title: Text mining patents for biomedical knowledge.
abstract: Biomedical text mining of scientific knowledge bases, such as Medline, has received much attention in recent years. Given that text mining is able to automatically extract biomedical facts that revolve around entities such as genes, proteins, and drugs, from unstructured text sources, it is seen as a major enabler to foster biomedical research and drug discovery. In contrast to the biomedical literature, research into the mining of biomedical patents has not reached the same level of maturity. Here, we review existing work and highlight the associated technical challenges that emerge from automatically extracting facts from patents. We conclude by outlining potential future directions in this domain that could help drive biomedical research and drug discovery.
authors.affiliation: Roche Pharmaceutical Research and Early Development, pRED Informatics, Roche Innovation Center Basel, 4070 Basel, Switzerland. Electronic address: raul.rodriguez-esteban@roche.com.
authors.forename: Raul
authors.initials: R
authors.lastname: Rodriguez-Esteban
authors.affiliation: Scientific & Business Information Services, Roche Diagnostics GmbH, 82377 Penzberg, Germany.
authors.forename: Markus
authors.initials: M
authors.lastname: Bundschus
mesh_terms: D035843:Biomedical Research; D057225:Data Mining; D055808:Drug Discovery; D010330:Patents as Topic