DocumentCode :
659610
Title :
BIG DATA infrastructures for pharmaceutical research
Author :
Seebode, Christian ; Ort, Miroslav ; Regenbrecht, Christian ; Peuker, Martin
Author_Institution :
ORTEC Med., ORTEC Med. GmbH, Berlin, Germany
fYear :
2013
fDate :
6-9 Oct. 2013
Firstpage :
59
Lastpage :
63
Abstract :
Big Data is an emerging paradigm covering production, collection, processing, analysis, access and presentation of huge data-sets: Big Data infrastructures represent an opportunity to approach this paradigm on an organizational level. We describe challenges and opportunities of big data infrastructures for the pharmaceutical industry. Pharmaceutical research and product development are huge investments and require intense exploration and analysis of data. Future trends show that pharmaceutical companies need to develop new methods of data and information processing to quicker and more precisely respond to changing markets and the need of patients and providers. The individual case and patients will become more influential in healthcare delivery and in consequence for the rationale behind these decisions. Our approach of a platform for semantic exploitation of BIG DATA supports a knowledge based infrastructure for deep analysis of clinical information from structured sources and clinical narratives. This infrastructure is able to pave the way towards the necessary big data-management possibilities. Example applications for cancer research will be given.
Keywords :
Big Data; data analysis; health care; pharmaceutical industry; product development; Big Data infrastructures; cancer research; data analysis; healthcare delivery; information processing; knowledge based infrastructure; organizational level; pharmaceutical industry; pharmaceutical research; product development; semantic exploitation; Data handling; Data storage systems; Information management; Medical diagnostic imaging; Pharmaceuticals; Technological innovation; bigdata; outcome oriented medicine; pharmaceutical research; semantic information processing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Big Data, 2013 IEEE International Conference on
Conference_Location :
Silicon Valley, CA
Type :
conf
DOI :
10.1109/BigData.2013.6691759
Filename :
6691759
Link To Document :
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