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（NOT-TR-21-028）提交的。 骨关节炎（OA）是关节炎最常见的形式。许多药物在人类临床的各个阶段都失败了 由于临床前开发期间未发现的不良治疗结局或意外毒性而进行的试验， 提示用于开发疾病改善药物的可用模型的缺陷。体外模型不能完全 包括OA是“整个关节疾病”的概念。动物模型有其固有的缺陷， 与人类的生理/基因组差异。这种困境促使OA药物的范式转变 发展最近，在母基金（UG 3/UH 3 TR 002136）的支持下，我们的团队设计了一个 整合骨软骨、滑膜和脂肪类似物的体外微生理关节芯片（microJoint） 使用人类间充质干细胞（MSC）。通过在培养基中引入白细胞介素1 β（IL-1β）， 只为滑膜组织提供营养，“发炎的滑膜组织”引起的软骨退化已经被 在microJoint中成功建模。为了验证microJoint作为模型预测新型 在人类OA的治疗干预中，关键是要评估已证实有效的药物对 微关节中的OA。目前，我们已经测试了Nastrogen，Wnt途径抑制剂SM 04690和sclerostin， 成纤维细胞生长因子18，白细胞介素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剂3、Kartogenin， 环巴胺、辛伐他汀、罗格列酮和核因子（NF）-κB诱饵寡脱氧核苷酸。另外我们 将使用microJoint评估MSC衍生产品的治疗价值，包括MSC条件 培养基和/或MSC来源的外泌体。因此，我们期望产生大量的定量数据。 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管理的机制。 分析结果。因此，在这个新项目中，我们建议使用微生理学系统数据库 （MPS-Db）团队来存储和处理我们的药物测试数据。具体来说，我们会上传实时PCR 和Luminex分析数据从药物测试到MPS-Db。通过内置的工具，我们将能够快速 分析数据，并通过系统评估所有的药物测试来确定最佳的治疗候选者。 整个数据。所提出的工作对于验证microJoint在骨关节炎建模中的作用非常重要， microJoint在预测人类药物反应中的效用。研究中公开的数据使用 microJoint对研究传统OA模型的研究人员也很有价值，例如体外细胞 文化和动物模型。例如，微关节中识别的生物标志物将告知特定的 分子的研究重点放在使用传统模型进行的研究。最后，上传这些 提交给MPS-Db的研究数据也清楚地向利益相关者提供了有关分析、模型、细胞来源和反应的信息 从而加速microJoint的临床应用。

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.