Drug Retention and Tumor Distribution of Polymeric Micelles for Cancer Therapy

用于癌症治疗的聚合物胶束的药物保留和肿瘤分布

基本信息

批准号：
10674967
负责人：
Jacob Daggett Ramsey
金额：
$ 3.92万
依托单位：
UNIV OF NORTH CAROLINA CHAPEL HILL
依托单位国家：
美国
项目类别：
财政年份：
2022
资助国家：
美国
起止时间：
2022-08-01 至 2024-07-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10674967
关键词：
Accounting Affect Animal Cancer Model Animal Model Behavior Binding Binding Proteins Biological Assay Breast Cancer Model Cancer Vaccines Circulation Clinic Clinical Clinical Trials Combined Modality Therapy Data Dialysis procedure Dose Drug Combinations Drug Delivery Systems Drug Exposure Drug Formulations Drug Interactions Drug Kinetics Drug Targeting Encapsulated Ensure Equilibrium European Exposure to Formulation Future Goals Homeostasis Human Immunotherapy In Vitro Individual International Liver Malignant Neoplasms Measurable Measurement Measures Medicine Micelles Modeling Nucleic Acids Pharmaceutical Preparations Phase Plasma Play Polymers Postdoctoral Fellow Proteins Proxy Research Role Serum Serum Proteins System Technology Therapeutic Thermodynamics Toxic effect Training Translating Translations Treatment Efficacy Tumor Tissue United States Food and Drug Administration Vaccines Warfarin Weight Work cancer therapy career chemotherapy copolymer delivery vehicle drug disposition drug distribution drug metabolism experience hydrophilicity improved in vitro Assay in vivo lipid nanoparticle molecular dynamics mouse model nanomedicine nanoparticle next generation nonhuman primate novel nucleic acid delivery pharmacokinetic model pre-clinical preclinical study protein complex rational design small molecule success therapy outcome triple-negative invasive breast carcinoma tumor tumor microenvironment

项目摘要

Abstract/Project Summary Polymeric micelles are powerful drug delivery vehicles with a promising future. There are currently no US Food and Drug Administration approved polymeric micelle formulations, but some have been approved by the European Medicines Agency and other international regulatory bodies. Traditional pharmacokinetic analysis focuses on two drug fractions-unbound free drug and drug which is bound to serum proteins. However, the inclusion of nanoparticles complicates pharmacokinetic analysis by introducing a third drug fraction which is nanomedicine encapsulated. Encapsulation into polymeric micelles alters drug partitioning to serum proteins. Polymeric micelles can preferentially accumulate into tumor tissues, improving tumor drug exposure. Little is known about how polymer-drug interactions influence drug partitioning between polymeric micelles and serum proteins. My preliminary data shows that we have developed an in vitro assay to measure micelle-protein partitioning which recapitulates known in vivo behavior, like the high protein binding of the drug warfarin. For the F99 phase of my proposal, I hypothesize that the in vitro partitioning of drug is related to polymer-drug interactions which we observe by NMR, micro-DSC, and molecular dynamics. In particular, we have shown that drug interaction with parts of the polymeric micelle hydrophilic corona leads to improved drug loading, and may lead to stronger retention in the polymeric micelles. In Aim 1.1, I propose to study how these measured polymer- drug interactions affect drug partitioning in a validated in vitro assay. This in vitro drug partitioning could correlate to tumor-drug exposure in vivo in a mouse model of triple negative breast cancer. In Aim 1.2, I hypothesize that improved micelle drug retention, as measured in vitro, will improve the distribution of drug to the tumor in vivo as measured by AUC and Cmax. Understanding how polymer-drug interactions influence partitioning and tumor exposure will lead to reduced preclinical studies and improved therapeutic outcomes. We will be able to select optimal formulations by applying in vitro partitioning results to pharmacokinetic modeling to predict tumor drug exposure. In Aim 1.3, we will analyze drug fractions in non-human primates to determine if drug partitioning is recapitulated in more human-like species. Altogether, the proposed F99 phase work will improve our understanding of polymeric micelle formulations and how drug retention affects tumor exposure and therapeutic efficacy. In the K00 phase, I propose to focus on polymer-nucleic acid and polymer-protein complexes for cancer therapeutics and vaccines. Utilizing the same principles from the F99 phase, polymer-cargo interactions can be used to inform targeted drug delivery of these different cargoes. My dissertation project and future postdoctoral work will provide the necessary training experience to prepare me for an independent research career focused on cancer therapeutics.

摘要/项目摘要聚合物胶束是强大的药物输送载体，具有广阔的前景。目前没有美国食品和药物管理局批准了聚合物胶束制剂，但有些已经获得了欧洲药品管理局和其他国际监管机构。传统药代动力学分析重点关注两种药物成分——未结合的游离药物和与血清蛋白结合的药物。然而，纳米粒子的引入使药代动力学分析变得复杂，因为引入了第三种药物成分，即纳米药物封装。封装到聚合物胶束中会改变药物与血清蛋白的分配。聚合物胶束可以优先积聚到肿瘤组织中，改善肿瘤药物的暴露。小的是了解聚合物-药物相互作用如何影响聚合物胶束和血清之间的药物分配蛋白质。我的初步数据表明我们已经开发出一种体外测定法来测量胶束蛋白分区概括了已知的体内行为，例如药物华法林的高蛋白结合。对于我的提案的F99阶段，我假设药物的体外分配与聚合物药物有关我们通过 NMR、微型 DSC 和分子动力学观察到的相互作用。特别是，我们已经证明药物与聚合物胶束亲水冠部分的相互作用导致药物负载量的改善，并且可能导致聚合物胶束中的保留更强。在目标 1.1 中，我建议研究如何测量这些聚合物- 药物相互作用会影响经过验证的体外测定中的药物分配。这种体外药物分配可能与三阴性乳腺癌小鼠模型体内肿瘤药物暴露的影响。在目标 1.2 中，我假设体外测量的胶束药物保留的改善将改善药物在体内的肿瘤分布，如下所示通过 AUC 和 Cmax 测量。了解聚合物-药物相互作用如何影响分配和肿瘤暴露将导致临床前研究减少并改善治疗结果。我们将能够选择通过将体外分配结果应用于药代动力学模型来预测肿瘤药物来优化配方接触。在目标 1.3 中，我们将分析非人类灵长类动物的药物组分，以确定药物分配是否合理。重演为更像人类的物种。总而言之，拟议的 F99 阶段工作将改善我们的了解聚合物胶束配方以及药物保留如何影响肿瘤暴露和治疗功效。在K00阶段，我建议重点关注用于癌症的聚合物核酸和聚合物蛋白质复合物疗法和疫苗。利用与 F99 相相同的原理，聚合物-货物相互作用可以用于通知这些不同货物的靶向药物输送。我的论文项目和未来的博士后工作将为我提供必要的培训经验，为我的独立研究职业做好准备关于癌症治疗。

项目成果

期刊论文数量（1）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Development of a sorafenib-loaded solid self-nanoemulsifying drug delivery system: Formulation optimization and characterization of enhanced properties.

索拉非尼负载固体自纳米乳化药物递送系统的开发：配方优化和增强特性的表征。

DOI：
10.1016/j.jddst.2023.104374
发表时间：
2023-04-01
期刊：
Journal of drug delivery science and technology
影响因子：
5
作者：
Chaemin Lim;Dayoon Lee;Mikyung Kim;Su;Yuseon Shin;Jacob D. Ramsey;Han‐Gon Choi;Eun;Y. Youn;K. Oh
通讯作者：
K. Oh