HLS-Cardiac Safety AI Trained Human Heart and Micro Heart Model

HLS-心脏安全 AI 训练的人类心脏和微心脏模型

基本信息

  • 批准号:
    9764845
  • 负责人:
  • 金额:
    $ 88.17万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2019
  • 资助国家:
    美国
  • 起止时间:
    2019-06-15 至 2021-05-31
  • 项目状态:
    已结题

项目摘要

HLS17-12. The US FDA is considering to establish a new cardiac safety assessment approach defined by a new paradigm called, “Comprehensive in vitro Proarrhythmia Assay (CIPA)”. The CIPA will 1) assess drug effects on each cardiac ion channel type individually using a high- throughput assay ion channel assays, 2) compute net effect on repolarization and risks for torsade pointes (TdP) using a mathematical model, and 3) confirm the computational prediction by measuring the drug’s effects on action potentials in induced pluripotent stem cell (iPSC) derived human cardiac myocytes (CMs). This paradigm shift, if successful, could reduce the cost of cardiac safety analyses by replacing or lowering the requirement to perform an expensive ($2-4 million) thorough QT study during clinical trials. Protecting consumers from drug induced arrhythmia and sudden deaths is a paramount importance for the regulators and pharmaceutical companies as well as lowing the cost of drug development. Many cardiac safety scientists, however, are skeptical about CIPA’s approach since CMs derived from human iPSCs exhibit a poor excitation-contraction coupling due to their immaturity. In addition, a proposed CIPA mathematical model was developed to simulate electrophysiology of human adult CMs, so there is a mismatch between experimental system and computational tool. To address these concerns, we proposed three specific aims in tw0 phases by following Fast- Track SBIR processes. Phase I feasibility Aim 1 will measure drug-induced changes in AP and CaT using human adult heart slices isolated from human donors. Here we will confirm our successful handling and analyzing human adult heart slices, which will be based on a recently published protocol by our collaborator, Dr. Igor Efimov, at George Washington University. After this validation, we will move on to perform the following two studies: Aim 2. Compare drug-induced changes in AP and CaT in NuHearts generated from adult CMs and cardiac fibroblasts from same human donor hearts; Aim 3. Validate and improve the computational models and train an artificial intelligence to predict cardiac safety risks of unknow compounds. After our successful completion proposed projects, we can establish an unprecedented cardiac safety assessment platform that can predict safety issues using a well-trained AI without doing any experiments using human heart slices that are rarely accessible for most of the safety laboratories or biotech firms.
HLS17-12美国FDA正在考虑建立一种新的心脏安全性评估方法 由称为“综合体外致心律失常测定(CIPA)"的新范例定义。的 CIPA将:1)使用高浓度- 通量测定离子通道测定,2)计算对复极化的净效应和 尖端扭转型室性心动过速(TdP),使用数学模型,以及3)通过以下方式确认计算预测: 测量药物对诱导多能干细胞(iPSC)衍生的动作电位的影响, 人心肌细胞(CM)。这种模式的转变,如果成功的话,可以降低成本, 心脏安全性分析,取代或降低要求,执行昂贵的(2 -4美元 在临床试验期间进行了全面的QT研究。保护消费者免受药物诱导 心律失常和猝死是一个至关重要的监管机构和制药 同时降低药物开发成本。 然而,许多心脏安全科学家对CIPA的方法持怀疑态度,因为CM来源于 来自人iPSC的细胞由于其不成熟而表现出差的兴奋-收缩偶联。在 此外,提出了一个CIPA数学模型,以模拟电生理学, 人类成年CM,因此实验系统和计算工具之间存在不匹配。 为了解决这些问题,我们提出了分两个阶段的三个具体目标,遵循快速- 跟踪SBIR流程。I期可行性目标1将测量药物诱导的AP变化, 使用从人类供体分离的成人心脏切片进行CaT。在这里,我们将确认我们的 成功地处理和分析人类成人心脏切片,这将是基于最近的一个 由我们的合作者,乔治华盛顿大学的Igor Efimov博士发表的方案。在此之后 为了验证,我们将继续进行以下两项研究:目标2。比较药物诱导 在成人CM产生的NuHearts中AP和CaT的变化以及来自 相同的人类供体心脏; Aim 3.优化和改进计算模型, 人工智能预测未知化合物的心脏安全风险。 在我们成功完成建议的项目后,我们可以建立一个前所未有的心脏 安全评估平台,可以使用训练有素的人工智能预测安全问题,而无需 任何使用人类心脏切片的实验, 实验室或生物技术公司。

项目成果

期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ monograph.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ sciAawards.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ conferencePapers.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ patent.updateTime }}

Tetsuro Wakatsuki其他文献

Tetsuro Wakatsuki的其他文献

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

{{ truncateString('Tetsuro Wakatsuki', 18)}}的其他基金

Diagnostic Tools for Targeted Heart Failure Treatments
心力衰竭靶向治疗的诊断工具
  • 批准号:
    10546035
  • 财政年份:
    2022
  • 资助金额:
    $ 88.17万
  • 项目类别:
An Aging Heart Model for Drug Discovery
用于药物发现的衰老心脏模型
  • 批准号:
    9331414
  • 财政年份:
    2016
  • 资助金额:
    $ 88.17万
  • 项目类别:
Engineered Tissue Based Phenotypic Screening of Mixture based Libraries
基于工程组织的混合物库表型筛选
  • 批准号:
    9145632
  • 财政年份:
    2015
  • 资助金额:
    $ 88.17万
  • 项目类别:
Engineered Tissue Based Phenotypic Screening of Mixture based Libraries
基于工程组织的混合物库表型筛选
  • 批准号:
    9221892
  • 财政年份:
    2015
  • 资助金额:
    $ 88.17万
  • 项目类别:
Engineered Tissue Based Phenotypic Screening of Mixture based Libraries
基于工程组织的混合物库表型筛选
  • 批准号:
    9047064
  • 财政年份:
    2015
  • 资助金额:
    $ 88.17万
  • 项目类别:
MASS PRODUCTION OF PERSONALIZED HUMAN ENGINEERED HEART TISSUES
大规模生产个性化人体工程心脏组织
  • 批准号:
    8927657
  • 财政年份:
    2014
  • 资助金额:
    $ 88.17万
  • 项目类别:
MASS PRODUCTION OF PERSONALIZED HUMAN ENGINEERED HEART TISSUES
大规模生产个性化人体工程心脏组织
  • 批准号:
    8780580
  • 财政年份:
    2014
  • 资助金额:
    $ 88.17万
  • 项目类别:
Engineered tissue-based, high-throughput compound profiling
基于组织的工程化高通量化合物分析
  • 批准号:
    8252293
  • 财政年份:
    2009
  • 资助金额:
    $ 88.17万
  • 项目类别:
Engineered tissue-based, high-throughput compound profiling
基于组织的工程化高通量化合物分析
  • 批准号:
    8619035
  • 财政年份:
    2009
  • 资助金额:
    $ 88.17万
  • 项目类别:
Engineered tissue-based, high-throughput compound profiling
基于组织的工程化高通量化合物分析
  • 批准号:
    8545867
  • 财政年份:
    2009
  • 资助金额:
    $ 88.17万
  • 项目类别:

相似海外基金

Kilohertz volumetric imaging of neuronal action potentials in awake behaving mice
清醒行为小鼠神经元动作电位的千赫兹体积成像
  • 批准号:
    10515267
  • 财政年份:
    2022
  • 资助金额:
    $ 88.17万
  • 项目类别:
Signal processing in horizontal cells of the mammalian retina – coding of visual information by calcium and sodium action potentials
哺乳动物视网膜水平细胞的信号处理 â 通过钙和钠动作电位编码视觉信息
  • 批准号:
    422915148
  • 财政年份:
    2019
  • 资助金额:
    $ 88.17万
  • 项目类别:
    Research Grants
CAREER: Resolving action potentials and high-density neural signals from the surface of the brain
职业:解析来自大脑表面的动作电位和高密度神经信号
  • 批准号:
    1752274
  • 财政年份:
    2018
  • 资助金额:
    $ 88.17万
  • 项目类别:
    Continuing Grant
Development of Nanosheet-Based Wireless Probes for Multi-Simultaneous Monitoring of Action Potentials and Neurotransmitters
开发基于纳米片的无线探针,用于同时监测动作电位和神经递质
  • 批准号:
    18H03539
  • 财政年份:
    2018
  • 资助金额:
    $ 88.17万
  • 项目类别:
    Grant-in-Aid for Scientific Research (B)
Population Imaging of Action Potentials by Novel Two-Photon Microscopes and Genetically Encoded Voltage Indicators
通过新型双光子显微镜和基因编码电压指示器对动作电位进行群体成像
  • 批准号:
    9588470
  • 财政年份:
    2018
  • 资助金额:
    $ 88.17万
  • 项目类别:
Enhanced quantitative imaging of compound action potentials in multi-fascicular peripheral nerve with fast neural Electrical Impedance Tomography enabled by 3D multi-plane softening bioelectronics
通过 3D 多平面软化生物电子学实现快速神经电阻抗断层扫描,增强多束周围神经复合动作电位的定量成像
  • 批准号:
    10009724
  • 财政年份:
    2018
  • 资助金额:
    $ 88.17万
  • 项目类别:
Enhanced quantitative imaging of compound action potentials in multi-fascicular peripheral nerve with fast neural Electrical Impedance Tomography enabled by 3D multi-plane softening bioelectronics
通过 3D 多平面软化生物电子学实现快速神经电阻抗断层扫描,增强多束周围神经复合动作电位的定量成像
  • 批准号:
    10467225
  • 财政年份:
    2018
  • 资助金额:
    $ 88.17万
  • 项目类别:
Fast high-resolution deep photoacoustic tomography of action potentials in brains
大脑动作电位的快速高分辨率深度光声断层扫描
  • 批准号:
    9423398
  • 财政年份:
    2017
  • 资助金额:
    $ 88.17万
  • 项目类别:
Noval regulatory mechanisms of axonal action potentials
轴突动作电位的新调节机制
  • 批准号:
    16K07006
  • 财政年份:
    2016
  • 资助金额:
    $ 88.17万
  • 项目类别:
    Grant-in-Aid for Scientific Research (C)
NeuroGrid: a scalable system for large-scale recording of action potentials from the brain surface
NeuroGrid:用于大规模记录大脑表面动作电位的可扩展系统
  • 批准号:
    9357409
  • 财政年份:
    2016
  • 资助金额:
    $ 88.17万
  • 项目类别:
{{ showInfoDetail.title }}

作者:{{ showInfoDetail.author }}

知道了