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: 7898310
• 负责人: SIMON SHERMAN
• 金额: $ 31.27万
• 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/7898310
• 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 history of; Glossary; Goals; Heart; Imagery; Information Systems; Internet; Italy; Laboratories; Language; 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; Recruitment Activity; Registries; Research Infrastructure; Research Personnel; Resources; Risk Factors; Solid; Staging; Statistical Models; Strigiformes; Survival Rate; System; Systematized Nomenclature of Medicine; Time; Training; United States National Institutes of Health; Validation; Vision; 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（由申请人提供）：已经开发了胰腺癌（PC）研究的生物医学计算基础设施，并得到了PI实验室的工作人员的支持。胰腺癌协作注册表（PCCR）是一种基于网络的软件系统，旨在在世界各地的癌症中心之间收集，验证和共享与胰腺癌相关的数据 - 是该基础设施的核心。目前，有9个中心正在利用PCCR，参与中心的数量继续增长。使用这些基础设施，人口统计，生活方式，生活质量，饮食偏好，体育锻炼，家族史，遗传和医学数据以及有关2000多个PC和正常（无PC）受试者的治疗和手术数据。 该项目的主要目的是显着增强PC生物医学计算基础架构，以使其易于升级，可修复和与其他相关系统互操作； （ii）符合对数据收集，访问，采矿，管理和共享的新兴要求； （iii）一个计算平台，可用于开发旨在更好地理解PC现象，确定PC风险因素和PC生存的预测因素并确定PC疗法的最佳实践的计算平台。为了实现这一目标，将实现以下目标。目标1：开发PCCR系统的受控词汇和本体学。 PCCR词汇表中的数千个术语将与癌症数据标准存储库（CADSR），NCI词库（NCIT）和医学临床术语（SNOMED CT）的术语进行协调。这些术语之间的本体论关系将使用Web本体论语言（OWL）创建。将要创建的PC本体将扩展NCIT和CADSR对PC域的覆盖范围。目标2：重新设计PCCR。对重新设计的需求是PCCR是由对系统和数据共享的互操作性的新的NIH要求决定的。在此目标中计划的活动将使此基础架构：（i）语义和句法在其他相关工具上可互操作； （ii）易于升级和可维修； （iii）符合数据收集，访问，采矿，管理和共享的新标准； （iv）与Catissue Suite一起用于管理生物测量数据； （iv）具有高级数据报告功能有益于数据可视化，数据挖掘和统计分析。目标3：开发PC研究的统计模型和计算工具。该目标的长期目标是开发可靠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）根据流行病学数据和物理和放射学检查的发现，确定需要进一步研究受试者PC的可能性； （iii）;选择最佳个性化PC治疗； （iv）在使用特定治疗的情况下，在被诊断为PC后具有某些特征的患者的存活率预测。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计算基础架构的系统，招募新中心，用户培训，数据收集，数据安全性，全面的数据验证和质量控制，数据共享和数据传播，需要开发实用方法并提供足够的资源。该目标的重点是确定持续维护和支持促进PC研究的计算活动所需的最合适的程序。 公共卫生相关性：胰腺癌（PC）是男性和女性癌症死亡的第四个主要原因。该项目旨在显着增强PC研究的生物医学计算基础架构，以使其成为开发新型假设和研究的平台，旨在鉴定PC危险因素和PC生存的预测因素，并确定PC疗法的最佳实践。