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Ole Isacson: Development of New Therapies for Parkinson's Disease
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Drug Repositioning to Accelerate Drug Development Using Social Media Data: Computational Study on Parkinson Disease.

Mengnan Zhao1, Christopher C Yang1

  • 1College of Computing and Informatics, Drexel University, Philadelphia, PA, United States.

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|October 13, 2018
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This study introduces a novel computational method for drug repositioning to find new Parkinson disease treatments. The approach successfully identified potential drugs by analyzing drug interactions and patient data.

Keywords:
Parkinson diseasedrug repositioningheterogeneous networksocial media

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Area of Science:

  • Computational biology
  • Pharmacology
  • Bioinformatics

Background:

  • Drug development is costly and has a low success rate.
  • Drug repositioning offers a viable strategy to discover new therapeutic indications for existing medications.
  • Identifying new uses for approved drugs is crucial for efficient pharmaceutical research.

Purpose of the Study:

  • To develop a novel computational drug repositioning method.
  • To identify potential repositioning drugs specifically for Parkinson disease (PD).
  • To leverage heterogeneous network mining for drug discovery in neurodegenerative diseases.

Main Methods:

  • Constructed a novel 3-layer heterogeneous network integrating disease, drug, and adverse drug reaction data.
  • Incorporated user-generated data from online health communities to enhance network analysis.
  • Employed network mining techniques to identify potential drug candidates for PD.

Main Results:

  • Identified 44 non-Parkinson drugs as potential candidates for repositioning.
  • Validated 28 of the identified drugs through comprehensive literature analysis.
  • Demonstrated the utility of adverse drug reactions as intermediaries in disease-drug relationship discovery.

Conclusions:

  • The proposed heterogeneous network mining approach is effective for identifying repositioning candidates for Parkinson disease.
  • Adverse drug reactions play a significant role in uncovering complex relationships between diseases and drugs.
  • This method offers a promising strategy for accelerating the discovery of new Parkinson disease therapies.