Fácil bula: sistema que estrutura o bulário eletrônico da Anvisa

• Ano de defesa: 2016
• Autor(a) principal: Silva, João Vitor Ferrari da
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Tecnológica Federal do Paraná; Cornelio Procopio; Brasil; Programa de Pós-Graduação em Informática; UTFPR
• Palavras-chave em Português: Mineração de dados (Computação); Medicamentos - Interações; Farmacologia; Data mining; Drug interactions; Pharmacology; CNPQ::CIENCIAS EXATAS E DA TERRA; Ciência da Computação
• Link de acesso: http://repositorio.utfpr.edu.br/jspui/handle/1/2551

The work done by health area professionals when facing the care of people consists on choosing the best medications for the success of the treatment of them. There are many medications available on the brazilian market, so for this professional find the information about the medication which could be the best match for the pacient there is which applications and tools make easier the search of drugs and helps this specialist. However, none of these systems had drug adverse reaction identification, contraindications, medical interactions, warnings and precautions between the overall association of drugs regulated by the “Agência Nacional de Vigilância Sanitária” (ANVISA). In this context, the ANVISA’s “Bulário Eletrônico” offers a collection of 6;961 professional medication guides in PDF file format. However, the information available in these guides are in an unstructured format. One of challenges of this work consisted in the automatic retrieval of information from ANVISA’s medication guides. This paper presents a semiautomatic procedure that maps ANVISA’s medication guides to DrugBank and SNOMEDCT. The medications, the diseases, the drugs, and their relations were structured and stored on a graph database using the Neo4j technology. Fácil Bula, was developed through results of studies, it is a website which goals to conceive tools to facilitate the medication and disease search for health professionals, it hits all the brazilian territory, mainly big capitals like S˜ao Paulo and Rio de Janeiro, as well as gain a good position in organic Google searches related to some keywords medicines and International Classification of Diseases (ICD).