Appalla Venkataprabhakar and I presented this at the Oracle\'s Annual Clinical Development and Safety Conference 2010 at Hyderabad, India on 6th October 2010.

1. Emerging Trends in Data
Management
A. V. Prabhakar, PhD
Senior Manager, Clinical Data Management
Dr. Arshad Mohammed
Director, Clinical Data Management
Disclaimer: The views in this presentation are of the authors and not necessarily of Quintiles

2. Thalidomide: Revived interest
Thalidomide became infamous in 1960s as one of the biggest drug
disasters
About 10,000 children born deformed since their
mothers used Thalidomide for morning sickness during
pregnancy
• 1998: FDA approved for treatment and Brazilian
suppression of cutaneous manifestations of
erythema nodosum leprosum (ENL). physicians
• 2006: Accelerated approval for thalidomide
(Thalomid, Celgene Corporation) in combination
with dexamethasone for the treatment of newly
Drug of choice
diagnosed multiple myeloma for the
• STEPS* program Since 1965
treatment of
severe ENL
FDA Approval
2
*System for Thalidomide Education and Prescribing Safety (S.T.E.P.S.) oversight program

3. Continued Industry Challenges
Time and money in R&D
• Drug R&D costs have rocketed 23 folds in last 28 years, touching an all time high of up
to $1.25 billion per new molecular entity (NME).
• Reducing patent protected market life as drug development time up from 11.6 years in
1970s to about 14 years
Returns and Profits
• Even with 20 years patent protection, some companies are unable to get their drug to
market before the patent’s expiration date.
R&D budgets falling and patent expiries looming: Urgent Priority
• Optimizing the clinical trial process
• Rationalize research pipelines
Industry is examining alternative ways for brining drug to market
• Relying on real time technologies including CTMS, EDC, Automation of processes,
shrinking timelines especially start up and close out
References:
1. Drug Discovery and Biotechnology Trends: Recent Developments in Drug Discovery : Improvements in Efficiency http://www.sciencemag.org/products/ddbt_0207_Final.dtl)
2. The productivity tiger - time and cost benefits of clinical drug development in India. (http://pharmalicensing.com/public/articles/view/1153412098_44bfac02291f1)
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4. Current Scenario in Clinical Research
Generation of
Clinical Operations Clinical Data
End Result for
Data Management Clean Data Biopharmaceutical
Industry
Analyzed
Biostatistics Data
A Safe and Effective
Medical Writing Clinical Study compound that can
Report be marketed
Regulatory
Submissions team Submission
4

5. Emerging Scenario
Advanced
Meaningful
Data Technology enabled
Information (Asset)
Transformation
Maximizing asset value, data Impact on Bio-Pharmaceutical
turned into information and used Industry
• Creates better compounds
before during after • Designs better study protocols
• Makes faster go or no-go
decisions
a clinical trial program • Alters assessments on
compounds in development
Protocol design Adaptive design Meta analysis
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6. Emerging Trends in CDM
Clinical
& DM
Cross Accelerated
Key Functional
Collaboration
Functional adoption of
Collaboration EDC
DM &
BIOS
Data Data
Analytics Standards
Data
Integration
Lab, ECG, IVRS, Cross Trial,
Safety etc Across Programs
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EDC Standards Integration Analytics Collaboration

7. Accelerated adoption of EDC
“By 2012 the expected number of
Despite its slow start, the use of
EDC studies would be greater than
EDC is on the rise at a rapid pace
70%” - By David Handelsman
Quintiles Bangalore, Sept 10
With skyrocketing costs – up to
$1.25 billion to bring a new drug to
market, $500 - $700 million of which EDC can help to reduce the clinical
is spent on clinical trials – companies research cost by ~20 – 28%
are seeking faster access to cleaner
clinical data
Reference: “Effective Clinical Trial Monitoring Using EDC Metrics” , Appalla Venkataprabhakar, Data Basics – Spring 2009 7
EDC Standards Integration Analytics Collaboration

8. Advantages of using EDC
• 25-30% savings realized using Overall
Saving Time EDC from decreasing Improvement
traditional monitoring / DDE
budgets • EDC provides
• PWC: Shift from paper to EDC better data
will bring 35-50% reductions accuracy
Time to DBL time & cost • Data
could be • Cost savings alone with EDC standardization
reduced by vs. Paper estimated about $60 • Centralized work
43% & million per drug flow
number of • Real time study
queries by results
86% • Low operations
cost
Saving Money
References
1. EDC Advantage : Shrinking LPO-DBL Timelines in EDC Study”, Appalla Venkataprabhakar, Data Basics – Spring 2010
2. Achieving cost savings using EDC effectively ” (http://74.41.95.83/resdyncgweb/RDCG_EDC_Paper.pdf)
3. DATATRAK International Releases Value Proposition of EDC to the Pharmaceutical Industry - Part II
(http://www.thefreelibrary.com/DATATRAK+International+Releases+Value+Proposition+of+EDC+to+the...-a078554673) 8
EDC Standards Integration Analytics Collaboration

9. Process and role changes
• Sponsors looking at 5, 8, • Follow the sun • Sponsor
15 weeks, etc for start methodology in • CRO
ups Database builds • Industry wide?
• Global EDC testing hubs
• Centralized UAT
Crunched EDC
Global EDC
start up Global Libraries
Build teams
timelines
• Protocol • DM: partial to total • Enhanced Project
• CRF outsourcing (FSP) management skills
• DMP documents, Edit • Outcomes based required
Checks • Partner DM staff at • Metrics driven
• UAT sponsor offices • Zero tolerance: Quality
• Shared Risks and and Compliance
Benefits • Project Reviews
Technology for Partnerships of Management of
Standardization next level CDM
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EDC Standards Integration Analytics Collaboration

10. Scenario due to Lack of Data
(Standard & Integration)
Example of sophisticated review process of an FDA reviewer
Reference
1.http://www.globalsubmit.com/home/LinkClick.aspx?fileticket=ta1z74CpCQw=&tabid=260.
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EDC Standards Integration Analytics Collaboration

11. Data Standards
Data Standards are agreed • Standardization helps improve efficiencies in trials
upon set of rules that allow by reusability of tools & ability to combine data
information to be shared and across clinical studies
processed in uniform & • Data standards make inter department & inter
consistent manner organizational collaboration possible
• Lack of globally accepted pharmaceutical data
Financial Impact formats believed to cost pharmaceutical industry
in excess of US $ 156 million per annum
• CDISC at the forefront of partnering with industry
and defining standards
Leading Organizations • HL7 is accepted messaging standard for
communicating clinical data & supported by most
major medical informatics system vendors
Reference
1. Facilitating the use of CDISC standards in clinical trials “ – http://www.iptonline.com/articles/public/Formedix1.pdf) 11
EDC Standards Integration Analytics Collaboration

12. CDISC* Standards Table & Purpose
Model / Standard Purpose
XML specification supporting interchange of data, metadata
Operational Data Model (ODM)
or updates of both between clinical systems
Clinical Data Acquisition Standards Data model for a core set of global data collection fields
Harmonization (CDASH) (element name, definition, metadata)
Submissions Data Tabulation Model Data model supporting the submission of data to the FDA
(SDTM) including standard domains, variables, and rules
Data model closely related to SDTM to support the statistical
Analysis Dataset Models (ADaM)
reviewer
XML Specification to contain the metadata associated with a
Define.xml clinical study for submission
Standards for the Exchange of non- Data model extending SDTM to support the submission of
clinical data (SEND) animal toxicity studies
Metadata model focused on the characteristics of a study
Protocol Representation Model (PRM) and the definition and association of activities within the
protocols, including "arms" and "epochs".
* Clinical Data Interchange Standards Consortium 12
EDC Standards Integration Analytics Collaboration

13. Data Integration
• Bringing data from • Out of box • Expedites data
multiple sources integrations cleaning &
(IVRS, Diary, Lab, • Life Sciences reconciliation
Randomization, Data Hub process
Coding) eliminates • Enhancing patient
redundant tasks like • IVRS & EDC
integration safety
reconciliation, same
data entry into • EDC & Safety • Strengthening
multiple systems integration quality
• Accelerates flow of • Quintiles Data • Reduce the risk of
critical information Factory data entry errors
to key stakeholders • Quintiles white paper • Accelerating
that aids faster for your reading timelines
decisions
Examples of Advantages of
Integration Data Data
Integration Integration
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EDC Standards Integration Analytics Collaboration

14. Clinical Trial Data Integration
Data Analytics and
Online Reports
Clinical
CTMS
Data Review
Financials
Clinical Trials
EDC / RDC / CDMS Progress Review
Data Exports,
Regulatory Compliant PDF / HTML Reports
Hand Held Device Data Integration & Reporting
Environment
IVRS
Business Process
Automation with Workflow
Clinical Research Central Labs
Organizations / Partners
Courtesy: Oracle LSH presentation
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EDC Standards Integration Analytics Collaboration

15. White Paper for your reading
Published: September 2010 15
EDC Standards Integration Analytics Collaboration

16. Data Analytics in New Health Landscape
Science of examining raw data with the purpose of drawing
conclusions about that information
• Make better cross functional business decisions - identify risks
& mitigate them in timely manner e.g. need of additional trainings for
staff at a site, fraud detection, signal detection, protocol deviations.
• Greater transparency into the status of a clinical trial subject
• Enhanced safety and efficacy monitoring via a holistic review of
individual and aggregated subject data
• Increased operational efficiency and quality made possible
through a transparent and holistic view of data
Benefits of Clinical Data Analytics
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EDC Standards Integration Analytics Collaboration

17. Applications of Data Analytics
Data Inconsistency
Trend of Temperature vs. Visit
100
98
Temperature (C)
96
94
92
90
Visit-1 Visit-2 Visit-3 Visit-4 Visit-5
Trend of Height vs. Visit
200
195
190
185
Height (Cms)
180
175
170
165
160
Visit-1 Visit-2 Visit-3 Visit-4 Visit-5
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EDC Standards Integration Analytics Collaboration

18. Applications of Data Analytics
Data Trends & Outliers
Discrepancies /Site compared to number of patients. Average time from patient admission to
performing ECG
20 18
4
Discrepancies / patient
16 3
Average Time (hr)
3
12 10 10
7 1.5
6 2
8 1 1.2 0.9
4 1
0 0
Site-1 Site-2 Site-3 Site-4 Site-5 Site-1 Site-2 Site-3 Site-4 Site-5
Query Rate Across Sites Lag Time Between DE & Visit Date
30 25 20
15
Average Lag Time (Days)
Queries / 100 eCRF Pages
25 16
20
12
15 10 9 12
8 5 4.2 6 5.4
8
10
4
5
0 0
Site-1 Site-2 Site-3 Site-4 Site-5 Site-1 Site-2 Site-3 Site-4 Site-5
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EDC Standards Integration Analytics Collaboration

19. Advanced Analytics
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EDC Standards Integration Analytics Collaboration

20. DM-BIOS Collaboration
Till recently Resulted in lot of rework
biostatisticians were on databases (including
involved at later part of locked) for the
study when the data was unidentified data errors
available to them for final identified by
statistical analysis biostatisticians
Involvement of a Data errors identified so
biostatistician from start late incur additional time,
of the study significantly costs and annoyed
helps the DM team avoid customer (internal /
a lot of potential rework. external)
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EDC Standards Integration Analytics Collaboration

21. Best Practice of DM-BIOS Collaboration
During Start up During Conduct During Close Out
Data Transfer & Non-CRF Interim transfers and early
Kick off Meeting
Data Guidelines Preparation BIOS feedback
Completes data issues log &
Protocol & CRF Preparation / Review of data at subsequent
provides final copy of the
Annotation intervals
same to the data team lead.
Early review of completed
Ensure BIOS feedback
CRF
Edit Check Document Review Key factor for early DB Locks: Effective
working relationship between DM & Bios
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EDC Standards Integration Analytics Collaboration

22. Clinical-DM Collaboration
Start-Up Phase Conduct Phase Close Out Phase
Inputs during designing of CDM & BIOS inputs if SDV Weekly calls* between CDM
CRF per study protocol < 100% and Clinical
CDM should share the
Clinical share Monitoring
CRF completion guidelines status updates or
Visit plan with DM
dashboards - live
CRF’s entered, Queries in
Review of edit check
Triggered Monitoring Visit open status, SDV, Freezing,
document
Locking, PI Signature etc
DM should share milestone Start about 2 months before
dates with Clinical the final DB lock
Monthly calls* between
CDM and Clinical
* Discuss issues or updates related to data points / queries / site response / site training / milestones, etc
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EDC Standards Integration Analytics Collaboration

23. Quintiles Case Study
Therapeutic
Area: Anti Go Live within 6 weeks
Infective
Indication:
Platform: Inform Typhoid Fever Last Patient Last Visit-
4.5 Vaccine
Database lock in 5 days
TOP 5 in terms of study
Duration of All major deliverables
Patients: 329 performance on Quintiles
Study: 1 year achieved before time
Inform Dashboard
Sites: 3 (All Sites
in US)
Loyalty Scores
Project Management
Customer Audit: No Start up: 96.7%
critical or major findings
Clinical Operations
Close out: 96.7%
Data Management
Overall I am very impressed with the management of the project. The whole team has
Lab been extremely accessible. Of particular note was the data management team in India
who seemed to work around the clock on this study. - Clinical Operations Manager,
BIOS Product Development,
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EDC Standards Integration Analytics Collaboration

24. Emerging Trends in CDM
Cross Accelerated
Functional adoption of
Collaboration EDC
Data Data
Analytics Standards
Data
Integration
24
EDC Standards Integration Analytics Collaboration

25. Thank you
appalla.venkataprabhakar@quintiles.com
arshad.mohammed@quintiles.com
Quintiles CDM, Bangalore
Disclaimer: The views in this presentation are of the authors and not necessarily of Quintiles