE的框架用于药物输送并降低随机性的尺寸通过新颖的精细建模概念进行系统。数学框架将通过使用体外微流体和体内小鼠将药物载体转运到靶向组织的实验急性肢体缺血的模型。体内鼠标模型将生成数据以开发数学模型及其校准和验证。新方法和计算机代码将是用于优化药物载体到靶血管壁的粘附和跨内皮迁移，考虑最佳的粒径和形状。这些研究将与提高质量直接相关患者护理和健康。