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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

Affiliations of the authors: Laboratoire d'informatique médicale et de bioinformatique (LIM&BIO), UFR Santé, Médecine, Biologie Humaine, Université Paris 13, Bobigny, France (CD, MG, AV); Laboratoire de microbiologie, CHI Saint Germain/Poissy, Saint Germain en Laye, France (GLC).

Correspondence and reprints: Catherine Duclos, PharmD, PhD, LIM&BIO, UFR de Santé, Médecine et Biologie Humaine Léonard de Vinci, 74 rue Marcel Cachin 93017 Bobigny cedex, France; e-mail: <catherine.duclos{at}avc.ap-hop-paris.fr>.

Received for publication: 07/15/03; accepted for publication: 02/04/04.

Objective: The aim of this study was to construct automatically a knowledge base concerning the pharmacodynamic properties of antibiotics and a visualization tool.

Design: 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.

Measurements: 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.

Conclusion: 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.