Sanofi is using MongoDB to build a centralized data repository to support its translational medicine platform. This will help bridge clinical research and data to facilitate more personalized, predictive, preventative, and participatory healthcare. Sanofi's new approach faces challenges in managing diverse data types and sources. MongoDB provides a flexible platform to integrate different data while maintaining consistency, traceability, and enabling collaboration across research teams. Initial use cases demonstrate time savings in data tagging and curation, as well as improved awareness and exploration of existing information assets.

1. Sanofi big data approach for
translational medicine
MongoDB World 2014
New York
June 23-25, 2014
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2. Agenda
● Sanofi a Pharma Company
● Translational Medicine Concept
● Sanofi Architecture View
● Why MongoDB?
● Use Cases: Overview and Deep Dive
● Benefits, Lessons Learned & Next Steps
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3. Information of December 31st 2013
SANOFI GROUP
●We are a global
healthcare company
engaged in the
research, development,
manufacturing and
marketing of healthcare
solutions. present
in more than
100
countries
more than
110 000
employees
A
comprehensive
offer
of pharmaceuticals,
vaccines and innovative
therapeutic solutions
112
Industrial sites
in 41 countries
R&D
A major biopharmacy
player
• 45% of revenues
generated by biologics
• 80% of development
projects are biologics
€33 bn*
In sales in 2013
* €32,951 M
Sanofi: A Big Pharma Company

4. Sanofi R&D
(1) Investor Relations Annual Results Meeting dated April 29th, 2014, excluding Merial R&D
(2) Source : Document de Référence 2013.
(3) Source : Document de Référence 2013. Includes all R&D positions within the Group (Affiliates, Industrial Affairs, etc)
Billions invested in R&D in
2013(2)
4,7 €
worldwide(2)
20 sites
More than
Clinical Study Units in
40 countries
Molecules and vaccines
in the R&D portfolio
50
Including 12 in late stage(1)
Employees worldwide contributing to
the research and development of
innovative health solutions(3)
16 500
Approximately
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5. Introduce ourselves
Global Solution Leader at Sanofi-Aventis R&D
• Translational Medicine Platform.
• Sanofi Representative in the eTRIKS
Project Manager at Sanofi-Aventis R&D
• Early research Enterprise Data Warehouse
• Big data project for Translational Medicine
Platform
Scrum Master, Technical leader at Apside
• Deep pharma experience (Servier, Fabre, Sanofi)
• Advanced agile expert
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david.peyruc@sanofi.com
erwan.david@sanofi.com florian.chuit@sanofi.com

6. Pharma Company Mutation
From curative to preventive medicine
● Main challenges for Pharmas
● Competition by generic,
● Leak of innovation,
● End of the blockbuster age,
● New paradigm: 4 P’s concept & translational medicine
● Personalized,
● Predictive,
● Preventive,
● Participatory
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7. ResearchKnowledge
OMICS
data
Hypotheses
Clinical Trials
EHRs
CROs
Evidence
● Personalized
● Efficient clinical trials
● One stop shop for TM
data & knowledge
● New capabilities for
OMICS data
Translational Medicine Concept
Bridge Clinical & Research
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8. New challenges raised by TM
● High diversity
of objects
● Consistency &
traceability
● Extract knowledge,
gain understanding
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9. Research
Molecular
Profiling
Clinical
Analysis
Big
Data
TM
Data-Hubs
Biomarker-
Research
Target validation
Interpretation
Biomarker
Epidemiology
Extraction
Curation
Normalization
Loading
Coordination & Collaboration
TM Data Mgmt Layer
A
C
B
D
011001101 BIOMARKER
MongoDB as a
central repository to
enhance biomarker
research
Sanofi Architecture View
Schematic Overview
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10. Why MongoDB?
ScalableAdapted to
file &
metadata
Easy
To install
To use
To understand
and to adopt 
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11. How we moved to mongoDB?
White
paper on
Big data
Install,
benchmark
PoC
1st
Release in
PROD
Q42013Q12013
Wow
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12. GridFS
fs.file/fs.chunk
Logs, tools…
User profile
Config
Metadata
Service
layer
(REST
API)
Third party software
Web site
Desktop integration
MongoDB Use Cases
General architecture
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13. MongoDB Use Cases
Annotation
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14. MongoDB Use Cases
Annotation
14

15. ● Geographic zone / Health activity
MongoDB Use Cases
360° Data Explorer
AND
7 docs
AND
16 docs
Same Data, exposed in
different organization
 Facetted Navigation
● Disease or Syndrome / Receptor
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16. Lessons Learned & Challenges
● Link together the hybrid landscape
● Keep in sync MongoDB an the Solr index
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● IT/infrastructure department needs supports
● MongoDB is not yet a standard in Sanofi
● But Convincing managers/architects is easy
• PoC can be set up very easily and show immediate
benefits
• The fast growing community/clients help a lot

17. Next Steps
● Curation process
● Improve curation by integrating open refine
● Collaboration
● Set up security at the smallest data piece (‘cell level
security’)
● Scale up
● Deploy to more department and geographic area
● Transition mongoDB support to infrastructure
teams
● To be finalized
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18. Benefits
● Scientists:
● Time gain in tagging and curation
● Awareness of existing data
● Explore data
● Integration of external data
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● IT:
● Time of development (agility) & implementation
● Flexibility
● Performance
● Documentation, support, training, MOOC

19. Thanks mongo!
Thank you !
david.peyruc@sanofi.comerwan.david@sanofi.com
www.linkedin.com/in/daviderwan www.linkedin.com/in/davidpeyruc
Any question ?
@DPeyruc@bob_dit_l_ane

20. Draft Agenda
● Challenges & business case (2 slides), the sanofi TM4P platform (2 slides):
how sanofi can be more innovative
● General idea (2 slides): research data hub : transform the way it’s done today
● Implementation
● MongoDB as a central store (metadata, gridFS: 2 – 3 slides)
● Ecosystem: solR integration (1 slide), DML (1 slide)
● (Business track not too technical) system data flow
● Demo by screenshots ? (3 slides)
● Challenges: set up an hybrid solution (solR/xxx )
● User testimony benefits (time, data quality & understanding)
● IT testimony: reduce the development time/agile
● deployment plan
● Next step/perspectives (2 slides)
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21. New challenges raised by TM
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22. 22

23. 23

24. 24

25. DML
• STORE
• ORGANISE
• COLLABORATE
• LINK DATA
• VISUALIZE
• ANALYSE
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