# Presentation: 783433

## The caBIGTM Clinical Trials Management Systems WorkspaceJohn SpeakmanMemorial Sloan-Kettering Cancer Center(SpeakmaJ@mskcc.org)

## Translating Molecular Understanding to Patient Outcomes – how are we doing?

- Deaths per 100,000 people declining 1% per year
- Five year survival 63%; ten million cancer survivors in USA *(Note: early detection doesn’t mean a longer life)*
_**BUT:**_
- Cancer is now #1 cause of death in Americans under age 85 *(age-adjusted)*
- 1,500 Americans die of cancer every day
- 1.5 million new cases every year
- Cost of cancer in USA estimated by NIH in 2004 at $190bn/yr (medical costs, lost productivity)

## Explosion of knowledge from biological research, continued growth in research spending
Slowdown in innovative therapies reaching patients
as measured by the number of new submissions to FDA
“The [drug development] process has not kept up with basic scientific innovation”
8% of drugs entering Phase I get to the market
“For drugs entering human clinical trials for the first time between 1989 and 2002 [average] cost per new drug [was] $868 million [...] $500 million to more than $2,000 million [...]
Health Affairs 25, no. 2 (April 2006)

- Slowdown in innovative therapies reaching patients
- as measured by the number of new submissions to FDA
*“**The [drug development] process has not kept up with basic scientific innovation”*
- 8% of drugs entering Phase I get to the market
*“**For drugs entering human clinical trials for the first time between 1989 and 2002 [average] cost per new drug [was] $868 million [...] $500 million to more than $2,000 million [...]*
- Health Affairs 25, no. 2 (April 2006)

- FDA* (Innovation or Stagnation, aka Critical Path, Woodcock 2004):*

## National Cancer Advisory Board Clinical Trials Working Group Report (July 2005)

- “Re-engineering the Cancer Clinical Research Enterprise”
- Initiative:  Promote the establishment of national clinical trial information technology infrastructures that are fully interoperable with NCI’s cancer Biomedical Informatics Grid
- “The long-term goal is for all clinical trial sites either to migrate to the caBIGTM architecture or to develop interfaces and other required enhancements such that their IT architecture is fully interoperable with the caBIG standards-based infrastructure.”
- Initiative: Establish a comprehensive National Clinical Trials Database, developed in concert with caBIGTM, to hold:
- Descriptive information on trial status, clinical trial results, links to published or presented data
- Site submission will be “routine” within three years (i.e., by Sept. 2008)

## CTWG Standardization Initiatives

- Create Standard Clinical Research Tools
- Establish national cancer clinical trials IT infrastructure – standards and standards-based tools – (i.e., caBIGTM)
- In consultation with industry and FDA, develop standard Case Report Forms incorporating Common Data Elements
- Accessible through caBIGTM for unrestricted use
- Build a credentialing system for investigators and sites recognized by NCI and industry
- Firebird

## Automates and centralizes the 1572 registration process
Enables investigators to register online with sponsors
Proves the feasibility and value of CRIX

- Automates and centralizes the 1572 registration process
- Enables investigators to register online with sponsors
- Proves the feasibility and value of CRIX

**Firebird**

## What’s CRIX? Clinical Research Information Exchange

- Grew out of NCI-FDA Inter-Agency Oncology Task Force (IOTF)
- Collaboration to implement a common, standards-based electronic infrastructure for regulatory submission, review and analysis

## CRIX Objectives

- Less manual, paper processing in FDA
- Less time on orientation to data by FDA reviewers
- More auditable data
- Less ambiguity in communications of information
- More efficient submission based on standards
- Reproducible, custom datasets for analysis
- Reusable tools for analysis and review
- Easier cross-study analyses
- Less data redundancy
- Use of common standards across the entire community (government, industry, academia)
- Interoperability with caBIG data sets, tools, capabilities

## President’s Cancer Panel Report 2005

- There is “no academic base” to the conduct of clinical trials
- Translation: the discipline needs to have some *formality* imposed
- One part of this is harmonizing best practices
- Our attempt to impose formality within data representation is called BRIDG (Biomedical Research Integrated Domain Group)

## What is BRIDG?

- A strategic initiative involving caBIGTM and:
- the Clinical Data Interchange Standards Consortium (CDISC)
- Health Level Seven (HL7)
- 	to develop a single domain representation standard for clinical research
- i.e., a formal domain analysis model of the shared semantics of clinical research
- Will ensure semantic interoperability, e.g., “what’s a protocol?”
- BRIDG will incorporate existing CDISC standards
- In caBIGTM, BRIDG will form the basis of interoperable clinical trial tool development

## Today’s Clinical Trial Protocol

- Full-text protocol

*Adapted from Greg Anglin, Eli Lilly*

- Protocol Database

- PDF

- Paper

- RTF

- One full-text source presented several ways

## Example BRIDG Application:Tomorrow’s Clinical Trial Protocol could be a data layer in the full-text source

- BRIDG
- Data Layer

- ProtocolDatabase

- Protocol
- Document

***Consistency guaranteed***

## Domain priorities for caBIGTM pilot

**0**

**5**

**10**

**15**

**20**

**25**

**30**

**35**

**Clinical Data Management Tools & Databases**

- Staff Resources

**Distributed General Data Sharing & Analysis Tools**

**Translational Research Tools**

**Access to Data**

**Tissue & Pathology Tools**

- Center Integration & Management

- Common Data Elements (CDE) & Architecture

- Meta-Project

- Vocabulary & Ontology Tools & Databases

- Statistical Data Analysis Tools

- Visualization & Front-End Tools

- Remote/Bandwidth

**Proteomics**

**Microarray & Gene Expression Tools**

- Meeting

- Laboratory Information Management Systems (LIMS)

- Licensing Issues

**Pathways**

- High Performance Computing

- Integration

- Imaging Tools & Databases

- Database & Datasets

**Number of Needs Reported**

## Priority Areas Within CTMS

- Adverse Event Reporting
- Laboratory Interface
- Routine NCI Reporting (i.e., CDUS / Theradex, Summary 3 and 4)
- Financial / Billing
*Structured Protocol Representation*
*Study Calendar*
*Best Practices *

## 2006 Clinical Trial Tools Development Activities		

- Cancer Adverse Event Reporting System (caAERS)
- Patient Study Calendar System
- Laboratory Data Hub
- Making other CTMS systems caBIG compatible

## What’s available today

- Cancer Central Clinical Database (C3D)
- A soup-to-nuts clinical trial data management system
- Based on common data elements
- Host-it-yourself or ASP (hosted at NCI)
- Not free (based on Oracle®)
- Automatic lab values loading and CTC grading
- Extraction to Theradex and CDUS
- Based on template forms composed of CDEs

## Clinical Trials Management:  Three Levels of Interaction Based on Institutional Readiness

**New caBIG modules**

**Existing System:**
**Change Imminent**

**exchange data**

**caBIG Open Source**
**Core Functionality**

**Interoperable**
**caBIG Community**

**No Existing System**

**C3D Adoption**

**Additional**
**Functionality**

**Existing System:**
**No Change**

**caBIG compatibility**
**efforts with vendor**

**Additional**
**Functionality**

## Pilot Project : caMATCHPersonalized matching of patient medical histories to clinical trials

- A patient-centric online clinical trials matching program in a pilot project for breast cancer patients in the San Francisco Bay Area
- Sponsored by the University of California San Francisco and caBIGTM
- 2007 Relaunch: Nationwide listing of trials

## caMATCH: www.breastcancertrials.org

**Database**

**Trial Criteria**

- 3. Patient calls research site, sends Personal Health Record securely

- 1. Patient self-reports
- medical history

- 2. BCT returns matches
- with trial summaries,
- contact information

- 4. Patient Visits research site, research staff determine eligibility, patient elects whether to enroll

***Source: Elly Cohen, UCSF***

## SpeakmaJ@mskcc.org

- That’s it!

- http://integratedtrials.nci.nih.gov/ict/CTWG_report_June2005.pdf