利用生物医学本体整合生物知识,以学习和预测药物不良反应。

Gene regulation and systems biology Pub Date : 2017-03-15 eCollection Date: 2017-01-01 DOI:10.1177/1177625017696075
Shadia Zaman, Sirarat Sarntivijai, Darrell R Abernethy
{"title":"利用生物医学本体整合生物知识,以学习和预测药物不良反应。","authors":"Shadia Zaman,&nbsp;Sirarat Sarntivijai,&nbsp;Darrell R Abernethy","doi":"10.1177/1177625017696075","DOIUrl":null,"url":null,"abstract":"<p><p>Drug-induced toxicity is a major public health concern that leads to patient morbidity and mortality. To address this problem, the Food and Drug Administration is working on the PredicTox initiative, a pilot research program on tyrosine kinase inhibitors, to build mechanistic and predictive models for drug-induced toxicity. This program involves integrating data acquired during preclinical studies and clinical trials within pharmaceutical company development programs that they have agreed to put in the public domain and in publicly available biological, pharmacological, and chemical databases. The integration process is accommodated by biomedical ontologies, a set of standardized vocabularies that define terms and logical relationships between them in each vocabulary. We describe a few programs that have used ontologies to address biomedical questions. The PredicTox effort is leveraging the experience gathered from these early initiatives to develop an infrastructure that allows evaluation of the hypothesis that having a mechanistic understanding underlying adverse drug reactions will improve the capacity to understand drug-induced clinical adverse drug reactions.</p>","PeriodicalId":73138,"journal":{"name":"Gene regulation and systems biology","volume":"11 ","pages":"1177625017696075"},"PeriodicalIF":0.0000,"publicationDate":"2017-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/1177625017696075","citationCount":"14","resultStr":"{\"title\":\"Use of Biomedical Ontologies for Integration of Biological Knowledge for Learning and Prediction of Adverse Drug Reactions.\",\"authors\":\"Shadia Zaman,&nbsp;Sirarat Sarntivijai,&nbsp;Darrell R Abernethy\",\"doi\":\"10.1177/1177625017696075\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Drug-induced toxicity is a major public health concern that leads to patient morbidity and mortality. To address this problem, the Food and Drug Administration is working on the PredicTox initiative, a pilot research program on tyrosine kinase inhibitors, to build mechanistic and predictive models for drug-induced toxicity. This program involves integrating data acquired during preclinical studies and clinical trials within pharmaceutical company development programs that they have agreed to put in the public domain and in publicly available biological, pharmacological, and chemical databases. The integration process is accommodated by biomedical ontologies, a set of standardized vocabularies that define terms and logical relationships between them in each vocabulary. We describe a few programs that have used ontologies to address biomedical questions. The PredicTox effort is leveraging the experience gathered from these early initiatives to develop an infrastructure that allows evaluation of the hypothesis that having a mechanistic understanding underlying adverse drug reactions will improve the capacity to understand drug-induced clinical adverse drug reactions.</p>\",\"PeriodicalId\":73138,\"journal\":{\"name\":\"Gene regulation and systems biology\",\"volume\":\"11 \",\"pages\":\"1177625017696075\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-03-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1177/1177625017696075\",\"citationCount\":\"14\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Gene regulation and systems biology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1177/1177625017696075\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2017/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Gene regulation and systems biology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1177/1177625017696075","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2017/1/1 0:00:00","PubModel":"eCollection","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 14

摘要

药物毒性是导致患者发病和死亡的主要公共卫生问题。为了解决这个问题,美国食品和药物管理局正在开展PredicTox计划,这是一个关于酪氨酸激酶抑制剂的试点研究项目,旨在建立药物毒性的机制和预测模型。该项目涉及整合制药公司开发项目中临床前研究和临床试验期间获得的数据,这些数据已同意放入公共领域,并公开提供生物、药理学和化学数据库。生物医学本体是一组标准化词汇表,用于定义术语和每个词汇表中术语之间的逻辑关系。我们描述了一些使用本体来解决生物医学问题的程序。PredicTox项目正在利用从这些早期倡议中收集的经验来开发一个基础设施,该基础设施允许对假设进行评估,即对药物不良反应的机制了解将提高了解药物引起的临床药物不良反应的能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

摘要图片

摘要图片

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Use of Biomedical Ontologies for Integration of Biological Knowledge for Learning and Prediction of Adverse Drug Reactions.

Drug-induced toxicity is a major public health concern that leads to patient morbidity and mortality. To address this problem, the Food and Drug Administration is working on the PredicTox initiative, a pilot research program on tyrosine kinase inhibitors, to build mechanistic and predictive models for drug-induced toxicity. This program involves integrating data acquired during preclinical studies and clinical trials within pharmaceutical company development programs that they have agreed to put in the public domain and in publicly available biological, pharmacological, and chemical databases. The integration process is accommodated by biomedical ontologies, a set of standardized vocabularies that define terms and logical relationships between them in each vocabulary. We describe a few programs that have used ontologies to address biomedical questions. The PredicTox effort is leveraging the experience gathered from these early initiatives to develop an infrastructure that allows evaluation of the hypothesis that having a mechanistic understanding underlying adverse drug reactions will improve the capacity to understand drug-induced clinical adverse drug reactions.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Pathway-Based Analysis of the Liver Response to Intravenous Methylprednisolone Administration in Rats: Acute Versus Chronic Dosing. Temporal and Spatial Differential Expression of Glutamate Receptor Genes in the Brain of Down Syndrome Introductory Chapter: Gene Regulation, an RNA Network-Dependent Architecture Model-based Evaluation of Gene Expression Changes in Response to Leishmania Infection. Gene Activation by the Cytokine-Driven Transcription Factor STAT1
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1