Physiologically based pharmacokinetic modeling and analysis of nanoparticle delivery to tumors

项目摘要和摘要 纳米药物在实验室癌症的诊断和治疗中有很好的应用前景 动物，但将动物结果转化为临床成功的比例很低。目前对中国的理解 纳米粒(NP)药代动力学的种间外推及其理化性质的作用 NPS在细胞内的摄取、组织分布和向肿瘤组织的输送仍然有限。的目标是 这项建议是为了确定在肿瘤递送效率中的关键生理和/或物理化学因素 不同的NPs使用基于生理的药代动力学(PBPK)建模方法。假设是这样的 不同NPs的组织分布和肿瘤递送可以使用最近发表的PBPK模型来模拟 来自首席研究员实验室的健康小鼠、大鼠和人类的金纳米粒框架，通过添加 肿瘤隔间和使用物种和NP特定的参数。设计了两个特定的目标来测试 这一假设在无机和有机NPs(或其中任何一种)中是否都成立。目标1：确定 无机纳米粒肿瘤传递效率的关键物理化学、生理学和动力学速率决定因素。 目的2：确定肿瘤递送效率的关键物理化学、生理和动力学速率决定因素 有机NP。这种设计是必要的，因为有机NPs的模型结构可能不同于 由于合成方法、稳定性、生物兼容性、生物降解性和 其他物理化学因素。用于PBPK模型校准的实验数据来自最近发表的 肿瘤纳米药物储存库(CNR)，其中肿瘤递送效率使用时间- 浓度下的积分面积作为剂量度量。这个项目很新颖，因为创建了一个PBPK 带有肿瘤隔室的模型框架允许使用依赖于时间的剂量学来评估递送 对器官特异性肿瘤的有效率。PBPK模式评估将以世界卫生组织为基础 PBPK建模指南。将进行敏感性、不确定性和多元回归分析，以 全面鉴定纳米粒肿瘤传递效率的关键物理化学决定因素。这个 提出的研究具有重要意义，因为癌症纳米药物的低递送效率是一项重要的研究 这一问题在过去10年里一直是在该领域取得进展的一个关键障碍。该项目具有广阔的应用前景。 影响，因为一旦成功完成，它将极大地提高我们对关键决定因素的理解 这一结果将有助于设计具有更高的肿瘤递送效率的纳米粒以加速 癌症纳米药物的动物到人类外推和改进现有新药物的临床翻译 纳米技术。这项提议是高度跨学科的，涉及材料科学、癌症生物学、 药理学、毒理学和数学建模。我们最近出版的NP PBPK的可用性 模型框架和中国北车数据库使该方案具有很高的可行性，非常适合R03 程序。

PROJECT SUMMARY AND ABSTRACT Nanomedicines have found promising applications in the diagnostics and treatment of cancer in laboratory animals, but the translation of animal results to clinical success is low. The current understanding of the interspecies extrapolation of nanoparticle (NP) pharmacokinetics and the role of physicochemical properties of NPs in the cellular uptake, tissue distribution, and delivery to the tumor tissue remains limited. The objective of this proposal is to identify key physiological and/or physicochemical factors in the tumor delivery efficiency of different NPs using a physiologically based pharmacokinetic (PBPK) modeling approach. The hypothesis is that tissue distribution and tumor delivery of different NPs could be simulated using a recently published PBPK model framework for gold NPs in healthy mice, rats, and humans from the principal investigator’s laboratory by adding a tumor compartment and using species- and NP-specific parameters. Two specific aims were designed to test whether the hypothesis is true in both inorganic and organic NPs (or in either one of them). Aim 1: To identify key physicochemical, physiological, and kinetic rate determinants of tumor delivery efficiency of inorganic NPs. Aim 2: To identify key physicochemical, physiological, and kinetic rate determinants of tumor delivery efficiency of organic NP. This design is necessary because the model structure for organic NPs may be different from that of inorganic NPs due to the differences in synthesis methods, stability, biocompatibility, biodegradability, and other physicochemical factors. Experimental data for PBPK model calibration are from a recently published Cancer Nanomedicine Repository (CNR), in which tumor delivery efficiency was evaluated using the time- integrated area under the concentration as a dose metric. This project is novel because the creation of a PBPK model framework with a tumor compartment allows using a time-dependent dosimetry to evaluate delivery efficiency to organ-specific tumors. PBPK model evaluation will be based on the World Health Organization PBPK modeling guidelines. Sensitivity, uncertainty, and multivariate regression analyses will be conducted to comprehensively identify the key physicochemical determinants of tumor delivery efficiency of NPs. The proposed research is significant as the low delivery efficiency of cancer nanomedicines is an important research problem, which has been a critical barrier to advance in the field in the past 10 years. This project has broad impacts because, upon successful completion, it will greatly improve our understanding of the key determinants of tumor delivery of NPs and the results will help design NPs with improved tumor delivery efficiency to accelerate animal-to-human extrapolation of cancer nanomedicines and improve the clinical translation of new existing nanotechnologies. This proposal is highly interdisciplinary, involving materials science, cancer biology, pharmacology, toxicology, and mathematical modeling. The availability of our recently published NP PBPK model framework and the CNR database makes this proposal highly feasible and ideally suitable for the R03 program.