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Enhancing the Biomedical Computing Platform for Pancreatic Cancer Research

增强胰腺癌研究的生物医学计算平台

基本信息

批准号：
8607515
负责人：
SIMON SHERMAN
金额：
$ 29.02万
依托单位：
UNIVERSITY OF NEBRASKA MEDICAL CENTER
依托单位国家：
美国
项目类别：
财政年份：
2010
资助国家：
美国
起止时间：
2010-04-01 至 2016-01-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8607515
关键词：
Biomedical Computing Cancer Center Cancer Etiology Caring Cessation of life Characteristics Clinical Communities Computer software Controlled Vocabulary Coupled Data Data Collection Data Reporting Data Security Databases Development Diagnosis Diet Engineering Epidemiology Family Glossary Goals Heart Imagery Information Systems Italy Laboratories Life Style Maintenance Malignant Neoplasms Malignant neoplasm of pancreas Medical Genetics Methods Mining NCI Thesaurus Online Systems Ontology Operative Surgical Procedures Patients Physical activity Procedures Production Quality Control Quality of life Questionnaires Recording of previous events Recruitment Activity Registries Research Infrastructure Research Personnel Resources Risk Factors Solid Staging Statistical Computing Statistical Models Survival Rate System Systematized Nomenclature of Medicine Time Training United States National Institutes of Health Validation Vision Web Ontology Language Woman anticancer research base cancer care cancer risk cancer therapy data mining data sharing design interoperability men novel preference public health relevance relational database repository software systems tool

项目摘要

DESCRIPTION (provided by applicant): The biomedical computing infrastructure for pancreatic cancer (PC) research has been developed and is being supported by the staff of the PI's laboratory. The Pancreatic Cancer Collaborative Registry (PCCR) - a Web- based software system that is designed to gather, validate, and share pancreatic cancer-related data among cancer centers around the world - is at the heart of this infrastructure. At the present time, nine centers are utilizing the PCCR and the number of participating centers continues to grow. Using this infrastructure, demographic, lifestyle, quality of life, dietary preferences, physical activities, family history, genetic and medical data, as well as treatment and surgery data on more than 2,000 PC and normal (PC-free) subjects has already been collected. The main objective of this project is to significantly enhance the PC biomedical computing infrastructure to make it: (i) easily upgradeable, repairable and interoperable with other related systems; (ii) compliant with the emerging requirements for data collection, access, mining, management and sharing; and (iii) a computing platform useful for developing novel hypotheses and studies aimed at better understanding the PC phenomena, identify PC risk factors and predictors of PC survival, and determine best practices for PC therapies. To achieve this objective, the following aims will be accomplished. Aim 1: Development of a controlled vocabulary and ontology for the PCCR System. Several thousands of terms from the PCCR glossary will be harmonized with terms from the Cancer Data Standards Repository (caDSR), the NCI Thesaurus (NCIT), and the Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT). The ontological relationships between these terms will be created using Web Ontology Language (OWL). The PC Ontology to be created, will extend NCIT's and caDSR's coverage of the PC domain. Aim 2: Re-engineering the PCCR. The need for the re-engineering the PCCR is dictated by new NIH requirements on the interoperability of the systems and data sharing. The activities planned in this aim will make this infrastructure: (i) semantically and syntactically interoperable with other related tools; (ii) easily upgradeable and repairable; (iii) compliant with new standards for data collection, access, mining, management, and sharing; (iv) coupled with the caTissue Suite for managing biospecimen data; and (iv) having advanced data reporting functionality beneficial for data visualization, data mining, and statistical analysis. Aim 3: Development of statistical models and computing tools for the PC research. The long-term goal of this aim is to develop a solid statistical basis and computing tools that will assist researchers in: (i) better understanding the PC phenomena; (ii) determining the need to further investigate the likelihood of PC for a subject, based on the epidemiological data and findings from physical and radiological examinations; (iii); choosing the best personalized PC treatment; and (iv) prediction of the survival rate for patients with certain characteristics after being diagnosed with PC, when a particular treatment will be used. Aim 4: Providing continuous maintenance of the biomedical computing platform and support of the PC research. Maintenance of the systems forming the PC computing infrastructure, recruiting new centers, user training, data collection, data security, comprehensive data validation and quality control, data sharing, and data dissemination, require the development of practical methods and contributing sufficient resources. This aim is focused on determining the most suitable procedures necessary for continuous maintenance and support of the computing activities promoting the PC research.

描述（由申请人提供）：胰腺癌（PC）研究的生物医学计算基础设施已经开发，并得到PI实验室工作人员的支持。胰腺癌协作登记处（PCCR）是一个基于网络的软件系统，旨在收集、验证和共享世界各地癌症中心的胰腺癌相关数据，是这一基础设施的核心。目前，有9家临床试验机构正在使用PCCR，参与临床试验机构的数量还在继续增长。利用这一基础设施，已经收集了2，000多名PC和正常（无PC）受试者的人口统计学、生活方式、生活质量、饮食偏好、体育活动、家族史、遗传和医疗数据以及治疗和手术数据。该项目的主要目标是大大加强个人计算机生物医学计算基础设施，使之：㈠易于安装、维修和与其他相关系统互操作; ㈡符合数据收集、访问、挖掘、管理和共享方面的新要求;和（iii）一个计算平台，用于开发新的假设和研究，旨在更好地理解PC现象，确定PC的危险因素和PC生存的预测因素，并确定PC治疗的最佳实践。为实现这一目标，将实现以下目标。目标1：为PCCR系统开发受控词汇表和本体。PCCR词汇表中的数千个术语将与癌症数据标准库（caDSR）、NCI词库（NCIT）和系统化医学临床术语命名法（SNOMED CT）中的术语协调一致。这些术语之间的本体关系将使用Web本体语言（OWL）创建。要创建的PC Ontology将扩展NCIT和caDSR对PC领域的覆盖。目标2：重新设计PCCR。重新设计PCCR的必要性取决于NIH对系统互操作性和数据共享的新要求。为此计划开展的活动将使这一基础设施：㈠在语义和语法上与其他相关工具互操作; ㈡易于安装和维修; ㈢符合数据收集、访问、挖掘、管理和共享的新标准; ㈣与caTissue Suite相结合，用于管理生物标本数据;以及（iv）具有有益于数据可视化、数据挖掘和统计分析的高级数据报告功能。目标3：为PC研究开发统计模型和计算工具。这一目标的长期目标是开发坚实的统计基础和计算工具，以协助研究人员：（一）更好地了解PC现象;（二）根据流行病学数据和体检及放射学检查的结果，确定是否需要进一步调查受试者患PC的可能性;（三）选择最佳的个性化PC治疗;（四）确定是否需要进一步调查受试者患PC的可能性。以及（iv）当将使用特定治疗时，预测具有某些特征的患者在被诊断患有PC后的存活率。目标4：提供生物医学计算平台的持续维护和PC研究的支持。维护构成个人计算机计算基础设施的系统、招募新的中心、用户培训、数据收集、数据安全、全面的数据验证和质量控制、数据共享和数据传播，都需要制定切实可行的方法并提供足够的资源。这一目标的重点是确定必要的持续维护和支持的计算活动，促进PC研究的最合适的程序。