A Review of Drug Side Effect Identification Methods

Author(s): Shuai Deng, Yige Sun, Tianyi Zhao, Yang Hu, Tianyi Zang*

Journal Name: Current Pharmaceutical Design

Volume 26 , Issue 26 , 2020


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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.

Keywords: Drug side effect, machine learning, biological experiment, text mining, drug database, experimental.

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Article Details

VOLUME: 26
ISSUE: 26
Year: 2020
Published on: 11 August, 2020
Page: [3096 - 3104]
Pages: 9
DOI: 10.2174/1381612826666200612163819
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