In silico Safety Pharmacology

计算机安全药理学

• 批准号: 9288209
• 负责人: COLLEEN E CLANCY
• 金额: $ 68.87万
• 依托单位: UNIVERSITY OF CALIFORNIA AT DAVIS
• 依托单位国家: 美国
• 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: https://reporter.nih.gov/project-details/9288209
• 关键词: Academia; Action Potentials; Acute; Adverse effects; Affinity; Amiodarone; Anti-Arrhythmia Agents; Arrhythmia; Behavior; Biological; Cardiac; Cardiotoxicity; Categories; Cells; Clinical Research; Complex; Computer Simulation; Dangerousness; Data; Dependence; Development; Drug Industry; Drug Interactions; Drug Targeting; Drug toxicity; Electrocardiogram; Estrogens; Exhibits; Experimental Models; Female; Goals; Gonadal Steroid Hormones; Government; Heart; Heart Abnormalities; Human; Industry; Ion Channel; Kinetics; Lead; Letters; Link; Long QT Syndrome; Mammalian Cell; Methodology; Modeling; Molecular Conformation; Moxifloxacin; Names; Pharmaceutical Preparations; Pharmacology; Pharmacotherapy; Phase; Physiological; Potassium Channel; Preclinical Drug Evaluation; Process; Property; Publishing; Rehabilitation therapy; Risk; Risk Factors; Risk stratification; Role; Safety; Sotalol; Specificity; Structure; Structure-Activity Relationship; Surrogate Markers; System; Testing; Tissues; Toxic effect; Triad Acrylic Resin; Verapamil; Work; analog; base; design; dofetilide; drug candidate; drug development; drug discovery; drug mechanism; drug rehabilitation; drug testing; experimental study; falls; healthy volunteer; heart electrical activity; heart pharmacology; heart rhythm; ibutilide; improved; interdisciplinary approach; mathematical model; multi-scale modeling; novel; novel strategies; pre-clinical; predictive modeling; prototype; ranolazine; receptor; screening; sex; simulation; subcellular targeting; virtual

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.

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 替代标记，例如心电图上的 QT 间期延长。 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. 因此，我们建议开发一种基于药物通道结构的新型多尺度方法 旨在预测药物引起的心脏毒性的相互作用和动力学：1) 临床前药物 筛查，2) 戒毒康复，以及 3) 药物效应与共存危险因素交叉点的预测。 我们的基本假设是药物相互作用的基本模式源自每种药物的独特性 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.我们聚集了一个专家团队来组装和测试新的多尺度 模型框架，连接详细的数学模型来预测药物的原子尺度相互作用 the promiscuous hERG potassium channel to functional scale predictions at the level of the channel, cell and 组织。 Predictions from the atomic structure simulations will be used to inform the kinetic parameters of 捕捉药物和离子通道复杂动态相互作用的模型。 The computational 然后将在通道、细胞和组织尺度的预测模型中研究成分，以揭示 紧急行为背后的基本机制和复杂的相互作用。 Experiments in 将利用哺乳动物细胞和组织来验证模型预测。 Drug properties will be 扰乱模型以恢复危险药物并降低其潜在毒性。 The multiscale model 我们将在此应用程序中开发的心脏药理学预测将应用于项目 证明其在复杂的生理系统中对药物治疗的功效或毒性的有用性 心脏。