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Challenges of Big Medical Data
Dr. Matthieu-P. Schapranow
Festival of Genomics, London, U.K.
Jan 19, 2016
■  Online: Visit we.analyzegenomes.com for latest research results, tools, and news
■  Offline: Read more about it, e.g. H...
What is the Hasso Plattner Institute, Potsdam, Germany?
Schapranow, Festival of
Genomics, Jan 19, 2016
Challenges of Big
M...
■ Founded as a public-private partnership
in 1998 in Potsdam near Berlin, Germany
■ Institute belongs to the
University of...
Prof. Dr. h.c. Hasso Plattner
■ Research focuses on the technical aspects of enterprise
software and design of complex app...
■  Since 2009 Program Manager E-Health & Life Sciences
■  2006-2014 Strategic Projects SAP HANA
■  Visiting Scientist at V...
Healthcare Interactions in the 21st Century
Schapranow, Festival of
Genomics, Jan 19, 2016
Challenges of Big
Medical Data
...
■  Patients
□  Individual anamnesis, family history, and background
□  Require fast access to individualized therapy
■  Cl...
■  Motivation: Can we enable patients to:
□  Understand and monitor their diseases to document the impact on their lives,
...
Our Methodology
Design Thinking
Schapranow, Festival of
Genomics, Jan 19, 2016
Challenges of Big
Medical Data
10
Our Methodology
Design Thinking
Schapranow, Festival of
Genomics, Jan 19, 2016
Challenges of Big
Medical Data
11
Desirabil...
Sequencing vs. Main Memory Costs
Schapranow, Festival of
Genomics, Jan 19, 2016
Challenges of Big
Medical Data
12
0.001
0....
IT Challenges
Distributed Heterogeneous Data Sources
13
Human genome/biological data
600GB per full genome
15PB+ in databa...
■  Requirements
□  Real-time data analysis
□  Maintained software
■  Restrictions
□  Data privacy
□  Data locality
□  Volu...
Clouds Trends?
Schapranow, Festival of
Genomics, Jan 19, 2016
Challenges of Big
Medical Data
15
Gartner's 2014 Hype Cycle ...
Schapranow, Festival of
Genomics, Jan 19, 2016
we.analyzegenomes.com
Real-time Analysis of Big Medical Data
16
In-Memory D...
Keep in contact with us!
Hasso Plattner Institute
Enterprise Platform & Integration Concepts (EPIC)
Program Manager E-Heal...
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Festival of Genomics 2016 London: Challenges of Big Medical Data?

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This presentation covers the "Challenges of Big Medical Data" presentation of the 2016 Festival of Genomics workshop "Big Medical Data in Precision Medicine: Challenges or Opportunities?" on Jan 19, 2016 in London.

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Festival of Genomics 2016 London: Challenges of Big Medical Data?

  1. 1. Challenges of Big Medical Data Dr. Matthieu-P. Schapranow Festival of Genomics, London, U.K. Jan 19, 2016
  2. 2. ■  Online: Visit we.analyzegenomes.com for latest research results, tools, and news ■  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 “Cebit” March 14-20, 2016 in Hanover, Germany. Important things first: Where do you find additional information? Schapranow, Festival of Genomics, Jan 19, 2016 Challenges of Big Medical Data 2
  3. 3. What is the Hasso Plattner Institute, Potsdam, Germany? Schapranow, Festival of Genomics, Jan 19, 2016 Challenges of Big Medical Data 3
  4. 4. ■ Founded as a public-private partnership in 1998 in Potsdam near Berlin, Germany ■ Institute belongs to the University of Potsdam ■ Ranked 1st in CHE since 2009 ■ 500 B.Sc. and M.Sc. students ■ 10 professors/chairs, 150 PhD students ■ Course of study: IT Systems Engineering Hasso Plattner Institute Key Facts Challenges of Big Medical Data 4 Schapranow, Festival of Genomics, Jan 19, 2016
  5. 5. Prof. Dr. h.c. Hasso Plattner ■ Research focuses on the technical aspects of enterprise software and design of complex applications □  In-Memory Data Management for Enterprise Applications □  Enterprise Application Programming Model □  Scientific Data Management □  Human-Centered Software Design and Engineering ■ Industry cooperations, e.g. SAP, Siemens, Audi, and EADS ■ Research cooperations, e.g. Stanford, MIT, and Berkeley Hasso Plattner Institute Enterprise Platform and Integration Concepts Group Schapranow, Festival of Genomics, Jan 19, 2016 Challenges of Big Medical Data 5 Partner of Stanford Center for Design Research Partner of MIT in Supply Chain Innovation and CSAIL Partner at UC Berkeley RAD / AMP Lab Partner of SAP AG
  6. 6. ■  Since 2009 Program Manager E-Health & Life Sciences ■  2006-2014 Strategic Projects SAP HANA ■  Visiting Scientist at V.A., Boston, MA and Charité, Berlin ■  Software Engineer by training (PhD, M.Sc., B.Sc.) With whom are you dealing? Schapranow, Festival of Genomics, Jan 19, 2016 Challenges of Big Medical Data 6
  7. 7. Healthcare Interactions in the 21st Century Schapranow, Festival of Genomics, Jan 19, 2016 Challenges of Big Medical Data 7 Indirect Interaction Direct Interaction C linician PatientResearcher Pharm aceutical Com pany H ealthcare Providers H ospital Research Center Laboratory Patient Advocacy G roup
  8. 8. ■  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, Festival of Genomics, Jan 19, 2016 8 Challenges of Big Medical Data
  9. 9. ■  Motivation: Can we enable patients to: □  Understand and monitor their diseases to document the impact on their lives, □  Receive latest information about their (chronic) diseases, □  Cooperatively exchange with physicians and patients to improve quality of living Our Motivation Make Precision Medicine Become Routine Challenges of Big Medical Data 9 Schapranow, Festival of Genomics, Jan 19, 2016
  10. 10. Our Methodology Design Thinking Schapranow, Festival of Genomics, Jan 19, 2016 Challenges of Big Medical Data 10
  11. 11. Our Methodology Design Thinking Schapranow, Festival of Genomics, Jan 19, 2016 Challenges of Big Medical Data 11 Desirability ■  Portfolio of integrated services for clinicians, researchers, and patients ■  Include latest treatment option, e.g. most effective therapies Viability ■  Enable precision medicine also in far-off regions and developing countries ■  Involve word-wide experts (cost-saving) ■  Combine latest international data (publications, annotations, genome data) Feasibility ■  HiSeq X Ten delivers 30x coverage whole genome of >18k humans / year ■  IMDB enables allele frequency determination of 12B records within <1s ■  Cloud-based data processing services reduce TCO
  12. 12. Sequencing vs. Main Memory Costs Schapranow, Festival of Genomics, Jan 19, 2016 Challenges of Big Medical Data 12 0.001 0.01 0.1 1 10 100 1000 10000 Jan2002 Jan2004 Jan2006 Jan2008 Jan2010 Jan2012 Jan2014 Costsin[USD] Date Main Memory Costs per Megabyte Sequencing Costs per Megabase
  13. 13. IT Challenges Distributed Heterogeneous Data Sources 13 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 Challenges of Big Medical Data Schapranow, Festival of Genomics, Jan 19, 2016
  14. 14. ■  Requirements □  Real-time data analysis □  Maintained software ■  Restrictions □  Data privacy □  Data locality □  Volume of “big medical data” ■  Solution? □  Federated In-Memory Database System vs. Cloud Computing Software Requirements in Life Sciences Schapranow, Festival of Genomics, Jan 19, 2016 Challenges of Big Medical Data 14
  15. 15. Clouds Trends? Schapranow, Festival of Genomics, Jan 19, 2016 Challenges of Big Medical Data 15 Gartner's 2014 Hype Cycle for Emerging Technologies
  16. 16. Schapranow, Festival of Genomics, Jan 19, 2016 we.analyzegenomes.com Real-time Analysis of Big Medical Data 16 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 Challenges of Big Medical Data Drug Response Analysis Pathway Topology Analysis Medical Knowledge CockpitOncolyzer Clinical Trial Recruitment Cohort Analysis ... Indexed Sources
  17. 17. 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, Festival of Genomics, Jan 19, 2016 Challenges of Big Medical Data 17

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