Hasso-Plattner-Institut
  
Hasso-Plattner-Institut
Prof. Dr. h.c. Hasso Plattner
  
 

Dr.-Ing. Matthieu-P. Schapranow

Program Manager E-Health

Click to view a high-res picture of Matthieu-P. Schapranow
  Phone: +49 (331) 55 09 - 1331
  Fax: +49 (331) 55 09 - 579
  E-Mail: ,
  Organization: Hasso Plattner Insitute
  Address: August-Bebel-Str. 88 Potsdam, Brandenburg, 14482 Germany
  Room: Hasso Plattner Institute Campus II, Villa, Room: V-1.01
  Profiles: XING, LinkedIn, Plaxo, University of Potsdam, Research Gate

Committees and Memberships

Awards

Dr. Matthieu-P. Schapranow is Program Manager E-Health at the HPI, Visiting Scientist at the Mass. Veterans Epidemiology Research and Information Center (MAVERIC) of the U.S. Department of Veterans Affairs and at Charité – University Medicine in Berlin, Germany. He is a valued member of the Berlin Cancer Society contributing to the Federal Association for Information Technology, Telecommunications and New Media (BITKOM) and the Global Alliance for Genomics and Health. Dr. Schapranow holds a PhD as well as the MSc and BSc degrees in Software Engineering. He was honored with the Personalized Medicine Convention Award 2015, the European Life Science Award in 2014, and the Innovation Award of the German Capital Region in 2012. Together with Prof. Dr. Plattner, he published the textbook "High-Performance In-Memory Genome Data Analysis" in 2013.

The full biography including high-res picture download are available in German and English.

Further Interests

  • Genomics
  • Life Sciences
  • Parallelization
  • Innovative Applications

Selected Patents

  • System and method for genomic data processing with an in-memory database system and real-time analysis (US20140214333, EP2759953)
  • Efficient genomic read alignment in an in-memory database (US20140214334, EP2759952)
  • Transparent control of access invoking real-time analysis of the query history (EP2667337)
  • Read more

Selected Presentations

Books

2014 (1)

  1. Hasso Plattner, Matthieu-P. Schapranow: High-Performance In-Memory Genome Data Analysis: How In-Memory Database Technology Accelerates Personalized Medicine, In-Memory Data Management Research, ISBN: 978-3-319-03034-0, 2014 BibTeX

2013 (1)

  1. Matthieu-P. Schapranow: Real-time Security Extensions for EPCglobal Networks: Case Study for the Pharmaceutical Industry, In-Memory Data Management Research, Springer, ISBN: 978-3-642-36342-9, 2013 BibTeX

 

 

IT-Aided Business Process Enabling Real-time Analysis of Candidates for Clinical Trials

Matthieu-P. Schapranow,Cindy Perscheid,Hasso Plattner
In Proceedings of the 4th International Conference on Global Health Challenges, pages 67-73, 2015 IARIA.

Abstract:

Recruitment of participants for clinical trials is a complex task involving screening of hundreds of thousands of candidates, e.g., testing for trial-specific inclusion and exclusion criteria. Today, a significant amount of time is spent on manual screening as improper selected candidates have impact on the overall study results. We introduce a candidate eligibility metric, which allows systematic ranking and classification of candidates based on trial-specific filter criteria in an automatic way. It is implemented as part of our web application, which enables real-time analysis of patient data and assessment of candidates. Thus, the time for identification of eligible candidates is tremendously reduced whilst additional degrees of freedom for assessing the relevance of individual candidates are available.

Keywords:

Clinical Trials,In-Memory Technology,Data Analysis,Eligibility Metric,Clustering

BibTeX file

@inproceedings{Matthieu-P.2015a,
author = { Matthieu-P. Schapranow,Cindy Perscheid,Hasso Plattner },
title = { IT-Aided Business Process Enabling Real-time Analysis of Candidates for Clinical Trials },
year = { 2015 },
pages = { 67-73 },
month = { 0 },
abstract = { Recruitment of participants for clinical trials is a complex task involving screening of hundreds of thousands of candidates, e.g., testing for trial-specific inclusion and exclusion criteria. Today, a significant amount of time is spent on manual screening as improper selected candidates have impact on the overall study results. We introduce a candidate eligibility metric, which allows systematic ranking and classification of candidates based on trial-specific filter criteria in an automatic way. It is implemented as part of our web application, which enables real-time analysis of patient data and assessment of candidates. Thus, the time for identification of eligible candidates is tremendously reduced whilst additional degrees of freedom for assessing the relevance of individual candidates are available. },
keywords = { Clinical Trials,In-Memory Technology,Data Analysis,Eligibility Metric,Clustering },
publisher = { IARIA },
booktitle = { Proceedings of the 4th International Conference on Global Health Challenges },
isbn = { 978-1-61208-424-4 },
issn = { 2308-4553 },
priority = { 0 }
}

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last change: Fri, 11 Dec 2015 16:38:59 +0100

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