This presentation shares a 10 minute pitch of big data potentials in the field of life sciences as presented at the 2015 CMS Global Life Science Forum on Nov 9, 2015 in Frankfurt

1. Big Data in Life Sciences
Dr. Matthieu-P. Schapranow
CMS Global Life Sciences Forum, Frankfurt, Germany
Nov 9, 2015

2. What is the Hasso Plattner Institute, Potsdam, Germany?
Schapranow, CMS Global
Life Sciences, Fankfurt,
Nov 9, 2015
Big Data in Life
Sciences
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3. What are the Trends?
Schapranow, CMS Global
Life Sciences, Fankfurt,
Nov 9, 2015
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https://www.google.com/trends/explore#q=Big data%2C Life sciences%2C Precision medicine&cmpt=q @ Nov 9, 2015
Life Sciences
Big Data
Precision Medicine

4. IT Challenges in Life Sciences
Distributed Heterogeneous Data Sources
Human genome/biological data
>750GB per complete human genome
>15PB in databases of leading institutes
Prescription data
1.5B records from 10,000 doctors and
10M Patients (100 GB)
Clinical trials
>30k recruiting trials on
ClinicalTrials.gov
Human proteome
160M data points (2.4GB) per sample
>3TB raw proteome data in ProteomicsDB
PubMed database
>24M unstructured
data in publications
Hospital information systems
>50GB structured relational data
Medical sensor data
Scan of a single organ creates
10GB of raw data within 1s
Cancer patient records
>160k records only at NCT
Big Data in Life
Sciences
Schapranow, CMS Global
Life Sciences, Fankfurt,
Nov 9, 2015
Chart 4

5. Healthcare Interactions in the 21st Century
Schapranow, CMS Global
Life Sciences, Fankfurt,
Nov 9, 2015
Big Data in Life
Sciences
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Indirect Interaction
Direct Interaction
C linician PatientResearcher
Pharm aceutical
Com pany
H ealthcare
Providers
H ospital
Research
Center
Laboratory
Patient
Advocacy
G roup

6. Use Case: Precision Medicine in Oncology
Identification of Best Treatment Option for Cancer Patient
■ Patient: 48 years, female, non-smoker, smoke-free environment
■ Diagnosis: Non-Small Cell Lung Cancer (NSCLC), stage IV
1. Surgery to remove tumor
2. Tumor sample is sent to laboratory to extract DNA
3. DNA is sequenced resulting in 750 GB of raw data per sample
4. Processing of raw data to perform analysis
5. Identification of relevant driver mutations using international medical knowledge
6. Informed decision making
Schapranow, CMS Global
Life Sciences, Fankfurt,
Nov 9, 2015
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Sciences
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7. Schapranow, CMS Global
Life Sciences, Fankfurt,
Nov 9, 2015
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8. Schapranow, CMS Global
Life Sciences, Fankfurt,
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9. Schapranow, CMS Global
Life Sciences, Fankfurt,
Nov 9, 2015
we.analyzegenomes.com
Real-time Analysis of Big Medical Data
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In-Memory Database
Extensions for Life Sciences
Data Exchange,
App Store
Access Control,
Data Protection
Fair Use
Statistical
Tools
Real-time
Analysis
App-spanning
User Profiles
Combined and Linked Data
Genome
Data
Cellular
Pathways
Genome
Metadata
Research
Publications
Pipeline and
Analysis Models
Drugs and
Interactions
Big Data in Life
Sciences
Drug Response
Analysis
Pathway Topology
Analysis
Medical
Knowledge CockpitOncolyzer
Clinical Trial
Recruitment
Cohort
Analysis
...
Indexed
Sources

10. Real-time Data Analysis and
Interactive Exploration
Drug Response Analysis
Data Sources
Schapranow, CMS Global
Life Sciences, Fankfurt,
Nov 9, 2015
Big Data in Life
Sciences
Smoking status,
tumor classification
and age
(1MB - 100MB)
Raw DNA data
and genetic variants
(100MB - 1TB)
Medication efficiency
and wet lab results
(10MB - 1GB)
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Patient-specific
Data
Tumor-specific
Data
Compound
Interaction Data

11. Schapranow, CMS Global
Life Sciences, Fankfurt,
Nov 9, 2015
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Sciences
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12. Showcase
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Life Sciences, Fankfurt,
Nov 9, 2015
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Calculating Drug Response…Predict Drug Response

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Life Sciences, Fankfurt,
Nov 9, 2015
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cetuximab might be more
beneficial for the current case

14. ■ Online: Visit we.analyzegenomes.com for latest research
results, slides, videos, tools, and publications
■ Offline: Read more about it, e.g.
High-Performance In-Memory Genome Data Analysis:
How In-Memory Database Technology Accelerates Personalized Medicine,
In-Memory Data Management Research, Springer,
ISBN: 978-3-319-03034-0, 2014
■ In Person: Join us for “Festival of Genomics” Jan 19-21, 2016 in London, UK
Where do you find additional information?
Schapranow, CMS Global
Life Sciences, Fankfurt,
Nov 9, 2015
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15. Keep in contact with us!
Hasso Plattner Institute
Enterprise Platform & Integration Concepts (EPIC)
Program Manager E-Health
August-Bebel-Str. 88
14482 Potsdam, Germany
Dr. Matthieu-P. Schapranow
schapranow@hpi.de
http://we.analyzegenomes.com/
Schapranow, CMS Global
Life Sciences, Fankfurt,
Nov 9, 2015
Big Data in Life
Sciences
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