Capturing dynamic and inter-dependent biointerfaces in nanotechnology designs

在纳米技术设计中捕获动态且相互依赖的生物界面

• 批准号: 8323331
• 负责人: Jessie L.-S. Au
• 金额: $ 29.8万
• 依托单位: OPTIMUM THERAPEUTICS, LLC
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-09-01 至 2015-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8323331
• 关键词: Accounting; Address; Affect; Antibodies; Apoptosis; Binding; Biocompatible Materials; Biodiversity; Biological; Biosensor; Blood Circulation; Caliber; Cell Density; Cell Surface Receptors; Cell membrane; Cells; Characteristics; Charge; Computer Simulation; Convection; Data; Deposition; Development; Diagnostic; Diffusion; Dilatation - action; Dose; Drug Kinetics; Endocytosis; Equation; Equilibrium; Evaluation; Extravasation; Frequencies; Generations; Genes; Goals; Heart Neoplasms; Heterogeneity; Human; In Vitro; Individual; Injection of therapeutic agent; Kidney; Latex Bead; Laws; Ligand Binding; Ligands; Literature; Liver; Malignant Neoplasms; Measurement; Measures; Modeling; Modification; Nanotechnology; Nature; Outcome; Paclitaxel; Penetration; Performance; Perfusion; Pharmaceutical Preparations; Property; Proteins; RNA Interference; Research; Route; Simulate; Site; Solid Neoplasm; Spatial Distribution; Spleen; Surface; System; Therapeutic; Time; Treatment Protocols; Uncertainty; chemotherapy; density; design; in vivo; interstitial; intravenous injection; models and simulation; monolayer; nanoparticle; neoplastic cell; predictive modeling; research study; small molecule; tumor; vector

DESCRIPTION (provided by applicant): Nanoparticle systems (NP) can be used to deliver diagnostics and therapeutics including small and large molecules, gene vectors, and biosensor. As NP is versatile and can be made of different types of materials, and can have different sizes, surface charges, and surface modifications, there is the potential to tailor the design of NP for its intended function. Such goals can be greatly facilitated by quantitative models that predict the NP delivery to target sites and the biointerfaces (e.g., NP disposition and interactions with targets). In general, tumor properties, biological in nature, are dynamic and altered by a variety of variables and can produce diverse and at times unexpected effects on NP disposition. These situations in turn create uncertainties on the fate of NP at target sites and hence questions on the NP design. For example, how should one design NP in anticipation of intratumoral heterogeneity in the transport mechanisms (diffusion vs convection) in different parts of a tumor, or treatment-induced changes in tumor vasculature or properties? What are the margins of error if the NP design/selection does not take into account the diverse/dynamic tumor properties? Similarly, some NP properties by design will produce uncertain or opposite outcomes. For example, NP is frequently surface-modified with targeting ligands, but binding of ligands to cell surface receptors limits NP transport. What are the binding characteristics that would yield an optimal balance between tumor selectivity and tumor penetration? Pegylation increases circulation times but also decreases the endocytosis of NP. What is the range of % pegylation to enable optimal tumor targeting? We propose that the above and similar questions can be addressed by developing computation models that use relatively few in vitro and in vivo experimental data to describe the extravasation, interstitial deposition and transport, and internalization of NP in solid tumors as functions of NP/tumor properties and biointerfaces, and treatment schedules (dose intensity and frequency). We will take a balanced empirical-theoretical approach that uses our combined expertise in pharmacokinetics, drug/NP delivery, modeling, simulations, tumor heterogeneity, and in vitro and in vivo experimentations. The model parameters are either lab-generated, obtained from the literature, calculated using well-known equations, or, in the case of parameters that cannot be measured, by fitting the data to equations. Model performance is evaluated by conducting experiments and comparing the lab-generated data to the model-predicted data. We have developed first-generation models that successfully used in vitro data of drug/NP-cell-protein interactions in 2-D monolayers to predict the in vivo transport/delivery of a small molecule drug and NP to tumors. We further used these models, together with in vivo measurements of vessel density and diameter, to simulate the effect of chemotherapy, as well as the effects of intra-tumoral heterogeneity. This project is expected to contribute to NP design principles and accelerate the development of cancer nanotechnology.

描述（由申请人提供）：纳米颗粒系统（NP）可用于提供诊断和治疗，包括小分子和大分子、基因载体和生物传感器。由于 NP 用途广泛，可以由不同类型的材料制成，并且可以具有不同的尺寸、表面电荷和表面改性，因此有可能根据其预期功能定制 NP 的设计。通过预测 NP 递送至目标位点和生物界面（例如 NP 处置和与目标的相互作用）的定量模型可以极大地促进这些目标。 一般来说，肿瘤的生物学性质是动态的，会受到各种变量的影响，并且可以对 NP 处置产生不同的、有时是意想不到的影响。这些情况反过来又给 NP 在目标位点的命运带来了不确定性，从而对 NP 设计产生了疑问。例如，应该如何设计 NP 来预测肿瘤不同部位运输机制（扩散与对流）的瘤内异质性，或治疗引起的肿瘤脉管系统或特性的变化？如果 NP 设计/选择没有考虑到多样化/动态肿瘤特性，误差范围是多少？同样，某些 NP 属性的设计会产生不确定或相反的结果。例如，NP经常用靶向配体进行表面修饰，但配体与细胞表面受体的结合限制了NP的运输。哪些结合特征可以在肿瘤选择性和肿瘤渗透之间产生最佳平衡？聚乙二醇化增加了循环时间，但也减少了 NP 的内吞作用。能够实现最佳肿瘤靶向的聚乙二醇化百分比范围是多少？ 我们建议通过开发计算模型来解决上述和类似的问题，该模型使用相对较少的体外和体内实验数据来描述实体瘤中 NP 的外渗、间质沉积和运输以及内化，作为 NP/肿瘤特性的函数和生物界面以及治疗方案（剂量强度和频率）。我们将采取平衡的经验理论方法，利用我们在药代动力学、药物/纳米粒子递送、建模、模拟、肿瘤异质性以及体外和体内实验方面的综合专业知识。模型参数可以是实验室生成的、从文献中获得的、使用众所周知的方程计算的，或者在参数无法测量的情况下，通过将数据拟合到方程中来计算的。通过进行实验并将实验室生成的数据与模型预测的数据进行比较来评估模型性能。我们开发了第一代模型，成功地利用二维单层中药物/NP-细胞-蛋白质相互作用的体外数据来预测小分子药物和 NP 向肿瘤的体内转运/递送。我们进一步使用这些模型以及血管密度和直径的体内测量来模拟化疗的效果以及肿瘤内异质性的影响。该项目预计将为纳米粒子设计原理做出贡献，并加速癌症纳米技术的发展。