Prediction of Drug-Drug Interactions

药物相互作用的预测

基本信息

批准号：
7470418
负责人：
Zeruesenay Desta
金额：
$ 30.25万
依托单位：
INDIANA UNIV-PURDUE UNIV AT INDIANAPOLIS
依托单位国家：
美国
项目类别：
财政年份：
2002
资助国家：
美国
起止时间：
2002-08-15 至 2009-07-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/7470418
关键词：
Accounting Address Admission activity Adverse event Biopsy Cataloging Catalogs Cause of Death Chemical Exposure Chemicals Clarithromycin Clinical Research Complementary DNA Complex Cultured Cells Cytochrome P450 3A4 Daily Data Dependence Diltiazem Dose Drug Interactions Duodenum Environmental Pollutants Enzymes Erythromycin Exposure to Fright Hepatic Hepatocyte Hospitals Human In Vitro Individual Intestines Intravenous Ketoconazole Liver Liver Microsomes Mediating Metabolic Midazolam Modeling Nursing Homes Nutrient Oral Patients Pharmaceutical Preparations Phase Physiological Plasma Polypharmacy Population Reaction Rifampin Serum Site Social Impacts Structure Subcellular Fractions Testing Therapeutic Time Treatment Protocols Visit Week base cytochrome P450 3A day enzyme activity experience immortalized cell in vivo inhibitor/antagonist older patient pharmacokinetic model predictive modeling simulation

项目摘要

Adverse drug reactions are the fourth leading cause of death in the US and account for 5% of hospital admissions. A large percentage of these adverse events result from drug-drug interactions and the chance of experiencing such an interaction represents one of the greatest fears of patients visiting their doctor. It is common for patients to receive 4 or more drugs simultaneously and 10 or more is common among the growing population of elderly patients in nursing homes. Despite this ubiquitous polypharmacy and social impact of drug-drug interactions there has been no structured attempt to predict and therefore manage complex multi-drug interactions. We are proposing to take the first step in remedying this shortfall by studying "ternary" drug interactions occurring within mixtures of 3 drugs. We will focus on metabolic drug interactions at the level of the CYP3A enzymes in the liver and intestinal wall because these represent the single most common cause of clinically important drug-drug interactions. We will first quantify the time course and concentration dependence of the induction of intestinal and hepatic CYP3A enzymes by the prototypical inducer, rifampin. We will use intravenous midazolam to reflect hepatic CYP3A activity and intestinal pinch biopsies to reflect intestinal CYP3A activity. This will allow us to build a predictive, physiologically based pharmacokinetic model of CYP3A induction by rifampin. In the subsequent studies we conduct ternary drug interaction studies. These studies will test the hypotheses that the effect of two CYP3A modulators given simultaneously is predictable from the individual binary interactions. We will use intravenous and oral midazolam as probes of intestinal and hepatic CYP3A activity. These ternary interactions will include combinations of inhibitors and combinations of inhibitor and the inducer, rifampin. We will develop physiologically based pharmacokinetic models of each of the drugs involved in the ternary interactions to examine the predictability of the interactions. We will also test the hypothesis that the ternary in vivo interactions can be predicted from in vitro data. The interactions between inhibitors, inducer and substrate will be quantified in subcellular fractions and cultured cells. The in vitro parameter estimates will be incorporated into our physiological pharmacokinetic models to test the predictive power and build a universal platform for complex interactions between chemicals.

不良药物反应是美国第四大死亡原因，占医院的5％招生。这些不良事件中很大一部分是由于药物 - 药物相互作用和机会经历这种互动是探访医生的最大恐惧之一。这是患者共同接受4种或更多药物，同时接受4种或更多药物，而10例或更多药物在该患者中很常见养老院中老年患者的人口不断增长。尽管这种普遍存在的一多药和社交药物互动的影响没有结构化预测和管理复杂的多药相互作用。我们提议迈出第一步，以弥补这一短缺研究在3种药物混合物中发生的“三元”药物相互作用。我们将专注于代谢药物肝脏和肠壁中CYP3A酶高度的相互作用，因为这些代表临床上重要的药物相互作用的最常见原因。我们将首先量化时间肠道和肝CYP3A酶诱导的过程和浓度依赖性原型诱导剂，利福平。我们将使用静脉内咪达唑仑反映肝CYP3A活动和肠捏活活检以反映肠道CYP3A活性。这将使我们能够建立一个预测性，利福平基于生理的CYP3A诱导的药代动力学模型。在随后的研究中，我们进行了三元药物相互作用研究。这些研究将测试假设两个CYP3A调节剂的效果同时可以从个人身上预测二进制互动。我们将使用静脉注射和口服咪达唑仑作为肠道和肝CYP3A的探针活动。这些三元相互作用将包括抑制剂和抑制剂和组合的组合诱导剂Rifampin。我们将开发每种药物的基于生理的药代动力学模型参与三元相互作用，以检查相互作用的可预测性。我们还将检验以下假设：从体外数据可以预测三元体内相互作用。这抑制剂，诱导剂和底物之间的相互作用将在亚细胞分数中进行定量和培养细胞。体外参数估计值将纳入我们的生理药代动力学模型测试预测能力，并为化学物质之间的复杂相互作用建立通用平台。