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Sharing Clinical Trial Data
Robin Jenkins
De-identification Symposium: Preserving Privacy AND
Advancing Data Analytics
October 21, 2014
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Disclaimer
• The opinions expressed in this presentation are my own, and not those of either Sanofi US or Project Data Sphere, LLC. The presentation is for informational purposes only.
• There are no representations or warranties expressed or implied, with respect to the usefulness or sufficiency of the information for the purposes of clinical trial sharing.
1: Savage & Vickers, 2009. PLoS One
FDA sees huge opportunities in opening up
drug dataLONDON | Mon Dec 5, 2011 9:23pm IST
(Reuters) - Regulators and drugmakers need to find ways to make
more clinical data openly available, since vital knowledge about
fighting disease is often locked away in confidential databases, the
head of the U.S. drugs watchdog said on Monday. Food and Drug
Administration (FDA) Commissioner Margaret Hamburg said opening
up data to public scrutiny needed to be done selectively, given
legitimate concerns among companies over commercial
confidentiality, but more could still be done.
The Data Sharing Landscape
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The Data Sharing Landscape
● Public pressure has been
mounting for the pharma
industry to be more ‘transparent’
about the results of clinical trials
● “Transparency Campaigners”
● 2013 - EMA proposed to release
all data they hold once a drug
has been approved
● Industry concerned about the
implications of this for
competitiveness, IP, data
protection
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The Data Sharing Landscape
● PhRMA working group drafted set of voluntary
guiding principles for the Responsible Sharing of
Clinical Trial Data.
● Adopted by PhRMA and EFPIA in July 2013.
● Came into effect Jan 1, 2014
● Five ‘commitments’
1. Enhancing Data Sharing with Researchers
2. Enhancing Public Access to Clinical Study Information
3. Sharing Results with Patients who Participate in Clinical Trials
4. Certifying Procedures for Sharing Clinical Trial Information
5. Reaffirming Commitments to Publish Clinical Trial Results
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The Data Sharing Landscape
● EMA, after stakeholder
feedback from the industry,
has re-thought it’s data
sharing proposals
● Policy final Oct 2014 and will
come into effect Jan 1 2015
● Clinical Study Reports will
become publically available
upon decision of the
application
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Access Models: One size doesn’t fit all..
1. Black Box, or Database Query model:
● May be suitable for some types of very sensitive health information
2. Gatekeeper Model:
● PhRMA / EFPIA principles
● Independent review board
● Limited access, and broad data
● Protection of Confidential Commercial Information
3. Broad Access Model:
● Immune Tolerance Network, Sage Bionetworks, and Project Data Sphere
● No Independent Review Panel
● Responsible-use attestation
● Broader access, but less data. Data integration. Crowd
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The Data Sharing Landscape
● Sage Bionetworks - Synapse
● Immune Tolerance Network
● ImmPort
● PhRMA / EFPIA
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● Lead to a better understanding of disease progression and
endpoints
● Promote more efficient research:
● Improved trial design and statistical methodology
● Secondary hypotheses & epidemiology
● Disease model development
● Smaller trials sizing
● Reduced duplication & increased transparency
● Real world corroboration with trial data
● Data standards & meta-analysis
● Analytics and insights
● Unknowns2
How may sharing data accelerate researchto benefit patients?
1: Vickers 2006
2: www.cardia.dopm.uab.edu: 475 publications from a single large dataset
Benefits of Sharing Data
www.clinicalstudydatarequest.com
Multi-sponsor Consortium
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www.clinicalstudydatarequest.comHigh-level Process
● Request access to data via Scientific Proposal
● Technical requirements met – e.g. statistician, publication plan, statistical
plan, etc…
● Reviewed by Independent Panel of Experts
● If approved, will sign data use agreement and will have access to the data
for 12 months
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Researcher
selects required
trials from list of
those requestable.
Researcher
completes
proposal request
form online
Independent
Review Board
considers request
If approved,
researcher signs
Data Use
Agreement with
Sanofi, data are
de-identified and
uploaded to SAS
hosting site
Technical review
www.clinicalstudydatarequest.comMetrics
● September YTD
● 74 proposals submitted
● 56 met requirements
● 51 IRP approved
● 19 In process
● 32 active projects
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The Reason Why
● 8.2 million people die everyyear from cancer whilehistorical data sets withuntapped potential sit inwarehouses gathering dust.1
● According to the WHO,more than 10m people willdie from cancer annually bythe year 2020.
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● Cancer is a major public health concern worldwide: more peopledie every year from cancer than HIV, malaria, and tuberculosiscombined.2
1International Agency for Research on Cancer (IARC) GLOBOCAN 20122Matthers and Loncar (2006) PLoS Medicine 3(11) e44.
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The Project Data Sphere initiative
● Independent, voluntary, not-for-profit initiative of the CEO Roundtable on Cancer’s Life Sciences Consortium
● One place to broadly share, integrate, and analyze cancer trial data ● from academic and industry Phase III clinical
trials
● historical, comparator arm data
● raw patient level data which are required to be de-identified by the data provider, data dictionary, protocols and CRFs
● State of the art analytic tools provided by SAS to free of charge to registered users within the PDS environment
www.projectdatasphere.org
Key Accomplishments
Our team spent over 2 years addressing historical barriers to data sharing:
Collaboration with privacy, academia, legal,technology, clinical, industry and patientrepresentatives to achieve an optimal platform
PDS ConceptFormed
20
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Analytics
Legal
Privacy
Resources
300M+ Media Impressions at
Launch:April 8, 2014
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People, Process and Technology
231 22 21 735
In Preparation
4,300
In Platform
8,921
To Achieve
our Goal:
11,779
Strategic
Pillar Summary Status
+Patients Lives are now at 9,000. We
anticipate 2-4 additional data sets in
October
-Still need to identify data sets representing
11,000 patient lives to meet the 25,000
patient lives goal by April, 2015
+Launch preparations for the Prostate
Cancer Research Challenge are underway.
+Website community tools launched in
September. User communications about the
new functionality are underway.
Nurture
Network
Expand
Use
Grow
Data
At Launch:
4,000
Potential Applications of Comparator-Arm Data
Unused data is an untapped resource and a missed opportunity; the multiple potential benefits include:
● Enable computer simulations and virtual control arm development
● Scientific advances from computer simulations and modeling could evolve clinical development to an era of data-driven decisions
● Optimized trial design and statistical methodology
● Disease modeling - clearer understanding of the natural history of tumor types/subtypes and rare disease
● Quick research – establish baseline rates for safety events
● Streamline protocol development / CRF development
● Build description of timelines of events related to therapies
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What is the Prostate Cancer Research Challenge?
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• Innovative, crowd-sourcing research project
• Collates Phase III prostate data from the Project Data
Sphere platform and makes it available to address
key research questions.
• Developed in collaboration with the Prostate Cancer
Foundation, Sage Bionetworks, The Dream Project,
and UNC.
• Novel approaches resulting from the challenge may
hold promise for improving treatments and foster
new collaborations.
National Cancer Institute & Mathematical Models
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National Cancer Institute (NCI) is developing a significant Comparator-
Arm use case based on the Project Data Sphere initiative
● Early research demonstrates that analysis
of Project Data Sphere prostate cancer
data allows for comparison of treatments
that have not been previously formally
conducted.
● Additionally the research is establishing a
pathway for virtual simulations to inform the
design and development of new drugs and
the clinical trials which enable them.
Cancer Commons
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● Cancer Commons using the platform as data source to: ● Validate their analytics
● Show patients/physicians what others have done/ experienced with their cancer treatment
● combined with other data sources and educational content to helps patients better understand their treatment options and decisions.
● Help answer the most important question cancer patients want answered: What have other patients like me done and what was the result?
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Prostate Lung Colon Breast
2
# o
f P
atie
nt
Live
s
4
6
8
10
12
14
16
Pancreas Myelo-fibrosis
Stomach Bladder Head &Neck
LysisSyndrome
Kidney
Data in the Platform
32 Data Sets currently in the platform or being prepared