Depositing Data Generated from Drug Test on microJoint Model into the Microphysiology Systems Database

摘要 本申请是根据PA-20-272(非-TR-21-028)提交的。 骨关节炎(OA)是最常见的关节炎形式。许多药物在人类临床的不同阶段都失败了 由于治疗结果不佳或在临床前开发期间未确定的意外毒性而进行的试验， 这表明现有的疾病修正药物开发模式存在缺陷。体外模型并不完全 包含这样一个概念，即骨性关节炎是一种“全关节疾病”。动物模型存在先天缺陷，因为 与人类的生理/基因组差异。这一困境促使了骨性关节炎药物的范式转变 发展。最近，在家长资助(UG3/UH3TR002136)的支持下，我们团队设计了一个 集成骨软骨、滑膜和脂肪类似物的体外微生理关节芯片(微关节) 使用人骨髓间充质干细胞(MSCs)。通过将白细胞介素1β(IL-1β)引入培养液中 仅供滑膜组织使用，“炎症的滑膜组织”导致的软骨退化 已在微关节中成功建模。微关节作为预测新药疗效的模型验证 对人类骨性关节炎的治疗干预，关键是评估已证实有效的药物对 微关节中的骨性关节炎。目前，我们已经测试了萘普生、Wnt途径抑制剂SM04690和硬化素， 成纤维细胞生长因子18，白介素1受体拮抗剂。我们将继续测试其他拟议的药物， 包括骨形态发生蛋白7、降钙素、金属蛋白酶组织抑制因子3、卡托根素、 环丙胺、辛伐他汀、罗格列酮和核因子(NF)-κB诱骗寡核苷酸。此外，我们 将使用MicroJoint来评估MSC衍生产品的治疗价值，包括MSC条件 中等，和/或由MSC衍生的外切体。因此，我们预计将产生大量的量化数据。 目前，我们使用Microsoft Excel来处理所有数据，这缺乏一种自主组织和 分析结果。因此，在这个新项目中，我们建议与微生理学系统数据库合作 (MPS-DB)团队存储和处理我们的药物测试数据。具体地说，我们将上传实时PCR 以及来自药物测试的Luminex化验数据输入MPS-DB。通过内置工具，我们将能够快速 通过对所有患者进行系统评估，分析数据并从药物测试中确定最佳治疗方案 将数据作为一个整体。所提出的工作对于验证微关节在骨关节炎模型中的有效性和 微关节在预测人类药物反应中的作用。这项研究的公开数据使用 微关节对研究传统的骨性关节炎模型，如体外细胞的研究也是有价值的 文化和动物模型。例如，在微关节中识别的生物标记物将通知特定的 将重点放在使用传统模型进行的研究上。最后，上传这些 MPS-DB的研究数据还清楚地告知利益相关者有关分析、模型、细胞来源和响应的信息 向化合物转化，加速微关节转化为临床应用。

ABSTRACTS This application is being submitted in response to PA-20-272 (NOT-TR-21-028). Osteoarthritis (OA) is the most prevalent form of arthritis. Many drugs fail at various stages of human clinical trials due to poor treatment outcomes or unexpected toxicity that were not identified during preclinical development, suggesting deficiencies of available models for developing disease-modifying drugs. In vitro models do not fully encompass the concept that OA is a “whole joint disease”. Animal models have inherent deficiencies because of physiological/genomic differences with humans. This predicament has prompted a paradigm shift in OA drug development. Recently, with the support from the parent grant (UG3/UH3TR002136), our team has engineered an in vitro microphysiological joint chip(microJoint) that integrates the osteochondral, synovial, and adipose analogs using human mesenchymal stem cells (MSCs). Through introducing the interleukin 1 beta (IL-1β) into the medium that feeds the synovium tissue only, "inflamed synovial tissue"-induced cartilage degradation has been successfully modeled in the microJoint. To validate the microJoint as a model to predict the efficacy of novel therapeutic interventions in OA in humans, it is critical to assess the impact of agents with proven efficacy for OA in the microJoint. Currently, we have tested Naproxen, Wnt pathway inhibitors SM04690 and sclerostin, fibroblast growth factor 18, interleukin-1 receptor antagonist. We will continue to test other proposed drugs, including Bone morphogenetic protein 7, calcitonin, Tissue inhibitor of metalloproteinase 3, Kartogenin, cyclopamine, simvastatin, rosiglitazone, and nuclear factor (NF)-κB decoy oligodeoxynucleotide. In addition, we will use the microJoint to assess the therapeutic value of MSC-derived products, including the MSC-conditioned medium, and/or MSC-derived exosomes. Therefore, we expect to generate copious amounts of quantitative data. Currently, we use Microsoft Excel to process all data, which lacks a mechanism to autonomously organize and analyze the results. In this new project, we thus propose to work with the Microphysiology Systems Database (MPS-Db) team to store and process our data from the drug tests. Specifically, we will upload the real-time PCR and Luminex assay data from drug tests into the MPS-Db. Through the built-in tool, we will be able to quickly analyze the data and determine the best treatment candidate from the drug tests by systemically assessing all the data as a whole. The proposed work is important to validating the microJoint in modeling osteoarthritis and the utility of microJoint in predicting drug responses in humans. The publicly accessible data from the study using the microJoint will also be valuable to researchers working on the traditional OA models, such as in vitro cell culture and animal models. For example, the biomarkers identified in the microJoint will inform the specific molecules to focus on the studies conducted in studies using traditional models. Lastly, the uploading of these research data to the MPS-Db also clearly informs stakeholders on assays, models, cell sources, and responses to compounds, accelerating the translation of the microJoint into clinical application.