Taking (some of) the mystery out of Big Data

Claus Stie Kallesøe

7th Berlin Conference on IP in Life Sciences

Focus on Big Data

February 7, 2014

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Introducing myself

Current roles:

Board of Directors, Pistoia Alliance

Head of Global Research Informatics

Background:

MSc. Pharm, Uni of Pharma Sciences, Copenhagen, 1997

Diploma Software Development, School of Engineering, Copenhagen, 2002

E-MBA, INSEAD, France, 2007

Linkedin: http://www.linkedin.com/in/clausstiekallesoe

Introduction

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NOT FOR PROMOTIONALUSE

Big Data –

Either VERY large datasets AND/OR other complexities

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Characteristics of big data

Source: IBM methodology

A couple of words about scale

100’s of Megabytes

This should not be a problem. Can be hand led with Matlab, R, Ruby

10’s of Gigabytes

This can all be loaded into the RAM of a laptop

100/500 Gigabytes – 1Terabyte

2 Terabyte harddrives can be bought in the local shop for €100

Connect it to your laptop and install postgresql or a no-sql database on it

> 5 Terabytes

Now you might have a size issue

5Inspired by: http://www.chrisstucchio.com/blog/2013/hadoop_hatred.html

NOT FOR PROMOTIONALUSE

Big Data - Definition

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"Big Data is high volume, high velocity, and/or high variety

information assets that require new forms of processing to enable enhanced decision making, insight discovery and process

optimization."

Cool, but remember where we are!Gartner Hype Cycle 2013

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Big Data in Pharma R&D

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What is Big Data in Pharma R&D?

Many ideas/possibilities across Pharma R&D and marketaccess

But many of them are likley NOT real Big Data problems!

Are they relevant and can they bring insights?Yes, very much so

Should we than find a way to handle them?Absolutely

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NOT FOR PROMOTIONALUSE

Linking R&D data

Semantic, Text indexes and search tools

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Purpose: Build text indexes which enables fast searches across

large data sets of linked data – both internal and external data

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Research

Databases

ClinicalTrials.gov

Clinicaltrialsregister.eu

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External

databases

Clinical

Databases

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Today

NOT FOR PROMOTIONALUSE

What about patents?

Text mining, linking and indexing

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Text mining of patent databases and other

sources…

Including chemicalname => structure

….followed by:

1. Convert to RDF => link with Semantic technologies

2. Enrich and load into a text index like Solr or similar

NOT FOR PROMOTIONALUSE

Pharmaceutical R&D – Future Big

Data Opportunities

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Online social networks and health records offer a huge repository of

real-world patient data that can be used to:

identify undiagnosed patients and serious adverse events

improve understanding of health outcomes and comparative

effectiveness

TechnologiesCan we do anything on our own

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For many people/companies”Big data technology” is a black box

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”A lot of stuff”

And then the vendors go:

If

{ box = magic or money}

then

{ box = expensive}

Working within a communityA lot of tools available

15From: http://people10.com/blog/ruby-on-rails-the-popular-platform-for-web-development/

New visualisations – easy and free

http://philogb.github.io/jit/demos.html

Automated calculationsLSP Front End

Job submitted to asynccalculation server

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5a

5b

5c

Etc……

https://circleci.com/

Also a lot of great tools to handle data

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Elasticsearch text indexes

All research assay metadata=> Google like search to find the relevant assay

All research project sharepoint workspaces=> Enable easy, fast cross project queries to find trends

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Conclusion – Big data in Pharma R&D

Many opportunitites across R&D and market access

More data linking and data analytics than Big Data

You can use freely available tools on ”normal” hardware

No magic ”Under the hood” – it’s just data

BUT you still need to define the questions you want to answer – before diving into technology!

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Please go home and read….

21http://blog.mongohq.com/you-dont-have-big-data/

http://ask.debian.net/