title: Structured representation of the pharmacodynamics section of the summary of product characteristics for antibiotics: application for automated extraction and visualization of their antimicrobial activity spectra.
abstract: OBJECTIVE
  The aim of this study was to construct automatically a knowledge base concerning the pharmacodynamic properties of antibiotics and a visualization tool.
  
  
  METHODS
  The authors studied the various guidelines used to write the pharmacodynamics section of the Summary of Product Characteristics (SPC) for antibiotics and constructed a conceptual model of the information. Particular words, syntagms, and punctuation elements were marked in the SPC texts, and automatic extraction was then used to build a knowledge base. This base was used to create dynamic HTML tables displaying the activity spectra of the antibiotics.
  
  
  METHODS
  The authors analyzed the performances of automatic extraction (recall and precision).
  
  
  RESULTS
  The conceptual pharmacodynamics model dealt with antibiotics, pathogens, susceptibility tests, and the prevalence of resistance. Automatic extraction had a recall rate of 97.9% and a precision of 96.2%. The tool displaying antibiotic spectra and resistance prevalences used color codes to identify differences in susceptibility.
  
  
  CONCLUSIONS
  This tool can provide an overview of the prevalence of resistance as expressed in SPC in primary care settings. Its potential impact should be evaluated.
authors.affiliation: Laboratoire d'informatique médicale et de bioinformatique (LIM&BIO), UFR de Santé, Médecine et Biologie Humaine, Paris 13, Bobigny cedex, France. catherine.duclos@avc.ap-hop-paris.fr.
authors.forename: Catherine
authors.initials: C
authors.lastname: Duclos
authors.forename: Gian Luigi
authors.initials: GL
authors.lastname: Cartolano
authors.forename: Michael
authors.initials: M
authors.lastname: Ghez
authors.forename: Alain
authors.initials: A
authors.lastname: Venot
mesh_terms: D000900:Anti-Bacterial Agents / Q000494:pharmacology*; D001185:Artificial Intelligence; D001419:Bacteria / Q000145:classification / Q000187:drug effects; D024881:Drug Resistance, Bacterial; D005060:Europe; D006801:Humans; D008962:Models, Theoretical; D010602:Pharmacopoeias as Topic; D011381:Programming Languages; D009626:Terminology as Topic; D014481:United States
chemical_list: D000900:Anti-Bacterial Agents