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

• 批准号: 10021681
• 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
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-20 至 2022-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10021681
• 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

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.

项目主任/首席调查员(最后、第一、中间)：马苏德，阿里夫 使用纳米载体的靶向药物输送是一个多方面的问题，其目的是实现 用最小的药物剂量达到最大的疗效。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一性。不确定性的来源既有 情感和认知，源于自然变异性、信息不确定性和建模 多个级别的近似。信息不确定性源于稀疏和不精确的数据 流体动力学效应和药物通过血流的传输，靶组织吸收药物的倾向 药物、临床测量和成像数据、处理误差和定性信息。型号 不确定性是由未知的模型参数、模型形式假设和解近似引起的 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以随机方法和相关的健壮性方法为基础 数值公式。然后可以使用这些模型来进行基于模拟的统计 分析建模参数的各种组合的影响，从而确定风险 明智的决策指导方针。 我们假设，药物载体的大小和形状在增加药物载体的数量方面起着重要作用 药物携带者到达目标、受伤的组织，进而到达可用于治疗的药物。一位数学家 将开发随机模型的框架和相关的计算机代码来模拟缺血 血管周围组织的血管损伤和随后的水肿，并优化药物载体的几何形状 最小的试验和错误。我们将通过验证所开发的数学模型来检验该假设 与药物载体在体外和体内双管齐下。我们将开发一个变分 耦合随机偏微分方程组和降维的随机给药框架 系统通过一种新颖的精细建模概念。数学框架将通过以下方式进行验证 药物载体向靶向组织转运的体外微流控和体内实验 急性肢体缺血模型的建立。活体小鼠模型将为发展 建立了数学模型，并对其进行了标定和验证。新的方法和计算机代码将是 用于优化药物载体对靶血管壁的黏附和跨内皮迁移， 考虑到最佳的颗粒大小和形状。这些研究将与提高质量直接相关 病人护理和健康。