{"title":"预测药物不良反应的网络医学和系统药理学方法","authors":"Alessio Funari, Giulia Fiscon, Paola Paci","doi":"10.1111/bph.17330","DOIUrl":null,"url":null,"abstract":"Identifying and understanding the relationships between drug intake and adverse effects that can occur due to inadvertent molecular interactions between drugs and targets is a difficult task, especially considering the numerous variables that can influence the onset of such events. The ability to predict these side effects in advance would help physicians develop strategies to avoid or counteract them. In this article, we review the main computational methods for predicting side effects caused by drug molecules, highlighting their performance, limitations and application cases. Furthermore, we provide an overall view of resources, such as databases and tools, useful for building side effect prediction analyses.","PeriodicalId":9262,"journal":{"name":"British Journal of Pharmacology","volume":"1 1","pages":""},"PeriodicalIF":6.8000,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Network medicine and systems pharmacology approaches to predicting adverse drug effects\",\"authors\":\"Alessio Funari, Giulia Fiscon, Paola Paci\",\"doi\":\"10.1111/bph.17330\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Identifying and understanding the relationships between drug intake and adverse effects that can occur due to inadvertent molecular interactions between drugs and targets is a difficult task, especially considering the numerous variables that can influence the onset of such events. The ability to predict these side effects in advance would help physicians develop strategies to avoid or counteract them. In this article, we review the main computational methods for predicting side effects caused by drug molecules, highlighting their performance, limitations and application cases. Furthermore, we provide an overall view of resources, such as databases and tools, useful for building side effect prediction analyses.\",\"PeriodicalId\":9262,\"journal\":{\"name\":\"British Journal of Pharmacology\",\"volume\":\"1 1\",\"pages\":\"\"},\"PeriodicalIF\":6.8000,\"publicationDate\":\"2024-09-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"British Journal of Pharmacology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1111/bph.17330\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"PHARMACOLOGY & PHARMACY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"British Journal of Pharmacology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1111/bph.17330","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PHARMACOLOGY & PHARMACY","Score":null,"Total":0}
Network medicine and systems pharmacology approaches to predicting adverse drug effects
Identifying and understanding the relationships between drug intake and adverse effects that can occur due to inadvertent molecular interactions between drugs and targets is a difficult task, especially considering the numerous variables that can influence the onset of such events. The ability to predict these side effects in advance would help physicians develop strategies to avoid or counteract them. In this article, we review the main computational methods for predicting side effects caused by drug molecules, highlighting their performance, limitations and application cases. Furthermore, we provide an overall view of resources, such as databases and tools, useful for building side effect prediction analyses.
期刊介绍:
The British Journal of Pharmacology (BJP) is a biomedical science journal offering comprehensive international coverage of experimental and translational pharmacology. It publishes original research, authoritative reviews, mini reviews, systematic reviews, meta-analyses, databases, letters to the Editor, and commentaries.
Review articles, databases, systematic reviews, and meta-analyses are typically commissioned, but unsolicited contributions are also considered, either as standalone papers or part of themed issues.
In addition to basic science research, BJP features translational pharmacology research, including proof-of-concept and early mechanistic studies in humans. While it generally does not publish first-in-man phase I studies or phase IIb, III, or IV studies, exceptions may be made under certain circumstances, particularly if results are combined with preclinical studies.