Data-driven drug discovery: investigating the molecular mechanisms of safety and efficacy

数据驱动的药物发现：研究安全性和有效性的分子机制

• 批准号: 10393864
• 负责人: Nicholas P Tatonetti
• 金额: $ 1.33万
• 依托单位: COLUMBIA UNIVERSITY HEALTH SCIENCES
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-05-01 至 2024-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10393864
• 关键词: Adverse drug event; Adverse effects; Adverse event; Affect; Area; Award; Biochemical; Computer Analysis; Computing Methodologies; Data; Databases; Development; Drug Interactions; Drug usage; Funding; Genetic Variation; Metabolism; Molecular; Parents; Participant; Pharmaceutical Preparations; Pharmacology; Physiological Effects of Drugs; Proteins; Research; Research Project Grants; Safety; Variant; Work; drug development; drug discovery; genetic variant; insight; interest; laboratory experiment; large datasets; pharmacovigilance; programs

Summary Up to 30% of adverse drug events can be attributed to drug-drug interactions in metabolism or mechanism of action. The study of drug-drug-protein interactions that drive these adverse effects, however, remains an underexplored area of research. This research project aims to offer one of the first comprehensive insights into the effect of genetic variants on adverse drug events, with a particular focus on drug-drug interactions. Through the utilization of large datasets and computational methods, we aim to develop a data-driven approach to identify genetic variations of target protein and metabolizing proteins associated with the development of adverse drug events. Expanding from our current work, we will identify genetic variants affecting the proteins of interest, participants in the study who have experienced the adverse drug events following use of the drugs and conduct association studies to identify any significant variants.

概括 多达30％的不良药物事件可以归因于代谢或机制中的药物相互作用 行动。然而，对驱动这些不良影响的药物 - 药物蛋白质相互作用的研究仍然是一种 研究领域不足。该研究项目旨在为最早的全面见解之一提供 遗传变异对不良药物事件的影响，特别侧重于药物相互作用。通过 大型数据集和计算方法的利用，我们旨在开发一种数据驱动的方法来识别 靶蛋白的遗传变异和与不良药物发展有关的代谢蛋白 事件。从当前的工作中扩展，我们将确定影响感兴趣蛋白质的遗传变异， 在使用药物和行为后经历过不良药物事件的研究参与者 协会研究以识别任何重要的变体。