A Translational Medicine Platform at Sanofi

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  • Make it more “provocative” create interest
    “sanofi, by implementing big data …. More innovation , ” create connection with audience
  • Sanofi is a global healthcare company focused on patient needs and engaged in the research, development, manufacturing and marketing of healthcare products.

    2013, net sales amounted to 32,951 million euros.
    We are the world’s third largest pharmaceutical company and the second largest in Europe. (source: IMS sales 2013)

    The Sanofi Group is organized around three principal activities: Pharmaceuticals, Human Vaccines via Sanofi Pasteur and Animal Health via Merial of which we are among the world leaders.

    We are present in approximately 100 countries on five continents with 110,000 employees at year-end 2013.
    As a global diversified healthcare company, our business includes a comprehensive offering of medicines, consumer healthcare products, generics, human vaccines and animal health.

    As of the beginning of February, our R&D portfolio included 49 projects and vaccine candidates in clinical development. 80% of development projects(1) are biologics.


    (1) 39 new molecular and vaccine entities of a total of 49
  • In the future, research will allow us to predict how, when, and in whom a disease will develop. We can envision a time when we will be able to precisely target treatment on a personalized basis to those who need it, avoiding treatment to those who do not. Ultimately, this individualized approach will allow us to preempt disease before it occurs, utilizing the participation of individuals, communities, and healthcare providers in a proactive fashion, as early as possible, and throughout the natural cycle of a disease process.”
  • The Promise for New and Better Drugs for Patients
    Can we remove a bit of text ? (2nd level bullet)
    Clarify the cloud ? A network of linked data
    Specific speak about the linked data, new part of story

    Question : what was happening BEFORE mongoDB ?
    During project? Why was it important

    Patient stratification
    Companion Diagnostics
    Efficacy / Safety
    Adaptive clinical trial design
    Clinical trial simulation


    Support Next Generation Sequencing
    Integrated with Knowledge Platform

    With combined clinical & research data
    Biological Pathways / Biomarkers
    Seamlessly include public information
    Build testable hypotheses


  • One challenge is to efficiently manage the overwhelming amount of relevant data files from various sources
    for a single disease program, the number of files to be managed can easily exceed thousand, including file of gigabytes.
    The tracability needs to be maintained, usually across multiple software
    Another challenge is to maintain the consistency across multiple data sources
    User friendly curation process

    Both are especially true in a research up to clinical translational approach
  • Regroup data : Unique file management across all software
    Foster use of metadata: for an easier data analysis and curation
    Powerful search capacity, including faceting
    Best place for knowledge extraction, data curation and NLP


  • Adapted to metadata

    The third make possible to proove that 1 & 2 are true
  • Wow effet: insister sur l’aspect quick demo qui tourne
    Big pharma / lantency / carefully

    Tell more about the momment of transformation, when the change really happend (precise time, anectote) exiting…


  • Like a prez itself. Need an intro ‘I’ll show how easy to tag… ’
  • Check facette speling ? 1 T
  • Font size large enouth ? Grey may not be good !

  • One challenge is to efficiently manage the overwhelming amount of relevant data files from various sources
    for a single disease program, the number of files to be managed can easily exceed thousand, including file of gigabytes.
    The tracability needs to be maintained, usually across multiple software
    Another challenge is to maintain the consistency across multiple data sources
    User friendly curation process

    Both are especially true in a research up to clinical translational approach
  • A Translational Medicine Platform at Sanofi

    1. 1. Sanofi big data approach for translational medicine MongoDB World 2014 New York June 23-25, 2014 1
    2. 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 2
    3. 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. 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 4
    5. 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 5
    6. 6. Pharma Company Mutation From curative to preventive medicine ● Main challenges for Pharmas ● Competition by generic, ● End of the blockbuster age, ● Leak of innovation, ● New paradigm: 4 P’s concept & translational medicine ● Personalized, ● Predictive, ● Preventive, ● Participatory 6
    7. 7. Research Clinical Knowledge OMICS data Hypotheses Trials EHRs CROs Evidence ● Efficient clinical trials ● Personalized medicine ● New capabilities for OMICS data ● One stop shop for TM data & knowledge Translational Medicine Concept Bridge Clinical & Research 7
    8. 8. New challenges raised by TM ● A diversity of objects to be connected ● Maintain consistency & traceability ● Extract knowledge, gain understanding 8
    9. 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 9
    10. 10. Why MongoDB? ScalableAdapted to file & metadata Easy To use To install To understand and to adopt  10
    11. 11. How we moved to mongoDB? White paper on Big data Install, benchmark PoC 1st Release in PROD Q42013Q12013 Wow 11
    12. 12. GridFS fs.file/fs.chunk Logs, tools… User profile Config Metadata Service layer (REST API) Web site Third party software Fuse/Desktop software MongoDB Use Cases General architecture 12
    13. 13. MongoDB Use Cases Annotation 13
    14. 14. MongoDB Use Cases Annotation 14
    15. 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 15
    16. 16. Lessons Learned & Challenges ● Link together the hybrid landscape ● Keep in sync MongoDB an the Solr index ● 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 16
    17. 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 17
    18. 18. Benefits ● Scientists: ● Time gain in tagging and curation ● Awareness of existing data ● Explore data ● Integration of external data ● IT: ● Time of development (agility) & implementation ● Flexibility ● Performance ● Documentation, support, training, MOOC 18
    19. 19. Question and answers 19
    20. 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) 20
    21. 21. New challenges raised by TM 21
    22. 22. 22
    23. 23. 23
    24. 24. 24
    25. 25. DML • STORE • ORGANISE • COLLABORATE • LINK DATA • VISUALIZE • ANALYSE 25

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