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BMC Microbiol ; 15: 275, 2015 Dec 09.
Artículo en Inglés | MEDLINE | ID: mdl-26653032

RESUMEN

BACKGROUND: Microbial contamination of pharmaceuticals poses a great problem to the pharmaceutical manufacturing process, especially from a medical as well as an economic point of view. Depending upon the product and its intended use, the identification of isolates should not merely be limited to the United States Pharmacopeia (USP) indicator organisms. RESULTS: Eighty-five pre-used non-sterile pharmaceuticals collected from random consumers in Egypt were examined for the eventual presence of bacterial contaminants. Forty-one bacterial contaminants were isolated from 31 of the tested preparations. These isolates were subjected to biochemical identification by both conventional tests as well as API kits, which were sufficient for the accurate identification of only 11 out of the 41 bacterial contaminants (26.8%) to the species level. The remaining isolates were inconclusively identified or showed contradictory results after using both biochemical methods. Using molecular methods, 24 isolates (58.5%) were successfully identified to the species level. Moreover, polymerase chain reaction (PCR) assays were compared to standard biochemical methods in the detection of pharmacopoeial bacterial indicators in artificially-contaminated pharmaceutical samples. CONCLUSION: PCR-based methods proved to be superior regarding speed, cost-effectiveness and sensitivity. Therefore, pharmaceutical manufacturers would be advised to adopt PCR-based methods in the microbiological quality testing of pharmaceuticals in the future.


Asunto(s)
Bacterias/aislamiento & purificación , Cosméticos , Contaminación de Medicamentos/prevención & control , Preparaciones Farmacéuticas , Tecnología Farmacéutica/métodos , Bacterias/clasificación , Técnicas de Tipificación Bacteriana , Costos y Análisis de Costo , Egipto , Humanos , Reacción en Cadena de la Polimerasa/economía , Reacción en Cadena de la Polimerasa/métodos , Control de Calidad , Sensibilidad y Especificidad , Factores de Tiempo
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