Wednesday, June 25, 2014

#mongoDBWorld @Sanofi talking about Cancer research Translational Medicine

Sanofi – Big Data and Translational Medicine

Session information: http://2.healthca.mp/1ryzDOj

Presentation by David Peyruc and David Erwan

www.sanofi.com

third largest Pharma company

Invest 4.7B Euros per year. From revenue of 33.4B Euros.

The challenge for Pharma

The classic business model is under threat. Generic drugs are a threat – “The Patent Cliff”

End of the Blockbuster Age.

New Paradigms

  • Personalized
  • Predictive
  • Preventive
  • Participatory

Translational Medicine is about bridging the gap between Clinical and Research worlds. Linking Hypothesis with Evidence.

Genomics and other *omics data needs to merge with other data. (See my other post from the Broad Institute from yesterday).

Translational Medicine Challenges

  • Diversity of data objects.
  • Large storage requirements. Genomics data is big.
  • Consistency and Traceability
  • User Friendly curation process for annotation to enable understanding and extract knowledge

Big Data (MongoDB) is used to help Extract, Curate, Normalize and Load data.
MongoDB is the central repository for Biomarker data.

Why MongoDB?

  • File and Metadata together.
  • Scalable (Data was sharded from day 1)
  • Easy to instal, use,understand and adapt/adopt.

The Journey to MongoDB

  • Big Data White Paper
  • Install and Benchmark
  • Proof of concept (a few javascript pages to demonstrate access)

MongoDB
- Runnong GridFS
- Apache Solr for search access
- Collections of Metadata, Config, User profile, Logs, tools etc.

  • Implement a REST API service layer
  • Build a web, Desktop and third party software integration interface (using Rest API)

Use Cases

360 degree Explorer

  • Disease or Syndrome / Receptor

Geographic Zone / Health Activity

  • Show the same data via faceted navigation

The platform is not a standard IT product. So there is minimal IT support.

Benefits

Scientists benefit:

  • More efficient tagging and curation
  • Awareness of more data sources
  • Easy exploration of data
  • Easier integration of external data

IT

  • Faster development
  • Flexibility
  • Performance
  • Documentation, support, training and community support.

Twitter connections for the presenters.
@bob_dit_l_ane
@DPeyruc

[tag health cloud BigData MongoDB MongoDBWorld NoSQL]

Mark Scrimshire
Health & Cloud Technology Consultant

Mark is available for challenging assignments at the intersection of Health and Technology using Big Data, Mobile and Cloud Technologies. If you need help to move, or create, your health applications in the cloud let’s talk.
Blog: http://2.healthca.mp/1b61Q7M
email: mark@ekivemark.com
Stay up-to-date: Twitter @ekivemark
Disclosure: I began as a Patient Engagement Advisor and am now CTO to Personiform, Inc. and their Medyear.com platform. Medyear is a powerful free tool that helps you collect, organize and securely share health information, however you want. Manage your own health records today. Medyear: The Power Grid for your Health.



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