In silico Safety Pharmacology
计算机安全药理学
基本信息
- 批准号:9176961
- 负责人:
- 金额:$ 73.97万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2016
- 资助国家:美国
- 起止时间:2016-07-05 至 2020-06-30
- 项目状态:已结题
- 来源:
- 关键词:AcademiaAction PotentialsAdverse effectsAffinityAmiodaroneAnti-Arrhythmia AgentsArrhythmiaBehaviorBiologicalCardiacCardiotoxicityCategoriesCellsClinical ResearchComplexComputer SimulationDataDependenceDevelopmentDrug IndustryDrug InteractionsDrug TargetingElectrocardiogramEstrogensExhibitsExperimental ModelsFemaleGoalsGonadal Steroid HormonesGovernmentHeartHumanIndustryIon ChannelKineticsLeadLettersLinkLong QT SyndromeMammalian CellMethodologyModelingMolecular ConformationMoxifloxacinNamesPharmaceutical PreparationsPharmacologyPharmacotherapyPhasePhysiologicalPlaguePotassium ChannelPreclinical Drug EvaluationProcessPropertyPublishingRehabilitation therapyRiskRisk FactorsRoleSafetySotalolSpecificityStratificationStructureStructure-Activity RelationshipSurrogate MarkersSystemTestingTissuesToxic effectVerapamilWorkanalogbasedesigndofetilidedrug candidatedrug developmentdrug discoverydrug mechanismdrug rehabilitationfallshealthy volunteerheart electrical activityheart pharmacologyheart rhythmibutilideimprovedinterdisciplinary approachmathematical modelmulti-scale modelingnovelnovel strategiespre-clinicalpredictive modelingprototyperanolazinereceptorresearch studyscreeningsexsimulationsubcellular targetingvirtual
项目摘要
PROJECT SUMMARY: A major factor plaguing drug development is that there is no preclinical drug screen
that can accurately predict unintended drug induced cardiac arrhythmias. The current approaches rely on
substitute markers such as QT interval prolongation on the ECG. Unfortunately, QT prolongation is neither
specific nor sensitive to indicate likelihood of arrhythmias. There is an urgent need to identify a new approach
that can predict actual proarrhythmia rather than surrogate indicators. Mathematical modeling and simulation
constitutes one of the most promising methodologies to reveal fundamental biological principles and
mechanisms, model effects of interactions between system components and predict emergent drug effects.
Thus, we propose the development of a novel multiscale approach based on drug-channel structural
interactions and kinetics intended to predict drug induced cardiotoxicity in the context of: 1) preclinical drug
screening, 2) drug rehabilitation, and 3) prediction of the intersection of drug effects and coexistent risk factors.
Our underlying hypothesis is that the fundamental mode of drug interaction derived from each drug’s unique
structure activity relationship determines the resultant effects on cardiac electrical activity in cells and tissue.
By capturing these complex drug channel interactions in a model, we expect to be able to predict drug safety
or electro-toxicity in the heart. We have brought together an expert team to assemble and test a new multiscale
model framework that connects detailed mathematical models to predict atomic scale interactions of drugs on
the promiscuous hERG potassium channel to functional scale predictions at the level of the channel, cell and
tissue. Predictions from the atomic structure simulations will be used to inform the kinetic parameters of
models that capture the complex dynamical interactions of drugs and ion channels. The computational
components will then be studied in predictive models at the channel, cell and tissue scales to expose
fundamental mechanisms and complex interactions underlying emergent behaviors. Experiments in
mammalian cells and tissues will be undertaken to validate model predictions. Drug properties will be
perturbed in models to rehabilitate dangerous drugs and reduce their potential toxicity. The multiscale model
for prediction of cardiopharmacology that we will develop in this application will be applied to projects
demonstrating its usefulness for efficacy or toxicity of drug treatments in the complex physiological system of
the heart.
项目摘要:困扰药物开发的主要因素是没有临床前药物筛查
这可以准确预测意外的药物引起的心律不齐。当前的方法依赖
替代标记,例如ECG上的QT间隔延长。不幸的是,QT延长都不是
对心律失常的可能性也不敏感。迫切需要确定一种新方法
这可以预测实际的心律失常,而不是替代指标。数学建模和仿真
构成揭示基本生物学原理和的最有前途的方法之一
机制,系统组件之间相互作用的模型影响和预测新兴药物的影响。
这,我们提出了一种基于药物通道结构的新型多尺度方法的开发
相互作用和动力学旨在在以下情况下预测药物诱导的心脏毒性:1)临床前药物
筛查,2)药物康复和3)预测药物作用和共存危险因素的交集。
我们的基本假设是,从每种药物的独特
结构活性关系决定了对细胞和组织中心脏电活动的影响。
通过在模型中捕获这些复杂的药物通道相互作用,我们希望能够预测药物安全
或心脏中的电毒性。我们汇集了一个专家团队来组装和测试新的多尺度
模型框架将详细的数学模型连接以预测药物的原子量表相互作用
在通道,单元和细胞水平上进行功能尺度预测的杂交HERG钾通道
组织。原子结构模拟的预测将用于告知动力学参数
捕获药物和离子通道的复杂动态相互作用的模型。计算
然后,组件将在通道,细胞和组织尺度的预测模型中进行研究以暴露
基本的机制和复杂的紧急行为行为。实验
将进行哺乳动物细胞和组织以验证模型预测。毒品特性将是
在模型中受到干扰,以恢复危险药物并降低其潜在毒性。多尺度模型
为了预测我们将在本申请中开发的心脏药理学,将应用于项目
证明其在复杂的物理系统中,对药物治疗的效率或毒性有用
心。
项目成果
期刊论文数量(0)
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会议论文数量(0)
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{{ truncateString('COLLEEN E CLANCY', 18)}}的其他基金
Multi-Scale Modeling of Vascular Signaling Units
血管信号单元的多尺度建模
- 批准号:
10406687 - 财政年份:2021
- 资助金额:
$ 73.97万 - 项目类别:
Multi-Scale Modeling of Vascular Signaling Units
血管信号单元的多尺度建模
- 批准号:
10394236 - 财政年份:2020
- 资助金额:
$ 73.97万 - 项目类别:
Multi-Scale Modeling of Vascular Signaling Units
血管信号单元的多尺度建模
- 批准号:
10614418 - 财政年份:2020
- 资助金额:
$ 73.97万 - 项目类别:
Development of the Predictive NeuroCardiovascular Simulator
预测性神经心血管模拟器的开发
- 批准号:
10397892 - 财政年份:2018
- 资助金额:
$ 73.97万 - 项目类别:
Development of the Predictive NeuroCardiovascular Simulator
预测性神经心血管模拟器的开发
- 批准号:
10001997 - 财政年份:2018
- 资助金额:
$ 73.97万 - 项目类别:
Development of the Predictive NeuroCardiovascular Simulator
预测性神经心血管模拟器的开发
- 批准号:
10092300 - 财政年份:2018
- 资助金额:
$ 73.97万 - 项目类别:
Development of the Predictive NeuroCardiovascular Simulator
预测性神经心血管模拟器的开发
- 批准号:
10215080 - 财政年份:2018
- 资助金额:
$ 73.97万 - 项目类别:
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