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Database (Oxford). 2013 Nov 28;2013:bat080. doi: 10.1093/database/bat080. Print 2013.

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

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Department of Biological Sciences, 3510 Thomas Hall, North Carolina State University, Raleigh, NC 27695-7617, USA, Computational Sciences Center of Emphasis, 200 Cambridgepark Drive, Pfizer Inc., Cambridge, MA 02139, USA, Department of Bioinformatics, P.O. Box 35, Old Bar Harbor Road, MDI Biological Laboratory, Salisbury Cove, ME 04672, USA, Compound Safety Prediction, MS 8118-B3, Eastern Point Road, Pfizer Inc., Groton, CT 06340, USA, Computational Sciences Center of Emphasis, Pfizer Inc., Ramsgate Road, Sandwich, Kent CT13 9NJ, UK, Computational Sciences Center of Emphasis, 558 Eastern Point Road, Pfizer Inc., Groton, CT 06340, USA and Drug Safety Research and Development, 558 Eastern Point Road, Pfizer Inc., Groton, CT 06340, USA.


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 254,173 toxicogenomic interactions (152,173 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:

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