AI Article Synopsis
- Drug side effects are crucial for assessing drug safety, but their frequent occurrence is often due to a lack of clinical understanding and delays in reporting post-approval effects.
- Researchers are actively developing various methods to identify these side effects, categorized into biological experiments, machine learning, text mining, and network approaches.
- The review highlights the strengths and weaknesses of each identification method and suggests future research directions to improve drug safety evaluation.
Article 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.
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| http://dx.doi.org/10.2174/1381612826666200612163819 | DOI Listing |
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