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: 10214966
• 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/10214966
• 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; 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; Randomized Clinical Trials; 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; base; career development; clinical decision-making; clinically actionable; clinically relevant; comorbidity; data mining; design; detection method; detection platform; drug development; evidence base; experience; frailty; functional status; improved; inhibitor/antagonist; innovation; instructor; insurance claims; medical schools; multiple chronic conditions; novel; novel strategies; patient subsets; programs; 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.

项目摘要 /摘要 这项指导研究科学家发展奖（K01）的申请由Katsiaryna Bykov提交 Pharmd，SCD，响应PA-20-190。 Bykov博士是一名同学流行病学家和医学讲师 在Brigham and妇女医院的药物epidemiology and Pharmacoecoecoecoecoecoecoecoepopopidemiology and Hospital in 哈佛医学院。她的长期目标是产生临床可行的证据，以指导安全和 在多功能和多种病态的复杂环境中，老年人有效使用药物。她最近 研究的重点是开发用于检测和评估药物的创新方法 使用电子保健数据的相互作用及其临床影响。 Bykov博士旨在获得专业知识 临床老年医学和糖尿病学，老年药物ePidemiology和高级统计方法的数据 采矿和信号检测将她的方法论工作转化为临床相关的研究。实现她 AIMS，BYKOV博士提出了一项为期5年的职业发展计划，并指导了研究以上的研究 开发有效有效的系统，用于检测和评估药物相互作用 老年人患有糖尿病。在该部门高产和支持性的研究环境中 Bykov博士将与跨学科的导师和合作者团队合作。 来自哈佛大学的整个机构和宾夕法尼亚大学的专业知识， 她提议的培训的特定实质领域的国家/国际声誉：临床老年医学和 糖尿病学，用于数据挖掘和信号检测的晚期统计方法，药物与药物相互作用研究， 和药物电子学。该提案的总体目标是为 糖尿病老年人的临床相关药物相互作用的检测和评估。 Bykov博士 提案进行了一种新型的2阶段筛查，该筛查将确定电子医疗数据中潜在相互作用的药物 然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 Medicare索赔数据，可在该部门提供，并链接到电子健康记录和门诊实验室 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定制 老年人的健康状况，包括不同程度的脆弱和多种病。拟议的工作将 提供高质量和临床相关的证据，这些证据将帮助患有糖尿病的老年人及其临床医生 更充分地评估在其他药物存在下添加新药物的收益和风险 合并症。从这项工作中获得的知识会影响数百万老年人患有糖尿病的老年人 美国，并将为申请人提供扎实的背景，以成为独立的研究者，并且 最终，在衰老人群中使用药物使用和结果的领导者。