Direct antimicrobial resistance prediction from clinical MALDI-TOF mass spectra using machine learning

  14 January 2022

Early use of effective antimicrobial treatments is critical for the outcome of infections and the prevention of treatment resistance. Antimicrobial resistance testing enables the selection of optimal antibiotic treatments, but current culture-based techniques can take up to 72 hours to generate results. We have developed a novel machine learning approach to predict antimicrobial resistance directly from matrix-assisted laser desorption/ionization–time of flight (MALDI-TOF) mass spectra profiles of clinical isolates. 

Further reading: Nature Medicine
Author(s): Caroline Weis, Aline Cuénod, Bastian Rieck, Olivier Dubuis, Susanne Graf, Claudia Lang, Michael Oberle, Maximilian Brackmann, Kirstine K. Søgaard, Michael Osthoff, Karsten Borgwardt & Adrian Egli
Smart Innovations  
Back

OUR UNDERWRITERS

Unrestricted financial support by:

LifeArc

Antimicrobial Resistance Fighter Coalition

Bangalore Bioinnovation Centre

INTERNATIONAL FEDERATION PHARMACEUTICAL MANUFACTURERS & ASSOCIATIONS





Ambassador Network

Join the AMR Insights Ambassador Network today!

Connect to over 650 AMR professionals and students in 65 countries!

More information

What is going on with AMR?
Stay tuned with remarkable global AMR news and developments!

Keep me informed