3. Clinical Trials:
Why Do We Need a Data Management System?
• Multi-centre co-operative trials
– Multiple sites capturing data
– Multiple disparate databases
– Multiple levels of reporting
– Critical, very specific information
– Multitude decision making at multiple sites
– Co-ordination demands details
– Real time query and real time response
4. Investigational
Sites
Product
Management
Project
Management
Drug & Clinical Trial Development
Extended Picture
IRB Regulatory
Documents
Relationship
Building
eMails
Partners &
Affiliates
Meetings
CROs
Contracts
Knowledge
Information
Safety
Communication
Resource
Management
Data Capture
Data Management
Multidirectional Flow of Data and Decisions
5. Clinical Trials:
Why Do We Need a Data Management System?
• Enormous volumes of data
– Example, a Phase-III trial in 10 centres with 100 patients
each
– 60 pages of CRF for each recruited patient
• 20 fields each page
– 40 pages of screening form for each candidate patient
• 20 fields each page
– [1000 (60 x 20)] + [1500 (40 x 20)]
= 12, 00000 + 12, 00000
= 24,00000 specific data points
6. Clinical Trial Data
• Useful only if it is clean & up to date.
• Data processing must be
– real-time
• subject randomization
• management of clinical trials materials
• laboratory uploads
• patient diary data
– Integrated
– Consistent
– Accurate
• Data structures must be
– Standard
– Validated
• Data transfer method must be
– Standard
– Validated
7. Data Management Services:
What Exactly Do They Do?
• Case report forms (CRFs) design
• Database design
• Database programming
• 21 CFR part 11 compliant validation process
• Loading, reconciliation and integration of external data
• Medical coding
• Status reporting
• Forms management
• Data entry and cleaning
• Data locking
• Statistical analysis
• Report generation
8. Clinical Data Management System
(CDMS)
Data Capture Strategy
Remote Data Capture
Portal Data Capture
Processes
Adverse Event Monitoring System
Compliance (GCP/GLP) Monitoring
Workflow Monitoring
Analytical Data Processing
Statistical Data Processing
Systems
Data Extraction
GLIB
TMS/Dictionaries
Reports
Validation
10. Clinical Data Management System
(CDMS)
Data Capture Strategy
Remote Data Capture
Portal Data Capture
Processes
Adverse Event Monitoring System
Compliance (GCP/GLP) Monitoring
Workflow Monitoring
Analytical Data Processing
Statistical Data Processing
Systems
Data Extraction
GLIB
TMS/Dictionaries
Reports
Validation
11. A
Data Extraction, Cleaning & Locking (2)
Real time query
Are the
queries answered?
Yes
No
Data cleaning
1. Detecting & diagnosing errors
2. Editing incorrect data
3. Integrated data passage
4. Outlier determination
5. Robust estimation of analytical parameters
Clean data
Approval required
Can this data
be locked?
Yes
NoRepeat
Observation/
Omission
Locked data B
12. Clinical Data Management System
(CDMS)
Data Capture Strategy
Remote Data Capture
Portal Data Capture
Processes
Adverse Event Monitoring System
Compliance (GCP/GLP) Monitoring
Workflow Monitoring
Analytical Data Processing
Statistical Data Processing
Systems
Data Extraction
GLIB
TMS/Dictionaries
Reports
Validation
13. B
Data Processing & Reporting (3)
Locked Clean Data
Statistical analysis
required?
Yes
No
SAS Data Sets
Statistical Data Analysis
Tests of Hypotheses
Cohort Analyses
Results
Report
Data Summary,
Charts/Graphs
16. CDMS Market Size in India
• [Gobally ~$1.5 billion]
• Estimated Indian Market
• The total Clinical Trial market in India is ~$600 million
• CDMS is about 7-8% of CTs
• Thus the CDMS market is estimated to around 40 – 45 million
dollars
• For big MNCs, it is still a very small portion
• But it has a huge potential to grow
18. Drivers of EDC & CDMS
• Context – why India and why EDC & CDMS
• Technology & market forces
• Cost advantage
• Concentration of resources
• Expertise (and lathes of expertise)
• Regulators are insisting on comprehensive risk
management and PV
• Large trials have dozens of international sites and
corresponding chunks of data
19. Facilitators of EDC & CDMS
• Context – why India and why EDC & CDMS
• Consultants who can integrate different parts
• One stop shopping
– Patients, diversity
– investigators
– CT conduct experience
– Top CROs
• Research subsidiaries of pharma MNCs and int’l CROs
• CDMS & EDC offer efficiency and timeliness of data collection
and reporting
• Understanding of harmonized data & analysis requirements
20. Sahoo U. (2005). Clinical data capture shifts paradigm. Pharmabiz, July 14, 2005
Stakeholders in CDMS & EDC
21.
22. Data Standards & Harmonization
• It is estimated that ~ 200 million dollars are wasted yearly
because of a lack of globally accepted clinical data format
• Following organizations are working for data standardization:
• Clinical Data Interchange Standards Consortium (CDISC)
• Health Level 7 (Hl7)
• WHO
• US National Cancer Institute (NCI)
• National Library of Medicine (NLM)
• Academia
• ISO
• …
24. Standards for Data Management
• Very important for the regulatory agencies
• Without a standard, sponsors file data in different
arrangements
• Once data is in a standardized structure, regulatory
agencies can preprogram software to run a macro
script
• Thereby data coming from different sources will
automatically format to conform to the regulatory
agencies requirements
25. MNC PV Activities & Databases in
India
• Example: Novartis
• Activities/Databses
– Periodic Safety Update Report (PSUR)
– Risk Management Plan (RMP) updates and associated activities
– safety signal detection
– management of large datasets
– analysis of large databases
– responses to external authorities
– review of clinical protocols
– other regulatory activities
– clinical review and evaluation of cases including input for follow-up
and data cleaning
– ….many other relevant activities
26. Advantages to MNCs: Outsourcing to
India
• Better, safer drugs to market faster
• Improve efficiency
• Improve communication
• Improve data collection
• Reduce redundant data submissions
• Other benefits
• Improve communication
• Decrease redundant data submission
• Decrease “learning curve”
• Cross study analysis
• User friendly tools
• Decrease delays
27. Technical Advantages
• Cloud computing possible
• Real-time access to all clinical trial data
• Easy filling of e-CRFs with
– Radiobutton choices
– Checkboxes
– Drop-down selections
– Unlimited text boxes for comments
• Real-time data entry validation checks
• Secure database
• Back-end clinical data management and programmed data
validation checks
• Electronic and automatic Audit Trail
• Simple e-mail query resolution or by on-line query database
• Configurable access rights
• Electronic signatures fully compliant with FDA's 21 CFR Part 11
28. Concluding Remarks
• CDMS provide a range of IT tools that give the trials personnel
the required information throughout clinical management
• CDMS mainly manages data capture, systems and analytical
process electronically
• EDC definitely adds value – efficiency and accuracy, however,
high costs and some technology issues remain
• Technical and automational advantages are countless
• The CDMS market in India is estimated to around 40 – 45
million dollars and growing
• Provides for data standardization and interchange in
universally acceptable formats
29. Concluding Remarks: India as a Hub
• India offers many advantages as a CDMS hub
• Cost
• Concentration of resources
• Expertise
• Comprehensive risk management databases, analysis, mitigation and
PV centres
• Consolidation of various databases (especially large ones)
• India’s IT sector is growing at ~25% per year thus maintaining
complex CDMSs at competitive costs in India is an added
advantage
• Abundant skilled personnel in all areas of CDM available
• Hub of almost all clinical trial activities in coming years
GLIB: global library is an organization wide central repository for containing standardized data definitions. TMS: thesaurus management system; e.g., Oracle TMS provides terminology services for Oracle Clinical, Oracle Remote Data Capture, Oracle Adverse Event Reporting System, and Oracle Life Sciences Data Hub. Allows access to any number of dictionaries, including multiple versions of the same dictionary ; supports any number of hierarchy levels
and supports custom or commonly used dictionaries, such as MedDRA, MedDRAJ, MedDRA SMQs, SNOMED, ICD9, WHO-ART, and WHO-Drug.
MedDRA or Medical Dictionary for Regulatory Activities is a clinically validated international medical terminology used by regulatory authorities and the regulated biopharmaceutical industry during the regulatory process, from pre-marketing to post-marketing activities, and for data entry, retrieval, evaluation, and presentation. In addition, it is the adverse event classification dictionary endorsed by the International Conference on Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use (ICH). MedDRA is used in the United States, European Union, and Japan. Its use is currently mandated in Europe and Japan for safety reporting.
