In silico Safety Pharmacology

计算机安全药理学

基本信息

批准号：
9176961
负责人：
COLLEEN E CLANCY
金额：
$ 73.97万
依托单位：
UNIVERSITY OF CALIFORNIA AT DAVIS
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：
https://reporter.nih.gov/project-details/9176961
关键词：
Academia Action Potentials Adverse effects Affinity Amiodarone Anti-Arrhythmia Agents Arrhythmia Behavior Biological Cardiac Cardiotoxicity Categories Cells Clinical Research Complex Computer Simulation Data Dependence Development Drug Industry Drug Interactions Drug Targeting Electrocardiogram Estrogens Exhibits Experimental Models Female Goals Gonadal Steroid Hormones Government Heart 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 Plague Potassium Channel Preclinical Drug Evaluation Process Property Publishing Rehabilitation therapy Risk Risk Factors Role Safety Sotalol Specificity Stratification Structure Structure-Activity Relationship Surrogate Markers System Testing Tissues Toxic effect Verapamil Work analog base design dofetilide drug candidate drug development drug discovery drug mechanism drug rehabilitation 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 research study screening sex simulation subcellular targeting virtual

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：困扰药物开发的一个主要因素是没有临床前药物筛选目前的方法依赖于能够准确预测意外药物引起的心律失常。心电图上的 QT 间期延长等替代标志物不幸的是，QT 间期延长两者都不是。明确或敏感地指示心律失常的可能性迫切需要确定一种新方法。可以预测实际的致心律失常而不是替代指标。构成了揭示基本生物学原理和最有前途的方法之一机制、系统组件之间相互作用的模型效应并预测出现的药物效应。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结构活动关系决定了细胞和组织中心电活动的最终影响。通过在模型中捕获这些复杂的药物通道相互作用，我们期望能够预测药物安全性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混杂的 hERG 钾通道在通道、细胞和水平上进行功能规模预测原子结构模拟的预测将用于告知组织的动力学参数。捕捉药物和离子通道复杂动态相互作用的模型。然后将在通道、细胞和组织尺度的预测模型中研究成分，以揭示紧急行为实验的基本机制和复杂的相互作用。将利用哺乳动物细胞和组织来验证模型预测的药物特性。扰乱模型以恢复危险药物并降低其潜在毒性。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。