Pharma vocabulary varies across countries, (sub-)industries, companies, departments, and decades of time. E.g.., what’s a gel pak? What’s the “street name” for ranitidine hydrochloride? Each of these n controlled vocabularies is an ontology with approximately 300k terms. Glaxo researchers need to issue a query in their current vocabulary, have it translated into a neutral “true meaning”, and then have that transformed in the opposite direction to find potential matches against documents each of which was written to comply with a particular known vocabulary. They had been using a large staff to do that manually. Cyc is used as the universal interlingua capable of representing the union of all the terms’ “true meanings”, and capable of representing the 300k transformations between each of those controlled vocabularies and Cyc, thereby converting an n2 problem into a linear one without introducing the usual sort of “telephone game” attenuation of meaning. Furthermore, creating each of those 300k mappings for each thesaurus is done in a largely automated fashion, by Cyc.