National C

U.S. DEPARTMENT 

OF HEALTH AND 

HUMAN SERVICES

National Institutes 

of Health

National C

U.S. DEPARTMENT 

OF HEALTH AND 

HUMAN SERVICES

National Institutes 

of Health

The caBIGTM

Pilot Phase

Report: 2003-2007
shortcomings, and to set the stage for broader adoption as it realizes the potential for 

transforming cancer research in coming years.

The Report is based on a review of caBIGTM–related documents and presentations 

produced by NCICB in recent years; materials about caBIGTM produced by the caBIGTM 

general contractor and other external entities; and one-on-one discussions held 

during the spring and summer of 2007 with caBIGTM participants and observers from 

government, academe, and industry. The NCICB is grateful to the many individuals 

who shared their knowledge and insights about caBIGTM for the Report.

November 2007
The caBIGTM

Pilot Phase

Report: 2003-2007
2

The Vision and Mission of caBIG . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

Overarching Objectives of caBIGTM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

The Principles of caBIGTM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 

caBIGTM Philosophy and Culture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

Pilot Phase Goals and Summary of Outcomes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

Financial Investment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

Chapter 2: Strategic Planning and Initiation .......................................................... 13

Strategic Approaches and Practices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

Key Participants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

Key Roles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

Assessment of Needs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

Launch Plan and Key Pilot Phase Deliverables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16

Case Study: caBIGTM License . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18

Chapter 3: Programs and Progress ................................................................... 20

Pilot Phase Stages . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20

Workspaces . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

The Development Cycle . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25

Funding Mechanism . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26

Progress on Deliverables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26

caBIGTM Connections to Other NCI Programs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27

caBIGTM Connections to External Programs and Organizations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28

Program Spotlight: Regulatory Data Exchange (RDE) Initiative . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28

Recognition of caBIGTM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30

Program Spotlight: BRIDG . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

caBIGTM in the Literature . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32

Case Study: The caBIGTM Community . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33

Chapter 4: Hindsight ................................................................................. 34

Program Management and Community Engagement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35

Communications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35

Business Processes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36

Software Development . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37

Role of the Private/For-profi t Sector . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 

Cultural Shifts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40

Chapter 5: Future Directions ......................................................................... 41

The Launch of the Enterprise Phase . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

caBIGTM Adoption Program . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

Enterprise Support Network . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

caBIGTM and the Patient Community . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42

caBIGTM as a Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43

Case Study: Early Adoption by Duke . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44
caBIGTM Pilot 

caBIGTM Initial Plan .......................................................................

caBIGTM Pilot Phase Key Activities . .......................................................

caBIGTM Workspace Organization . .......................................................

Representative Attendance on caBIGTM Workspace

Teleconferences 2004 through 2006/2007 ...............................................

caBIGTM Software Development Flow of Activities . .......................................

caBIGTM Annual Meeting Attendance 2004 – 2007 ........................................

caBIGTM Deliverables by Category ........................................................

caBIGTM Web site Visits ...................................................................

Future Directions for caBIGTM .............................................................

Figure 3. 

Figure 4. 

Figure 5. 

Figure 6. 

Figure 7. 

Figure 8. 

Figure 9. 

Figure 10. 

Figure 11. 

1

2

2

2

2

2

2

3

4
4

Over time, the need for a “worldwide web of cancer 

research,” as caBIGTM has been described, has become 

increasingly urgent. Cancer continues to be a major 

problem globally, and the vast amount of data that 

researchers must collect, analyze, and store continues 

to expand as the pace of discovery accelerates. 

The caBIGTM initiative has been an unprecedented 

eff ort. At the time of its launch, there was no such 

interconnected standardized biomedical informatics 

platform in place anywhere within the biomedical 

research community that could be used as an 

organizational or technical model. In that context, 

caBIGTM was—and continues to be—highly ambitious, 

especially in light of the cultural shifts within the 

research community that are required to make it 

a reality.

caBIGTM Goals and Outcomes

The caBIGTM initiative was formally launched in February 

2004 as a three-year Pilot, overseen by the NCI Center 

for Bioinformatics (NCICB).1 The objectives of the Pilot 

Phase were twofold: to test the ability of a complex 

informatics initiative to achieve measurable goals and 

deliverables toward enhancing cancer research, and to 

assess the opportunities and challenges of connecting 

a disparate biomedical community on a national 

and eventually international scale. Those objectives 

have been met, often beyond the expectations of the 

community, as follows:

• Goal: Illustrate that a spectrum of Cancer Centers 

with varying needs and capabilities can be joined

• Goal: Demonstrate that Cancer Centers, in 

collaboration with NCI, will develop new enab

software tools and systems to support multipl

research organizations.

• Outcome: More than 300 software component

have been delivered during the Pilot Phase, 

including over 40 end-user applications and a 

range of infrastructure components such as da

standards and software development toolkits. 

Over 45 biomedical datasets have been deliver

in caBIGTM compliant formats, derived from clin

and molecular studies, and are in use at severa

cancer research sites. These components were 

derived from over 5,000 analysis and requirem

gathering task orders issued to the community

 Due to the availability of this software at the cl

of the Pilot Phase, activities were under way in 

2007 to provide installation and support servic

1

 In 2007, NCI Center for Bioinformatics (NCICB) became part of the 

new overarching Center for Biomedical Informatics and Information 

Technology (CBIIT).

Attendance

2004 2005 2006 

0

1,000

500

169

366

784

caBIGTM Annual Meeting Attendance 2004 - 2007
caBIGTM Pilot 

are dependent on the sharing of data.

• Outcome: When caGrid (the data transmission 

network upon which caBIGTM works) was launched, 

several nodes (i.e., connection points where 

research organizations log onto the caBIGTM 

system) and software tools were available. As of 

June 2007, caGrid was extensively being used as 

a testing platform for the many caBIGTM software 

applications that will be grid-enabled to support 

the cancer research community in the 

Enterprise Phase.

• Goal: Create an extensible infrastructure that 

will continue to be expanded and extended to 

members of the cancer research community 

beyond the NCI-designated Cancer Centers.

• Outcome: NCICB has actively collaborated with NCI 

programs (such as SPOREs,2

 The Cancer Genome 

Atlas,3

 the Cooperative Groups,4 and Cancer 

Genetic Markers of Susceptibility5); other NIH 

Institutes and Centers (such as National Institute 

of Neurological Disorders and Stroke,6 National 

Human Genome Research Institute,7 National 

Heart, Lung and Blood Institute8

 and National 

Center for Research Resources9); other NIH-funded

 programs (such as Biomedical Informatics 

Research Network,10 and Clinical and Translational

Central Tenets of caBIGTM

Interoperability is central to caBIGTM; that is, 

compatibility among information technology 

tools used to collect, analyze, and share data. Thi

compatibility provides a means of linking togeth

all the scientists, clinicians, patients, and other 

participants so that they can conduct more dyna

collaborative, and ultimately more successful rese

Among the hallmarks of the caBIGTM initiative 

has been the building of community. From initial 

outreach to Cancer Centers to identify the most 

pressing research needs, to the organization of 

community-based workspaces encompassing 

multiple disciplines to organize activities to addr

those needs, to the process for development and 

testing of software tools, caBIGTM has been of and 

the cancer community.

 2 http://spores.nci.nih.gov/.

 3 http://cancergenome.nih.gov/index.asp.

 4 http://www.cancer.gov/cancertopics/factsheet/NCI/clinical-trials-

 cooperative-group.

 5 http://cgems.cancer.gov/.

 6 http://www.ninds.nih.gov

 7 http://www.genome.gov

 8 http://www.nhlbi.nih.gov

 9 http://www.ncrr.nih.gov/clinical_research_resources/.

Recognition of caBIG

• 40+ Peer-Reviewed Publications13 

• ComputerWorld Honors Program 200614

• Three reports from The NIH National Center 

for Research Resources, 200615 

10 http://www.nbirn.net/index_ie6.shtm.

11 http://ctsaweb.org/about.html.

12 http://www.ncri.org.uk/.

13 http://caBIG.nci.nih.gov/Library/Library/caBIG_Scientifi c_Pubs.h

14 http://www.cwhonors.org

15 http://www.ncrr.nih.gov/publications/informatics/caBIG.pdf; 

http://www.ncrr.nih.gov/publications/informatics/caBIG_

OpportunitiesAndChallenges_12-26-06.pdf; 

 http://www.ncrr.nih.gov/publications/informatics/caBIG-Plus_

ConceptualView_12-26-06.pdf
6

Another key characteristic has been the openness 

of the caBIGTM initiative, as refl ected in the open 

source nature of the standards and software and the 

open access to the initiative for any constituencies 

within the biomedical community who wished to 

participate. The caBIGTM initiative was also marked by 

the dynamic nature of its management structure and 

operations, which retained a highly fl exible capacity 

to change over time as conditions in the community 

changed, as well as to absorb lessons learned as the 

program evolved.

Moving into Enterprise Phase

The caBIGTM Pilot Phase concluded in March 2007, 

followed by a transition to an Enterprise Phase, which 

has built on caBIGTM accomplishments and lessons 

learned. In the Enterprise Phase, an expanding 

number of organizations—including additional 

Cancer Centers, the pharmaceutical and biotech 

community, and the commercial IT sector—are 

being invited to achieve connectivity via the broader 

adoption of caBIGTM tools, infrastructure, and 

interoperability framework. caBIGTM is also sharing 

its experience, expertise, and tools with the larger 

biomedical community to serve as a model, so that 

other disease-focused endeavors

Finally, while the caBIGTM initiative benefi ted 

from the participation of numerous patient 

advocates, caBIGTM itself has not been visibl

most cancer patients thus far. It is expected 

in the future, patients will benefi t from caBI

through its ability to facilitate selection of 

treatment and entry into clinical trials of 

experimental treatments, monitor for treatm

response and adverse eff ects, and monitor 

recurrence of disease.

Dr. John Niederhuber, Director of the Natio

Cancer Institute, predicts that “caBIGTM will d

clinical trials of the future. It will be the way 

bring genomics, proteomics, and clinical da

together for each patient in a clinical trial.”

01/01/04 01/01/05 01/01/06 01/01/07

0

9,437
caBIGTM Pilot 

by what we can see and touch—or by w

is revealed under a microscope—but at 

molecular level. It is not a question of if, 

rather when and how, Molecular Medic

translates into personalized care...

We cannot achieve this (translation) 

without great interconnectivity and 

coordination across the cancer enterpri

The Inception of caBIGTM 

In 2004, the National Cancer Institute launched 

the cancer Biomedical Informatics GridTM (caBIGTM) 

initiative as part of its mission to advance research on 

cancer and improve clinical outcomes for patients. 

NCI recognized that the ability to connect people, 

organizations, and data through information 

technology would be critical to fulfi lling NCI’s 

mission and to taking advantage of the research 

opportunities off ered by 21st century science. 

caBIGTM, overseen by the NCI Center for Bioinformatics 

(NCICB), began with a three-year Pilot Phase, in order 

to test the ability of a complex informatics initiative to 

achieve measurable goals and produce deliverables 

and to assess the opportunities and challenges of 

connecting a disparate biomedical community on a 

national and eventually international scale.

The caBIGTM initiative was an unprecedented 

eff ort. At the time of its launch, there was no such 

interconnected, standardized biomedical informa

platform in place anywhere within the biomedica

research community. Even within the academic 

medical research community, networked data sh

and analysis infrastructure were largely limited to 

particular departments or internal groups. These 

disparate groups did not link together all the var

research functions in a single institution, much le

link entire networks of institutions. In contrast wi

other national eff orts, such as in defense or feder

funded physics research, the nation’s biomedical 

research enterprise had never undertaken such a 

large Information Technology (IT) project. 

16 Andrew C. von Eschenbach, M.D., and Kenneth Buetow, Ph.D. (2

 “Cancer Informatics Vision: caBIGTM” Cancer Informatics 2006:2 (
8

In that context, the imperatives of the caBIGTM 

initiative were highly ambitious: to integrate the 

existing biological and clinical “silos” of cancer 

research activity; to integrate IT infrastructure, 

software, and data; and to integrate institutions and 

people, so that information could be transformed 

into knowledge at the requisite scale and speed of 

molecular-based translational research.

Cancer and the Shift to 

Molecular Medicine 

Cancer continues to be a major problem in both the 

United States and globally, and solutions are

still diffi cult to fi nd. Though progress has been 

made in the form of declining death rates for certain 

cancers and increasing 5-year survival rates for many 

others, 1,500 Americans die every day of cancer, and 

1.5 million Americans will hear the words “you have 

cancer”17 this year. 

support multiple research organizations;

• Demonstrate that Cancer Centers will actively 

use the grid and realize greater value in their 

cancer research endeavors by using this 

network to support powerful collaborations 

that are dependent on the sharing of data; and

• Create an extensive infrastructure that will 

continue to be expanded and extended to 

members of the cancer research community 

beyond the NCI-designated Cancer Centers.

for analyzing genes and proteins, and the 

advancement of systems biology have illuminate

cancer as a collection of many individually comp

diseases, each with its own molecular signature 

and characteristics. Such molecular understandin

of cancer is being translated into a new generatio

of individualized diagnostics and therapeutics.

The implications of these new molecular and 

technological approaches to understanding canc

and other diseases are far-reaching. Twentieth 

century medicine focused primarily on treatmen

attempted to diagnose disease based on 

morphologic and pathologic analysis of tissues a

a cellular level, and did not systematically connec

research with clinical care. The era of Molecular 

(“personalized”) Medicine in the 21st century 

focuses on understanding biological processes

18 http://progressreport.cancer.gov/index.asp. 

19 Kim Lyerly, M.D., Director, Duke Comprehensive Cancer Center, d

 on May 30, 2007.

“What is required in cancer research to fi n

defi nitive answers is a system to share da

and leverage all the events in the cancer 

world. It is impossible to succeed without 

embracing that notion. The concept of 

caBIGTM is, therefore, right on target.”19

Kim Lyerly, M.D.

Director, Duke Comprehensive Cancer Center

17 American Cancer Society, Cancer Fact and Figures 2007. 
caBIGTM Pilot 

Similarly, translational research—which transforms 

scientifi c discoveries arising from laboratory, clinical, 

or population studies into clinical applications to 

reduce cancer incidence, morbidity, and mortality20

—relies on IT connectivity to amass, analyze, and 

apply information.

The Challenges of Connectivity

While the era of Molecular Medicine can potentially 

increase opportunities for scientifi c breakthroughs 

and improved care, its implementation has faced

Clinical Trial

Management

Discovery

Research

Image Sharing

and Analysis

Tissue

Banking

Figure 1. Molecular Medicine: Selected Domains

Needed to Enable Translational Research 

20 http://www.cancer.gov/trwg/TRWG-defi nition-and-TR-continuum.

of data, and the ability to collect, analyze, share, a

integrate such quantities of biological data in rea

time is a prerequisite to biological understanding

But information technology within the biomedic

enterprise has been slow to develop and is rarely 

connected between laboratories even within a si

institution, much less between diff er

institutions. Frequently, the same typ

of biomedical data are collected by 

research groups using their own “ho

grown” information systems that do 

base their data models on any kind o

widely shared standard. Additionally

there are often no agreed-upon data 

models or standards within a single 

discipline, compounding the inabilit

to share data even among those wh

collect data using the same analytica

platform. The result of many such 

“disconnects” along the continuum o

translational research—from laborat

values, to epidemiological data, to 

clinical records, to biospecimen reco

to imaging data, to molecular data—

that vital scientifi c discoveries are no

made, and the pace of progress agai

cancer is slowed.

Thus, to address the complexities of 

cancer and these discontinuities of the research 

process, a 21st century cancer research enterprise 

requires interoperability; that is, access to integrat

tools to collect, analyze, and share data in standar
10

share data and knowledge to accelerate the discovery 

of new approaches to prevention, diagnostics, and 

therapeutics, which together will improve patient 

outcomes.

The mission of the caBIGTM initiative is to provide 

infrastructure for creating, communicating, and 

sharing bioinformatics tools, data, and research 

results, while using shared applications, shared data 

standards, and shared data models, all operating on 

a cancer community network (caGrid). Through this 

infrastructure, caBIGTM supports the development of 

new types of analysis within and across experiments 

and allows new forms of collaboration in which 

biomedical data sets are easily exchanged and more 

rapidly and effi ciently analyzed and integrated via an 

interoperable set of software tools.21

Overarching Objectives of caBIGTM

The transformation of the cancer research enterprise 

into a “worldwide web of information, people and 

institutions”22 is by defi nition a long-term endeavor. 

Thus, the initial objectives of caBIGTM at the highest 

level were to:

• Connect scientists and practitioners through a 

shareable, interoperable infrastructure;

• Develop standard rules, a unifi ed architecture, 

and a common language to more easily share 

information; and

• Open Access: Participation in caBIGTM and the 

products delivered by caBIGTM are open to all, 

enabling access to tools, data, and infrastructu

by the cancer and greater biomedical research 

communities.

• Open Development: Software development 

projects are assigned to particular participants

are informed iteratively with multiple opportu

for review, comment, further modifi cation, and 

development by the caBIGTM community. The 

materials that are associated with the planning

testing, validation, and deployment of caBIGTM 

tools and infrastructure are also open to the en

cancer research community.

• Open Source: The software code underlying 

caBIGTM tools developed with the support of th

NCI is available to software developers for use 

modifi cation. This software is licensed as open 

source to promote the reuse of existing code, 

hence optimizing the full benefi t of the researc

dollars spent. However, the open source licens

industry-friendly, allowing commercialization o

derivative products and fostering industry inte

and innovation, while still adhering to the prin

of open source for caBIGTM-funded activities (Se

Case Study: caBIGTM License)

• Federation: caBIGTM software and standards en

local organizations, such as Cancer Centers, to 

share data resources with the larger cancer car

and research community and to use resources 

contributed by others. On the grid, these resou

can be aggregated from multiple sites to appe

21 caBIGTM Primer, page 5, https://cabig.nci.nih.gov/overview/cabigprimer, accessed June 1, 2007.

22 Dr. Ken Buetow, NCI Associate Director for Bioinformatics and 

Information Technologies, “caBIGTM: Power of Connection,” 

 http://cabig.cancer.gov/resources/video.asp, accessed June 1, 2007.

23caBIGTM Primer p. 7, https://cabig.nci.nih.gov/overview/cabig-pri

accessed June 1, 2007.
caBIGTM Pilot 

 • Outcome: As of June 2007, there were over 

190 organizations participating in the caBIGTM 

community (See Appendix B for complete listin

This community includes 51 Cancer Centers; fe

agencies; and academic, not-for-profi t, and ind

entities, represented by close to 1,000 individua

• Demonstrate that Cancer Centers, in collabora

with NCI, can develop new enabling software 

tools and systems to support multiple research 

organizations.

 • Outcome: More than 300 software component

have been delivered during the Pilot Phase, 

including over 40 end-user applications, and a 

range of infrastructure components, such as da

standards and software development toolkits. 

45 biomedical datasets have been delivered in 

are built according to the community’s needs, and 

that the community faces the fewest barriers 

possible when adopting those solutions.

caBIGTM Philosophy and Culture

Under the supervision of the NCI Center for 

Bioinformatics, the caBIGTM initiative placed 

heavy emphasis on collaboration with its many 

constituencies, not only within the cancer research 

enterprise but also in the larger external environment 

of public and private biomedical informatics 

initiatives. Such collaboration was a primary factor 

in the inclusive nature of caBIGTM activities, refl ected 

in the program values of “open development” and 

“open access.” In fact, among biomedical data sharing 

initiatives, caBIGTM has distinguished itself by the 

focus on its constituent communities and its open 

approach to data sharing and development.

The concept of a “caBIGTM community” surfaced 

early in the Pilot Phase, and it drove not only 

the underlying strategy of the initiative but also 

much of its organization and culture. A plethora 

of mechanisms were employed to invite, engage, 

and sustain relationships between participants 

who previously had not interacted, from the fi rst 

step of information-gathering, through ongoing 

personal and electronic interactions. A wide diversity 

of participants—including informatics experts, 

clinicians, bench researchers, patient advocates, 

and senior executives—were welcomed to caBIGTM. 

The tools, knowledge, and expertise of the caBIGTM 

initiative have been freely shared among them.

24 Michael Becich, M.D., Ph.D., Chairman and Professor, Departme

Biomedical Informatics, UPMC, discussion on June 13, 2007.

“caBIGTM is the most signifi cant assembly 

of informatics minds for cancer ever 

assembled. And I have certainly met ma

people through it that I would never hav

had contact with otherwise. In fact... 

caBIGTM has transformed this communit

Michael Becich, M.D., Ph.D.

Chairman and Professor, Department 

of Biomedical Informatics

University of Pittsburgh School of Medicine
12

interoperability framework to NCI Cancer Centers. 

The future availability of these tools and datasets 

over caGrid will enable an increasing number of 

investigators to share knowledge as it emerges.

• Demonstrate that Cancer Centers will actively 

use the grid and realize greater value in their 

cancer research endeavors by using this network 

to support powerful collaborations that are 

dependent on the sharing of data.

• Outcome: When caGrid (the data transmission 

network upon which caBIGTM works) was launched, 

six nodes (i.e., connection points where research 

organizations log onto the caBIGTM system) and 

seven software tools/services were available. As of 

June 2007, caGrid included over 85 services being 

hosted or accessed by over 80 organizations, and 

it was extensively being used as a testing platform 

for the many caBIGTM software applications that 

will be grid-enabled to support the cancer research 

community in the Enterprise Phase.

• Create an extensible infrastructure that will 

continue to be expanded and extended to 

members of the cancer research community 

beyond the NCI-designated Cancer Centers.

 • Outcome: NCICB has actively collaborated with NCI 

programs (such as SPOREs,25 The Cancer Genome 

Atlas,26 the Cooperative Groups,27 and Cancer 

Genetic Markers of Susceptibility28); other NIH

Cancer Research Institute35). Wherever possible

interoperability with such initiatives has been 

sought, and caBIGTM tools and infrastructure ar

consistently made available for either adoption 

further development.

Financial Investment

The caBIGTM Pilot was funded by NCICB at the leve

$20 million annually for each of the three years fr

FY 2004 to 2006. 

29 http://www.ninds.nih.gov

30 http://www.genome.gov

31 http://www.nhlbi.nih.gov

32 http://www.ncrr.nih.gov/clinical_research_resources/.

33 http://www.nbirn.net/index_ie6.shtm.

34 http://ctsaweb.org

35 http://www.ncri.org.uk/.

25 http://spores.nci.nih.gov/.

26 http://cancergenome.nih.gov/index.asp.

27 http://www.cancer.gov/cancertopics/factsheet/NCI/clinical-trials-

 cooperative-group.

28 http://cgems.cancer.gov/.
caBIGTM Pilot 

Strategic Approaches and Practices

The following strategic approaches were defi ned and 

developed in the fi rst year, and they guided caBIGTM 

activities throughout the Pilot Phase:

• Establish a community of participants to serve 

as advisors about cancer research IT needs, as 

developers and adopters of the infrastructure and 

tools, and as disseminators of information about 

caBIGTM to their home institutions. The initiative 

should encourage and be able to manage the 

caBIGTM community growth steadily over time, and 

it should ensure that the community represented a 

diverse cross-section of disciplines and sectors.

• Allocate resources to ensure that, for each of the 

identifi ed stakeholder needs, an interoperable 

software tool would be available to link data from 

diverse scientifi c and clinical sources and support 

their Molecular Medicine research activities. An 

alternative approach—to focus single-mindedly 

on a small number of software tools in one or two 

key areas such as clinical trials or imaging—was 

thought to be less valuable, since seamless 

connectivity around the entire translational 

research process was the ultimate objective. It 

is important to note that this strategy was not 

intended to develop every software application

 from scratch; rather, where software applicatio

already existed, they were to be adopted and 

adapted to be “interoperable” with caBIGTM in o

to save time and resources.

• Recognize legacy IT systems to facilitate 

adoption. The initiative recognized the fact th

varying levels of investment in IT infrastructure 

had already taken place within the cancer rese

community in recent years, and that there wou

as a result, be varying paths to caBIGTM adoptio

Emphasis has been on interoperability with ca

rather than on urging institutions to “rip and 

replace” their existing IT capabilities.

• Balance caBIGTM project management betwe

top-down guidance from the NCICB and botto

up input from the grass-roots of the cancer 

community. In this way, caBIGTM could incorpor

the needs and expertise of the community wh

adhering to NCI’s core mission and sustaining 

effi cient project coordination.

• Leverage academic institutions for software 

development in order to keep the developmen

tools closely tied to the end-user base; howeve

fund such development eff orts via contracts, a

opposed to grants, in order to achieve the rigo

timelines and specifi c deliverables. This approa

organization de novo, adapting the attributes of 

other large-scale IT initiatives as appropriate.
14

Centers have helped shape and continue to he

shape caBIGTM priorities by gathering general n

and specifi c requirements; developing, refi ning

and testing standards, programming toolkits, a

software applications; providing data sets; and 

setting policy and guidelines. 

• Patient Advocates: Patient advocates from 

NCI’s CARRA (Consumer Advocates in Research 

and Related Activities) program and from othe

organizations have been active members of the 

caBIGTM community since its inception. CARRA 

was created to integrate the perspective of 

people aff ected by cancer into NCI’s programs 

and activities.37 Each caBIGTM workspace include

patient advocate “to help ensure that the caBIG

end product will ultimately benefi t the cancer 

patient by improving patient care and outcome

in the most eff ective and timely way possible.”3

Patient advocates also contribute valuable 

expertise from outside the academic communi

According to the patient advocate statement o

expectations, “It is the expectation of the caBIG

Patient Advocates that caBIGTM will have a direc

impact on the cancer patient’s journey from 

diagnosis through treatment and beyond, by 

providing the tools necessary to lead to 1) mor

rapid translation of basic research to the clinic, 

centralized clinical trial information that is easil

accessible to clinicians, and 3) feedback from th

patient to the research community.39

strategic approach presumed that existing software 

would be developed with suffi cient modularity and 

programming interfaces to support the addition of 

standardized connections to the grid.

• Educate the community on an ongoing basis 

about the activities and potential benefi ts of 

caBIGTM to address cultural barriers to adoption.

Key Participants 

At the outset, NCICB realized that the participants in 

the caBIGTM Pilot Phase would have to include all 

sectors of the cancer community.

The key participants included:

• The National Cancer Institute Center for 

Bioinformatics (NCICB): NCICB is NCI’s strategic 

and tactical arm for research information 

management. Its mission is to provide foundational 

biomedical informatics infrastructure, tools, 

and data to serve NCI research initiatives and 

the cancer research community. NCICB’s work 

enables disparate research data across the “bench 

to bedside continuum” to be integrated and 

harmonized. As the guiding organization of caBIGTM, 

NCICB represents NCI in all management and 

operational decisions and facilitates the activities of 

the community. Through NCICB, NCI has invested 

resources for administration and management 

of caBIGTM, alleviating the resource burden on the 

participating community.

• NCI-designated Cancer Centers: The NCI Cancer 

Centers Program supports major academic and

36 http://www.cancer.gov/cancertopics/factsheet/NCI/cancer-cen

accessed June 1, 2007.

37 http://carra.cancer.gov/about/whatiscarra.

38 caBIGTM 2007 Annual Meeting Newcomer’s Guide, page 29. 

39 http://cancer.gov, Statement of Expectations, Purpose and Goal

the caBIGTM Patient Advocates, accessed June 1, 2007.
caBIGTM Pilot 

community needs, to the prioritization of 

development of software tools to meet those 

needs, and to the guidance of the overall direc

of the caBIGTM initiative.

• Developers: Based upon competitive bidding 

contracts, these participants have carried out t

work of designing, building, or adapting caBIG

software tools and infrastructure.

• Adopters: These participants—who have a 

real-world need for a specifi c application—hav

acted as beta testers to install and evaluate the 

software, providing both informatician and bas

and clinical researcher feedback on functionali

This information was expected to fuel revisions 

and improvements to enable use of these tools 

as the vehicle for providing data to the caBIGTM 

community.

Assessment of Needs

caBIGTM was to be built by and for the cancer 

biomedical research community. Each step in the 

process was stipulated to include open, frequent

direct dialogue with the community of participan

that was identifi ed as central to caBIGTM success. T

fi rst step that NCI took in the caBIGTM initiative wa

obtain insight from the Cancer Center communit

identify critical IT and research needs, as well as t

existing strengths and capabilities. NCICB staff an

BAH undertook a series of fact-fi nding trips and o

initiatives with Cancer Centers to collect and prio

informatics gaps. The Cancer Centers expressed a 

wide variety of needs, with clinical data managem

• Providing a channel for communications 

regarding guidance and priorities; 

• Providing measures of participant progress;

• Fostering accountability; and

• Providing mechanisms for confl ict resolution.

• Industry Partners and Participants: Members of 

industry were welcome to participate in caBIGTM 

activities from the beginning of the initiative. 

Mid-point in the Pilot Phase, in September 2005, 

the Industry Partners Meeting strengthened this 

connection by formally providing opportunities 

to commercial organizations to participate in 

development. Organizations at the meeting 

included information technology companies and 

large-scale software integrators, pharmaceutical 

and biotechnology companies, biomedical research 

tools vendors, and small, specialized ventures. 

Industry participation has continued since then, 

and it has ranged from volunteer involvement 

in workspace teleconferences and face-to-face 

meetings to funded development of caBIGTM 

applications. When the program was launched, 

all funded participants were academic centers; 

however, as of the end of the Pilot Phase there 

were eight directly funded industry participants. 

This number does not include commercial software 

developers funded under subcontracts from task 

orders issued to academic centers.

Additional participants in the caBIGTM Pilot Phase 

have included, and continue to include, other federal 

agencies such as the U.S. Food and Drug
16

measurable progress 

during the Pilot Phase. 

three-year initial plan w

designed that included 

set of milestones, defi n

deliverables, and plans 

track program progres

against them. (See Figu

The key deliverables fe

into several overarchin

categories, as follows:4

Software tools: Softw

tools are the end-user 

products that enable 

investigators to perfor

their research function

The list of tools planne

development by caBIG

was developed in response to the fact-fi nding 

needs assessment activities and then refi ned b

community during the Pilot Phase. caBIGTM soft

applications have been categorized into the ar

of Tissue Banking & Pathology, Integrative Can

Research, Clinical Trials Management Systems, 

In Vivo Imaging.

• Policies and Procedures: Within the human 

subjects research and patient protection doma

there is signifi cant regulatory ambiguity that 

translates to misunderstanding and variability 

of policies across the biomedical research 

establishment. Since caBIGTM was expected to 

develop and deliver tools that manage and

All of the 49 Cancer Centers that participated in the 

initial information-gathering activities submitted 

concepts for pilot projects for review by NCICB. 

During this review, it was decided that, rather than 

limiting participation in caBIGTM to 10 to 15 Cancer 

Centers as initially planned, a strategy of wide 

inclusion would be adopted, maximizing Cancer 

Center participation and building on synergies in the 

respective strengths of the Centers. By the end of 

October 2003, a list of participating Cancer Centers 

and their respective roles was fi nalized, and the 

caBIGTM Pilot Phase was offi cially launched at a Kickoff 

Meeting in Washington, D.C., in February 2004.40

40 History of caBIGTM (https://cabig.nci.nih.gov/overview/history), 

accessed June 2, 2007.

41 caBIGTM community Tools, Infrastructure, Data Resources (https:/

cabig.nci.nih.gov/inventory/), accessed June 21, 2007.

Database & Datasets

Imaging Tools & Databases

Integration

High Performance Computing

Pathways

Licensing Issues

LIMS

Meeting

Microarray & Gene Expression Tools

Proteomics

Remote/Bandwidth

Visualization & Front End Tools

Statistical Data Analysis Tools

Vocabulary & Ontology Tools & Databases

Meta-Project

Common Data Elements & Architecture

Center Integration & Management

Tissue & Pathology Tools

Access to Data

Translational Research Tools

Distributed Data Sharing/Analysis Tools

Staff Resources

Clinical Data Management Tools

0 5 10 15 20 25 30 35

Cancer Center involvement identified priority areas for caBIGTM

•
caBIGTM Pilot 

cancer types are u

and that data are 

tagged with meta

so that all system

point to the same 

dictionary defi nin

those terms), so 

that the informat

exchanged can 

be understood 

and meaningfully 

integrated.

• caBIGTM compatibility evaluation:

42

This program was developed to defi ne a set of 

criteria used to measure the extent to which 

software applications meet caBIGTM compatibil

guidelines. The caBIGTM compatibility guideline

defi ne three levels—Bronze, Silver, and Gold—

which specify increasingly rigorous concurrenc

with software functionality, engineering, and 

documentation standards. As of the end of the 

Pilot Phase, Bronze and Silver criteria were tota

specifi ed, while the Gold level criteria were 

close to completion. During the Pilot Phase, th

cross-cutting Architecture and Vocabularies an

Common Data Elements (VCDE) Workspaces 

implemented a Silver level review process for 

software developed with funding from the caB

program. In addition, a Bronze compatibility 

process for any application (whether develope

with caBIGTM funding or not) was initiated. 

community about the ways in which caBIGTM 

enhances their ability to remain in compliance with 

regulations and best bioethics practice.

• The Grid: caGrid is a set of specifi cations and 

software modules that defi ne a data transmission 

network upon which computer services operate 

to transmit data between collaborators. caBIGTM 

software applications were expected to adhere 

to grid interface specifi cations, so that they could 

connect to this network and seamlessly exchange 

data with other software applications using the 

same standards. caGrid was designed to include 

software features that ensure authorization and 

authentication of users and data security for any 

service operating on the grid.

• Standards: For data to be gathered, stored, and 

meaningfully exchanged through interoperable 

software tools, the adoption of standards for 

data formats, data elements, APIs (Application

Year 1 Year 2 Year 3

Figure 3. caBIG Initial Plan

42 https://cabig.nci.nih.gov/guidelines_documentation.
18

Background on Open Source Licenses

Open source licenses for software are predicated on the general availability of source code—the human-reada

version of instructions to a computer—so that other developers can understand, use, and modify the software

if desired. However, open source licenses generally have other requirements beyond access to source code. Th

typically include features such as not restricting what party can distribute software, as well as requiring that th

software can be distributed as source code and compiled programs, that the software can be modifi ed or used 

derivative works, and that the license must not discriminate against any category of person, entity, or fi eld of u

Key Benefi t of the caBIGTM License

The key benefi t of the caBIGTM open source license to developers and distributors of software is that they are fr

to incorporate caBIGTM-developed software into their own products, and they need not release those products

source code. As a result, software developers can more easily develop products that are compatible with caBIG

(i.e., can interoperate on caGrid) by simply incorporating already developed components that are freely availab

Additionally, if they so choose, developers can incorporate caBIGTM technologies, but do so in a way that, while 

simplifying their own technology development eff orts, may result in a product not compatible with caBIGTM.

One of the greatest benefi ts of the non-viral feature of the caBIGTM license accrues to commercial software 

providers the ability to develop software that is compatible with caBIGTM standards, utilizing freely available op

source code, and to subsequently release proprietary products that retain their full intellectual property rights

Principles Guiding the caBIGTM License Terms

The public health missions of the NIH and the NCI drive the community access requirements for technologies 

developed with such agencies’ funding. NIH policies—coupled with the caBIGTM guiding principles (“open sour

open access, open development, and federation”)—were the key factors behind development of the license te

to which all NCI-funded caBIGTM developers would have to adhere. These policies and programmatic criteria req

that NIH-funded resources developed to support biomedicine, including software and data, should be broadly 

disseminated to promote research, development, and application; that the broadest possible use of such softw

and data will ultimately benefi t the biomedical community; and that NIH-funded research projects with indust

should maintain academic freedom and encourage the broadest possible dissemination of research results.
caBIGTM Pilot P

 In contrast, software developed with NCI funding and distributed under the caBIGTM license is “non-viral.” 

Software developers are free to derive new or modifi ed products from caBIGTM software without the 

requirement to distribute the resulting software products on an open source basis.

• caBIGTM Software Developed with NCI Funds: The requirement to release software under the caBIGTM 

license is specifi cally dependent upon the source of funds used to develop that software. Basically, if 

the developer used NCI funds from the caBIGTM program directly or via the caBIGTM general contractor, 

the developer must release the software under the caBIGTM license terms. If the developer is using other 

public or private funds, there is no such requirement, thereby providing further fl exibility for the software 

development community. 

 NCI developed this policy framework for software access and distribution by negotiating broad 

rights through the Federal Acquisition Regulation (FAR), which governs procurements by the Federal 

government. In most cases, if the Federal government contracts for the development of software, the 

developer retains rights to that software for other uses or sales. In the case of caBIGTM, however, as a 

condition for funding, NCI obtained “unlimited rights” in caBIGTM software developed with such funding, 

which included the requirement that developers release the source code for caBIGTM products under the 

caBIGTM license or equivalent terms.

• caBIGTM Trademark: It should be noted that simply modifying or incorporating caBIGTM code does 

not confer the moniker of “caBIGTM compatibility.” The NCI has trademarked the term “caBIGTM,” and it 

consequently limits the use of the marks to appropriate situations. The caBIGTM license specifi cally states 

that end users of caBIGTM licensed code do not obtain the right to use any trademarks owned by NCI in 

any products except as permitted by NCI or otherwise endorsed by NCI or institutions in the caBIGTM 

community. NCI will separately license the use of the caBIGTM trademark to those whose software 

applications have been independently validated as having passed compatibility tests.

Support from the caBIGTM Community

The caBIGTM Data Sharing and Intellectual Capital (DSIC) Workspace includes individuals with legal and

licensing backgrounds who were involved in the development of the policies and language of the caBIGTM 

license. Individuals and institutions that wish to adopt caBIGTM software and need help navigating the 

intellectual property issues can contact the leader of the DSIC Workspace for general questions about this 

license structure.
20

Expanding the Network 

• More caBIGTM compatible systems and tools

• Resources for adoption and support

• New partners from IT and biomedicine

• Extension to other disease categories

Delivering Software Tools and caGrid

• 40+ software products delivered 

• caGrid 1.0 launched December 18th

• 900+ active participants at 80+ institutions

• New partnerships – private sector, regions, federal agencies

Establishing Connectivity

• Connectivity achieved between pilot nodes of caGrid

• Pre-existing software “retrofitted” for caBIGTM compatibility

• caBIGTM compatibility embedded into NCI Advanced 

 Technology programs, Cancer Centers, and external product 

 development activities

Building Community

• caBIGTM pilot launched - February 2004

• Project plans developed and Working Groups established

• Standards conventions determined

• First generation software tools developed

• NCI studies the IT challenges and develops strategic plan 

 for a large-scale bioinformatics network 2003

2004

2005

2006

2007

Figure 4. caBIGTM Pilot Phase Key Activities

Pilot Phase Stage

As shown in Figure 4, the 

Pilot Phase progressed th

thematic stages of develo

in which the number of 

participants expanded, a

their roles evolved over t

• Building Community

2003 and 2004, the in

focused on understan

cancer research need

on putting the structu

and organization in p

to enable a multiplicit

development program

The process of gather

input and determinin

priorities itself resulte

formation of a comm

individuals and institu

that would carry out t

program activities, gr

in size and diversity

community—was critical because it res

in a community of participants within 

the “workspace” structure established t

manage and inform the project.
caBIGTM Pilot 

by teleconference, had a particular area of focus 

included teams of Cancer Center representatives 

provided to the program by the Cancer Center 

Directors; contractors; both funded and voluntee

participants; software developers and adopters; a

subject matter (domain) experts who gave direct

to the project(s) housed within each workspace. 

Additionally, several workspaces (especially VCDE 

and Architecture) were places where mentors co

be trained to provide guidance and assistance to 

the program at large. In each workspace, softwar

technologies that supported similar biomedical 

research activities were grouped together to faci

the gathering of information and management o

feedback from development eff orts. 

The primary role of each workspace was to deter

priorities within that workspace domain and to p

projects based upon caBIGTM strategic priorities. 

The funded participants in each workspace were 

also specifi cally tasked to act as liaisons to ensure 

continuous fl ow of shared information about rela

activities among all workspaces. Also, special inte

groups (SIGs) evolved within workspaces to serve 

stewards for particular projects, as well as to keep app

of events and developments in external standard

organizations that could impact workspace activ

These workspaces were the fundamental buildin

blocks of what grew into the caBIGTM community, 

their activity level grew steadily over time. In the 

year, the workspaces met for 182 teleconferences

in years 2 and 3 there were almost 500 such 

teleconferences per year. Workspace attendance 

has also steadily grown. 

technology were key milestones that instructed 

future software developments, standards, and 

infrastructure.

• Delivering Software Tools and caGrid: During 

the second year, participants began to focus 

more on delivery of software applications, data 

standards, and tools. By the culmination of the 

Pilot Phase in 2007, over 40 software tools had 

been developed that span all the research and 

infrastructure domains identifi ed as areas of focus 

for caBIGTM. caGrid, the essential data exchange 

network of caBIGTM, was launched with six 

institutions operating on it. 

The Pilot Phase was offi cially completed in 

March 2007. 

“The caBIGTM Pilot Phase was extremely 

ambitious. In three years, it has been trying 

to accomplish what other endeavors have 

done over decades.”43

Kim Lyerly, M.D.

Director, Duke Comprehensive Cancer Center

43 Kim Lyerly, M.D., Director, Duke Comprehensive Cancer Center, 

discussion on May 30, 2007.
22

range of needs, and it also has been interactin

with vendors interested in establishing caBIGTM 

compatibility for their products.

Integrative Cancer 

Research (ICR): ICR 

tools enable integra

between molecular 

biomedical informa

applications and 

data. Translational 

research requires 

the integration of 

traditional clinical s

information with th

molecular informat

derived from highthroughput genom

study platforms. 

Technologies such 

as DNA sequencing

polymorphism ana

DNA modifi cation 

(e.g., methylation), 

chromosomal 

changes (e.g., loss o

heterozygosity, cop

number variation), and gene activity measures

such as RNA and protein expression analysis, 

are increasingly used in clinical studies. These 

technologies generate vast quantities of highl

structured data that must be integrated with 

clinical data. Furthermore, the utility of such

 integrated datasets is then subject to the 

(i.e., integration of molecular and other data from 

diverse technologies), in vivo imaging, and tissue (i.e., 

biospecimen) banking and pathology tools.

• Clinical Trials Management Systems (CTMS): 

CTMS tools are designed to meet the diverse clinical 

trials management challenges of the Cancer Center 

community. Cancer Centers were grappling with 

an overall lack of clinical trials management 

systems—and/or diversity of non-interoperable

 systems—to manage studies, patient registries and 

Clinical 

Trials 

Management 

Systems 

Workspace

(CTMS)

Tissue 

Banks & 

Pathology 

Tools 

Workspace

(TBPT)

caBIGTM Vocabularies and Common Data Elements Workspace (VCDE)

caBIGTM Architecture Workspace (ARCH)

Strategic 

Planning 

Workspace

(SP)

Training 

Workspace

(D&T)

Integrative 

Cancer 

Research 

Workspace

(ICR)

In Vivo 

Imaging 

Workspace

(IMAG)

Data Sharing 

& Intellectual 

Capital 

Workspace

(DSIC)

Figure 5. caBIGTM Workspace Organization44

As depicted above, the workspaces comprised three broad types of activities: Domains, Cross-Cutting, and Strategic Level.

•

44 http://caBIG.nci.nih.gov/index_html/workspaces/index_html, 

accessed July 3, 2007
caBIGTM Pilot 

Attendance

CTMS

70

60

50

40

30

20

10

0

25

ICR IMAG TBPT ARCH VCDE SP DSIC D&T

60

36 35

31

21

25

37

19

38

19

35

14

24

15

18 16

18

Figure 6. Representative Attendance on caBIGTM Workspace Teleconferences 

 2004 through 2006/2007 

2004

2006/200

tissue samples. Robust systems to collect, 

manage, and annotate such tissues is a we

known unmet need in cancer clinical resea

and future Molecular Medicine is predicate

upon meeting that need. Additionally, 

samples must be annotated with diverse 

information ranging from the ethical and 

protocol parameters (e.g., informed consen

clinical trial protocol) under which the don

consented to provide material, to the clinic

and diagnostic pathology data collected as 

part of the donor’s clinical care. Such system

must be able to work over the Internet and 

researchers managing geographically disp

and MRIs for both human and animal models of 

cancer. Imaging data in biomedical research 

derives from diverse sources, and it is commonly 

not organized to support investigations. Among 

key cancer center needs in utilizing image 

data for research are standard vocabularies for 

annotation, image markup tools, applications 

for extracting de-identifi ed structured data from 

radiology reports, reference data sets of images, 

and ways to normalize data obtained from 

diff erent instruments. The Imaging Workspace, 

launched in 2005 and comprising both academic 

users and industry device vendors, had been 

assessing the Cancer Center needs and prioritizing 
24

structured in caBIGTM is that all specifi cations 

include both specifi c human-readable defi niti

and machine-readable components that assis

software to transmit and incorporate the data 

without signifi cant programmer customizatio

Earlier attempts to create common vocabular

between disciplines focused solely on the hum

comprehension and communication. Within 

caBIGTM, making the data specifi cation machin

readable provides a framework for rapid adop

of data standards by new software and databa

systems with a minimum of human interventi

Strategic-Level Workspaces: These planning an

management workspaces develop policies and 

guidelines that support the other workspaces, an

develop and refi ne the caBIGTM strategic plan.

• Data Sharing & Intellectual Capital (DSIC): D

addresses issues and develops recommendation

related to data sharing, patient privacy, 

intellectual capital, security, and other policies. 

Bringing together researchers, clinicians, 

technology transfer specialists, attorneys, poli

specialists, patient advocates, bioethicists, 

and bioinformaticians, the DSIC Workspace 

facilitates education and reduces barriers to 

caBIGTM adoption by addressing legal, regulato

ethical, policy, academic, proprietary, security, 

and contractual barriers to data exchange. DS

also functions as a resource for members of th

caBIGTM community when projects intersect w

regulations related to patient privacy and acce

to patient data. 

workspaces were created to support the specifi cation 

of the data standards and standard software 

infrastructure needed by the Domain Workspaces to 

ensure interoperability of data managed by those 

respective tools and systems. This requirement for 

“semantic and syntactic interoperability” is the key 

technical requirement that needs to be in place 

for the vision of caBIGTM to succeed. These CrossCutting Workspaces have provided a management 

framework to ensure that such interoperability was 

built into systems created as part of the caBIGTM 

program. The Cross-Cutting Workspaces, through 

multiple channels of communication, ensure that the 

software tools developed by the Domain Workspaces 

employ compatible vocabularies, that data formats 

and application programming interfaces (APIs) are 

standardized for effi cient interchange between 

diff erent software tools and computer systems, and 

that the connectivity infrastructure (i.e., caGrid) is in 

place for data sets to be accessed by researchers at 

diff erent places, both by geography and by where 

they work on the translational research process.

• Architecture (ARCH): ARCH is software, 

architecture, and standards for caBIGTM 

infrastructure, including software development 

toolkits, application programming interfaces, 

and the grid network layer. ARCH guides the 

development of caGrid, the underlying network 

architecture and platform that provides the basis 

for connectivity of software applications and 

databases, enabling data sharing among caBIGTM 

participants. The Grid also supports access to 

data and analytical services, and it provides a
caBIGTM Pilot 

• Strategic Planning (SP): SP provides broad and 

timely community input to the NCI and general 

contractor project management leadership. The 

caBIGTM initiative is working in domains that 

rapidly change with new technological and clinical 

developments. The SP Workspace originally 

included individuals attuned to this “pulse” and

p, p

formally funded beta-testing and evaluation with

the community through an “adopter” program 

designed to include real-world situations within 

Cancer Centers. Testing results and feature reque

would feed back via the workspaces, and they wo

lead to iterative development.

Evaluates

Prioritizes { Decides }

NCI Center for 

Bioinformatics

Workspaces

• Special Interest Groups

• Liaisons

Adopters

Issues RFPs { }

Generate ideas,

guidance, { specifications }

Develop software { } Test/Evaluate in

real-life scenerios and { feed back results }

General

Contractor Developers

Figure 7. caBIGTM Software Development Flow of Activities
26

best practices, governmental policies, and 

regulations, including a framework to support 

contracts and funding of caBIGTM project activ

The management structure was designed at t

outset to be fl exible, with early program staff 

anticipating that the pilot phase of any large 

distributed IT project would have to be adapt

to unknown hurdles. Dedicated NCICB and 

contractor staff over the three years of the Pilo

Phase comprised more than 80 professionals.

• Development and deployment of a robust, 

community-driven organizational and operat

structure (the workspaces) designed to captu

user needs and priorities identifi ed by 

stakeholders in the planning phase, refi ne tha

competitively based on responses from caBIG 

community participants to RFPs issued by BAH for the 

development of specifi c tools or standards based on 

priorities established by the Domain Workspaces and 

the caBIGTM strategic plan. The contracts included task 

orders that usually had two to six month timeframes.

Progress on Deliverables 

Virtually all the individuals in the caBIGTM community 

who shared their observations for this Report believe 

that the caBIGTM Pilot Phase has exceeded reasonable 

expectations of what could be done in a three-year 

period, especially in the context of a rapidly-changing 

and highly varied biomedical research environment. 

Many observers pointed out that 

there were shortcomings and problems, 

but they also acknowledged that 

such issues are typical of large IT 

projects and are precisely what 

the Pilot Phase was intended 

to expose and address (See 

Hindsight, Chapter 4).

The progress on deliverables, as 

well as other accomplishments, 

included the following key 

cultural, technical, managerial, 

and operational successes:

• Formation, launch, and 

implementation of a vibrant 

national and international 

caBIGTM collaborating 

community, including 54

Attendance

2004 2005 2006 2007

0

1,000

500

169

366

784

1060

Figure 8. caBIGTM Annual Meeting Attendance 2004 - 2007
caBIGTM Pilot 

business architectures.

• Coordination and collaboration with related 

public and private sector healthcare, cancer, a

biomedical research IT initiatives.

caBIGTM Connections to Other 

NCI Programs

The caBIGTM initiative has, since its inception, bee

connected to and supportive of other NCI progra

Among the NCI Advanced Technology Initiatives 

for which caBIGTM provides tools and infrastructu

are The Cancer Genome Atlas (TCGA) (http:// 

cancergenome.nih.gov); The Integrative Cancer 

Biology Program (ICBP) (http://icbp.nci.nih.gov); 

The NCI Alliance for Nanotechnology in Cance

(http://nano.cancer.gov); Clinical Proteomic 

Technologies Initiative in Cancer (CPTI) (http://

proteomics.cancer.gov); and Offi ce of Bioreposito

and Biospecimen Research (OBBR) (http://

biospecimens.cancer.gov). 

component-based clinical trials solutions, tissue 

bank and pathology tools, and integrative 

cancer research applications. There are currently 

approximately 40 tools freely available on the 

caBIGTM Web site, as well as infrastructure elements 

and data resources. (See 

Appendix A for a list and 

description of caBIGTM tools 

developed during Pilot 

Phase.) In 2004 and 2005, a 

total of 4 tools were released, 

increasing to 24 tools in 

2006. By workspace, this 

equated to 10 CTMS-related 

tools, 1 DSIC-related tool, 24 

ICR-related tools, 2 Imagingrelated tools, and 3 TBPTrelated tools developed to the point where they 

are downloadable via the caBIGTM Web site. As of 

June 2007, 12 tools have completed the Silver level 

compatibility review process, and 2 tools have 

been certifi ed as Bronze compliant.

• Development of standard data models, relevant 

common data elements and terminologies for use 

by the caBIGTM community, as well as processes to 

expand, adopt, and modify these standards as part 

of caBIGTM activities. 

• Development and promulgation of common 

guidelines and standards for programming 

interfaces for caBIGTM application and database 

network connectivity, including formation of a 

prototype unifying network architecture for 

2004/05 2007 2006 (June 30) To

Software Code

Analysis / Documentation

Dataset

Other

Total

293

2830

9

1713

4845

130

1452

22

803

2407

79

1041

14

275

1409

5

53

4

27

86

Figure 9. caBIGTM Deliverables by Category
45Janet Woodcock, M.D., Chief Medical Offi cer, U.S. Food and Drug 

 Administration, discussion on June 7, 2007.

caBIGTM has also reached out to SPOREs (Specialized 

Programs of Research Excellence). For example, it 

now provides a supporting informatics platform 

for the Prostate and Breast Cancer SPOREs. Other 

SPOREs, such as the Melanoma and Lymphoma 

SPORE, are evaluating aspects of caBIGTM software to 

support various parts of their eff orts. For Cooperative 

Groups (groups of researchers, Cancer Centers, and 

community doctors who are involved in studies of 

new cancer treatment, prevention, early detection, 

quality of life, and rehabilitation), caBIGTM has helped 

to evaluate which clinical trials management system 

might be best suited to their needs. The Cooperative 

Groups have also included a caBIGTM compatibility 

criteria in their software evaluation process. 

(http://cancer.gov)

caBIGTM Connections to External 

Programs and Organizations

NCICB has emphasized a collaborative approach 

toward other federal institutes and agencies as 

well as toward the international community, with 

a willingness to share standards, tools, knowledge 

and experience. Whenever possible, the goal is to 

achieve interoperability between caBIGTM and other 

initiatives to facilitate data-sharing across the widest 

possible biomedical network. Key examples of such 

interactions include:

• U.S. Food and Drug Administration: NCI and

FDA have launched several projects that focus 

on interoperability for regulatory information 

exchange. The data standardization features of

paper-based. This cumbersome process is a con

factor to the low numbers of new drug approva

growth in research spending. A secure and stand

based system for transmitting such data would 

to biomedical research, supporting the ultimate 

speeding research discoveries to patients.

In 2003, the NCI and Food and Drug Administra

(FDA) used the Interagency Oncology Task Force 

launch the Regulatory Data Exchange (RDE) ini

outgrowth of Clinical Research Information eXc

or CRIX) to begin to address some of these probl

The partners to the project have since been expa

include not only government, but also other key 

in the drug discovery, development, testing, and 

process. These key players include industry, acad

standards bodies, and patient advocates. The g

of this group, the caBIGTM Regulatory Data Excha

Steering Committee, is to build a shared, standa

collaborative research infrastructure for regulat

and document submission, review and, analysis

It is intended that the resolution infrastructure w

the secure transmission of clinical research infor

among all relevant parties: sponsors, investigat

regulatory authorities. Additionally, the project 

facilitate the adoption of electronic data standa

standardized terminologies, and software syste

perform electronic transactions and submission

tools, when made open and accessible to all inte

users, are intended to reduce the overall cost of 

information gathering and submissions process

as the tasks of analysis and review.

28
caBIGTM Pilot P

for standards-based data submission, re-usability o

analysis tools, reduction of data redundancy, easier 

data audits, and use of less manual, paper-based d

management. In a second phase, the system will be 

populated with actual (but historical) trial data, to 

its ability to support FDA reviewers with their stand

suite of data access and statistical analysis tools.

Both pilots have been successful, and Janus is now 

undergoing a second phase of development that 

integrates additional industry standard data mode

Role of caBIGTM in the RDE Initiative

There are two key components of caBIGTM that mak

tools especially useful for the RDE goal of standardi

data storage and transmission. First, the caBIGTM 

terminology and data element systems developed 

by the VCDE workspace support the unambiguous 

defi nition of clinical trial information data sets. Sec

the caCore and caGrid architectures provide a stand

based object-oriented framework, developed with 

biomedical research in mind, for accessing the data 

transmitting it over the Internet.

The long term strategic goal of the partnership is to 

move these projects out of the government into self

sustaining entities, whose clients would be all the 

interested parties in clinical trials. As of June 2007, 

FDA and NCI are soliciting responses from nongovernmental organizations to adopt these tools.

Registry for Biomedical Informatics Research Data 

(FIREBIRD) system to manage the registration of 

investigators, as required by law. The FIREBIRD system 

permits investigators to register and document 

their accreditation online with both academic and 

commercial sector trial sponsors, and it implements 

a legally enforceable electronic signature capability 

for documents submitted by the investigator. Among 

the features of the system is the ability to maintain 

investigator profi les, manage registration with 

various entities, submit and receive queries from 

various entities, and upload documents. The FIREBIRD 

application provides a “one stop shop” for investigators 

to submit their information to both trial sponsors and 

to regulatory agencies, removing the opportunity for 

ambiguous identity.

 As of June 2007, FIREBIRD has been successfully piloted 

with partners, including NCI, FDA, 5 biopharmaceutical 

companies, 9 academic medical centers, over 30 

clinical centers and diagnostic labs, and more than 

450 investigators. The project is currently in limited 

production at the NCI Division of Cancer Prevention 

and is undergoing review to identify enhancements 

in preparation for adoption by the FDA and NCI 

community and a broader rollout. 

JANUS

Another key project is Janus, a standards-based clinical 

data repository that utilizes an open source data model 

of the same name. Janus was created through a joint 

venture of the FDA and IBM. The Janus data model 

provides a standard repository for clinical trial data
initiative has attempted to harmonize with 

their standards to maximize interoperability.

Recognition of caBIGTM

During the Pilot Phase, caBIGTM was identifi ed in 

a wide range of settings and publications as a 

contributor to enabling connectivity and data 

sharing within the cancer community.

The NIH National Center for Research Resources 

published three reports about caBIGTM, as follows

• caBIGTM Overview, May 2006. This report noted

“Acknowledgements of the promise held forth 

by both translational research and large-scale 

team science is widespread. But truly realizing 

this promise involves a sea change in the mind 

set of clinicians, researchers, and funding entit

working in the life sciences...caBIGTM is buildin

a cohesive community among the clinical canc

research in which this sea change is occurring. 

It is as much about bringing people together t

embrace a fundamental change in how scienc

 is conducted as it is about developing the 

 enabling technology.”48

• caBIGTM: Opportunities and Challenges for Us

Beyond Cancer, June 2006. This report noted: 

“The caBIGTM model appears, generally, to be 

extensible to other domains, but it will need to 

be further developed to include more tools an

processes...Attention needs to be paid to the 

human and political aspects of information sha

Researchers will need to be convinced that sha

a group of programmatic grants specifi cally 

designed to support the integration of the various 

historically independent disciplines in biomedical 

research that must work together to successfully 

deliver Molecular Medicine. Another Roadmap 

initiative in which caBIGTM community researchers 

have collaborated is the “Re-engineering 

the Clinical Research Enterprise” information 

standardization project. caBIGTM has also provided 

input to the Biomedical Information Science and 

Technology Initiative (BISTI) as it attempts to 

recognize the potential benefi ts to human health 

that can be realized from applying and advancing 

the fi eld of biomedical computing.46

• Offi ce of the National Coordinator: The Offi ce of 

the National Coordinator for Health Information 

Technology (ONC) provides counsel to the 

Secretary of HHS and Departmental leadership for 

the development and nationwide implementation 

of an interoperable health information technology 

infrastructure.47 NCICB has kept ONC staff 

updated on caBIGTM activities and resources and 

collaborated on numerous ONC activities. 

• United Kingdom’s National Cancer Research 

Institute: NCRI is a partnership between the UK 

government, charity and industry, which promotes 

cooperation in cancer research among 20 member 

organizations. NCI and the NCRI have been 

cooperating to share caBIGTM tools and achieve 

data interoperability for sharing of research results. 

(http://www.ncri.org.uk/)

46 www.BISTI.nih.gov, as of July 4, 2007.

47 http://www.hhs.gov/healthit/onc/mission/; accessed July 6, 2007. 48 http://www.ncrr.nih.gov/publications/informatics/caBIG.pdf.

30
caBIGTM Pilot P

49http://www.bridgmodel.org.

be a technology independent and machine readab

data structure describing a clinical trial. The caBIGTM 

policies and tools that specify controlled terminolog

data element structure, data models, and computa

metadata about those data elements are all openly 

developed, made freely available, and provide a pre

made framework for an eff ort like BRIDG. According

the caBIGTM program has been a key partner and 

supporter of BRIDG and was instrumental in the pro

of bringing the interested parties together. 

As of June 2007, version 1.0, the fi rst offi cial release 

BRIDG, has been made available to the community 

can be freely downloaded from the caBIGTM softwar

repository. Currently, there are several sub-projects 

BRIDG, all under active development, including a cl

trial design model, a statistical model (supporting, f

example, trial size justifi cation power calculations), 

a trial registry model (e.g., for depositing trial existe

information in a central registry).

of caBIG technology has been at the interface

specifi cally supporting the movement of the investigator 

data from entity to another. Another area where caBIGTM 

technologies have delivered value is in standardizing the 

structure and meaning of the data itself.

When conducting a clinical trial, much attention is 

focused on data generated about the patients in the 

trial: their clinical histories, diagnoses, and certainly 

their responses to the investigative treatment and 

eventual outcomes. However, one of the more 

intractable information management domains in 

clinical trials has been dealing with information about 

the clinical trial process itself; for example, data about 

sponsors (the entities that pay for and organize trials), 

activities to be undertaken during the trial (such as 

the randomization of patients), or the sites where the 

trial is being run. The Biomedical Research Integrated 

Domain Group (BRIDG) Model is a multi-party publicprivate partnership to build a standard data model that 

captures this “metadata” about a clinical trial. Written 

more formally, the BRIDG model is a standard data 

structure that describes pre-clinical and clinical research, 

a domain succinctly defi ned on the caBIGTM Web site as:

Protocol-driven research and its associated 

regulatory artifacts, i.e., the data, organization, 

resources, rules, and processes involved in the 

formal assessment of the utility, impact, or other 

pharmacological, physiological, or psychological 

eff ects of a drug, procedure, process, or device 

on a human, animal, or other biologic subject or 

substance plus all associated regulatory artifacts 

required for or derived from this eff ort.49
pp

Honors Program “annually identifi e

and records the accomplishments 

the men and women, organization

and institutions that are creating th

global best practices in leading the 

world’s ongoing IT revolution.” 

caBIGTM was listed as a “Noteworthy Case Study” 

in the Journal of the Computerworld Information 

Technology Awards Foundation, which conclude

that: “With a committed team, and by providing 

mechanisms from the beginning to integrate 

and drive the program, the caBIGTM program has 

successfully met the challenges, both technical a

social, to create an integrated grid with which ca

research data can be shared broadly throughout 

the community.” 53

data will not compromise the integrity of their 

studies and that other researchers will not “beat 

them to the punch” or adversely aff ect their ability 

to publish their work. All participants will need to 

be convinced that data and personal information 

are secure.”50

• caBIG-PlusTM Conceptual View: Beyond Cancer, 

July 2006. This report concluded: “caBIGTM has 

benefi ted the cancer community by enabling 

collaboration in the community and by speeding 

the dissemination of novel discoveries through data 

exchange and development of data analysis tools...

The non-cancer research community faces many 

of the same issues the cancer research community 

faces. caBIGTM expansion into caBIG-Plus will benefi t 

the entire biomedical research community.”51

caBIGTM in the Literature

More than 40 peer reviewed papers about caBIGTM 

or research using caBIGTM tools and resources have 

appeared in the scientifi c literature since 2003,52 as well 

as abstracts, and news articles in the life sciences press. 

In addition, numerous presentations about caBIGTM have 

50http://www.ncrr.nih.gov/publications/informatics/caBIG_

 OpportunitiesAndChallenges_12-26-06.pdf.

51 http://www.ncrr.nih.gov/publications/informatics/caBIG-Plus_

 ConceptualView_12-26-06.pdf.

52 https://cabig.nci.nih.gov/Library/Library/caBIG_Scientifi c_Pubs.html. U

01/01/04 01/01/05 01/01/06 01/01/07

0

50,000

9,437

50,259

53 http://www.cwhonors.org.

54 Joel Saltz, M.D., Ph.D., Professor and Chair, Department of Biom

Informatics, The Ohio State University College of Medicine, discu

 May 23, 2007.

 “caBIGTM was designed fl exibly enough t

ask who in the community can contribu

and allow anyone to answer.”54

 Joel Saltz, M.D., Ph.D.

 Professor and Chair, Department of 

Biomedical Informatics

 The Ohio State University College of Medicin

32
caBIGTM Pilot P

Changing Scientifi c Strategies

Traditionally, research investigation has been conducted as a solitary endeavor, and projects were funded via gran

individual investigators. Incentives for researchers were in the form of publication in peer-reviewed journals, autho

which was highly prized and substantially contributed to promotion and ability to attract and direct research fund

environment, connectivity among researchers was not perceived as either necessary or desirable.

Today, however, molecular-based translational research demands that inform

carried seamlessly from one department to another within an institution, or 

multiple institutions. Team science has thus become a requisite, as is rapid ac

to data sets from other researchers’ eff orts, in a form that can be read, studie

manipulated. In this paradigm, IT connectivity becomes the lifeblood of the 

endeavor. caBIGTM enables this new, more collaborative form of research whi

same time empowering richer forms of traditional institutional research. 

The Development of the caBIGTM Community

The concept of gathering supporters arose at the outset of the planning process for the caBIGTM initiative, and cont

throughout the Pilot Phase. The overall sensibility was to accept all interested participants; as a result, while the ca

community was largely comprised of informatics experts from NCI-designated Cancer Centers, it also sought, with 

success, to encompass clinicians, biologists, pathologists, and professionals from other disciplines. The formation o

the caBIGTM community was a proactive eff ort and well resourced: of the 247 funded task orders issued by the gene

contractor during the fi rst two years, 135 were for support of participation in workspaces. During the third year, th

proportion rose to 172 out of 232 task orders.

To cultivate a team spirit and common sense of purpose, the caBIGTM initiative emphasized communications throug

a caBIGTM community Web site, electronic announcements, face-to-face meetings, teleconferences, annual meeting

newcomer training sessions, conference presentations, and program update documents. As shown in Figure 10, th

site was a central location for caBIGTM information, and visits have grown steadily over time. 

From approximately 100 interested participants at the time of launch in 2004, the caBIGTM community grew to ove

participants from academe, federal agencies, Cancer Centers and related programs, industry, patient advocacy gro

not-for-profi t community, and international cancer institutes. As the initiative entered its Enterprise Phase in 2007, 

institutions were participating.

55 Robert Beck, M.D., Vice President and Chief Information Offi cer, Deputy Director, Population Sciences, Fox Chase Cancer Center, discussion on June 1, 2

56 Anna D. Barker, Ph.D., Deputy Director, Strategic Scientifi c Initiatives, National Cancer Institute, discussion on May 16, 2007.

“Building the community 

was key to caBIGTMsuccess.”56

 Anna D. Barker, Ph.D.

 Deputy Director, Strategic 

 Scientifi c Initiatives

 National Cancer Institute 
34

operations. (One caBIGTM participant no

ironically that had the caBIGTM concept 

been presented to an NCI study section 

a grant application, it would have been 

rejected as being overly ambitious.)

With the benefi t of more than four year

of experience, perspective has now 

been gained on the cultural, technical, 

managerial, and operational issues tha

arose in the Pilot Phase. As described in 

Chapter 3, NCICB designed its manager

approach to maximize fl exibility, so tha

it became obvious that some tactics wo

be more eff ective than others, it would b

feasible to shift gears. 

Based on assessments and insights from 

NCI and NCICB leadership, the general 

contractor’s management team, cancer 

community participants, leaders of oth

government agencies, and academic an

commercial researchers, a number of 

criticisms have been noted, and caBIGTM 

strategies and programs have been 

adapted to address them.
caBIGTM Pilot 

immediate end-user deployment. In addition, 

some participants noted that there was a 

reluctance within caBIGTM program manageme

rapidly address projects that were failing to m

development goal; in a couple of extreme case

this perceived reluctance resulted in a commu

expectation that a particular software applicat

was ready for use when in fact it was not. Som

sectors of the community, who had been 

expecting delivery of software tools by the clo

of the Pilot Phase, were discouraged as a resul

of these communications disconnects.

NCICB communications currently stress what is 

to be expected in each program area, and timelin

for release of software applications have become 

more explicit.

• Communications to diff erent user groups:

caBIGTM communications were of relevance 

primarily to informatics experts, and they 

were often issue-specifi c during the software 

development process. As a result, the biomedi

researchers who were not part of the active ca

development community, but who are expect

ultimately to be the end users of caBIGTM softw

tools, were at times left out of the communica

loop. In particular, biomedical participants 

noted that they had diffi culty fi nding out wha

software tools were in development that woul

applicable to their specifi c areas of research (e

clinical trials management, biobanking), the st

of those tools, the features of those tools in ter

of how functional they would actually be, and 

anticipated release timing. One participant no

As a result, the program was overwhelmed, and 

delays in funding occurred. In this regard, NCICB 

wished to allow all comers to participate, but it 

did not “prepare for success” with an operational 

plan that envisioned a rapid growth scenario. The 

community became frustrated. Several participants, 

while understanding the programmatic value of 

broadening the number of participants, opined that 

the number of participating Cancer Centers should 

have remained in the 10 to 15 range, as the larger 

number resulted in the dilution of funds, strategic 

ambiguity, and managerial burden. 

Over time, NCICB learned to reduce the impact of 

unpredictable response levels in a variety of ways, 

including more narrowly focusing RFPs to refl ect the 

strategic plans and priorities of the workspaces, and 

asking for letters of intent from interested responders 

prior to submissions of bids to gauge response rates. 

Communications

Some participants expressed the view that caBIGTM 

communications were “terrifi c” or “excellent.” Others, 

however, noted that while NCICB disseminated 

information to the workspaces on the “big picture” 

of the initiative, there was a lack of communication 

about what diff erent projects were doing 

specifi cally to move the initiative forward. 

The following areas for improvement in caBIGTM 

communications have been identifi ed: 

• Setting expectations: The majority of 

community participants did not have experience 

with large-scale information technology projects, 

particularly in the life sciences/healthcare sectors
36

also apparent in a few situations where separa

workspaces were duplicating development eff 

(in some cases incompatibly) to similar challen

As a result, some developers now have to retro

their applications to achieve harmonization.

A combination of formal liaisons, mentoring, join

face-to-face meetings, and large scale harmoniz

activities are helping to address these issues. In 

particular, the creation of “backbone information 

models” and other standard models, such as BRID

are providing technology while the caBIGTM ment

program is supplying cross-cutting expertise to a

caBIGTM projects.

• Timing of business process defi nition and 

implementation: Some participants believe 

that it would have been helpful had the busine

practices been more concretely defi ned at 

the launch of the initiative, although they 

acknowledge that it would have been diffi cult 

derive such practices without fi rst experiencin

the strengths and weaknesses of the caBIGTM 

community structure.

 Refl ecting lessons learned, the business processe

of the caBIGTM program going forward will includ

a comprehensive refi nement of the overall fi nanc

and business methodologies to allow more (and 

more fl exible) options for funding caBIGTM activit

• Strategic planning: While the caBIGTM 

organizational structure included a Strategic 

Planning (SP) Workspace intended to be a rob

environment for high level planning, some 

participants in that workspace felt that the

• The caBIGTM community Web site 

(http://cabig.nci.nih.gov): This Web site was the 

core vehicle for communications during the Pilot 

Phase, and it continues to be the central repository 

for archival and current information about the 

initiative. The Web site suff ered from several 

drawbacks, however. It was not always updated in 

a timely way (for example, meeting minutes were 

often months out of date), and it was primarily 

targeted to the needs of IT people rather than 

research users. As archival information expanded, 

it also became unwieldy to use.

NCICB has initiated numerous improvements to 

the Web site, including the use of Plone (a content 

management system), which automates much of 

the process for maintaining a dynamic Web site. 

Extensive user input was solicited and usability 

testing was conducted in multiple phases to 

better serve the needs of diverse audiences, with 

a commitment to regular user testing. Additional 

enhancements to the site are planned for the 

caBIGTM Enterprise Phase to facilitate adoption by an 

expanding number of institutions. In addition, NCICB 

developed a companion Web site for patients and the 

public to use (http://cabig.cancer.gov) that presents 

updates about caBIGTM in lay language, in order to 

encourage involvement of additional constituencies 

to get involved in the caBIGTM endeavor.

Business Processes

The development of eff ective business processes was 

an important task to ensure that product development
caBIGTM Pilot 

• Data sharing agreements: Initial adoption 

agreements assumed that institutions adoptin

caBIGTM software tools would engage in data 

sharing within the adopter framework for soft

testing, since such sharing was central to the 

caBIGTM vision from the start. Data sharing per 

was not defi ned as a “deliverable,” however. 

 NCICB now ensures that data sharing is an integ

part of the agreements with Cancer Centers, in o

to achieve the overarching objective of accelerat

and enhancing research across the community.

Software Development

• Academically-based development: Numero

participants questioned the strategy of provid

resources to academic centers for the develop

of professional-grade software, since capabilit

varied widely among Cancer Centers, with som

able to deliver appropriate tools on time, but m

fi nding it diffi cult, if not impossible, to do so. A 

component of NCICB’s initial strategy was to u

academic institutions for the development eff 

based on the premise that there was signifi can

capability embedded in those sites and that th

existing applications, data, and infrastructure 

could and would be adopted to avoid unneces

de novo development. NCICB’s actual experien

however, was that a Cancer Center’s scientifi c a

clinical excellence did not necessarily correlate 

with its ability to generate commercial-grade 

software, and that metrics to measure such an 

ability in advance were lacking. Moreover, at s

Centers that had advanced their own IT produ

from the community to help formulate a process for 

developing the caBIGTM strategic plan for the next 

three years, including development of a potential 

new governance structure.

• Contracting mechanism: The shortcoming most 

commonly noted by participants has been the 

caBIGTM Firm Fixed Price (FFP) contract mechanism. 

The NCI-designated Cancer Centers, in particular, 

found this mechanism daunting due to their nearly 

exclusive familiarity with grant-based federal 

funding programs. For example, one participant 

noted that academic institutions operate with 

virtually no cash reserve; consequently, their staff 

needs to be predictably funded. This shift from a 

grants-based model to a fi rm-fi xed priced contract 

model was a major cultural challenge for the 

Cancer Centers. In spite of challenges, the NCICB 

eventually negotiated a base agreement with 

each participating Cancer Center, via the general 

contractor. Tasks were executed within that base 

agreement in order to avoid an unwieldy process 

of re-negotiating with each Center for each new 

activity. The process took several iterations to fi nd 

the best method to channel fi nancial resources 

to the Centers while setting success criteria that 

would enable NCICB to re-direct resources based 

on success or failure. Drawbacks of the initial 

approach were that dollar amounts were too small 

and the time frames too limited to achieve the 

objectives. Cancer Centers expressed concern over 

the lengths of the contracts, currently set at 12 

months, with task orders of two to six months, in 

contrast with grants-based funding, which
38

combinations of IT and research expertise, and us

centered design is incorporated as appropriate.

• User interface consistency: caBIGTM software 

developers designed interfaces unique to their 

philosophies, since no guidance on standardizi

the user interfaces of the software tools had be

developed for the program. As a result, tools 

produced by diff erent developers had signifi ca

diff erent interfaces.

 As of June 2007, this issue continues to be problem

NCICB, working with its contractor and with particip

has developed a style guide. Future RFPs will requ

adherence to this guide as one of the project delivera

• Software testing: The caBIGTM adopters progra

was envisioned as a mechanism to test, both 

from a technical and end user perspective, the 

quality of software developed within the initiat

Specifi cally, the end user group was intended t

be comprised of actual basic and clinical resear

users, with real data and real problems, who 

would devote time to test software in parallel 

to production settings. In practice, however, th

funded adopters were primarily the technically

oriented Cancer Center staff who were involved 

with caBIGTM from the workspaces, and they 

infrequently developed testing relationships w

such “real” users.

The caBIGTM Clinical Trials Management Systems 

Workspace has funded active clinical researchers 

to participate in Task Forces, whose responsibilitie

involve user acceptance testing of software in 

realistic conditions.

assessment of software development capabilities of 

respondents to development RFPs. The initiative has 

also adopted a Unifi ed Process Framework (UPF), 

a methodology for standardizing management of 

complex software projects. Additionally, as a result of 

the increasing stringency of the review process and an 

increasingly strong pool of participants as the caBIGTM 

program grows, the current winning proposals 

often refl ect a partnership of academic participants 

with domain expertise and commercial software 

developers that provide high-quality and costeff ective development. Also, the developer learning 

curve has been reduced with the publication of 

compatibility guidelines enabling new developers to 

write code from the outset that meets caBIGTM standards.

• Software tool applicability and usability: NCICB 

envisioned that the development of software tools 

would be executed through a “pairing” of software 

developers and researchers, in order to address 

real-life scientifi c needs. Toward that end, the 

workspaces were structured to encompass both 

IT experts and domain expert “end users.” But in 

practice, initial software tool development eff orts 

focused more on the IT and technological aspects 

of software design and implementation, rather than 

on the needs of end users. 

As the Pilot Phase advanced, it became apparent 

that the domain experts were not suffi ciently 

involved, and that as a result, software 

development primarily became a refl ection of 

the viewpoints of the IT participants and did not 

necessarily mesh with the day-to-day operations
caBIGTM Pilot 

in caBIGTM tool development. 

The overarching goal of caBIGTM is to provide and 

encourage the development of interoperable tools, 

not siloed point solutions. The NCICB believed that i

was important to identify and adopt interoperabilit

standards in the context of real application 

development and testing, not in the abstract. NCICB 

did have a process of outreach to the commercial 

community, and several vendors who attended 

caBIGTM Pilot Phase meetings did go on to participa

in development activities. However, many commerc

entities appeared to be reluctant to participate, and 

may have believed that caBIGTM as a pilot endeavor 

at too early a stage to be a good business opportun

Many existing vendor systems known to the commu

did not include the key technical requirements need

for the caBIGTM data sharing goal. For example, ther

was a lack of open and documented programming 

interfaces to enable semantically interoperable 

communications or connections to caGrid. Addition

many products did not capture or return data in a 

manner that leverages terminology and data struct

standards, rendering the contents of such systems l

usable by scientifi c peers at other institutions. There

since adequate COTS products were not generally 

available due to lack of interest from the vendors, th

program turned to a number of open source alterna

to prove out the interoperability framework during 

the Pilot Phase. At the same time, however, new too

were developed that will enable vendors of comme

products to more easily adapt their systems to beco

caBIGTM compatible. NCI hopes that an increasing

encountered numerous software bugs, leading to 

confusion about the true maturity of some tools. 

This problem resulted from the experience of 

academic developers, who usually write software 

that they themselves install and manage for a 

local community of users. These developers did not 

recognize the signifi cant investment in installation 

testing and support required to move software off site.

 Some developers also observed, however, that 

while they wished to carry development of the 

tools to completion, caBIGTM program management 

did not fund the projects long enough to deliver that.

caBIGTM has implemented more rigorous screens of 

the software development capabilities of institutions 

bidding for development tasks, as described above. 

For some organizations, caBIGTM implemented an 

education regimen that introduced more formal 

modern software development methodologies. 

Additionally, the program is incorporating a set of 

initiatives into the post-Pilot Phase that will provide 

longer-term and more stable means of funding 

software throughout the development life cycle.

Role of the Private/For-profi t Sector

Some participants felt that early and signifi cant 

private sector involvement would have been

benefi cial to the caBIGTM Pilot Phase as a whole, and 

that it also would have smoothed the transition 

from the Pilot Phase to the Enterprise Phase. Some

also observed that the project should have had a

funding mechanism for inclusion of commercial 

off -the-shelf software (COTS) products. While a few
40

Director’s offi ce at participating Cancer Centers, wh

will serve on site to plan, advocate for, and oversee 

caBIGTM adoption. 

g

community. Some participants noted, however, that 

at the pragmatic level of software tools adoption, 

a considerable amount of organizational change 

management is required, and that more assistance 

from NCICB is still needed to reinforce adoption of 

caBIGTM. “You need a team of people to visit and say 

‘here are the tools, and how can we help you?’” said 

one participating oncologist. Others noted that there 

is not yet suffi cient “mindshare” within their Cancer 

Center to drive caBIGTM adoption and that such a shift 

in sensibility and willingness to change will require 

dedicated internal champions. 

Some of these challenges pertain to the role of IT 

overall, rather than just caBIGTM. For example, the 

scientifi c community and the information technology 

community have typically functioned apart from 

each other, in silos, with little communication or 

sense of common purpose. Moreover, within many 

organizations, information technology is often 

viewed as a technical service rather than a requisite 

strategic partner. IT experts may not play a role at the 

leadership level, making it diffi cult to approach the 

challenge of connectivity within an organization’s 

own departments, much less between diff erent 

organizations, in a comprehensive way. The caBIGTM 

initiative was not fully prepared to address these 

environmental factors at the outset, which slowed 

caBIGTM adoption.

NCICB has noted in recent months that the cultural 

shifts are accelerating; these shifts are most likely due, 

in some part, to the demands of molecular-based 

translational research. “Connectivity” also is becoming 
caBIGTM Pilot 

The Launch of the Enterprise Phase

The overarching objective continues to be caBIGTM-

enabled connectivity of the people, institutions, 

and data in the cancer community that will lead to 

answers for the complex questions of cancer biology 

and thereby improve patient outcomes. 

In the spring of 2007, caBIGTM entered its Enterprise 

Phase, the goals of which include:

• A systematic rollout of available caBIGTM tools and 

infrastructure to NCI-designated Cancer Centers; 

• Formation of an enterprise support network to 

diversify and broaden access to caBIGTM knowledge 

and expertise; and

• Engagement with a broader community of 

government, academic, and private sector 

entities that in the aggregate constitute a future 

“ecosystem” of those who will adopt caBIGTM, further 

develop it, and provide compatible software, 

services, and support.

caBIGTM Adoption Program

NCICB is collaborating with the NCI Cancer Centers 

program and others to achieve caBIGTM compatibility 

throughout the cancer research community. 

The process begins with a self-assessment within 

each organization wishing to become caBIGTM 

compatible. This evaluation is followed by the 

development of a caBIGTM deployment plan. 

Organizations will then work with NCI to get 

connected to caBIGTM through the installation of 

caBIGTM “bundles” or compatibility products, whic

form the backbone of key software infrastructure 

and data sharing policies and practices needed 

to become caBIGTM compatible. The bundles are 

described below:

• caBIGTM Clinical Trials Compatibility Framew

This bundle includes components to support t

conduct of human clinical trials and related typ

of human subject research. 

• caBIGTM Life Science Distribution: This bundle 

includes tools and applications that support a va

of basic and translational research capabilities. 

• Data Sharing and Security Framework: This 

bundle is based on the caBIGTM Data Sharing 

Framework. The Framework, when fully built o

will consist of a set of policies, processes, mode

agreements, model data sharing plans, and oth

materials that participating Centers agree to h

develop and to adopt as appropriate. 

Enterprise Support Network

NCI is augmenting its traditional support of the 

caBIGTM community with the caBIGTM Enterprise 

larger universe of networked organizati

that link the entire cancer community.
42

institutions. It will serve to provide the higher 

levels of support and additional resources that 

institutions often need when they introduce 

new and powerful software tools. The program 

will initially focus on adopting applications fro

the TBPT Workspace to support biospecimen 

annotation and management.

caBIGTM and the Patient Communi

As mentioned previously, patient advocates were 

an integral part of the Pilot Phase community, 

participating in workspa

and other caBIGTM 

development activities. M

cancer patients, howeve

have not seen, experienc

or even been aware of th

development of caBIGTM, 

since to date it has been 

foundational IT endeavo

In the future, however, a

caBIGTM tools are integra

into every step of a patie

centric clinical experienc

patients will potentially benefi t from caBIGTM thro

its ability to facilitate selection of treatment and 

entry into clinical trials of experimental treatmen

monitoring for treatment response and adverse 

eff ects, and monitoring for recurrence of disease

example, programs such as caMatch enable patie

to fi nd clinical trials for which they would be elig

participants. This 21st century paradigm of molec

and biotechnology companies. The programs include:

• Service Providers: Comprehensive Technical 

and End-User Support. Service Providers are 

third-party organizations that will deliver software 

application and infrastructure technical support to 

end users and IT professionals on a fee-for-service 

basis. These organizations will be designated 

by caBIGTM to help ensure that recipients of their 

services are getting the most accurate, up-to-date, 

and eff ective support of caBIGTM technology.

• Knowledge Centers: External-facing Domain 

Experts. Knowledge 

Centers will provide 

domain-specifi c 

expertise within the 

caBIGTM community 

and serve as points of 

contact for education, 

outreach, training, tool 

enhancements, and 

deployment needs to the 

rest of the community. 

Each Knowledge Center 

will focus on a niche 

technology area and serve as an all-purpose 

consulting and service resource for that particular 

technology, serving any institution that seeks help.

• Program Offi ces: Internal-facing Institutional 

caBIGTM Expertise. Program Offi ces will be caBIGTM 

teams that will be established within an individual 

institution and tasked with facilitating and 

expediting the adoption of caBIGTM technology in 

that institution. Such offi ces will be helpful to 

“caBIGTM will drive clinical trials of 

the future. It will be the way we 

bring genomics, proteomics, and 

clinical data together for each 

patient in a clinical trial.”57

John Niederhuber, M.D.

Director, National Cancer Institute

57 John Niederhuber, M.D., Director, National Cancer Institute, 

discussion on May 30, 2007.
caBIGTM Pilot 

endeavor de novo. Most caBIGTM to

and infrastructure components a

widely applicable beyond cancer. Moreover, as th

nation’s healthcare delivery sector moves increas

towards electronic health records (EHRs) and syst

to connect laboratory, imaging, and clinical data 

all patients, it will be logical to use caBIGTM or caB

like technology to link research and clinical care. 

(See Figure11)

As caBIGTM capabilities spread throughout the can

community, into other disease areas, and across 

the translational research continuum, the caBIGTM 

initiative will have helped to enable a new gener

of Molecular Medicine for the benefi t of millions 

of patients. 

based translational research will thereby be 

experienced at the individual patient level, with 

the intended benefi ts of better prevention, earlier 

diagnoses, more eff ective treatment, and improved 

outcomes. In a biomedical world connected with 

caBIGTM and “caBIGTM-like” technologies, doctors and 

patients will be able to make treatment decisions 

using systematic and evidence-based metrics 

selecting the personalized therapy that gives the 

patient the best chance for a positive outcome. 

caBIGTM as a Model

Many participants and observers have commented 

that caBIGTM—including its community, tools, 

caBIGTM infrastructure 

and tools may link cancer 

community globally.

caBIGTM capabilities may 

be integrated into 

health IT.

caBIGTM may serve as a 

model for other disease 

research and biomedical 

endeavors.

Figure 11. Future Directions for caBIGTM

58 Elias A. Zerhouni, M.D., Director, National Institutes of Health, based on 

remarks at the 2007 caBIGTM Annual Meeting, February 6, 2007.
44

profi ling. Duke staff ’s cumulative experience with caBIGTM and the intense 

informatics support needs of this trial provide a clear opportunity to test the 

new informatics technologies. Cancer Center leadership has stated that the 

principles envisioned by the caBIGTM program are requirements for this trial, and 

that caBIGTM software will be part of the informatics infrastructure. The extent 

to which caBIGTM software will be part of the informatics infrastructure is the 

subject of this case study, which describes the Cancer Center’s goals for caBIGTM, 

but does so in light of the decisions that early adopters face in selecting any 

new technology for use in actual research.

The Risks Faced by Early Adopters

With any new technology, early adopters are to be lauded: they face signifi cant 

risks of increased eff ort and expense to deploy new technologies, and they also have an obligation to report th

experience back to the technology’s developers. Such eff orts are, however, absolutely critical to fi nding bugs a

more importantly, to identifying missing functionality that paves the way for that technology to be ultimately 

successful. In the case of Duke University, Cancer Center leadership completely supports the principles envisio

by the caBIGTM program and has decided to implement all caBIGTM components that are ready now to be integr

in the trial.

Duke’s Participation in caBIGTM During the Pilot Phase

Several groups at Duke University have been funded participants in caBIGTM since the initiative’s inception. 

Signifi cant knowledge has been accumulated by Duke groups as both developers and adopters of tools in 

the architecture, tissue banking, integrative cancer research, and clinical trials workspaces. Duke has specifi c 

experience in managing clinical trials data collection using C3D (See Appendix A); using caGrid to link proteom

data generation with an analysis framework, based upon the R statistical language, connected to a graphical u

interface; and within the caTRIP project, sharing the data from a large tissue bank management application on 

Grid by using caTISSUE as a piece of interface software. (See Appendix A)

 data in this project 

 caBIGTM compatible, a

 whenever possible, w

 will make use of caBI

 software.”59

Kim Lyerly, M.D.

Director, Duke 

Comprehensive 

Cancer Center

59Kym Lyerly, M.D., Director, Duke Comprehensive Cancer Center, discussion on May 30, 2007.
caBIGTM Pilot P

electronic data collection, study and patient management, adverse event reporting, and imaging, this trial will 

need to make extensive use of annotated tissue bank management systems, as well as pathology informatics a

molecular bioinformatics data management and analysis tools. Ideally, the data gathered should be integrated 

able to be queried from a number of investigators whose frame of reference could be from diff erent places in t

Molecular Medicine translational research process. (See Figure 1)

The caBIGTM platform is being developed to achieve precisely the data integration and interoperability desired 

for this trial, and there are many caBIGTM capabilities that are extant, especially in data standardization. Howeve

because the trial is likely to begin in the fall of 2007 when many caBIGTM tools do not include the full functional

required by end users, Duke informatics staff will have to make real-time decisions about which caBIGTM tools t

use, which to wait for and integrate later, and which to skip in favor of currently available software alternatives

Feedback to Inform the Future of caBIGTM

Since the Duke investigators are launching this breast cancer trial as the caBIGTM initiative is entering its Enterp

Phase, there is an opportunity for signifi cant “real-life” experience. Thus, the Duke eff orts to deploy caBIGTM too

for this project may provide the fi rst eff ective model of supporting a Molecular Medicine translational research 

program, from end to end, with integrated informatics, and they may provide extensive programmatic feedba

caBIGTM management for future deployment of the platform. 
46

 Clinical Trials Management 

Cancer Central 

Clinical Participant 

Registry (C3PR)SC(R)

Clinical Data 

Exchange / Lab 

Integration Hub 

(caXchange)SC

Clinical Trials Object 

Data System 

(CTODS)

Clinical Data System 

(CDS)

Patient Study 

Calendar (PSC)

Cancer Adverse 

Event Reporting 

System (caAERS)

caTRIPSC(R)

https://ca

.gov/too

https://ca

.gov/too

LabInteg

https://ca

.gov/too

https://ca

.gov/too

https://ca

.gov/too

StudyCal

https://ca

.gov/too

https://ca

.gov/too

Clinical trial data collection

Clinical trial datasubmission

Patientcalendarmanagement

Adverse event management

Outcomesanalysis

currently supports electronic submission of clinical trials data to the National 

Cancer Institute’s (NCI) Clinical Data System (CDS) and the Clinical Trials Monitoring 

Service (CTMS/Theradex). C3D consists of three Web-based components: Oracle 

Clinical, for protocol building; Remote Data Capture, for data entry and management; and Integrated Review / Java Review, for real-time access to clinical data 

within and across clinical studies to authorized users.

Cancer Central Clinical Participant Registry (C3PR) is a Web-based application for 

managing clinical trial data across multiple cancer clinical trials. The tool is used to 

improve clinical trials activation and execution by providing a large-scale and 

efficient Web-based clinical trials information management system available for use 

by multiple cancer research centers across the country.

The Laboratory Integration Hub (caXchange) is an open source software tool used 

to collect, process, and report laboratory data gathered during a clinical trial.

The Clinical Trials Object Data System (CTODS) is a virtual clinical data warehouse 

that enables data from any Clinical Trials Data Management System (CDMS) or data 

source to be available to the cancer research community. It provides clinical 

researchers with identifiable clinical trials data (as permitted) and provides the 

broader cancer research community with de-identified clinical trials data (data that 

have all patient identification information removed).

The Clinical Data System (CDS) is an independent and stand-alone data submission 

infrastructure (electronic) that serves as the primary data submission system for 

NCI-sponsored clinical trials. Data is submitted via a Web-based interface. The 

system also provides a mechanism for data access by stakeholders, including 

cancer centers, cooperative groups, and single institutions via a data analysis 

interface. This interface enables users to view and generate reports about various 

aspects of the clinical trial process.

The Patient Study Calendar (PSC) is an open source, standards-compliant software 

application that can be used by organizations that manage patients on clinical 

trials. The PSC is a stand-alone, Web-based application providing the ability to 

create and edit study calendar templates, generate and view prospective calendars 

of patient activities, track activities as they occur, and manage calendars as they 

change during a study.

The Cancer Adverse Event Reporting System (caAERS) is an open source software 

tool that is used to collect, process, and report adverse events that occur during 

clinical trials.

caTRIP allows users to query across a number of caBIGTM data services, join on 

common data elements (CDEs), and view their results in a user-friendly interface. 

Having as its initial focus the enabling of outcomes analysis, caTRIP allows clinicians 

to query across data from existing patients with similar characteristics to find 

treatments that were administered with success. In doing so, caTRIP can help 

inform treatment and improve patient care, as well as enable the search for 

available tumor tissue, locate patients for clinical trials, and investigate the 

association between multiple predictors and their corresponding outcomes such 

as survival.
caBIGTM Pilot 

Biospecimen Banking 

ImageAnalysis

DataMapping

Pre-Clinical Data Management

ClinicaManag

caTissue CoreSC

cancer Text 

Information 

Extraction System 

(caTIES)SC

caTissue Clinical 

Annotation Engine 

(CAE)

National Cancer 

Imaging Archive 

(NCIA)

caAdapter

Electronic 

Laboratory 

Management 

Information 

Resource (caELMIR)

Research Data 

(FIREBIRD)

https://ca

.gov/too

core

https://ca

.gov/too

https://ca

.gov/too

https://ca

.gov/too

https://ca

gov/tools

https://ca

.gov/tool

Regulatory compliance ment suppo

Cancer imagearchive andretrieval

Data mappingtransformationand validation

Pre-Clinical data management

Biospecimen tracking and annotation

Biospecimenannotation

caTissue Core is a tissue bank repository tool for biospecimen inventory, tracking, 

and basic annotation. Version 1.2 of caTissue permits users to track the collection, 

storage, quality assurance, and distribution of specimens as well as the derivation 

and aliquotting of new specimens from existing ones (e.g., for DNA analysis). It also 

allows users to find and request specimens that may then be used in molecular, 

correlative studies.

The cancer Text Information Extraction System (caTIES) is a locator to tissue 

resources via the extraction of coded information from free text surgical pathology 

reports. caTIES uses controlled terminologies to populate caBIGTM-compliant data 

structures. It provides researchers with the ability to query, browse, and acquire 

annotated tissue data and physical material across a network.

caTissue Clinical Annotation Engine (CAE) is a Web-based user interface for 

standards-based manual annotation of biospecimens with clinical information. It 

supports importing structured data from clinical information systems such as 

anatomic pathology laboratory systems (APLIS), cancer tumor registries, and clinical 

pathology laboratory systems. caTissue CAE allows the integration of annotations 

from multiple sources within the cancer centers, providing a complete picture of a 

patient’s disease. The potential users of caTissue CAE include researchers, tissue 

bankers, pathology assistants, pathologists, and registrars. The current version 

contains only anatomic pathology annotation.

The National Cancer Imaging Archive (NCIA) is a searchable, national repository 

integrating in vivo cancer images with clinical and genomic data. NCIA provides the 

cancer research community, industry, and academia with public access to: DICOM 

images, image markup, annotations, and rich meta data.

caAdapter is an open source tool set that facilitates data mapping, transformation, 

and validation among different kinds of data sources, including HL7 version 3 

messages, Study Data Tabulation Model (SDTM) data sets, object models and data 

models. It possesses the capability to perform vocabulary validation and integrates 

with NCICB caCORE components. caAdapter has a component-based architecture 

that offers a tool set to support data mapping, transformation, and standard data 

reporting.

The Electronic Laboratory Management Information Resource (caELMIR) provides 

the pre-clinical scientist with a data management system to record experimental 

data. caELMIR is a “LIMS” system for basic scientific data.

* For explanation of symbols “SC(R)” and “SC” see page 53
48

Data Integration Genome Analysis

GenePattern

caIntegratorSC

caBench-to-Bedside 

(caB2B)

SEEDSC

Transcript 

Annotation 

Prioritization and 

Screening System 

(TrAPSS)SC

Function Express 

(caFE)SC

https://ca

.gov/too

GenePatt

https://ca

.gov/too

caIntegra

https://ca

.gov/too

https://ca

.gov/too

https://ca

.gov/too

https://ca

.gov/too

_Express

Molecular biology 

Molecular biology and clinical data analysis

Genomeannotation

Genome annotation to find diseasecausing mutations

Microarrayprobe annotation

GenePattern puts sophisticated computational methods into the hands of the 

biomedical research community. A simple application interface gives a broad 

audience access to a growing repository of analytic tools for genomic data while an 

Application Programming Interface (API) supports computational biologists. 

GenePattern is a powerful analysis workflow tool developed to support multidisciplinary genomic research programs and designed to encourage rapid integration 

of new techniques. 

caIntegrator is a novel translational informatics platform that allows researchers 

and bioinformaticians to access and analyze clinical and experimental data across 

multiple clinical trials and studies. The caIntegrator framework provides a mechanism for integrating and aggregating biomedical research data and provides access 

to a variety of data types (e.g., Immunohistochemistry (IHC), microarray-based gene 

expression, SNPs, clinical trials data etc.) in a cohesive fashion.

caBench-to-Bedside (caB2B) is a caGrid client that permits bench scientists, 

translational researchers, and clinicians to leverage caBIGTM compatible data and 

analytical services through a graphical user interface. Its metadata-based query 

interface enables end users to search virtually any caGrid data service. This single 

tool was designed to integrate and analyze diverse biomedical data sets seamlessly. 

It has been developed to facilitate the individual steps of cancer research analyses 

and to reduce the bench-to-bedside barrier.

SEED is a tool for making and sharing genomic annotations, and it can be 

used to access annotations already made, perform queries upon them, and 

perform computations upon the annotations or upon information collated with 

the annotations, (e.g., perform a psi-blast amongst sequence data for all genes 

matching an annotation search). In these two broad categories, the former requires 

read/write services while the latter requires just read-only services.

Transcript Annotation Prioritization and Screening System (TrAPSS) predicts the 

potential of gene sub-sequences to contain disease-causing mutations, utilizes 

annotation to prioritize focused regions of a gene during mutation screening, and 

aids scientists who are searching for the genetic mutation or mutations that are 

linked to expression of a disease phenotype.

Analysis of microarray data using gene annotation is essential for the identification 

of aberrant pathways in tumors. Function Express is an ETL tool that annotates 

probes on microarrays using publicly available biomedical databases and automatically update these annotations on a regular basis. This data can be queried using a 

Web-based query interface or programmatically using the caCore-like Application 

Programming Interface (API).
caBIGTM Pilot 

Genome Analysis Statistical Analysis Data Services

GeneConnect

Visual Statistical 

Data Analyzer 

(VISDA)

Distance Weighted 

Discrimination 

(DWD)

Protein Information 

Resource (PIR)SC 

caArray

https://ca

.gov/too

GeneCon

https://ca

.gov/too

https://ca

.gov/too

https://ca

.gov/too

https://ca

.gov/too

Determbiologiusing g

Mapping and interlinking of genomic dividers

Multivariatecluster-modeling

Statistical corrections

Protein data collectionand analysis

Microarray data collection and analysis

a gene-by-gene approach, GoMiner classifies the genes into biologically coherent 

categories and assesses these categories.

GeneConnect is a caBIGTM mapping service that makes interoperability possible by 

interlinking approved genomic identifiers. These include: Ensembl Gene ID, Ensembl 

Transcript ID, Ensembl Protein ID, Entrez Gene ID, UniGene ID, GenBank mRNA 

Accession Number, GenBank Protein Accession Number, RefSeq mRNA Accession 

Number, RefSeq Protein Accession Number, and UniProtKB Primary Accession Number.

To interlink all of these identifiers, database annotations (either direct or inferred) 

and an alignment engine have been used to construct pair wise connections, and 

then all-to-all relationships have been calculated by traversing all possible combinations of edges in the graph using every node as the starting point. For each 

query, composed of one or more input identifiers and a set of paths that may be 

traversed, the Path Score and Frequency are calculated. The GeneConnect application is an independent component with the following modules: GeneConnect 

server, Web application, and XML-RPC server.

The Visual Statistical Data Analyzer (VISDA) is an analytical tool for cluster modeling, 

visualization, and discovery. Being statistically-principled and visually-insightful, 

VISDA exploits the human gift for pattern recognition and allows users to discover 

hidden clustered data structure within high dimensional and complex biomedical 

data sets. The unique features of VISDA include its hybrid algorithm, robust 

performance, and “tree of phenotype.” With global and local biomarker identification and prediction functionalities, VISDA allows users across the cancer research 

community to analyze their genomic/proteomic data to define new cancer 

subtypes based on the gene expression patterns, construct hierarchical trees of 

multiclass cancer phenotypic composites, or to discover the correlation between 

cancer statistics and risk factors. 

Distance Weighted Discrimination (DWD) is a tool that performs statistical corrections to reduce systematic biases resulting from different sources of RNA, batches 

of microarrays, and particularly different microarray platform.

The Protein Information Resource (gridPIR) service provides a data resource for 

genomic and proteomic research containing rich, high quality, and annotated 

information on all protein sequences. The resource is supported by UniProt 

Knowledgebase (UniProtKB) and other relevant Protein Information Resource (PIR) 

databases. 

caArray is an open source microarray data management system that allows users to 

submit, annotate, and download microarray data. caArray was developed using the 

caBIGTM compatibility guidelines, as well as the Microarray Gene Expression Data 

(MGED) society standards for microarray data. Compatibility with these standards 

and guidelines will facilitate data sharing and integration of diverse data types 

including clinical, imaging, tissue, and functional genomics data. A number of 

analytical tools that connect to caArray are already available, including geWorkbench and GenePattern, which both provide a variety of data analysis, visualization, 

and annotation functions for microarray and other data types.
50

Protein Analysis

Gene Expressionand Protein Analysis

Q5

Proteomics 

Laboratory 

Information 

Management 

System (protLIMS)SC

Cancer Molecular 

Pages (CMP)

Computational 

Proteomics Analysis 

System (CPAS) / 

LabKey

Biconductor

RProteomicsSC

https://c

.gov/too

RProteom

https://c

.gov/too

https://c

.gov/too

Proteom

https://c

.gov/too

Molecula

https://c

.gov/too

https://c

.gov/too

Biocondu

Collection of damodels of hum

Mass spectrometry data analysis

Management of 2D gel labprocessing

Collection and analysis of protein data relevant to cancer

Microarray,DNA processing, and assessment

Search—Users can retrieve information about the making of models, their genetic 

descriptions, histopathology, images, microarray data, and therapeutic trials in 

which the models were used, among other things.

System Function Administration—The Admin function provides services for user 

registration, review of submitted models, and database management.

RProteomics is a package for analyzing mass spectrometry proteomics data. 

Specifically, these routines have been tailored for the analysis of MALDI style data, 

including LC-MS data, although use of these routines for the analysis of SELDI data 

and FT-ICR data is possible. The current implementation of the RProteomics system 

meets the Gold level of caBIGTM compatibility. This guide is geared toward the use of 

the application via the GUI. All components should be installed according to the 

instructions found in the RProteomics System Installation/Administration Reference 

Manual. Data and analyses may be performed locally or via the grid.

Closely associated with RProteomics, Q5 has shown utility in disease classification 

of expression-dependent proteomic data from mass spectrometry of human 

serum. Q5’s ability to classify complex fragment mixtures was evaluated by testing 

its ability to discriminate the mass spectra of healthy vs. diseased human serum 

samples. The two disease states examined in testing were ovarian and prostate 

cancer. Existing screening methods for both cancers carry a low positive predictive 

value (PPV). 

protLIMS is a Laboratory Information Management System dedicated to studies in 

the realm of proteomics. The goal of the prototype version is to develop the system 

to the point in the analytical workflow where samples are prepared for mass 

spectroscopy. This entails recording of biological sample data, sample preparation, 

protein separation/resolution, and isolated protein sample preparation, etc.

The Cancer Molecular Pages (CMP) project was developed to automatically 

annotate cancer-related proteins in and make the annotations widely available on 

the caBIGTM grid. CMP has these essential features: appending local annotations to a 

computed database, processing lists of proteins, using a range of homology tools, 

and linking protein entries to relevant caBIGTM datasets.

Computational Proteomics Analysis System (CPAS) is a proteomics application that 

runs on LabKey Server, the open source platform for high-throughput biology 

research. CPAS automates the process of peptide scoring and running tools from 

the Trans Proteomic Pipeline, and then loads the results into a SQL database. 

Researchers can use the Web interface of CPAS to analyze and compare results 

across thousands of experiments and share their results securely with colleagues 

around the world. CPAS is now caBIGTM Silver-level compliant. 

Bioconductor is an established open source collection of software packages for 

high-throughput genome analysis. Packages adapted for caBIGTM allow preprocessing of microarray data, DNA copy number assessment from gene expression data, 

and SELDI-TOFF mass spectrometry peak finding.

Data S
caBIGTM Pilot 

Pathway Analysis

Pathway Interaction 

Database

Pathway Tools

ReactomeSC

https://ca

gov/tools

https://ca

gov/inven

resources/

interaction

https://ca

.gov/tool

Pathways

Analysis oand pathwrelevant t

Analysis of biomolecular interactions and key cellular processes

Human pathwayanalysis

The Reactome data sharing establishes Reactome as a data feed to caBIGTM by 

extending the caBIO data model, providing Web Services APIs, and setting up a 

Web Services server.

The Pathway Interaction Database is a highly structured, curated collection of 

information about known biomolecular interactions and key cellular processes 

assembled into signaling pathways. Users can query the database by pathway 

name, by molecule name, or by accession. Molecular detail includes protein 

post-translational modifications and cellular location. Annotations on interactions 

include literature citations and evidence codes. All data is available in BioPAX Level 

2 export.

Pathways is a suite of tools, which include: cPath, an open source pathway database 

and software suite designed for systems biology research and Cytoscape, used to 

overlay gene expression data and visualize the results. The third piece is Biological 

Pathway Exchange language, which is a data standard currently under development to model biological pathways.
52

Core Infrastructure Vocabularies

Biomedical 

Research Integrated 

Domain Group 

(BRIDG) Model

Cancer Common 

Ontologic 

Representation 

Environment 

(caCORE) 

Cancer 

Bioinformatic 

Infrastructure 

Objects (caBIO)SC

NCI Enterprise 

Vocabulary Services 

(EVS)

Cancer Data 

Standards 

Repository (caDSR)

caCORE Software 

Development Kit 

(caCORE SDK)

https://c

.gov/inve

infrastruc

https://c

.gov/inve

Infrastru

https://c

.gov/too

https://c

.gov/inve

Infrastru

https://ca

.gov/inve

Infrastruc

https://ca

.gov/inve

Infrastruc

Standardization of clinical data exchange

Common data managementand application developmentframework

Development of controlled vocabularies

Standardization of metadata in the form of common data descriptors

Creation of a “caCORE-like” software system

The Biomedical Research Integrated Domain Group (BRIDG) project is a collaborative effort of stakeholders from the Clinical Data Interchange Standards Consortium 

(CDISC), the HL7 Regulated Clinical Research Information Management Technical 

Committee (RCRIM TC), the National Cancer Institute (NCI), and the U.S. Food and 

Drug Administration (FDA) to produce a shared view of the dynamic and static 

semantics that collectively define a shared domain-of-interest, (i.e., the domain of 

clinical and pre-clinical protocol-driven research and its associated regulatory 

artifacts).

The Cancer Common Ontologic Representation Environment (caCORE) is the open 

source group of software products developed by the NCI Center for Bioinformatics 

(NCICB). By providing a common data management and application development 

framework, caCORE helps streamline informatics development throughout the 

cancer community. Components of caCORE support the development and 

utilization of semantically interoperable data systems, ensuring that biomedical 

research data deployed within this framework is consistent and comparable. 

The Cancer Bioinformatic Infrastructure Objects (caBIO) project provides a robust 

platform and independent infrastructure that illustrates data integration 

techniques, allowing researchers to perform innovative analysis via a variety of 

APIs, Web services, and html interfaces. caBIO employs industry-standard software 

engineering methodologies to develop objects, data models, middleware, 

vocabularies, and ontologies for biomedical research. caBIO is the primary 

programming interface to caCORE, a synthesis of software, vocabulary, and 

metadata models for cancer research. caBIO objects are implemented using Java, 

and they represent biological and laboratory entities such as genes, chromosomes, 

sequences, SNPs, libraries, clones, pathways, and ontologies.

The NCI Enterprise Vocabulary Services (EVS) develops standard, controlled 

vocabularies as part of caCORE. This service produces the NCI Thesaurus and the 

NCI Metathesaurus, which is based on NLM's Unified Medical Language System 

Metathesaurus and supplemented with additional cancer-centric vocabulary.

The Cancer Data Standards Repository (caDSR) is a metadata registry in caCORE 

that stores and manages Common Data Elements (CDEs) that are developed by 

caBIGTM participants and various NCI-sponsored organizations.

The caCORE Software Development Kit (caCORE SDK) is a set of tools designed to 

aid in the design and creation of a “caCORE-like” software system. This system is 

“semantically integrated” __ all exposed API elements have runtime accessible 

metadata that defines the meaning of the elements using controlled terminology.
caBIGTM Pilot 

Vocabularies

Mouse-Human 

Anatomy Mapping 

Ontology (MHAP)

Cancer Nutrition 

Ontology

https://ca

.gov/inve

Infrastruc

https://ca

gov/inven

Infrastruc

Voinsan

Standard vocabularydevelopment for humanand mouse anatomy

Standard vocabulary development for cancer nutrition

The Mouse-Human Anatomy Project (MHAP) provides a mapping and harmonization of Human and Mouse anatomical descriptors as they are currently used for 

murine and human models by Mouse Genome Informatics and the NCI Thesaurus. 

This ontology will facilitate closer integration of human and mouse cancer data, 

promote the use of the mouse as a model for cancer research, and accelerate 

translation of basic research discoveries into new clinical therapies.

The Cancer Nutrition Ontology provides a publicly available, unified set of nutrition 

vocabularies, based on external standards, that would provide vocabulary/ 

conceptual uniformity across applications. The need for a nutrition ontology is 

driven from studies that search for nutritional factors that alter the risk of getting 

cancer. Clinical trials study chemopreventative agents and primary or adjuvant 

therapeutic agents, such as SELECT (Selenium, Vitamin E, and prostate cancer). 

Development of this ontology involved gathering input from numerous experts 

and sources, including USDA, InFoods, NCI Office of Dietary Supplements, IUPAC, 

University of Hawaii, and others.

SILVER COMPATIBILITY

In addition, several tools were developed outside of caBIGTM and submitted for compliance review. The majority of developer projects in caBIGTM 

developing to Silver level compatibility. https://cabig.nci.nih.gov/guidelines_documentation/Silver_Review/#silver 

SC(R) = Tools currently under review for Silver Compatibility [This includes: Cancer Central Clinical Participant Registry (C3PR), caTRIP, Cancer Mod

 Database (caMOD)]

 SC = Silver Compatible Products [This includes: caTissue Core, cancer Text Information Extraction System (caTIES), caIntegrator, SEED, Transcrip

 Annotation Prioritizing and Screening System (TrAPSS), Clinical Data Exchange/Lab Integration Hub (caXchange), Function Express (caFE) 

 Information Resource (PIR), RProteomics, Proteomics Laboratory Information Management System (protLIMS), Reactome, Cancer Bioinfor

 Infrastructure Objects (caBIO)]

BRONZE COMPATIBILITY

The caBIGTM Bronze certification program is a mechanism for software products not created as part of the caBIGTM program to be certified as com

with the caBIGTM compatibility guidelines at the Bronze level. Current Bronze-level products include: BioXM, TrialCheck, Biological Specimen Inv

System (BSI) https://cabig.nci.nih.gov/guidelines_documentation/bronze/#bronze
54

Recognition_Program_fi nal.pdf/view/, and https://cabig.nci.nih.gov/News_Folder/caBIG_AwardeePDF.pdf/. 

The following is a list of organizations participating at the conclusion of the Pilot Phase. The NCI-designated Cancer 

Centers that were the initial participants in the caBIGTM Pilot Phase are marked in bold. Their pioneering activity set 

the stage for the growth that followed. 

Cancer Center/Medical Center Participants

• Albert Einstein Cancer Center

• Arizona Cancer Center – University of Arizona

• Baylor College of Medicine

• Brown University

• The Burnham Institute

• Case Western Reserve University School of 

Medicine

• Cancer Research Center of Hawaii

• Chao Family Comprehensive Cancer Center − 

University of California at Irvine

• City of Hope National Medical Center & Beckman 

Research Institute

• Cold Spring Harbor Laboratory

• College of William and Mary

• Columbus Children’s Research Institute

• Drexel University

• Duke Comprehensive Cancer Center

• Norris Cotton Cancer Center − 

Dartmouth-Hitchcock Medical Center

• Dana-Farber Cancer Institute − Harvard University

• DPRN Coordinating Center 

• Emory University School of Medicine

• Fox Chase Cancer Center

• Fred Hutchinson Cancer Research Center

• George Washington University

• Georgia Institute of Technology

• Lombardi Comprehensive Cancer Center at 

Georgetown University

• Group Health Cooperative

• H. Lee Moffi tt Cancer Center & Research Institute 

− University of South Florida

• Helen F. Graham Cancer Center, Christiana Care 

Health Services

• Herbert Irving Comprehensive Cancer Center 

Columbia University

• Holden Comprehensive Cancer Center − 

University of Iowa

• Indiana University

• Jackson Laboratory

• Kimmel Cancer Center −

Thomas Jeff erson University

• Louisiana Cancer Research Consortium

• Louisiana State University Health Sciences Cen

• Mayo Clinic Comprehensive Cancer Center

• Massachusetts Institute of Technology Center f

Cancer Research

• MD Anderson Cancer Center − University of T

• Memorial Sloan-Kettering Cancer Center 

• Mouse Genome Informatics

• New York University Cancer Institute 

• Robert H. Lurie Comprehensive Cancer Cente

Northwestern University

• The Ohio State University Research Foundati

• Oregon Health and Science University

• Penn State College of Medicine 

• Meyer L. Prentis / Karmanos Comprehensive 

Cancer Center of Metropolitan Detroit

• Roswell Park Cancer Institute

• The Sidney Kimmel Comprehensive Cancer 

Center − Johns Hopkins University

• Siouxland Hematology Oncology Associates
caBIGTM Pilot 

University of California, Davis

• University of California, Los Angeles

• University of California, San Francisco 

Comprehensive Cancer Center

• Rebecca and John Moores UCSD Cancer Center −

University of California, San Diego

• University of Chicago Cancer Research Center

• University of Colorado Health Sciences 

Department of Preventive Medicine and 

Biometrics (UC-PMB)

• University of Maryland

• University of Michigan Comprehensive Cancer 

Center

• University of Minnesota Cancer Center

• University of Nebraska Medical Center −

Eppley Cancer Center

• University of New Mexico Cancer Research and 

Treatment Center

• UNC Lineberger Comprehensive Cancer Center − 

University of North Carolina, Chapel Hill

• University of Pennsylvania − Abramson Cancer 

Center

• University of Pittsburgh Medical Center

• University of the Sciences in Philadelphia

• University of Southern California −

Norris Comprehensive Cancer Center

• University of Utah

• University of Wisconsin Paul P. Carbone 

Comprehensive Cancer Center

• University of Vermont

• University of Virginia

• Vanderbilt-Ingram Cancer Center

• Virginia Commonwealth University −

Massey Cancer Center

• Virginia Polytechnic Institute and State University

• Wake Forest Comprehensive Cancer Center

• The Wistar Institute

• Yale Cancer Center

gg g

• NCI Cancer Therapy Evaluation Program

• NCI Consumer Advocates in Research and 

Related Activities (CARRA) or Patient Advocate 

Representative

• NCI Center for Bioinformatics

• NCI Center for Cancer Research 

• NCI Division of Cancer Control and 

Population Sciences

• NCI Division of Cancer Prevention 

• NCI Division of Cancer Treatment and Diagnos

• NCI Division of Epidemiology and Genetics

• NCI Offi ce of Biorepositories and 

Biospecimen Research 

• NCI Offi ce of Cancer Content Management

• NCI Offi ce of Centers, Training, and Resources

• NCI Offi ce of Communications

• NCI Offi ce of the Director

• NCI Operational Research Offi ce 

• Virginia Cancer Registries

Cooperative Groups and Community Clin

Oncology Program Centers (CCOP)

• American College of Radiology Imaging Netwo

• Coalition of Cancer Groups

• Eastern Cooperative Oncology Group

• Cancer and Leukemia Group B (CALGB)

• Illinois Oncology Research Association CCOP

• National Surgical Adjuvant Breast and 

Bowel Project

• North Central Cancer Treatment Group

• Radiation Therapy Oncology Group 

• Southwest Oncology Group

• Wichita CCOP
56

Industry Partners

• 3rd Millennium, Inc. 

• 5AM Solutions 

• 9Star Research, Inc. 

• Advanced Clinical Software 

• Agfa HealthCare 

• Akaza Research 

• Alpha-Gamma Technologies, Inc.

• Amgen Inc.

• Apelon, Inc. 

• Aptia Systems, Inc.

• BioClinformatics LLC 

• Business Technologies Group

• Capital Technology Information Services, Inc. (CTIS)

• Cedara Software Corporation 

• Center for Health Research, Hawaii (CHRH) – Kaiser 

Permanente Hawaii

• Cerner Corporation

• Constella Group, LLC / Constella Health Sciences

• The Daedalus Group, Inc. 

• Dataworks Development, Inc. 

• Ekagra Software Technologies, Ltd.

• The EMMES Corporation 

• First Clinical Research LLC

• First Genetic Trust 

• General Electric Company / GE Global 

Research Center 

• GulfStream Bioinformatics Corporation 

• HK Stevenson, Inc.

• IBM Corporation 

• IMPAC Medical Systems, Inc. 

• INCOGEN, Inc. 

• Independent Oncology Services 

• Information Management Services, Inc. (IMS)

• Intel Americas Inc. 

• Kitware, Inc. 

• Mesh Ferguson 

• Nortel Government Solutions 

• OmniComm Systems, Inc. 

 Siemens Corporate Research 

• SRA International, Inc. 

• Stone Bond Technologies 

• TeraMedica Inc.

• TerpSys 

• Terrapin Systems, LLC 

• Theradex® 

• Velos, Inc. 

• Vivalog Technologies 

• Vital Images, Inc. 

• Westat 

• Xcalibur

Pharmaceutical Industry Participants

• GlaxoSmithKline plc.

• Millennium Pharmaceuticals, Inc.

• Pfi zer, Inc

• RadPharm

Attorneys

• Hall, Render, Killian, Heath & Lyman, P.C. 

NIH Publication No. 07-6244

Printed November 2007