Development of an integrated 4-organ animal model
Development of an integrated 4-organ animal model
批准号:
9986123
负责人:
James J Hickman
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
项目状态:
已结题
起止时间:
2018-09-17 至 2021-08-31
关键词:
AcuteAdultAnimal ModelAnimal OrganAnimal SourcesAnimalsArchivesBiological MarkersBloodBolus InfusionCardiacCell Culture TechniquesCellsChemicalsChronicClinical DataClinical TrialsConsumptionDevelopmentDevicesDoseDrug CompoundingDrug KineticsDrug or ChemicalEvaluationExposure toFemaleGoalsHealthHourHumanIn VitroLaboratoriesLeadLiquid substanceLiteratureLiverMeasurementMechanicsMetabolicMicroelectrodesMicrofluidicsModelingMonitorMuscleMyocardiumNatureNeonatalNeuraxisNeuronsOrganOrgan ModelPharmaceutical PreparationsPharmacodynamicsPhasePhenotypePhysiologicalPre-Clinical ModelPublishingRattusReportingSerumSkeletal MuscleSystemSystems DevelopmentTechniquesTestingTissue ModelTissuesToxicologyWorkanimal databasebody on a chipbody systemcantilevercell typeclinical predictorscost effectivedrug metabolismexperienceexperimental studyimprovedin vitro Modelin vivoinduced pluripotent stem cellinnovationinterestliver metabolismmalemicrophysiology systemmodels and simulationnon-invasive monitornutrient metabolismorgan on a chippharmacokinetics and pharmacodynamicsresponseshear stressskillsspecies differencesuccess
中文摘要
项目摘要/摘要
我们建议从人类出发构建多器官微生理系统(BoACs)
和大鼠细胞,作为了解暴露在药物或化学品中的物种差异的基础
在这个新的平台上。然后将结果与临床数据进行比较,如果有的话,并与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种体外模型是否能准确地复制物种
对已知药物的反应不同。一种基于人类细胞的临床前模型,可以准确预测
人类的反应应该导致更好的决定,无论是接触化学物质还是化学混合物
对人类有害。与标准的体外系统(例如
多孔板),是组织可以交换代谢物和体内的剂量动力学两者
化合物和代谢物比单一细胞类型暴露于团注剂量时表现得更好。
此外,通过比较急性和慢性影响,它将能够预测临床试验的成功,以及确定
化合物的pK。此外,对来自IPSCs的动物细胞的比较将使评估成为可能
它们是否可以替代原始的动物细胞。如果成功,这可能会带来稳定的细胞来源
用于动物模型,减少这些研究所需的动物数量。
对于这项提议,我们将建立在最近发表在《自然科学报告》上的四器官模型的基础上
(Oleaga等人)2016),其中包括肝脏、心脏、骨骼肌和神经元的模型组织
正确预测对五种化合物的临床反应的隔室。构建一个定义明确的系统
我们将使用一种常见的无血清培养基来模拟血液的主要特征。希克曼已经开发出
集成在芯片上的微电极阵列和悬臂系统,允许非侵入性电子
以及机械读数,不仅适用于急性测试,也适用于慢性测试。要提高可操作性并启用
对于最终的代谢物评估,我们将使用无泵系统(Sung,et al.210)和自我
包含的设备。
我们还将利用微流控分析组件进行快速和灵敏的生物标志物评估。
然而,监测细胞健康和功能的生物标志物的数量将在我们的
系统使用的功能读数。系统将通过使用CFD进行模拟来建模,以建立
营养素和药物代谢的可接受范围以及剪切力和预测药物
系统中的浓度分布还启用PK/PD预测功能。我们相信这项技术
将导致对药物疗效和毒理学潜力的更准确和更具成本效益的评估
化学物质或化学混合物,这种方法将对改善人类健康产生重大影响。
英文摘要
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.
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