A pharmacological interaction occurs when the effects of a one drug are modified by the presence of another. The consequences can be harmful if the interaction causes an increase in the toxicity of the drug or if it diminishes its effect, possibly even causing the patient's death, in the worst case scenario. At present, there are databases for checking possible interactions between drugs administered to patients, but the main problem is that many of the databases are not updated for three years. "The biomedical literature is the best system for staying up-to-date with respect to new interactions, but each year 300,000 articles are published just within the pharmacology domain, which is an avalanche of information overwhelming medical personnel", remarked one of the researchers, Isabel Segura, from the Bases de Datos Avanzadas (advanced Database Group) (LABDA) of UC3M.
Once the problem is located, a solution must be sought. In this case, it is necessary to develop automated tools which offer medical personnel efficient administration and access to all of this information, according to the researchers, who have created a system to detect the names of drugs in biomedical texts with 90% accuracy, according to the scientific article published in the journal Drug Discovery Today by professors Isabel Segura and Paloma Martínez, of the Department of Information Technology at UC3M, and María Segura of the University Hospital of Móstoles. The system combines terminological resources and the rules of nomenclature recommended by the World Health Organization.
"The system we describe permits identification of drug names and their classification within drug families in scientific texts", professor Segura explained. "In our case", she pointed out, "it is a prior step, crucial for locating interactions between drugs from the related literature which facilitates keeping the specialized databases up-to-date". Notwithstanding, the system could have immediate usefulness to improve upon the current search engines, whose functioning is based exclusively on the terms which appear in the documents, adding something of significance. A semantic search engine, for example, could improve the results of the search for a drug family by including the articles which mention the concrete drugs of that family.