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A CTD–Pfizer collaboration: manual curation of 88 000 scientific articles text mined for drug–disease and drug–phenotype interactions

机译:CTD与辉瑞公司的合作:人工整理了88 000篇有关药物疾病和药物表型相互作用的科学文章文本

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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/
机译:改善化学毒性的预测是环境健康研究和药物开发共同的目标。为了改进安全性检测测定,至关重要的是要有一组具有明确毒性注释的参考分子,以进行培训和验证。在这里,我们描述了辉瑞(Pfizer)安全研究人员与比较毒物基因组数据库(CTD)的研究团队之间的合作,以发短信给我,并人工审核88 629篇文章的集合,这些文章涉及1200多种药物与心血管,神经系统疾病,肾和肝毒性。在1年中,CTD生物策展人策划了2 54 173个毒物基因组相互作用(1 52 173个化学疾病,58 572个化学基因,5 345个基因疾病和38083个表型相互作用)。所有的化学-基因-疾病相互作用都与公共CTD完全集成,并且可以下载表型相互作用。我们将描述辉瑞公司的文本挖掘过程以整理文章,并介绍CTD的策展策略,性能指标,增强的数据内容以及用于表型信息管理的新模块。同样,我们展示了数据集成如何将表型与疾病联系起来。可以利用这种方法来获取有关对药物安全性重要的毒性终点的信息,并有助于为药物疾病事件开发可检验的假设。从七十年的科学文献中精选出的这些详细的,有具体背景的高质量注释,将有助于促进用于药物化合物存活的新的机械筛选试验。这种独特的伙伴关系表明了公共和私人实体之间资源共享和协作的重要性,并强调了环境健康科学和制药界的补充需求。数据库网址:http://ctdbase.org/

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