Journal article
Drug Repositioning to Accelerate Drug Development Using Social Media Data: Computational Study on Parkinson Disease
Journal of medical Internet research, v 20(10), pp e271-e271
11 Oct 2018
PMID: 30309833
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Due to the high cost and low success rate in new drug development, systematic drug repositioning methods are exploited to find new indications for existing drugs.
We sought to propose a new computational drug repositioning method to identify repositioning drugs for Parkinson disease (PD).
We developed a novel heterogeneous network mining repositioning method that constructed a 3-layer network of disease, drug, and adverse drug reaction and involved user-generated data from online health communities to identify potential candidate drugs for PD.
We identified 44 non-Parkinson drugs by using the proposed approach, with data collected from both pharmaceutical databases and online health communities. Based on the further literature analysis, we found literature evidence for 28 drugs.
In summary, the proposed heterogeneous network mining repositioning approach is promising for identifying repositioning candidates for PD. It shows that adverse drug reactions are potential intermediaries to reveal relationships between disease and drug.
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Details
- Title
- Drug Repositioning to Accelerate Drug Development Using Social Media Data: Computational Study on Parkinson Disease
- Creators
- Mengnan Zhao - College of Computing and Informatics, Drexel University, Philadelphia, PA, United StatesChristopher C Yang - College of Computing and Informatics, Drexel University, Philadelphia, PA, United States
- Publication Details
- Journal of medical Internet research, v 20(10), pp e271-e271
- Publisher
- Canada
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Information Science
- Web of Science ID
- WOS:000447165200001
- Scopus ID
- 2-s2.0-85054772117
- Other Identifier
- 991014877992004721
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Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Health Care Sciences & Services
- Medical Informatics