Drug-drug interactions and kidney disease in hospitalized patients

住院患者的药物相互作用和肾脏疾病

• 批准号: 10531253
• 负责人: Todd Anthony Miano
• 金额: $ 15.8万
• 依托单位: UNIVERSITY OF PENNSYLVANIA
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-02-01 至 2025-11-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10531253
• 关键词: Acceleration; Acute; Acute Renal Failure with Renal Papillary Necrosis; Address; Admission activity; Adverse event; Affect; Amiodarone; Animal Model; Antibiotics; Antimicrobial Resistance; Binding Proteins; Chronic Kidney Failure; Clinical; Cohort Studies; Creatinine; Data; Database Management Systems; Databases; Disease; Drug Exposure; Drug Interactions; Drug Kinetics; Drug Modelings; Drug toxicity; Enzymes; Fostering; Funding; Future; Generations; Goals; Health; Health system; Hepatic; Hospitalization; Hospitals; Human; Infection; Injury; Inpatients; Investigation; Kidney; Kidney Diseases; Knowledge; Lead; Life; Measures; Mediating; Metabolism; Methodology; Methods; Molecular Profiling; Nature; Outcome; Outcome Study; Patients; Pattern; Pharmaceutical Preparations; Pharmacoepidemiology; Pharmacology; Pharmacotherapy; Physiology; Piperacillin-Tazobactam; Polypharmacy; Population; Prevention strategy; Property; Prospective cohort; Prospective, cohort study; Proteins; Renal function; Research; Research Design; Research Personnel; Retrospective cohort study; Risk; Role; Safety; Sepsis; Severities; Source; Statistical Models; Testing; Toxic effect; Training; United States Department of Veterans Affairs; Vancomycin; Vulnerable Populations; Warfarin; Work; burden of illness; clinical effect; clinically significant; cohort; design; disorder risk; drug development; epidemiology study; experience; improved; insight; medication safety; models and simulation; nephrotoxicity; novel; novel strategies; pharmacokinetic model; physiologically based pharmacokinetics; post gamma-globulins; predictive modeling; prevent; preventive intervention; prospective; response; rosuvastatin; septic patients; simulation; skills; translational approach; translational model; virtual

PROJECT SUMMARY As polypharmacy becomes increasingly common in patients with kidney disease, drug-drug interactions (DDIs), the phenomenon of one drug altering the effect of another drug, grow as potential sources of preventable harm in this vulnerable population. The clinical impacts of DDIs are poorly understood, particularly in the hospital setting, where up to half of patients have acute or chronic kidney disease. Further, the potential for bidirectional relationships between kidney disease and DDIs—with kidney disease functioning as both an outcome of DDIs and a baseline factor that alters DDI severity—complicates epidemiologic study and necessitates novel methodologic approaches. This proposal aims to improve the safety of pharmacotherapy in patients with kidney disease through the following broad objectives: 1) examine whether commonly used antibiotics in the hospital setting interact to increase the risk of acute kidney injury (AKI) and subsequent chronic kidney disease (CKD); 2) examine whether changes in kidney function in turn produce variability in DDI severity; 3) train the applicant in renal pharmacoepidemiology, prospective research design and analysis, and pharmacokinetic simulation methods, which will enable a novel translational approach to DDI research; and 4) provide the preliminary data and mechanistic insights for future R01 funded studies that quantify the health impacts of DDIs in the kidney disease population and develop preventive interventions. The applicant will integrate the results from large scale pharmacoepidemiologic studies, prospective cohort studies, and simulation models to achieve the stated objectives. The applicant will first determine the impact of a potential DDI between two common antibiotics on inpatient AKI risk and subsequent CKD using a large-scale health system database and prospective cohort study (Aim 1). The applicant will then examine the effect of kidney disease on the magnitude of a DDI mediated by hepatic CYP450 inhibition using two distinct, yet complementary approaches: developing a pharmacokinetic simulation model of the interaction, followed by a retrospective cohort study of the same interaction (Aim 2). Integration of methods will provide insights into the effects of kidney disease on CYP inhibition that wouldn't be possible with either method in isolation. This proposal will train the candidate in renal pharmacoepidemiology, advanced statistical modeling, and pharmacokinetic simulation, and have important implications for drug safety in the 35 million hospital admissions each year. This research will generate new knowledge extending beyond the specific drugs under study and foster the candidate's progression towards becoming an independent investigator in renal pharmacoepidemiology.

项目摘要 随着多种药物治疗在肾病患者中越来越普遍， DDI是一种药物改变另一种药物作用的现象， 对这一弱势群体的可预防伤害。DDI的临床影响知之甚少，特别是 在医院环境中，多达一半的患者患有急性或慢性肾脏疾病。此外，潜在的 对于肾脏疾病和DDI之间的双向关系，肾脏疾病既起作用， DDI的结果和改变DDI严重程度的基线因素-使流行病学研究复杂化， 需要新的方法论。 该提案旨在通过以下措施提高肾病患者药物治疗的安全性： 以下广泛的目标：1）检查医院环境中常用的抗生素是否与 增加急性肾损伤（阿基）和随后的慢性肾病（CKD）的风险; 2）检查 肾功能的变化是否反过来导致DDI严重程度的变异性; 3）对申请人进行肾功能方面的培训， 药物流行病学、前瞻性研究设计和分析以及药代动力学模拟方法， 这将为DDI研究提供一种新的转化方法;以及4）提供初步数据并 为未来R 01资助的研究提供机制见解，量化DDI对肾脏的健康影响 疾病人群，并制定预防干预措施。 申请人将整合大规模药物流行病学研究、前瞻性研究和 队列研究和模拟模型，以实现既定目标。申请人将首先确定 两种常用抗生素之间潜在的DDI对住院阿基风险和随后的CKD的影响 大规模卫生系统数据库和前瞻性队列研究（目标1）。然后，申请人将审查 肾脏疾病对肝脏CYP 450抑制介导的DDI幅度的影响， 但互补的方法：开发相互作用的药代动力学模拟模型，然后 相同相互作用的回顾性队列研究（目标2）。方法的整合将提供对以下方面的见解： 肾脏疾病对肾脏抑制的影响，这两种方法都不可能单独使用。 该提案将对候选人进行肾脏药物流行病学，高级统计建模， 和药代动力学模拟，并对3500万医院的药物安全性具有重要意义。 每年招生。这项研究将产生新的知识，超越特定的药物， 研究和培养候选人的进展，成为一个独立的研究者在肾脏 药物流行病学