Development of an integrated 4-organ animal model

综合四器官动物模型的开发

基本信息

  • 批准号:
    9986123
  • 负责人:
  • 金额:
    $ 74.47万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2018
  • 资助国家:
    美国
  • 起止时间:
    2018-09-17 至 2021-08-31
  • 项目状态:
    已结题

项目摘要

Project Summary/Abstract We propose to construct multi organ microphysiological systems (“Body-on-a-Chip” or BoaCs) from human and rat cells to use as a basis to understand species differences in response to exposure to drugs or chemicals in this new platform. The results will then be compared to clinical data, where available, and to archived in vivo animal data. This work will directly test whether such in vitro models can accurately reproduce species differences in response to known drugs. A preclinical model based on human cells that can accurately predict human response should lead to better decisions on whether exposure to a chemical or chemical mixture will be harmful to humans. An advantage of this in vitro approach, compared to standard in vitro systems (e.g. such as multiwell plates), is that the tissues can exchange metabolites and the dose dynamics in the body of both parental compounds and metabolites are better represented than when a single cell type is exposed to a bolus dose. Also, by comparing acute to chronic effects it will enable prediction on clinical trial success as well for determining PK of the compounds. In addition, the comparison of animal cells derived from iPSCs will enable the assessment of whether they can be substituted for primary animal cells. If successful, this could lead to stable cell sources for the animal models and reduce the number of animals needed for these studies. For this proposal we will build upon a four-organ model we recently published in Nature Scientific Reports (Oleaga, et al. 2016) which included model tissues for the liver, cardiac, skeletal muscle, and neuronal compartments that correctly predicted clinical response to five compounds. To construct a well defined system we will use a common serum free medium which mimics key features of blood. Hickman has developed microelectrode arrays and cantilever systems that are integrated on chip that allow for noninvasive electronic and mechanical readouts for not only acute but also chronic tests as well. To improve operability and enable a low volume system for eventual metabolite evaluation, we will use a pumpless system (Sung, et al. 210) and self contained devices. We will also utilize microfluidic analytical components for rapid and sensitive biomarker assessment. However, the number of biomarkers to be monitored for cell health and function will be greatly reduced in our systems from use of the function readouts. The system will be modeled by simulation using CFD to establish acceptable ranges for consumption of nutrients and drug metabolism as well as shear stress and to predict drug concentration profiles in the system to also enable PK/PD prediction capabilities. We believe that this technique will lead to more accurate and cost-effective assessment of the efficacy and toxicological potential of drugs chemicals or chemical mixtures and this approach will have a major impact on improving human health.
项目总结/摘要 我们提出了构建人体多器官微生理系统(Body-on-a-Chip,BoaCs)的设想 和大鼠细胞作为基础,以了解物种对药物或化学品暴露的反应差异 在这个新平台上。然后将结果与可用的临床数据以及体内存档的数据进行比较 动物数据。这项工作将直接测试这样的体外模型是否能够准确地繁殖物种 对已知药物的反应差异。基于人类细胞的临床前模型,可以准确预测 人类的反应应导致更好地决定是否接触化学品或化学混合物, 对人类有害。与标准体外系统(例如, 多孔板),是组织可以交换代谢物和剂量动力学在体内的父母双方 化合物和代谢物比当单一细胞类型暴露于推注剂量时更好地表现。 此外,通过比较急性和慢性效应,它将能够预测临床试验的成功,以及确定 化合物的PK。此外,比较来源于iPSC的动物细胞将使评估成为可能。 它们是否可以替代原代动物细胞。如果成功,这可能会导致稳定的细胞来源 用于动物模型,并减少这些研究所需的动物数量。 对于这个提议,我们将建立在我们最近发表在《自然科学报告》上的四器官模型上。 (Oleaga等人,2016),其中包括肝脏、心脏、骨骼肌和神经元的模型组织 正确预测了对五种化合物的临床反应。构建一个明确的系统 我们将使用模拟血液关键特征的普通无血清培养基。希克曼开发了 微电极阵列和悬臂梁系统集成在芯片上, 以及机械读数,不仅适用于急性测试,也适用于慢性测试。为了提高可操作性, 对于最终的代谢物评价,我们将使用无泵系统(Sung等人,210)和自 包含的设备。 我们还将利用微流体分析组件进行快速和灵敏的生物标志物评估。 然而,在我们的研究中,要监测细胞健康和功能的生物标志物的数量将大大减少。 系统使用功能读数。该系统将通过使用CFD的模拟来建模,以建立 可接受的范围内的消耗的营养素和药物代谢以及剪切应力和预测药物 在系统中的浓度曲线,也使PK/PD预测能力。我们相信这种技术 将导致对药物的功效和毒理学潜力进行更准确和更具成本效益的评估 这种方法将对改善人类健康产生重大影响。

项目成果

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James J Hickman其他文献

James J Hickman的其他文献

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{{ truncateString('James J Hickman', 18)}}的其他基金

Investigating the role of Alzheimer's disease familial mutations in neuromuscular physiology
研究阿尔茨海默病家族突变在神经肌肉生理学中的作用
  • 批准号:
    10448570
  • 财政年份:
    2022
  • 资助金额:
    $ 74.47万
  • 项目类别:
Investigating the role of Alzheimer's disease familial mutations in neuromuscular physiology
研究阿尔茨海默病家族突变在神经肌肉生理学中的作用
  • 批准号:
    10620712
  • 财政年份:
    2022
  • 资助金额:
    $ 74.47万
  • 项目类别:
Modulatory Role of Blood-Brain-Barrier and Enzymatic Activity in an Innovative Human Model of Cholinergic Drug Induced Dementia
血脑屏障和酶活性在胆碱能药物诱发痴呆的创新人类模型中的调节作用
  • 批准号:
    10258975
  • 财政年份:
    2021
  • 资助金额:
    $ 74.47万
  • 项目类别:
Hesperos Diversity Supplement forgrant number 1 R44AG071386
Hesperos 多样性补充补助金编号 1 R44AG071386
  • 批准号:
    10577655
  • 财政年份:
    2021
  • 资助金额:
    $ 74.47万
  • 项目类别:
Populating MPS database with data from multi-organ, human-on-a-chip microphysiological systems
用来自多器官、人体芯片微生理系统的数据填充 MPS 数据库
  • 批准号:
    10435269
  • 财政年份:
    2021
  • 资助金额:
    $ 74.47万
  • 项目类别:
Modulatory Role of Blood-Brain-Barrier and Enzymatic Activity in an Innovative Human Model of Cholinergic Drug Induced Dementia
血脑屏障和酶活性在胆碱能药物诱发痴呆的创新人类模型中的调节作用
  • 批准号:
    10467040
  • 财政年份:
    2021
  • 资助金额:
    $ 74.47万
  • 项目类别:
Multi-organ human-on-a-chip system to address overdose and acute and chronic efficacy and off-target toxicity
多器官人体芯片系统解决用药过量、急慢性疗效和脱靶毒性问题
  • 批准号:
    10351973
  • 财政年份:
    2019
  • 资助金额:
    $ 74.47万
  • 项目类别:
Drug-drug interactions for antivirals with opioids and Narcan in a 5- organ human-on-a-chip model
抗病毒药物与阿片类药物和纳洛酮在 5 器官芯片模型中的药物相互作用
  • 批准号:
    10224388
  • 财政年份:
    2019
  • 资助金额:
    $ 74.47万
  • 项目类别:
Human on a chip systems to investigate disease comorbidities common in the aged population
人类芯片系统研究老年人群中常见的疾病合并症
  • 批准号:
    10402384
  • 财政年份:
    2018
  • 资助金额:
    $ 74.47万
  • 项目类别:
Human on a chip system to investigate genetic risk factors in Alzheimer's disease
人类芯片系统研究阿尔茨海默病的遗传风险因素
  • 批准号:
    9628532
  • 财政年份:
    2018
  • 资助金额:
    $ 74.47万
  • 项目类别:

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