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Crusading against Breast Disorders through Prevention, Diagnosis, Treatment and Research
  Clinical CareRisk ReductionTissue BankingFocused ResearchBiomedical Informatics  

Biomedical Informatics

Pillar Specific Objectives:

  • Develop and implement a clinically-relevant prospective, longitudinal computerized database for use in patients with all types of breast care needs.
  • Link this database information through the Internet to data set at a rural primary breast care center with appropriate security and firewall protections.
  • Develop the database to allow for "on-the-fly," relational, clinically-relevant statistical analysis.
  • Develop an informatics companion to the prospective serum / breast tissue bank.

The biomedical informatics effort is a collaborative development effort between Walter Reed Army Medical Center, Windber Research Inistitute and Inforsense, driving the development of a comprehensive data warehouse storing clinical and molecular data related to breast disease This is a resource for all CBCP investigators and is exportable for use by other investigators, programs, and organ sites. The data warehouse uniquely integrates clinical data with genomic and proteomic analysis of patient samples and is being extended to incorporate an image repository. This is being developed in close collaboration with industry leaders in the high-end database field, specifically Inforsense and Concentia Digital. Extensive efforts to model the pathways of breast cancer and its risk factors are underway at Windber with consultation from Walter Reed.

CBCP tracks the genomic and proteomic experiments of microarray, genotyping, DNA sequencing and 2 Dimensional Difference in Gel-Electrophoresis/Mass Spectrometry. In addition, CBCP tracks operations at the clinical end from patient enrollment and questionnaire completion, to specimen collection, preparation and shipping. CBCP also tracks research activities including sample and questionnaire receiving, double data entry, tissue banking, and sample preparation, including laser capture microdissected tissue. Each blood or solid tissue specimen has a unique sample ID that provides a link to the donor’s corresponding clinical information. This unique ID also serves as a link that allows for experimental data tracking (e.g., DNA and RNA processing).

CBCP operates a reporting system with canned reports for each platform. Examples of such reports include the number of subjects enrolled in each protocol, number of blood samples from patients meeting certain criteria, number of breast cancer tissues meeting certain criteria and details of the samples with which microarray experiments have been conducted. There is also an ad hoc query system to allow a user to develop a specific report if it is not already available.

Biomedical Informatics

Hai Hu, Ph.D.The Department of Biomedical Informatics, under the direction of Hai Hu, Ph.D., shoulders two responsibilities in the Institute; one is to provide informatics and analytical support to the institute’s daily operations, and the other is to conduct biomedical informatics research. WRI is equipped with multi-processor computer systems in both Windows and Unix for development, testing, and production. The currently hosted applications include a Laboratory Information Management System (LIMS), a data warehouse, and a variety of commercial software and in-house developed application tools.

LIMS

WRI currently deploys the Laboratory Workflow System (LWS) from Cimarron Software (Salt Lake City, UT) to track genomic and proteomics experiments involving microarray, genotyping, DNA sequencing, and 2-Dimensional Difference in Gel-Electrophoresis/Mass Spectrometry (2D-DIGE/MS). In addition, WRI co-developed, with Cimarron, a Clinical LWS (CLWS) system to track operations at the clinical end. The CLWS connects clinical data to wet-lab based operations. WRI is conscientious of new technologies that appear on the horizon constantly, and is making efforts to enhance LIMS capabilities to support the new technologies being deployed at the Institute.

Data warehouse and data models

WRI generates a large amount of genomic and proteomic experimental data in addition to the clinical data collected. A hybrid data warehouse has been envisioned to integrate and federate internal data from all the platforms in addition to external public data for integrative biomedical informatics research. The current development, in collaboration with InforSense Ltd. (London, UK), is Oracle based. A production version of this data warehouse, focusing on clinical data with an On-Line Analytical Processing tool (OLAP), has been released for use by WRI and its partners.

A questionnaire-based data warehouse focusing on breast disease studies has been developed and deployed. To improve the data warehouse for better handling of temporal data and easy expansion to support future clinical/translational projects, WRI started to develop a generalized patient-centric, object-oriented data model containing disease-independent (such as demographics) and disease-specific objects, including temporal and non-temporal objects. This new data model will allow for the easy dissection of study participants’ clinical and molecular data. In addition, when a new disease type is studied, most of the new data can be stored in existing data objects and only a few new disease-specific objects need to be developed, thus allowing easy adaptation of the objects to new disease studies. The same principles apply to the design of new questionnaires using such a data object structure.

QA/QC

WRI holds the opinion that the quality of the data lays the foundation of the subsequent data analysis and experiments. They are determined to strive for the highest data quality. To obtain high-quality data many QA/QC procedures have been embedded into SOPs. For example, the clinical QA program consists of: 1) a visual inspection of missing values and obvious inconsistencies, 2) double data-entry to reduce data entry errors, and 3) a computer program that deploys established QA metrics to check for data integrity across the entire questionnaire. A microarray QA program can identify outlier slides from a population of similar slides. Additional QA programs have been developed or are in the process of being developed to ensure the quality of the data generated at WRI.

Research projects and new application developments

Research projects span across clinical, genomic, and proteomic areas. WRI not only helps lab scientists design experiments, perform QA, and conduct data analysis, but also carries out biomedical informatics research. Since biomedical informatics research is relatively new, not all the studies can be conducted using existing applications, so novel tools need to be developed. The following is a list of a few active research and development projects:

  • A study on pathology diagnosis co-occurrence and the development of novel tools to visualize study results
  • Use of Gene Ontology-derived similarity measures for quantitative characterization of direct and indirect protein interactions within human regulatory pathways
  • Neural network modeling using clinical and molecular study data for patient classifications
  • Development of a new LC-MS data analysis method
  • Development of a Quality Assurance Issue Tracking (QAIT) system

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