This presentation shows application examples of the analyzegenomes.com service for precision medicine. It was presented at 2016 HIMSS conference in Las Vegas, NV

1. Analyze Genomes Services for Precision Medicine
Dr. Matthieu-P. Schapranow
Healthcare Information and Management Systems Society Conference, Las Vegas, NV
Mar 2, 2016

2. ■ Patients
□ Individual anamnesis, family history, and background
□ Require fast access to individualized therapy
■ Clinicians
□ Identify root and extent of disease using laboratory tests
□ Evaluate therapy alternatives, adapt existing therapy
■ Researchers
□ Conduct laboratory work, e.g. analyze patient samples
□ Create new research findings and come-up with treatment alternatives
The Setting
Actors in Oncology
Schapranow, HIMSS, Mar
2, 2016
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Analyze Genomes
Services for Precision
Medicine

3. IT Challenges
Distributed Heterogeneous Data Sources
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Human genome/biological data
600GB per full genome
15PB+ in databases of leading institutes
Prescription data
1.5B records from 10,000 doctors and
10M Patients (100 GB)
Clinical trials
Currently more than 30k
recruiting on ClinicalTrials.gov
Human proteome
160M data points (2.4GB) per sample
>3TB raw proteome data in ProteomicsDB
PubMed database
>23M articles
Hospital information systems
Often more than 50GB
Medical sensor data
Scan of a single organ in 1s
creates 10GB of raw dataCancer patient records
>160k records at NCT
Analyze Genomes
Services for Precision
Medicine
Schapranow, HIMSS, Mar
2, 2016

4. Schapranow, HIMSS, Mar
2, 2016
Our Approach
Analyze Genomes: 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
Analyze Genomes
Services for Precision
Medicine
Drug Response
Analysis
Pathway Topology
Analysis
Medical
Knowledge CockpitOncolyzer
Clinical Trial
Recruitment
Cohort
Analysis
...
Indexed
Sources

5. Combined column
and row store
Map/Reduce Single and
multi-tenancy
Lightweight
compression
Insert only
for time travel
Real-time
replication
Working on
integers
SQL interface on
columns and rows
Active/passive
data store
Minimal
projections
Group key Reduction of
software layers
Dynamic multi-
threading
Bulk load
of data
Object-
relational
mapping
Text retrieval
and extraction engine
No aggregate
tables
Data partitioning Any attribute
as index
No disk
On-the-fly
extensibility
Analytics on
historical data
Multi-core/
parallelization
Our Technology
In-Memory Database Technology
+
++
+
+
P
v
+++
t
SQL
x
x
T
disk
5
Schapranow, HIMSS, Mar
2, 2016
Analyze Genomes
Services for Precision
Medicine

6. Our Software Architecture
A Federated In-Memory Database System
Schapranow, HIMSS, Mar
2, 2016
Analyze Genomes
Services for Precision
Medicine
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Federated In-M em ory D atabase System
M aster Data and
Shared Algorithm s
Site A Site BCloud Provider
Cloud IM D B
Instance
Local IM DB
Instance
Sensitive D ata,
e.g. Patient Data
R
Local IM DB
Instance
Sensitive Data,
e.g. Patient D ata
R

7. 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
■ Markers: KRAS, EGFR, BRAF, NRAS, (ERBB2)
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, HIMSS, Mar
2, 2016
Analyze Genomes
Services for Precision
Medicine
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8. Schapranow, HIMSS, Mar
2, 2016
Analyze Genomes
Services for Precision
Medicine
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9. Schapranow, HIMSS, Mar
2, 2016
Analyze Genomes
Services for Precision
Medicine
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10. App Example I: Integrating Processing and Real-time Analysis
of Genome Data in the Clinical Routine
■ Control center for processing of raw DNA data, such as
FASTQ, SAM, and VCF
■ Personal user profile guarantees privacy of uploaded
and processed data
■ Supports reproducible research process by storing all
relevant process parameters
■ Implements prioritized data processing and fair use, e.g.
per department or per institute
■ Supports additional service, such as data annotations,
billing, and sharing for all Analyze Genomes services
■ Honored by the 2014 European Life Science Award
Analyze Genomes
Services for Precision
Medicine
Standardized Modeling and
runtime environment for
analysis pipelines
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Schapranow, HIMSS, Mar
2, 2016

11. ■ Query-oriented search interface
■ Seamless integration of patient specifics, e.g. from EMR
■ Parallel search in international knowledge bases, e.g. for biomarkers, literature,
cellular pathway, and clinical trials
App Example II:
Medical Knowledge Cockpit for Patients and Clinicians
Analyze Genomes
Services for Precision
Medicine
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Schapranow, HIMSS, Mar
2, 2016

12. Real-time Data Analysis and
Interactive Exploration
App Example III: Identifying Best Chemotherapy using
Drug Response Analysis
Schapranow, HIMSS, Mar
2, 2016
Analyze Genomes
Services for Precision
Medicine
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

13. ■ For patients
□ Identify relevant clinical trials and medical experts
□ Become an informed patient
■ For clinicians
□ Identify pharmacokinetic correlations
□ Scan for similar patient cases, e.g. to evaluate therapy efficiency
■ For researchers
□ Enable real-time analysis of medical data, e.g. assess pathways
to identify impact of detected variants
□ Combined mining in structured and unstructured data, e.g. publications,
diagnosis, and EMR data
What to Take Home?
Test it Yourself: AnalyzeGenomes.com
Schapranow, HIMSS, Mar
2, 2016
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Analyze Genomes
Services for Precision
Medicine

14. Keep in contact with us!
Hasso Plattner Institute
Enterprise Platform & Integration Concepts (EPIC)
Program Manager E-Health
Dr. Matthieu-P. Schapranow
August-Bebel-Str. 88
14482 Potsdam, Germany
Dr. Matthieu-P. Schapranow
schapranow@hpi.de
http://we.analyzegenomes.com/
Schapranow, HIMSS, Mar
2, 2016
Analyze Genomes
Services for Precision
Medicine
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