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FDA approves BRUKER MALDI Biotyper CA system for the identification of C. auris which can cause serious infections in hospitalized patients.-Bruker Daltonik GmbH.

Read time: 1 mins
Last updated: 21st Apr 2018
Published: 21st Apr 2018
Source: Pharmawand

The FDA has authorized the first test to identify the emerging pathogen Candida auris (C. auris), which can cause serious infections in hospitalized patients. Specifically, the FDA permitted marketing for a new use of the BRUKER MALDI Biotyper CA system for the identification of C. auris, adding to the system�s already cleared uses for the identification of 333 species or species groups, covering 424 clinically relevant bacteria and yeast species.

�Although mass spectrometry technology has been a powerful scientific tool since the 1980s, it is only within that the last five years that it has been effectively used for the identification of microbiological organisms and is now a widely recognized standard of practice for clinical laboratories,� said Donald St. Pierre, acting director of the Office of In Vitro Diagnostics and Radiological Health in the FDA�s Center for Devices and Radiological Health. �The FDA has confidence in this technology and recognizes the need to rapidly address outbreaks both for C. auris and for other pathogenic microorganisms to help protect Americans through the recognition and identification of emerging infectious pathogens.�

Comment:The MALDI Biotyper CA System is a qualitative in vitro diagnostic device indicated for use in conjunction with other clinical and laboratory findings to aid the diagnosis of bacterial and yeast infections. Bruker has conducted a multi-site clinical trial comparing performance of the MALDI Biotyper CA System to 16S ribosomal RNA gene sequencing. The overall accuracy of the MALDI Biotyper CA System was comparable to that of nucleic acid sequencing.

Comment: The MALDI Biotyper CA System can identify 333 species or species groups, covering 424 clinically relevant bacteria and yeast species, and representing more than 98% of the typical bacterial identification workflow of clinical microbiology laboratories.

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