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Personalizing Class I anti-Arrhythmic Drug Therapy

个性化 I 类抗心律失常药物治疗

基本信息

批准号：
10606511
负责人：
JONATHAN R SILVA
金额：
$ 57.22万
依托单位：
WASHINGTON UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2020
资助国家：
美国
起止时间：
2020-04-01 至 2025-03-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10606511
关键词：
Adrenergic Agents Affect Amiodarone Anti-Arrhythmia Agents Arrhythmia Biophysics Blinded Cardiac Cardiac Myocytes Cardiomyopathies Clinical Clinical Research Clinical Trials Computer Models Data Diagnosis Discipline Disease Dose Drug Interactions Drug Modelings Drug Prescriptions Drug Regulations Genetic Genetic Variation Genotype Guidelines Implantable Defibrillators Macromolecular Complexes Maps Mass Spectrum Analysis Measures Membrane Methods Mexiletine Modeling Molecular Molecular Conformation Movement Mutation Outcome Outcome Measure Pain Patients Peripheral Blood Mononuclear Cell Pharmaceutical Preparations Pharmacology Pharmacotherapy Phosphorylation Phosphorylation Site Physicians Precision therapeutics Process Protocols documentation Regimen Registries Regulation Reporting Shock Sodium Channel Structure Syndrome Testing Toxic effect Variant Ventricular Ventricular Arrhythmia Ventricular Fibrillation Ventricular Tachycardia biophysical properties cohort cost drug efficacy experimental study genetic information genetic variant genomic data heart rate variability heart rhythm implantable device improved improved outcome induced pluripotent stem cell insight novel outcome prediction patient registry patient response patient subsets personalized medicine predicting response predictive modeling prevent prospective rational design response side effect simulation stem cell differentiation stem cell model therapy outcome translational approach treatment strategy voltage wearable device

项目摘要

Summary We want to improve arrhythmia therapy outcomes by predicting an optimal anti-arrhythmic drug regimen for ventricular arrhythmia patients using genomic data and heart rhythm reports from wearable and implanted devices. Today, amiodarone is commonly prescribed to prevent painful shocks from defibrillators that are implanted in patients who suffer from ventricular arrhythmia. Nevertheless, amiodarone is toxic for many patients when it is used over a period of years. In contrast, the class 1b molecule, mexiletine has many fewer side effects, but is effective in fewer patients. We have shown that cardiac Na+ channel variants in patients with Long QT Type 3 Syndrome can significantly affect key biophysical gating parameters that determine whether patients respond to mexiletine therapy. We propose to apply a similar approach to determine how common genetic variants and β-adrenergic tone regulate mexiletine response in patients with ventricular arrhythmias. The project aims have been developed to 1) gain novel insight into the molecular mechanisms of β-adrenergic and variant regulation of the drug response, 2) create a predictive model by mapping parameters associated with these mechanisms to patient response in a clinical study, and 3) improve the model by gaining insight from an optimized induced pluripotent stem cell based model of the drug response. If the aims of the proposal are successful, we will set the stage for a prospective clinical trial that uses a predictive model to identify ventricular arrhythmia patients who will respond to mexiletine based on data that is becoming readily available to physicians.

摘要我们希望通过预测最佳的抗心律失常药物来改善心律失常的治疗结果。使用基因组数据和心率报告的室性心律失常患者的治疗方案可穿戴和植入式设备。今天，胺碘酮通常是用来预防疼痛的植入室性心律失常患者体内的除颤器的电击。尽管如此，胺碘酮在使用数年后对许多患者来说是有毒性的。在……里面相比之下，1b类分子美西律的副作用要少得多，但在更少的情况下有效病人。我们已经证明长QT_3型患者的心脏Na+通道变异综合征会显著影响关键的生物物理门控参数患者对美西律治疗有反应。我们建议使用类似的方法来确定常见基因变异和β肾上腺素能调节美西律对患者疗效的影响室性心律失常。该项目的目标是1)获得新的洞察 β-肾上腺素能的分子机制及药物反应的变异调节，2) 通过将与这些机制相关联的参数映射到患者来创建预测模型临床研究中的响应，以及3)通过从优化的基于诱导多能干细胞的药物反应模型。如果提案的目的是成功后，我们将为使用预测性模型进行前瞻性临床试验奠定基础根据以下数据确定美西律对室性心律失常患者的反应变得容易被医生使用。