3. Clinical Trials:
Why Do We Need a Data Management System?
โข Multi-centre co-operative trials
โ Multiple sites capturing data
โ Multiple disparate databases
โ Multiple levels of reporting
โ Critical, very specific information
โ Multitude decision making at multiple sites
โ Co-ordination demands details
โ Real time query and real time response
4. Knowledge Investigational
Sites
Contracts
Partners &
Affiliates CROs
Relationship
Building
Meetings Communication
IRB Data Capture
Regulatory
Data Management
Documents Product
Safety Management
Project eMails
Management
Resource
Management
Information
Drug & Clinical Trial Development
Extended Picture
Multidirectional Flow of Data and Decisions
5. Clinical Trials:
Why Do We Need a Data Management System?
โข Enormous volumes of data
โ Example, a Phase-III trial in 10 centres with 100 patients
each
โ 60 pages of CRF for each recruited patient
โข 20 fields each page
โ 40 pages of screening form for each candidate patient
โข 20 fields each page
โ [1000 (60 x 20)] + [1500 (40 x 20)]
= 12, 00000 + 12, 00000
= 24,00000 specific data points
6. Clinical Trial Data
โข Useful only if it is clean & up to date.
โข Data processing must be
โ real-time
โข subject randomization
โข management of clinical trials materials
โข laboratory uploads
โข patient diary data
โ Integrated
โ Consistent
โ Accurate
โข Data structures must be
โ Standard
โ Validated
โข Data transfer method must be
โ Standard
โ Validated
7. Data Management Services:
What Exactly Do They Do?
โข Case report forms (CRFs) design
โข Database design
โข Database programming
โข 21 CFR part 11 compliant validation process
โข Loading, reconciliation and integration of external data
โข Medical coding
โข Status reporting
โข Forms management
โข Data entry and cleaning
โข Data locking
โข Statistical analysis
โข Report generation
8. Clinical Data Management System
(CDMS)
Data Capture Strategy Processes
Remote Data Capture Adverse Event Monitoring System
Portal Data Capture Compliance (GCP/GLP) Monitoring
Workflow Monitoring
Analytical Data Processing
Systems
Statistical Data Processing
Data Extraction
GLIB
TMS/Dictionaries
Reports
Validation
9. Data Capture (1)
CRF
Manual data
Electronic data No
Raw data
to be combined?
(Manual)
Yes
Electronic Get approval
data
Raw data
A
10. Clinical Data Management System
(CDMS)
Data Capture Strategy Processes
Remote Data Capture Adverse Event Monitoring System
Portal Data Capture Compliance (GCP/GLP) Monitoring
Workflow Monitoring
Analytical Data Processing
Systems
Statistical Data Processing
Data Extraction
GLIB
TMS/Dictionaries
Reports
Validation
11. Data Extraction, Cleaning & Locking (2)
A
Real time query
No
Are the
queries answered? Approval required
Yes
Repeat No
Data cleaning Observation/
Can this data
be locked?
1. Detecting & diagnosing errors Omission
2. Editing incorrect data
3. Integrated data passage Yes
4. Outlier determination
5. Robust estimation of analytical parameters
Clean data Locked data B
12. Clinical Data Management System
(CDMS)
Data Capture Strategy Processes
Remote Data Capture Adverse Event Monitoring System
Portal Data Capture Compliance (GCP/GLP) Monitoring
Workflow Monitoring
Analytical Data Processing
Systems
Statistical Data Processing
Data Extraction
GLIB
TMS/Dictionaries
Reports
Validation
13. Data Processing & Reporting (3)
B
Locked Clean Data
No Data Summary,
Statistical analysis Charts/Graphs
required?
Yes
SAS Data Sets
Statistical Data Analysis
Tests of Hypotheses
Cohort Analyses
Report
Results
14. CRF
Maker CRF
Data Entry Editor
(Form)
Layout
CRF
Database
Edited
Hard Copy
Electronic Case Report Forms
15. Electronic Data Capture (EDC)
Define
gn
Desi
Bu
ild
C
en
ry R tr
nt ) ep a
E
ite os l D a
Compliance
21CFR Part 11
ta
tD
a lS ito ta
na
Test
c o ry
u bje ati (H
S tig U
v es B
(In )
Data Review
Sponsor/Monitor Use
16. CDMS Market Size in India
โข [Gobally ~$1.5 billion]
โข Estimated Indian Market
โข The total Clinical Trial market in India is ~$600 million
โข CDMS is about 7-8% of CTs
โข Thus the CDMS market is estimated to around 40 โ 45 million
dollars
โข For big MNCs, it is still a very small portion
โข But it has a huge potential to grow
18. Drivers of EDC & CDMS
โข Context โ why India and why EDC & CDMS
โข Technology & market forces
โข Cost advantage
โข Concentration of resources
โข Expertise (and lathes of expertise)
โข Regulators are insisting on comprehensive risk
management and PV
โข Large trials have dozens of international sites and
corresponding chunks of data
19. Facilitators of EDC & CDMS
โข Context โ why India and why EDC & CDMS
โข Consultants who can integrate different parts
โข One stop shopping
โ Patients, diversity
โ investigators
โ CT conduct experience
โ Top CROs
โข Research subsidiaries of pharma MNCs and intโl CROs
โข CDMS & EDC offer efficiency and timeliness of data collection
and reporting
โข Understanding of harmonized data & analysis requirements
20. Stakeholders in CDMS & EDC
Sahoo U. (2005). Clinical data capture shifts paradigm. Pharmabiz, July 14, 2005
21.
22. Data Standards & Harmonization
โข It is estimated that ~ 200 million dollars are wasted yearly
because of a lack of globally accepted clinical data format
โข Following organizations are working for data standardization:
โข Clinical Data Interchange Standards Consortium (CDISC)
โข Health Level 7 (Hl7)
โข WHO
โข US National Cancer Institute (NCI)
โข National Library of Medicine (NLM)
โข Academia
โข ISO
โข โฆ
24. Standards for Data Management
โข Very important for the regulatory agencies
โข Without a standard, sponsors file data in different
arrangements
โข Once data is in a standardized structure, regulatory
agencies can preprogram software to run a macro
script
โข Thereby data coming from different sources will
automatically format to conform to the regulatory
agencies requirements
25. MNC PV Activities & Databases in
India
โข Example: Novartis
โข Activities/Databses
โ Periodic Safety Update Report (PSUR)
โ Risk Management Plan (RMP) updates and associated activities
โ safety signal detection
โ management of large datasets
โ analysis of large databases
โ responses to external authorities
โ review of clinical protocols
โ other regulatory activities
โ clinical review and evaluation of cases including input for follow-up
and data cleaning
โ โฆ.many other relevant activities
26. Advantages to MNCs: Outsourcing to
India
โข Better, safer drugs to market faster
โข Improve efficiency
โข Improve communication
โข Improve data collection
โข Reduce redundant data submissions
โข Other benefits
โข Improve communication
โข Decrease redundant data submission
โข Decrease โlearning curveโ
โข Cross study analysis
โข User friendly tools
โข Decrease delays
27. Technical Advantages
โข Cloud computing possible
โข Real-time access to all clinical trial data
โข Easy filling of e-CRFs with
โ Radiobutton choices
โ Checkboxes
โ Drop-down selections
โ Unlimited text boxes for comments
โข Real-time data entry validation checks
โข Secure database
โข Back-end clinical data management and programmed data
validation checks
โข Electronic and automatic Audit Trail
โข Simple e-mail query resolution or by on-line query database
โข Configurable access rights
โข Electronic signatures fully compliant with FDA's 21 CFR Part 11
28. Concluding Remarks
โข CDMS provide a range of IT tools that give the trials personnel
the required information throughout clinical management
โข CDMS mainly manages data capture, systems and analytical
process electronically
โข EDC definitely adds value โ efficiency and accuracy, however,
high costs and some technology issues remain
โข Technical and automational advantages are countless
โข The CDMS market in India is estimated to around 40 โ 45
million dollars and growing
โข Provides for data standardization and interchange in
universally acceptable formats
29. Concluding Remarks: India as a Hub
โข India offers many advantages as a CDMS hub
โข Cost
โข Concentration of resources
โข Expertise
โข Comprehensive risk management databases, analysis, mitigation and
PV centres
โข Consolidation of various databases (especially large ones)
โข Indiaโs IT sector is growing at ~25% per year thus maintaining
complex CDMSs at competitive costs in India is an added
advantage
โข Abundant skilled personnel in all areas of CDM available
โข 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.