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Trajectory analysis of drug-research trends in pancreatic cancer on PubMed and ClinicalTrials.gov

Authors
 Yoo Kyung Jeong  ;  Go Eun Heo  ;  Keun Young Kang  ;  Dong Sup Yoon  ;  Min Song 
Citation
 JOURNAL OF INFORMETRICS, Vol.10(1) : 273-285, 2016 
Journal Title
JOURNAL OF INFORMETRICS
ISSN
 1751-1577 
Issue Date
2016
Keywords
Pancreatic cancer ; Text mining ; Bibliometric analysis ; Data analysis ; Information extraction
Abstract
Increasing interest in developing treatments for pancreatic cancer has led to a surge in publications in the field. Analyses of drug-research trends are needed to minimize risk in anti-cancer drug development. Here, we analyzed publications on anti-cancer drugs extracted from PubMed records and ClinicalTrials datasets. We conducted a drug cluster analysis by proposing the entity Dirichlet Multinomial Regression (eDMR) technique and in-depth network analysis of drug cluster and target proteins. The results show two distinct research clusters in both the ClinicalTrials dataset and the PubMed records. Specifically, various targets associated with anti-cancer drugs are investigated in new drug testing while the diverse chemicals are studied together with a standard therapeutic agent in the academic literature. In addition, our study confirms that drug research published in PubMed is preceded by clinical trials. Although we only evaluate drugs for pancreatic cancer in the present study, our method can be applied to drug-research trends of other diseases.
Full Text
http://www.sciencedirect.com/science/article/pii/S1751157715301280
DOI
10.1016/j.joi.2016.01.003
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Surgery (외과학교실) > 1. Journal Papers
Yonsei Authors
Yoon, Dong Sup(윤동섭) ORCID logo https://orcid.org/0000-0001-6444-9606
URI
https://ir.ymlib.yonsei.ac.kr/handle/22282913/146407
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