Informatics Tools for Pharmacogenomic Discovery using Practice-based Data

使用基于实践的数据进行药物基因组发现的信息学工具

• 批准号: 9307936
• 负责人: Joshua C. Denny
• 金额: $ 60.05万
• 依托单位: VANDERBILT UNIVERSITY MEDICAL CENTER
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-18 至 2019-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9307936
• 关键词: Adverse drug event; Adverse event; Algorithms; Anthracyclines; Archives; Award; Biocompatible Materials; Biology; Biomedical Computing; Biomedical Research; Boston; Cardiotoxicity; Cells; Clinic; Clinical; Clinical Data; Clostridium difficile; Colitis; Communities; Computer software; Computerized Medical Record; Coupled; DNA; Data; Databases; Disease; Drug Exposure; Drug Modelings; Drug toxicity; Event; Foundations; Funding; Genetic Variation; Genomics; Genotype; Grant; Healthcare Systems; Heparin; Informatics; Information Management; Institution; Knowledge Discovery; Link; Methods; Modeling; Morphologic artifacts; Natural Language Processing; Nature; Observational Study; Ontology; Outcome; Patients; Pediatric Hospitals; Pharmaceutical Preparations; Pharmacogenomics; Phenotype; Population Heterogeneity; Research; Research Personnel; Resources; Sampling; Science; Site; Standardization; Structure; System; Terminology; Text; Thrombocytopenia; Time; TimeLine; Toxic effect; Treatment outcome; United States National Institutes of Health; Vancomycin; Vision; Warfarin; base; biobank; case control; clinical care; clopidogrel; cost; data integration; disorder risk; drug efficacy; exome sequencing; genetic variant; genomic data; improved; longitudinal dataset; novel; open source; personalized medicine; phenotypic data; public health relevance; rapid growth; rare variant; response; study population; success; tool; user-friendly; virtual

DESCRIPTION (provided by applicant): Rapid growth in the clinical implementation of large electronic medical records (EMRs) has led to an unprecedented expansion in the availability of dense longitudinal datasets for observational research. More recently, huge efforts have linked EMR databases with archived biological material, to accelerate research in personalized medicine. EMR- linked DNA biobanks have identified common and rare genetic variants that contribute to risk of disease. An appealing vision, which has not been extensively explored, is to use EMRs-linked biobanks for pharmacogenomic studies, which identify associations between genetic variation and drug efficacy and toxicity. The longitudinal nature of the data contained within EMRs make them ideal for quantifying drug outcome (both efficacy and toxicity). Efforts are already underway to link these EMRs across institutions, and standardize the definition of phenotypes for large-scale studies of treatment outcome, specifically within the context of routine clinical care. Despite its success, EMR-based pharmacogenomic studies are often hampered by its data-intensive nature -- it is time- consuming and costly to extract and integrate data from multiple heterogeneous EMR databases, for large-scale pharmacogenomic studies. The Informatics for Integrating Biology and the Bedside (i2b2) is a National Center for Biomedical Computing based at Partners Healthcare System. I2b2 has developed a scalable informatics framework to enable clinical researchers to repurpose existing EMR data for clinical and genomic discovery. In this study, we will collaborate with i2b2 to extend its informatics framework to the pharmacogenomics domain, by proposing the following specific aims: 1) Develop new methods to extract and model drug exposure and outcome information from EMR and integrate them with the i2b2 NLP components; 2) Build ontology tools to normalize and integrate pharmacogenomic data across different sites; 3) Conduct known and novel pharmacogenomic studies to evaluate and refine tools developed in Aim 1 and 2; and 4) Disseminate the developed informatics tools among pharmacogenomic researchers.

描述（由申请人提供）：大型电子病历（emr）临床应用的快速增长导致了观察性研究密集纵向数据集可用性的前所未有的扩展。最近，巨大的努力将电子病历数据库与存档的生物材料联系起来，以加速个性化医疗的研究。与EMR相关的DNA生物库已经确定了导致疾病风险的常见和罕见的遗传变异。一个尚未被广泛探索的有吸引力的愿景是将emrs相关的生物库用于药物基因组学研究，以确定遗传变异与药物功效和毒性之间的关联。电子病历中包含的数据的纵向性质使其成为量化药物结果（疗效和毒性）的理想选择。人们已经在努力将这些电子病历跨机构地联系起来，并为治疗结果的大规模研究标准化表型的定义，特别是在常规临床护理的背景下。尽管取得了成功，但基于EMR的药物基因组学研究往往受到其数据密集型性质的阻碍——从多个异构EMR数据库中提取和整合数据，用于大规模药物基因组学研究，既耗时又昂贵。整合生物学和床边信息学（i2b2）是一个基于伙伴医疗保健系统的国家生物医学计算中心。I2b2开发了一个可扩展的信息学框架，使临床研究人员能够重新利用现有的EMR数据进行临床和基因组发现。在本研究中，我们将与i2b2合作，通过提出以下具体目标，将其信息学框架扩展到药物基因组学领域：1)开发新的方法，从EMR中提取和模拟药物暴露和结果信息，并将其与i2b2 NLP组件集成；2)构建本体工具，对不同站点的药物基因组学数据进行规范化和整合；3)开展已知的和新的药物基因组学研究，以评估和完善目标1和目标2中开发的工具；4)在药物基因组学研究人员中推广开发的信息学工具。

项目成果

Semantic Role Labeling of Clinical Text: Comparing Syntactic Parsers and Features.

临床文本的语义角色标记：比较句法解析器和特征。

• 发表时间: 2016
• 期刊: AMIA ... Annual Symposium proceedings. AMIA Symposium
• 作者: Zhang,Yaoyun;Jiang,Min;Wang,Jingqi;Xu,Hua
• 通讯作者: Xu,Hua

Temporal data representation, normalization, extraction, and reasoning: A review from clinical domain.

• DOI: 10.1016/j.cmpb.2016.02.007
• 发表时间: 2016-05
• 期刊: Computer methods and programs in biomedicine
• 影响因子: 6.1
• 作者: Madkour M;Benhaddou D;Tao C
• 通讯作者: Tao C

Developing Customizable Cancer Information Extraction Modules for Pathology Reports Using CLAMP.

使用 CLAMP 开发用于病理报告的可定制癌症信息提取模块。

• DOI: 10.3233/shti190383
• 发表时间: 2019
• 期刊: Studies in health technology and informatics
• 作者: Soysal,Ergin;Warner,JeremyL;Wang,Jingqi;Jiang,Min;Harvey,Krysten;Jain,SandeepKumar;Dong,Xiao;Song,Hsing-Yi;Siddhanamatha,Harish;Wang,Liwei;Dai,Qi;Chen,Qingxia;Du,Xianglin;Tao,Cui;Yang,Ping;Denny,JoshuaCharles;Liu,Hongfa
• 通讯作者: Liu,Hongfa

An Empirical Study for Impacts of Measurement Errors on EHR based Association Studies.

测量误差对基于 EHR 的关联研究影响的实证研究。

• 发表时间: 2016
• 期刊: AMIA ... Annual Symposium proceedings. AMIA Symposium
• 作者: Duan,Rui;Cao,Ming;Wu,Yonghui;Huang,Jing;Denny,JoshuaC;Xu,Hua;Chen,Yong
• 通讯作者: Chen,Yong

Evaluating phecodes, clinical classification software, and ICD-9-CM codes for phenome-wide association studies in the electronic health record.

• DOI: 10.1371/journal.pone.0175508
• 发表时间: 2017
• 期刊: PloS one
• 影响因子: 3.7
• 作者: Wei WQ;Bastarache LA;Carroll RJ;Marlo JE;Osterman TJ;Gamazon ER;Cox NJ;Roden DM;Denny JC
• 通讯作者: Denny JC