A CTD-Pfizer collaboration: manual curation of 88,000 scientific articles text mined for drug-disease and drug-phenotype interactions.
A CTD-Pfizer collaboration: manual curation of 88,000 scientific articles text mined for drug-disease and drug-phenotype interactions.
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DOI：
10.1093/database/bat080
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发表时间：
2013
期刊：
影响因子：
--
通讯作者：
Mattingly CJ
中科院分区：
文献类型：
--
作者：
Davis AP;Wiegers TC;Roberts PM;King BL;Lay JM;Lennon-Hopkins K;Sciaky D;Johnson R;Keating H;Greene N;Hernandez R;McConnell KJ;Enayetallah AE;Mattingly CJ
改善化学品毒性的预测是环境健康研究和药物开发的共同目标。为了改进安全性检测测定，具有用于训练和验证目的的具有明确定义的毒性注释的分子参考集是至关重要的。在这里，我们描述了辉瑞公司的安全性研究人员和比较毒理学基因组学数据库（CTD）的研究团队之间的合作，以文本挖掘和手动审查88629篇文章的集合，这些文章涉及超过1200种药物，它们可能涉及心血管，神经，肾脏和肝脏毒性。在1年内，CTD生物创造者策划了254173个毒性基因组学相互作用（152173个化学-疾病，58572个化学-基因，5345个基因-疾病和38083个表型相互作用）。所有化学-基因-疾病相互作用都与公共CTD完全集成，表型相互作用可以下载。我们描述了辉瑞公司的文本挖掘过程中整理的文章，和CTD的策展策略，性能指标，增强的数据内容和新的模块，以策展表型信息。此外，我们还展示了数据整合如何将表型与疾病联系起来。这种策展可以用来获取对药物安全性很重要的毒性终点信息，并帮助开发药物-疾病事件的可检验假设。这些详细的，情境化的，高质量的注释的可用性来自七十年的科学文献，应该有助于促进新的药物化合物存活的机制筛选测定。这种独特的伙伴关系表明了公共和私营实体之间资源共享和合作的重要性，并强调了环境健康科学和制药界的互补需求。数据库URL：http://ctdbase.org/
Improving the prediction of chemical toxicity is a goal common to both environmental health research and pharmaceutical drug development. To improve safety detection assays, it is critical to have a reference set of molecules with well-defined toxicity annotations for training and validation purposes. Here, we describe a collaboration between safety researchers at Pfizer and the research team at the Comparative Toxicogenomics Database (CTD) to text mine and manually review a collection of 88 629 articles relating over 1 200 pharmaceutical drugs to their potential involvement in cardiovascular, neurological, renal and hepatic toxicity. In 1 year, CTD biocurators curated 2 54 173 toxicogenomic interactions (1 52 173 chemical–disease, 58 572 chemical–gene, 5 345 gene–disease and 38 083 phenotype interactions). All chemical–gene–disease interactions are fully integrated with public CTD, and phenotype interactions can be downloaded. We describe Pfizer’s text-mining process to collate the articles, and CTD’s curation strategy, performance metrics, enhanced data content and new module to curate phenotype information. As well, we show how data integration can connect phenotypes to diseases. This curation can be leveraged for information about toxic endpoints important to drug safety and help develop testable hypotheses for drug–disease events. The availability of these detailed, contextualized, high-quality annotations curated from seven decades’ worth of the scientific literature should help facilitate new mechanistic screening assays for pharmaceutical compound survival. This unique partnership demonstrates the importance of resource sharing and collaboration between public and private entities and underscores the complementary needs of the environmental health science and pharmaceutical communities. Database URL: http://ctdbase.org/
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影响因子：
14.9
作者：
Davis AP;Murphy CG;Saraceni-Richards CA;Rosenstein MC;Wiegers TC;Mattingly CJ
通讯作者：
Mattingly CJ
影响因子：
3
作者：
Jimeno-Yepes AJ;Plaza L;Mork JG;Aronson AR;Díaz A
通讯作者：
Díaz A
影响因子：
3.5
作者：
Choi, Jaejoon;Kim, Kwangmin;Lee, Doheon
通讯作者：
Lee, Doheon
影响因子：
1.9
作者：
Davis, Allan Peter;Murphy, Cynthia G.;Mattingly, Carolyn J.
通讯作者：
Mattingly, Carolyn J.
影响因子：
3.7
作者：
Ding Y;Song M;Han J;Yu Q;Yan E;Lin L;Chambers T
通讯作者：
Chambers T