Development of a computational platform to investigate reports of adverse events attributed to generic drugs

开发一个计算平台来调查仿制药不良事件的报告

• 批准号: 9075257
• 负责人: LAWRENCE LESKO
• 金额: $ 25万
• 依托单位: UNIVERSITY OF FLORIDA
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-10 至 2018-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9075257
• 关键词: Development; computational; platform; investigate; reports

Project Summary This research is intended to develop 3 computational pathways which will be used to investigate adverse events (AEs) reported for generic drugs, as well as to predict the relative risk of AEs for brand name drugs coming off patent in the next 5 years. The 3 computational pathways are: 1. A physiologically based PK model that integrates drug and formulation properties with biologic system properties to predict exposure to a drug product (PK). Sensitivity analysis is used to identify factors which are most likely to cause differences in PK between a generic and brand name product. 2. An empirical PK/PD model which simulates the clinical response of two drug products with different PK profiles as a function of time after administration. The PD profiles are compared to determine how sensitive they are to changes in PK. 3. A system pharmacology model that maps the targets and pathways of a drug to determine the likelihood of that drug causing the purported AEs. The model includes other drugs which are positive controls for the AE of interest to determine similarity of target and pathway with the generic drug.

项目摘要 本研究旨在开发3种计算途径，用于研究 仿制药报告的不良事件（AE），以及预测品牌AE的相对风险 在未来五年内将取消专利的药物名称。 这三条计算路径是： 1.基于生理学的PK模型，将药物和制剂特性与生物 系统特性来预测药物产品暴露（PK）。敏感性分析用于识别 最有可能导致仿制药和品牌药之间PK差异的因素。 2.一种经验PK/PD模型，模拟两种不同药物制剂的临床反应， 给药后随时间变化的PK曲线。比较PD曲线以确定 它们对PK的变化很敏感。 3.一种系统药理学模型，用于绘制药物的靶点和途径，以确定 该药物引起声称的AE的可能性。该模型包括其他药物， 关注AE的对照，以确定与仿制药的靶点和途径相似性。