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

• 批准号: 8034678
• 负责人: SIMON SHERMAN
• 金额: $ 30.19万
• 依托单位: UNIVERSITY OF NEBRASKA MEDICAL CENTER
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-04-01 至 2015-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8034678
• 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; 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

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. PUBLIC HEALTH RELEVANCE: Pancreatic Cancer (PC) is the fourth leading cause of cancer death in both men and women. This project is aimed to significantly enhance the biomedical computing infrastructure for PC research to make it a platform for the development of novel hypotheses and studies aimed to identify PC risk factors and predictors of PC survival, and to determine best practices for PC therapies.

描述(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完成，并得到PI实验室工作人员的支持。胰腺癌合作登记处(PCCR)是这一基础设施的核心，它是一个基于Web的软件系统，旨在收集、验证和在世界各地的癌症中心之间共享胰腺癌相关数据。目前，有九个中心正在使用PCCR，参与中心的数量还在继续增长。使用这一基础设施，已经收集了2000多名个人电脑和正常(非个人电脑)受试者的人口统计、生活方式、生活质量、饮食偏好、体力活动、家族史、遗传和医学数据以及治疗和手术数据。 该项目的主要目标是大幅加强PC生物医学计算基础设施，使其能够：(I)易于升级、维修和与其他相关系统互操作；(Ii)符合对数据收集、访问、挖掘、管理和共享的新要求；以及(Iii)一个可用于发展新的假设和研究的计算平台，旨在更好地了解PC现象，确定PC生存的风险因素和预测因素，以及确定PC疗法的最佳实践。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主题词库(NCIT)和医学临床术语系统化术语(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。即将创建的PC本体将扩展NCIT和CADSR对PC领域的覆盖。目标2：重新设计PCCR。重新设计PCCR的需要是由NIH对系统互操作性和数据共享的新要求决定的。这一目标计划的活动将使这一基础设施：(I)在语义和句法上可与其他相关工具互操作；(Ii)易于升级和修复；(Iii)符合数据收集、访问、挖掘、管理和共享的新标准；(Iv)与用于管理生物样品数据的caTIssue Suite相结合；以及(Iv)具有有利于数据可视化、数据挖掘和统计分析的高级数据报告功能。目标3：为计算机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，以帮助研究人员：(I)更好地了解PC现象；(Ii)根据流行病学数据以及身体和放射检查的结果，确定是否有必要进一步调查某一对象发生PC的可能性；(Iii)选择最佳的个性化PC治疗；以及(Iv)预测具有某些特征的患者在被诊断为PC后的存活率，届时将使用特定的治疗方法。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PC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，都需要开发实用的方法并提供足够的资源。这一目标的重点是确定持续维护和支持促进个人计算机研究的计算活动所需的最适当程序。 公共卫生相关性：胰腺癌(PC)是导致男性和女性癌症死亡的第四大原因。该项目旨在显著增强PC研究的生物医学计算基础设施，使其成为开发新假设和研究的平台，旨在确定PC存活的风险因素和预测因素，并确定PC治疗的最佳实践。