Novel approaches to identify and quantify the impact of drug-drug interactions in older adults with diabetes, with a focus on multimorbidity and polypharmacy

识别和量化老年糖尿病患者药物相互作用影响的新方法，重点关注多发病和多药治疗

• 批准号: 10599953
• 负责人: Katsiaryna Bykov
• 金额: $ 13.09万
• 依托单位: BRIGHAM AND WOMEN'S HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-04-15 至 2026-03-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10599953
• 关键词: Address; Adverse effects; Adverse event; Affect; Age; Aging; Alternative Therapies; Area; Benefits and Risks; Biometry; Clinical; Cohort Studies; Complex; Complications of Diabetes Mellitus; Crossover Design; Data; Decision Making; Detection; Development; Diabetes Mellitus; Doctor of Pharmacy; Drug Evaluation; Drug Interactions; Drug usage; Elderly; Electronic Health Record; Environment; Epidemic; Epidemiologist; Epidemiology; Evaluation; Exclusion; Exposure to; Face; Fracture; Geriatrics; Goals; Health; Health Insurance; Health Status; Healthcare; Heterogeneity; Hospitals; Hypoglycemia; Impaired cognition; In Vitro; Institution; International; Knowledge; Laboratories; Link; Medicare claim; Medicine; Mentored Research Scientist Development Award; Mentors; Mentorship; Methodology; Methods; Mission; Modification; National Institute on Aging; Observational Study; Outcome; Outpatients; Patient Care; Patients; Pennsylvania; Pharmaceutical Economics; Pharmaceutical Preparations; Pharmacoepidemiology; Pharmacology; Physiological; Polypharmacy; Population; Population Study; Positioning Attribute; Predisposition; Premature Mortality; Productivity; Research; Research Personnel; Risk; Risk Factors; Scanning; Signal Transduction; Solid; Statistical Methods; Subgroup; Sulfonylurea Compounds; Syndrome; Test Result; Testing; Time; Training; Translating; Trees; United States Food and Drug Administration; Universities; Woman; Work; active comparator; age related; career development; clinical decision-making; clinically actionable; clinically relevant; comorbidity; data mining; design; detection method; detection platform; drug development; eHealth; evidence base; experience; frailty; functional status; improved; inhibitor; innovation; instructor; insurance claims; medical schools; multiple chronic conditions; novel; novel strategies; patient subsets; programs; randomized, clinical trials; research clinical testing; response; screening; sex; skills; tool

PROJECT SUMMARY / ABSTRACT This application for a Mentored Research Scientist Development Award (K01) is submitted by Katsiaryna Bykov, PharmD, ScD, in response to PA-20-190. Dr. Bykov is an Associate Epidemiologist and Instructor in Medicine in the Division of Pharmacoepidemiology and Pharmacoeconomics at Brigham and Women’s Hospital and Harvard Medical School. Her long-term goal is to generate clinically actionable evidence to guide the safe and effective use of medications in older adults in the complex milieu of polypharmacy and multimorbidity. Her recent research has focused on developing innovative methods for the detection and evaluation of drug-drug interactions and their clinical impact using electronic healthcare data. Dr. Bykov aims to acquire expertise in clinical geriatrics and diabetology, geriatric pharmacoepidemiology, and advanced statistical methods for data mining and signal detection to translate her methodological work into clinically relevant research. To achieve her aims, Dr. Bykov proposes a 5-year program of career development and mentored research centered on the development of a valid and efficient system for the detection and evaluation of drug-drug interactions in older adults with diabetes. Within the highly productive and supportive research environment of the Division of Pharmacoepidemiology, Dr. Bykov will work with an interdisciplinary team of mentors and collaborators drawn from across institutions at Harvard and University of Pennsylvania who have deep expertise and national/international reputations in the specific substantive areas of her proposed training: clinical geriatrics and diabetology, advanced statistical methods for data mining and signal detection, drug-drug interactions research, and pharmacoepidemiology. The overarching objective of the proposal is to develop a framework for the detection and evaluation of clinically relevant drug-drug interactions in older adults with diabetes. Dr. Bykov proposes a novel 2-stage screening that will identify potentially interacting drugs in electronic healthcare data and will be followed by a rigorous hypothesis-driven evaluation of identified interactions. The approach will use Medicare claims data, available in the Division and linked to electronic health records and outpatient laboratory test results for a subset of patients, and will be specifically tailored to address the heterogeneity and complexity of health status in older adults, including varying degrees of frailty and multimorbidity. The proposed work will provide high quality and clinically relevant evidence that will help older adults with diabetes and their clinicians to more fully assess the benefits and risks of adding a new medication in the presence of other medications and co-morbidities. The knowledge gained from this work will impact several million older adults with diabetes in the US and will provide the applicant with a solid background to become an independent investigator and, ultimately, a leader in the study of medication use and outcomes in aging populations.

项目概要/摘要 指导研究科学家发展奖（K01）的申请由 Katsiaryna Bykov 提交， 药学博士、科学博士，响应 PA-20-190。 Bykov 博士是流行病学家和医学讲师 布莱根妇女医院药物流行病学和药物经济学部门 哈佛医学院。她的长期目标是产生临床上可行的证据来指导安全和 在多种药物和多种疾病的复杂环境中有效地使用老年人的药物。她最近的 研究重点是开发药物检测和评价的创新方法 使用电子医疗数据的相互作用及其临床影响。 Bykov 博士的目标是获得以下方面的专业知识 临床老年病学和糖尿病学、老年药物流行病学以及先进的数据统计方法 挖掘和信号检测将她的方法论工作转化为临床相关研究。去成就她 为了实现这一目标，Bykov 博士提出了一个为期 5 年的职业发展计划和指导研究，重点关注 开发有效且高效的系统来检测和评估药物间相互作用 患有糖尿病的老年人。在该部门高效且支持性的研究环境中 Bykov 博士将与药物流行病学系的导师和合作者组成的跨学科团队合作 来自哈佛大学和宾夕法尼亚大学的各个机构，他们拥有深厚的专业知识和 在她提议的培训的具体实质性领域享有国内/国际声誉：临床老年病学和 糖尿病学、数据挖掘和信号检测的先进统计方法、药物相互作用研究、 和药物流行病学。该提案的总体目标是制定一个框架 检测和评估老年糖尿病患者临床相关的药物相互作用。拜科夫博士 提出了一种新颖的两阶段筛选，将识别电子医疗数据中潜在相互作用的药物 随后将对已确定的相互作用进行严格的假设驱动评估。该方法将使用 医疗保险索赔数据，可在该部门获取并链接到电子健康记录和门诊实验室 针对一部分患者的测试结果，并将专门针对解决异质性和复杂性问题进行定制 老年人的健康状况，包括不同程度的虚弱和多种疾病。拟议的工作将 提供高质量的临床相关证据，帮助老年糖尿病患者及其临床医生 更全面地评估在其他药物存在的情况下添加新药物的益处和风险，以及 合并症。从这项工作中获得的知识将影响数百万患有糖尿病的老年人 美国并将为申请人提供成为独立调查员的坚实背景，并且， 最终，成为老龄化人口药物使用和结果研究的领导者。