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Gesundheit geht uns alle an: Smart Data ermöglicht passendere Entscheidungen – in Echtzeit!

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This is the slide deck presented at the IHK/Bitkom Big Data Summit in Berlin on Sep 27, 2016 .

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Gesundheit geht uns alle an: Smart Data ermöglicht passendere Entscheidungen – in Echtzeit!

  1. 1. Gesundheit geht uns alle an: Smart Data ermöglicht passendere Entscheidungen – in Echtzeit! Dr. Matthieu-P. Schapranow Bitkom/IHK Big Data Summit Berlin Sep 27, 2016
  2. 2. Patient Doctor Interaction Schapranow, Bitkom/IHK Big Data Summit, Sep 27, 2016 Analyze Genomes Services for Precision Medicine 2 What about the relevant data?
  3. 3. IT Challenges of Healthcare Distributed Heterogeneous Data Sources 3 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, Bitkom/IHK Big Data Summit, Sep 27, 2016
  4. 4. 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 4 Schapranow, Bitkom/IHK Big Data Summit, Sep 27, 2016 Analyze Genomes Services for Precision Medicine
  5. 5. Schapranow, Bitkom/IHK Big Data Summit, Sep 27, 2016 Digital Health powered by AnalyzeGenomes.com: Real-time Analysis of Big Medical Data 5 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
  6. 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 ■  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, Bitkom/IHK Big Data Summit, Sep 27, 2016 Analyze Genomes Services for Precision Medicine 6
  7. 7. Schapranow, Bitkom/IHK Big Data Summit, Sep 27, 2016 Analyze Genomes Services for Precision Medicine 7
  8. 8. Schapranow, Bitkom/IHK Big Data Summit, Sep 27, 2016 Analyze Genomes Services for Precision Medicine 8
  9. 9. App Example: 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 9 Schapranow, Bitkom/IHK Big Data Summit, Sep 27, 2016
  10. 10. ■  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: Medical Knowledge Cockpit for Patients and Clinicians Analyze Genomes Services for Precision Medicine 10 Schapranow, Bitkom/IHK Big Data Summit, Sep 27, 2016
  11. 11. Real-time Data Analysis and Interactive Exploration App Example: Identifying Best Chemotherapy using Drug Response Analysis Schapranow, Bitkom/IHK Big Data Summit, Sep 27, 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) 11 Patient-specific Data Tumor-specific Data Compound Interaction Data
  12. 12. Heart Failure Sleeping disorder Fibrosis Blood pressure Blood volume Gene ex- pression Hyper- trophyCalcium meta- bolism Energy meta- bolism Iron deficiency Vitamin-D deficiency Gender Epi- genetics ■  Integrated systems medicine based on real-time analysis of healthcare data ■  Initial funding period: Mar ‘15 – Feb ‘18 ■  Funded consortium partners: Systems Medicine Model of Heart Failure (SMART) Schapranow, Bitkom/IHK Big Data Summit, Sep 27, 2016 Analyze Genomes Services for Precision Medicine 12 A R T + T RAM S + S M
  13. 13. ■  Process definition through user interviews ■  Identification of time-consuming and manual process steps ■  Requirements for a computer-aided research process: 1.  Sharing of data 2.  Improved communication 3.  Reproducible data processing Requirements Engineering for System Medicine Computer-aided Systems Medicine Process Schapranow, Bitkom/IHK Big Data Summit, Sep 27, 2016 Analyze Genomes Services for Precision Medicine 13
  14. 14. ■  In-Memory Database (IMDB) as data integration platform ■  Automatic synchronization of partner data ■  Event-driven notifications ■  Specific real-time analysis workflows, e.g. for RNAseq SMART Data Integration and Analysis Platform Schapranow, Bitkom/IHK Big Data Summit, Sep 27, 2016 Analyze Genomes Services for Precision Medicine 14
  15. 15. ■  Interdisciplinary partners collaborate on enabling real-time healthcare research ■  Initial funding period: Aug 2015 – July 2018 ■  Funded consortium partners: □  AOK German healthcare insurance company □  data experts group Technology operations □  Hasso Plattner Institute Real-time data analysis, in-memory database technology □  Technology, Methods, and Infrastructure for Networked Medical Research Legal and data protection Smart Analysis Health Research Access (SAHRA) Schapranow, Bitkom/IHK Big Data Summit, Sep 27, 2016 Analyze Genomes Services for Precision Medicine 15
  16. 16. 1.  AP4.12: Data exploration, e.g. graphical exploration and linkage of data 2.  AP4.17: Matching, e.g. to identify sets of patients with similar features 3.  AP4.22: Prediction, e.g. of future patient developments using training data from similar patients SAHRA Pilot Applications Schapranow, Bitkom/IHK Big Data Summit, Sep 27, 2016 Analyze Genomes Services for Precision Medicine 16
  17. 17. ■  Deep learning supporting radiologists at Charité, e.g. MRI segmentation ■  Natural language processing with DKG, e.g. question answering, clinical trials, publications ■  Real-time Exploration of the Human Immune System, NCT Heidelberg Further Digital Health Activities Schapranow, Bitkom/IHK Big Data Summit, Sep 27, 2016 Analyze Genomes Services for Precision Medicine 17
  18. 18. Control your Personal Data Schapranow, Bitkom/IHK Big Data Summit, Sep 27, 2016 Analyze Genomes Services for Precision Medicine 18 Data Donation Pass Personal Interests ■  Asthma ■  Diabetes II Notifications ■  9/27: Granted Dr. House access to resp. lab data ■  9/25: Respiratory laboratory data available ■  9/21: Asthma self management study publ.
  19. 19. ■  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, Bitkom/IHK Big Data Summit, Sep 27, 2016 19 Analyze Genomes Services for Precision Medicine
  20. 20. Keep in contact with us! Schapranow, Bitkom/IHK Big Data Summit, Sep 27, 2016 Analyze Genomes Services for Precision Medicine 20 Dr. Matthieu-P. Schapranow Program Manager E-Health & Life Sciences Hasso Plattner Institute August-Bebel-Str. 88 14482 Potsdam, Germany schapranow@hpi.de http://we.analyzegenomes.com/

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