CDISC dth N ti lC I tit t CDISC and the National Cancer Institute

CDISC and
d the
th National
N ti
l Cancer
C
Institute
I tit t
CDISC Interchange
N
November
b 11,
11 2009
John Speakman
Associate Director, Center for Biomedical Informatics and Information Technology
National Cancer Institute
1
21st Century Biomedicine
• Personalized, Predictive,
Preemptive, Participatory……
• Unifies discovery, clinical
research, and clinical care,
(bench-bedside-bed) into a
seamless continuum
• Results in improved clinical
outcomes
• Accelerates the time from
discovery to patient benefit
• E
Enables
bl a health
h l h care system,
not a disparate “sector”
p
consumers in
• Empowers
managing their health over a
lifetime
Reality on the Ground
• We know “how cancer
works”
• BUT:
• Estimated US cancer
deaths 2009: 562,340
(American Cancer Society)
• Estimated new US cancer
cases 2009: 1,479,350
(American Cancer Society)
• Cost of cancer deaths:
$960.7 billion in 2000,
estimated $1,472.5
$1 472 5 billion in
2020 (Journal of the National Cancer
Institute, Dec. 9, 2008)
NCI believes that information exchange is
part of the challenge
• Translational research and personalized medicine require
integration
g
of multiple
p modalities and dimensions of data
(clinical care / clinical trials / pathology / imaging / gene
expression / population data, and so on)
• This integration is currently achieved by custom-built point
solutions, if at all
• As a result, where it’s available, the data thus produced are
more than likely not comparable
• Research studies are artisanal, handcrafted from one-of-akind components; clinical trials take too long to initiate, too
long to accrue patients and too long to report outcomes
• Access to, and maturity of, informatics tools within the
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research community is inconsistent
Challenges:
The Biomedical Landscape
• Isolated
so ated information
o at o
“islands”
• Information dissemination
uses models recognizable
to Gutenberg
• Pioneered by
Royal Academy of
Science of London in the
17th century
• Write manuscripts
• “Publish”
• Exchange information at
meetings
The caBIG® Initiative
caBIG® Goal
A virtual web of interconnected data
data, individuals
individuals, and organizations that
redefines how research is conducted, care is provided, and
patients/participants interact with the biomedical research enterprise.
.
caBIG® Vision
• Connect the cancer research community through a shareable,
interoperable infrastructure
• Deploy and extend standard rules and a common language to more
easily share information
• Build or adapt
p tools for collecting,
g, analyzing,
y g, integrating
g
g and
disseminating information associated with cancer research and care
A Siloed Healthcare Infrastructure
Regulatory
Reporting
Environment
Healthcare
Delivery /
Patient Care
Clinical
Research
Environment
A Common Healthcare Infrastructure
Regulatory
Reporting
Environment
Healthcare
Delivery /
Patient Care
Clinical
Research
Environment
Standards allow information to be
exchanged
A Common Healthcare Infrastructure
Regulatory
Reporting
Environment
Healthcare
Delivery /
Patient Care
Outcomes
Warehouse
caXchange
caEHR/PHR
caEHR
EHR/PHR
EHR
/PHR
Patient Registration & Enrollment
Capture of Clinical Lab Data
Scheduling of Treatment
Capture of Adverse Effects
Investigator
Registry,
g y
Results
(Janus)
Clinical
Research
Environment
Research
Data
Warehouse
caBIG® tools provide functionality to
enable a seamless continuum
caBIG® Capabilities Advance Discovery,
Clinical Research, and Clinical Care
• Track clinical trial
registrations
• Use NBIA repository
for medical images
including CAT scans
and MRIs
• Facilitate automatic
capture
t
off clinical
li i l
laboratory data
• Manage reports
describing adverse
events during
clinical trials
• Combine proteomics,
gene expression,
and other basic
research data
• Submit and annotate
microarray data
• Integrate microarray
d t from
data
f
multiple
lti l
manufacturers and
permit analysis and
visualization of data
• Visualize images using
DICOM-compliant
tools
Clinical Research
Imaging
• Annotated Images with
distributed tools
• Access library of well
characterized and
clinically annotated
biospecimens
Cli i l Care
Clinical
C
• Use tools to keep an
inventory of a user’s
p
own samples
Discovery Research
Pathology
• Track storage,
distribution, and quality
assurance of specimens
caBIG® as a Platform for a Biomedical “App Store”
Biomedical
Information (caBIO)
Medical
Imaging (OsiriX)
Biomedical
Services (caGrid)
Biospecimens
(caTissue)
Moving to a Semantic Services-Oriented
Architecture
• Architectural decision: pull redundant functionality out of
applications into services
Application 1
Application 2
Application 3
Service A
Application 4
Example: NCI Electronic Health Record
Project
• Specify (under way, with ASCO, HL7-based)
•
•
•
•
An EHR specification, i.e.,
•
A coherent representation of functional and static requirements
and a traceable way of delivering the functional requirements to
the static ones
Vet
•
Multiple Stakeholders
Stakeholders, including FDA (Sentinel)
•
EHR Vendors are a key group
Develop
p
•
Reference implementation – a functional “lightweight” EHR
•
Iterative and incremental development
Deploy
•
NCI’s National Community Cancer Centers Program (NCCCP)
•
Support, train users, maintain
20th Century Biomedical Paradigm
Discovery
• Biological pathways
• Target identification and
validation
Product
Development
• Candidate selection and
Optimization
• Pre-clinical testing
• Phase I, II, III
• New Drug application and
A
Approval
l
Clinical Care
Outcomes &
Surveillance
• Product launch
• Reporting of serious/fatal ADRs
• Clinical adoption
• Re-labeling (or recall) as
needed
• Additional indications as
warranted
21th Century Biomedical Paradigm:
a Learning Health System
Analysis and
Learning
Outcomes &
Surveillance
Discovery
Product
Development
Clinical
Care
Galvanizing the Community on a National Scale
• Capacity for interoperability makes it feasible to
d
demonstrate
t t research-to-care-to-research
ht
t
h (i
(i.e., a “Rapid
“R id
Learning Healthcare System”) on a national scale
• Stakeholder “mega
mega-community
community” (care providers
providers, patients
patients,
consumers, advocates, IT vendors, biopharma) can create a
Patient Data Outcomes Service for cancer
• Caregivers and patients can enter clinical outcomes information
into a database for use in care determinations and research
• Such a data service is completely feasible and could be launched
in cancer within the next 12 months…thereby demonstrating in
real-time the “Rapid Learning Healthcare System” and providing
a platform for all diseases
CDISC / NCI caBIG® Collaborations
1996: Enterprise Vocabulary
Services (EVS)
•
The NCI Enterprise Vocabulary Services Project provides the terminological
foundation upon which sharing and re
re-use
use of data
data, services and applications
applications,
and other resources depend. The caBIG community, NCI and certain other
NIH institutes, and collaborating organizations such as FDA and CDISC
depend on the EVS for their terminology needs
needs.
•
The EVS project began in 1996 as an NCI applied research project.
Production quality products emerged beginning in 1999 with NCI
Metathesaurus. NCI Thesaurus emerged in 2000, and shortly thereafter
became the foundation terminology upon which the NCI metadata and data
models infrastructure were built.
•
Today the EVS project publishes freely available tools for terminology and
ontology development and for serving terminology and ontology data. The NCI
Thesaurus and Metathesaurus have been joined by the BiomedGT ontology,
which will support instance reasoning on caGrid.
CDISC Terminology
•
EVS is partnered with CDISC to support SDTM and other CDISC
terminology including SEND, Glossary, CDASH
2004: BRIDG
• A Domain Analysis Model is the map of the shared
semantics of a given domain (in this case, clinical
research)
• Initiated by CDISC
CDISC, developed jointly by caBIG®,
CDISC, Health Level Seven and FDA
• Initial caBIG® demonstration: from requirements
definition to working demonstration of real-world
interoperability between components in two months
• Separate development teams, different contractor
organizations limited interaction
organizations,
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2008: Standardized Electronic Case Report Form (eCRF)
Modules
• CDISC Clinical Data Acquisition Standards Harmonization
(CDASH) initiative has a common goal with ours:
harmonizing and standardizing data collection for clinical
research
• CDASH focus:
f
elements
l
t that
th t are common to
t allll clinical
li i l studies
t di
• caBIG® focus: oncology studies
• caBIG® modules will include all CDASH “mandatory”
mandatory
questions, plus additional oncology content
• Review of content of first forms with CDASH standard:
84% match on first pass
• All areas of disparity have so far been reconciled
2009: SHARE/MDR
•
•
•
•
•
•
•
NCI is migrating to new tools for semantic management including a new
metadata repository (MDR)
NCI will include all CDISC requirements for SHARE in its repository
development process, would like direct CDISC participation in the
development team
NCI wishes to support tools for SHARE that will be customizable
customizable, global
global, and
cover all therapeutic areas
NCI’s MDR development will be based requirements from a wide variety of
groups to include research and broader healthcare standards; SDOs - HL7,
HL7
CDISC and other; regulatory entities; pharmaceutical; providers and vendors
The new ISO 11179 standard MDR will be based on a federated, distributed
architecture;
hit t
meaning
i it will
ill b
be d
decentralized,
t li d allowing
ll i ffor multiple
lti l peer
repositories
Allows for modular development of many and varied customized applications
and
d services
i
ffor diff
differentt users, b
butt with
ith a common foundation
f
d ti and
d generic
i
API
Open, Platform & Vendor Neutral, Distributable, Shareable
For more information, please visit:
http://caBIG cancer gov
http://caBIG.cancer.gov
http://BIGHealthConsortium.org
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