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

项目概要/摘要 本指导研究科学家发展奖（K 01）申请由Katsiaryna比科夫提交， PharmD，ScD，响应PA-20 - 190。比科夫博士是一名流行病学副专家和医学讲师 布里格姆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可操作的证据，以指导安全和 在多种药物和多种药物的复杂环境中，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价药物-药物的创新方法， 使用电子医疗保健数据的相互作用及其临床影响。比科夫博士的目标是获得专业知识， 临床老年病学和糖尿病学、老年药物流行病学和先进的数据统计方法 挖掘和信号检测，将她的方法学工作转化为临床相关研究。实现她 比科夫博士提出了一个为期5年的职业发展计划，并以 开发一种有效和高效的系统，用于检测和评价药物相互作用， 老年糖尿病患者。在该司富有成效和支持性的研究环境中， 药物流行病学，比科夫博士将与导师和合作者组成的跨学科团队合作， 来自哈佛和宾夕法尼亚大学的各个机构，他们拥有深厚的专业知识， 在她拟议培训的具体实质性领域的国家/国际声誉：临床老年医学和 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为 检测和评价老年糖尿病患者的临床相关药物相互作用。比科夫博士 提出了一种新的2阶段筛选，将确定潜在的相互作用的药物在电子医疗保健数据 随后将对确定的相互作用进行严格的假设驱动评价。该方法将使用 医疗保险索赔数据，可在该司查阅，并与电子健康记录和门诊实验室相关联 测试结果的一个子集的患者，并将专门针对解决异质性和复杂性 老年人的健康状况，包括不同程度的虚弱和多发性硬化。拟议的工作将 提供高质量且临床相关的证据，帮助老年糖尿病患者及其临床医生 更全面地评估在存在其他药物的情况下添加新药的获益和风险， 合并症从这项工作中获得的知识将影响数百万老年糖尿病患者， 美国，并将为申请人提供坚实的背景，成为一个独立的调查员， 最终，成为老龄化人群药物使用和结果研究的领导者。

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.