Human on a chip systems to investigate disease comorbidities common in the aged population

项目摘要 老年人和制药业都将从芯片上的人类发展中受益 系统能够系统地研究疾病合并症及其对候选药物的反应， 由于缺乏良好的多模式疾病模型，老年人群处于临床前阶段 组合。我们将调查老年人口中最常见的疾病，包括非老年人， 酒精性脂肪肝病（NAFLD）、心肌病、恶病质/肌肉减少症和II型糖尿病。的影响 代谢性疾病，特别是II型糖尿病，对老年人和患病患者的影响是众所周知的，但很少 在临床前水平进行研究。该提案将建立在赫斯珀罗斯的专业知识和他们目前的 与UCF和佛罗里达大学分支药效学中心合作，位于 奥兰多.我们将使用Hesperos的专利多器官功能系统来研究多种疾病 表型来确定器官或模式中的其他缺陷如何增强或引起疾病， 或限制每个器官的治疗选择。目前还不清楚正常的衰老是如何受到 代谢紊乱，尽管已经观察到一些相关性。人体芯片模型由 再循环介质中的多个器官将提供受控的可再现系统，以评价对 毒品此外，通过比较急性和慢性效应，该模型将能够预测临床试验 基于这些临床前研究，成功地使用模型为临床疾病试验设计提供信息。 我们将在正在进行的计划的基础上，通过以下措施将PBPK/PD建模和模拟平台扩展到老年医学领域： 解释了基础病理生理学随年龄的变化。这些模型也可以作为 药物开发早期阶段的筛选工具， 选择具有更有利的PK和制剂性质的化合物。构建一个定义明确的 系统中，我们将使用一种常见的无血清培养基，使用微电极阵列进行功能读数， 集成在芯片上的杠杆，允许无创电子和机械读数，用于急性 第一阶段的药物反应和第二阶段的慢性药物试验。本提案的第一阶段部分将显示 三个器官可以联系在一起--肝脏、心脏和肌肉--它们对治疗的反应 可以在临床试验中重现反应。然后，将在多路复用系统中测试药物和药物组合。 与健康或非合并症系统相比，急性疾病模型的疗效和毒性改变。后 I期的定量里程碑已经实现，急性研究将扩展到慢性研究， 第二阶段的应用。我们还将通过利用不同的基因在系统中建立II型糖尿病表型。 通过整合目标1中的系统开发的五器官系统中的胰岛素和葡萄糖浓度 脂肪和胰腺。在I期引入系统的疾病表型和联合效应 将用于评估系统中的治疗方法。

Project Summary Both older adults and the pharmaceutical industry would benefit from the development of human-on-a-chip systems to be able to systematically investigate disease comorbidities and their response to drug candidates in the aged population at the preclinical stage due to the lack of good multimodal models of disease combinations. We will investigate diseases that are most prevalent in the aged population including non- alcoholic fatty liver disease (NAFLD), cardiomyopathy, cachexia/sarcopenia and type II diabetes. The influence of metabolic diseases, especially type II diabetes, on aged and diseased patients is well known, but little studied at the preclinical level. This proposal will build upon the expertise at Hesperos and their current collaborations with UCF and the Center for Pharmacodynamics at the University of Florida branch, located in Orlando. We will use Hesperos’ patented multi-organ functional systems to investigate multiple disease phenotypes to determine how other deficits in organs or modalities enhance or cause disease, hasten progression or limit treatment options in each organ. It is also unclear how normal aging is affected by metabolic disorders, although some correlations have been observed. Human-on-a-chip models composed of multiple organs in recirculating media will provide a controlled reproducible system to evaluate responses to drugs. In addition, by comparing acute to chronic effects, the model will enable prediction of clinical trial success using models to inform clinical disease trial design based on these preclinical studies. We will build on ongoing initiatives to expand PBPK/PD modeling and simulation platforms to geriatrics by accounting for changes in the underlying pathophysiology with age. These models may also serve as screening tools during early stages of drug development and facilitate decision-making with respect to selecting the compound with a more favorable PK and formulation properties. To construct a well-defined system, we will use a common serum free medium with functional readouts using microelectrode arrays and cantilevers that are integrated on chip that allow for noninvasive electronic and mechanical readouts for acute drug responses in Phase I and chronic drug tests in Phase II. The Phase I portion of this proposal will show that three organs can be linked together - liver, cardiac and muscle- and that their response to therapeutics can reproduce responses in clinical trials. Drug and drug combinations will then be tested in the multiplexed disease models acutely for altered efficacy and toxicity compared to healthy or non-comorbidity systems. After the quantitative milestones for Phase I have been achieved, the acute studies will be extended to chronic applications in Phase II. We will also establish a type II diabetic phenotype in the system by utilizing different concentrations of insulin and glucose in a five-organ system developed by integrating the system in Aim 1 with adipose and pancreas. The disease phenotypes introduced into the system in Phase I and the combined effect of metabolic diseases will be used to evaluate therapeutics in the system.