It has been a privilege to have recently been involved in an exciting new collaboration with Alexander Tropsha and Denis Fourches at the University of North Carolina. The team carried out a cheminformatics analysis of the assertional metadata (AMD) from BioWisdom’s Safety Intelligence Program (SIP), the world’s largest, ever-expanding collection of the known effects of drugs and other chemicals. SIP makes use of BioWisdom’s collection of key concept metadata and Sofia technology, which translates the varied and diverse language used by scientists into a semantically consistent form. The study has provided a fresh new perspective on historic public domain data, bringing together isolated fragments of toxicology information, spanning decades, to provide new insight into drug safety. The resulting article, entitled “Cheminformatics Analysis of Assertions Mined from Literature That Describe Drug-Induced Liver Injury in Different Species”, was published in Chemical Research in Toxicology on December 16, 2009.

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The Assertional Metadata (AMD) contained within our Safety Intelligence Program (SIP) represents the largest ever-expanding collection of known effects of chemicals occurring in the different tissue, drugs effects on clinical biomarkers of tissue injury and drug molecular mechanisms.

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Sofia enables the creation of networks of Assertional Metadata (AMD), a form of Intelligent Metadata that summarises the assertions made within unstructured or poorly formatted text and providing a semantically consistent method of navigation.   Sofia liberates intelligence from structured and unstructured data, regardless of its original format.

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