CDISC is a non-profit organization that establishes clinical research data standards to support data acquisition, exchange, and submission. It has developed several standards including CDASH, which aims to standardize data collection fields across clinical trials to streamline data analysis and reduce errors. CDASH defines a set of common safety domains and variables that can be collected consistently across studies in a standardized way. This helps analyze data more efficiently, reduces training time for sites, and decreases potential errors from inconsistent data collection.

1. Gowthami.Saripalli
Executive-CDM
Executive CDM
Paradigm IT

2. What is CDISC?
CDISC is a global, open, multidisciplinary, non-profit organization
non profit
that has established standards to support the acquisition,
exchange, submission and archive of clinical research data and
metadata.
It is for :-
“Good data management practices” are essential to the success
of a trial because they help to ensure that the data collected is
complete and accurate.
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3. CDISC
Founded in 1997; incorporated in 2000
Nearly 200 member organizations
• Biopharmaceutical companies
• Academic Research Institutes
• Technology Vendors etc
Vendors, etc…
Active Coordinating Committees
• Europe
• Japan
Additional activities
• Australia
• India
• S. America and Africa
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4. CDISC
• CDISC standards catalyze information flow through the entire
pre-clinical and clinical research process, from study protocol
and various sources of data collection to analysis and reporting
through regulatory submission and electronic data archive.
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5. CDISC
• Standard for Exchange of Nonclinical Data(SEND):
– The SENDIG is intended to guide the organization, structure,
and format of standard nonclinical tabulation datasets for
interchange between organizations such as sponsors and
CROs and for submission to the US Food and Drug
Administration (FDA)
(FDA).
• Protocol Representation Model (PRM):
– The content and format standard supporting the interchange
of clinical t i l protocol i f
f li i l trial t l information. Thi i a collaborative
ti This is ll b ti
effort with Health Level Seven (HL7).
• Trial Design Model (TDM):
– The content standard that defines the structure for
representing the planned sequence of events and the
treatment plan of a trial. This is a subset of the SDTM and
p
Protocol Representation.
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6. CDISC
• Operational Data Model (ODM):
– The XML-based content and format standard for the
XML based
acquisition, exchange, reporting or submission, and archival
of case report form (CRF)-based clinical research data.
• Clinical Data Acquisition Standards Harmonization (CDASH):
– A CDISC-led collaborative initiative to develop the content
standard for basic data collection fields in case report forms.
This standard is based upon the SDTM
SDTM.
• Laboratory Data Model (LAB):
– The content and format standard for data transfer between
clinical laboratories and study sponsors /CROs.
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7. CDISC
• Study Data Tabulation Model (SDTM):
– The content standard for regulatory submission of case report
form data tabulations from clinical research studies.
• Analysis Data Model (ADaM):
– The content standard for regulatory submission of analysis
datasets and associated files.
• Case Report Tabulation Data Definition Specification (CRTDDS)
(define.xml):
(d fi l)
– The XML-based content and format standard referenced by
the FDA as the specification for the data Definition for CDISC
SDTM datasets. This standard, also known as define.xml,is
an extension of the ODM.
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8. Global CDISC Integration
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9. Clinical Data Acquisition Standard Harmonization
• To develop a set of ‘content standards’ (element name,
definition,
definition metadata) for a basic set of global industry
wide data collection fields that support clinical research
• The initial scope - ‘safety data/domains’
• These safety domains cut across all therapeutic areas
• (TA independent)

10. Why CDASH?
• Most Clinical trials…
– D ’t employ a standard f d t capturing
Don’t l t d d for data t i
• Result
Result…
– Analyzing of clinical trial data efficiently and
systematically is difficult and time consuming.
y y g
– Especially for multicentre trials
• Ex: How many women participate in trial?
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11. Study 2 -Demog
ID GENDER
A1 FEMALE
Study 1-Demo A2 MALE Study 3-Dmog
SUBJID SEX A3 FEMALE USUBJID GENDER
0001 M A4 MALE 00011 0
0002 F 00012 1
Study 4-Demographics
0003 F 00013 0
PID SEX
0004 M 00014 1
0R1 2
0R1 1
0R3 2
0R4 2
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12. Difficulties in understanding the data…
• No standard file names
• N standard variable names
No t d d i bl
• No standard terminology
– Which code resembles which sex?
Result:-
Analysis of data is
f
Difficult
Time Consuming
Expensive
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13. Benefits of CDASH
• The main benefit is standardizing the definitions
for the data that is collected over multiple
studies.
• CDASH defines data that can be used in the
cleaning of data and for the conformation of
missing data.
g
• CDASH is valuable for reducing the production
time for CRF design, reducing the training time
g g g
for sites.
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14. CDASH benefits
• Eliminates some of the variety in CRFs seen at
sites
• S
Streamlines
li training
i i & increases
i common
understanding of CRF completion instructions
• Reinforces collecting only key data
• Reduces collection of duplicate data
• decreasing the potential for error
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15. Standard Domains
• Common Identifier Variables • ECG (EG)
• Common Timing Variables • Exposure (EX)
• Adverse Events (AE) • Inclusion Exclusion (IE)
• Concomitant Medications (CM) • LAB Test Results (LB)
• Comments (CO) • Medical History (MH)
• Drug Accountability (DA) • Physical Exam (PE)
• Demographics (
g p (DM)) • Vital Signs (VS)
g ( )
• Disposition (DS) • Subject Characteristics (SC)
• Protocol Deviations (DV) • Substance Use (SU)
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16. Standards variables
Highly Recommended:
• A data collection field that should be on the CRF (e.g., a
regulatory requirement, if applicable)
• (e.g. Adverse Event Term)
Recommended/Conditional:
• A data collection field that should be collected on the CRF for
specific cases
• (may be recorded elsewhere in the CRF or from other data
collection sources)
• (e.g. AE Start Time)
( g )
Optional:
• A data collection field that is available for use if needed
• (
(e.g. W any AE experienced?)
Was i d?)
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17. Expectations
• Highly Recommended data collection variables
should always be present on the CRF
• S
Sponsors will need t add data collection
ill d to dd d t ll ti
fields as needed to meet protocol-specific
and other data collection requirements
(e.g. therapeutic area specific data variables
and others as required per protocol, business
practice and operating procedures)
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18. To Implement
Existing Standards?
Gap Analysis – do not forget terminology!
Negotiation
1. Internal stakeholders
2. External stakeholders
• Training
• Establish Relationship with other standards
p
• Follow the guidelines
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19. References
http://www.cdisc.org/standards/cdash/downloads/
CDASH_STD-1_0_2008-10-02.pdf
CDASH STD 1 0 2008 10 02 pdf
http://www.cdisc.org/models/sdtm/v1.1/index.htm
htt // di / d l / dt / 1 1/i d ht
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