# Presentation: 498434

## caTRIP Scientific Overview and Demo

*Patrick McConnell*
*Duke Comprehensive Cancer Center*

## Agenda

- Background
- Scientific use cases
- Datasets and tools
- Architecture
- Demo
- Features and timelines

## Who is involved

- Duke Bioinformatics
- Jamie Cuticchia (PI)
- Patrick McConnell (lead architect)
- Duke Information Systems
- Bob Annechiarico (PM)
- Wilma Stanley (developer)
- Mark Peedin (developer)
- Mohamad Farid (DBA)
- Jeff Allred (IT manager)
- Duke Pathology
- Raj Dash (domain expert)
- Chris Hubbard (developer)
- Duke CALGB
- Kimberly Johnson (DataMart liaison)

- Semantic Bits
- Ram Chilukuri (lead developer)
- Vinay Kumar (developer)
- Sanjeev Agarwal (developer)
- Srini Akkala (developer)
- 5 AM Solutions
- Bill Mason (developer)
- 3rd Millennium
- Julie Klemm (ICR WS lead)
- NCI
- Carl Shaefer (NCI rep)
- Subha Madhavan (caIntegrator PM)

## What is translational research?

**Bench-to-Bedside**
- Wikipedia (the source of all knowledge):*Translational medicine is a branch of medical research that attempts to more directly connect basic research to patient care.*
- Basic research occurs in the lab
- Patient care occurs in the clinic

## Translational research extension

- Also from Wikipedia:*Translational medicine can also have a much broader definition, referring to the development and application of new technologies in a patient driven environment - where the emphasis is on early patient testing and evaluation.**...facilitate the interaction between basic research clinical medicine, particularly in clinical trials.*
- Our focus will be on connecting existing data systems, including basic science data, to enhance patient care

## Initial problem scenario

- Outcomes analysis: using data from existing patients to inform the treatment of another patient
- Leverage clinical, pathology, tissue, and basic science data
- Scenario:Patient A enters the clinic.  What treatments were applied with success on other patients with similar characteristics (race, sex, symptoms, pathology results, adverse events, biomarkers).

## Scientific use cases

- Find available tumor tissue
- caTissue CORE: protocol #, pathological status, clinical diagnosis
- CAE: ER, PR, Her-2/neu, EGFR status
- Find factors of survival
- Cohorts of patients who have survived a certain number of years following their diagnosis
- Tumor registry: dates of diagnosis/treatment/death, nodal/distant metastasis status, grade of tumor
- CAE: ER, PR, Her-2/neu, EGFR status
- SNP: BRCA1/BRCA2 status

## Scientific use cases

- Determine the distribution of disease factors over time
- Factors that may contribute to or reflect progression of a disease state
- Tumor registry: dates of diagnosis/treatment/death, nodal/distant metastasis status, grade of tumor
- CAE: ER, PR, Her-2/neu, EGFR status
- Find patients for trials
- Example is that of the triple negative hormone
- Tumor registry: dates of diagnosis/treatment/death, nodal/distant metastasis status, grade of tumor
- CAE: ER, PR, Her-2/neu, EGFR status

## Scientific use cases

- Determine correlation of factors pre and post surgery
- Patients that have particular factors change before and after surgery
- Tumor registry: dates of surgery
- CAE: ER, PR, Her-2/neu, EGFR status
- Find pathology reports of interest
- Tumor registry: dates of diagnosis/treatment/death, nodal/distant metastasis status, grade of tumor
- CAE: ER, PR, Her-2/neu, EGFR status
- caTIES: pathology report

## Scientific use cases

- Find SNP results correlated with factors
- Tumor registry: nodal/distant metastasis status, grade of tumor
- CAE: ER, PR, Her-2/neu, EGFR status
- SNP: BRCA1/2 status, genotype finding, gene biomarker

## Duke databases

- Medical Assistant on the World Wide Web (MAW3)
- Entity-centric database
- Tissue banking, pathology, and some clinical annotations
- Tumor Registry
- Relational database
- Endpoint data since 1980
- Genetic Modifiers of BRCA1 and BRCA2 (GEMS)
- SNP Illumina flat-files
- Investigation to identify factors that influence the incidence of breast cancer in germline BRCA1/2 mutation carriers
- Decision Support Repository (DSR) (maybe)
- Data warehouse
- Patient clinical data, crossing all medical specialties

## caBIG Tools

- Tissue bank: **caTissue CORE**
- Clinical annotations: **CAE**
- Pathology reports: **caTIES**
- Endpoint/treatment: **Tumor Registry**
- SNP: **caIntegrator CGEMS**

## caTRIP Architecture

- MAW3

- Tumor Registry

- SAS, Illumina

- caTIES

- CAE

- caTissueCORE

- TR

- CGEMSSNP

- Duke

- Domain Grid Services

- Distributed Query Engine

- query

- discover

- GUI

- IndexService

- IdPService

- Core Grid Services

- Domain Controller

- authenticate

- caTissue CORE

- caTIES

- CAE

- TR

- caIntegrator

## Demo

## Demo Architecture

- MAW3

- Tumor Registry

- SAS, Illumina

- caTIES

- CAE

- caTissueCORE

- TR

- CGEMSSNP

- Duke

- Domain Grid Services

- Distributed Query Engine

- query

- discover

- GUI

- IndexService

- IdPService

- Core Grid Services

- Domain Controller

- authenticate

- caTissue CORE

- caTIES

- CAE

- TR

- caIntegrator

## Demo queries

- red=attribute, blue=class, black=filter criteria
- _caTissue Core:_ What are all the tissue specimens where tissue site is breast?
- _caTissue CAE:_ What are all the participants having total score of Nottingham Histopathalogic Grade greater than 5?
- _caTissue Core & caTissue CAE:_ What are all the tissue specimens that are available from patients having total score of Nottingham Histopathalogic Grade greater than 5?
- Review in the models

## Implementation details

- GUI
- Drag-and-drop and drop-down menu interfaces
- Metadata driven (caDSR service, metadata extract)
- Discovery API to find services via IndexService
- Java Webstart application
- Distributed query engine
- Decomposes DCQL into CQL
- Aggregates and joins
- Domain services
- caCORE SDK-built silver services
- caGrid Introduce-built grid services
- HQL CQL-processor
- Oracle backend

## Future implementation details

- GUI
- IdP service for authentication
- Customized reporting
- Saving/sharing queries
- Synchronizing queries between simple and advanced query builders
- Drop-down menus for enumerated value domains
- Drop-down menus for available values
- DQE
- Will use generic grid client, XML results
- Enhanced query optimization
- Domain services
- CSM for authorization
- Common auditing/logging module

## Timelines

- Phase 1 (5/2006-11/2006)
- Demonstrable prototype
- All services
- Test data, some real data
- Limited functionality
- Security, generic DQE, reporting
- Limited use cases
- Phase 2 (11/2006-5/2006)
- Production system
- Full functionality, use cases
- All data exposed at Duke
- Breast Cancer DataMart

## For more information

- GForge (_[http://](http://gforge.nci.nih.gov/projects/catrip/)__[gforge.nci.nih.gov/projects/catrip](http://gforge.nci.nih.gov/projects/catrip/)__[/](http://gforge.nci.nih.gov/projects/catrip/)_)
- Wiki
- Document manager
- File manager
- Mailing lists
- catrip-general, catrip-user, catrip-developer
- CVS (cvs -d :ext:*NAME*@cbiocvs2.nci.nih.gov checkout *catrip*)

## Backup slides

## Service implementation

- domainmodel

- caCORE SDK

- CQL Engine

- database

- Object-relational mapping

- Index Service

- caGrid Data Service

- Distributed Query Engine

- advertise

- advertise

- CQL Query

## Distributed query engine overview

- DCQL

- Distributed Query Engine

- CQL

- CQL

- CQL

- caGrid data service

- caGrid data service

- caGrid data service

- database

- database

- database

- data objects

- data objects

- data objects

- data objects

## Security overview

- caGrid Authentication Service

- SAML Assertion

- User Credentials

- Dorian

- Duke Authentication Plugin

- Duke Domain ControllerNT Security

- Grid Data Service

- User Grid Certificate

- CSM

- database

| Grid User | App User |
| --- | --- |
|  |  |
|  |  |
|  |  |
|  |  |

- authentication

- authorization

- existing application security

- new security model

## Breast Cancer DataMart (Phase II)

- NCI-supported Cooperative Groups
- Will provide a data-mining capability that would allow contemporaneous and frequent analyses of pooled breast cancer research data from the contributing Cooperative Groups
- The data includes general patient and protocol information, surgical procedures, disease description, and endpoints in treatment
- The Breast Cancer Data Mart is currently housed at the NCICB in a C3D database
- The ultimate programmatic access mechanism for this data will be the Clinical Trials Object Model (CTOM)
- Formal approval processes in place for access to the data in DataMart