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A review of drug side effect identification methods

  • Beijing Forestry University
  • Harbin Medical University
  • School of Life Science and Technology, Harbin Institute of Technology

Research output: Contribution to journalReview articlepeer-review

Abstract

Drug side effects have become an important indicator for evaluating the safety of drugs. There are two main factors in the frequent occurrence of drug safety problems; on the one hand, the clinical understanding of drug side effects is insufficient, leading to frequent adverse drug reactions, while on the other hand, due to the long-term period and complexity of clinical trials, side effects of approved drugs on the market cannot be reported in a timely manner. Therefore, many researchers have focused on developing methods to identify drug side effects. In this review, we summarize the methods of identifying drug side effects and common databases in this field. We classified methods of identifying side effects into four categories: biological experimental, machine learning, text mining and network methods. We point out the key points of each kind of method. In addition, we also explain the advantages and disadvantages of each method. Finally, we propose future research directions.

Original languageEnglish
Pages (from-to)3096-3104
Number of pages9
JournalCurrent Pharmaceutical Design
Volume26
Issue number26
DOIs
StatePublished - 2020
Externally publishedYes

Keywords

  • Biological experiment
  • Drug database
  • Drug side effect
  • Experimental
  • Machine learning
  • Text mining

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