Antimicrobial resistance is a growing threat to the health and safety of the world’s population. The World Health Organisation recognizes faster, more accurate laboratory detection of antimicrobial resistance as a key contributor to protecting the efficacy of our dwindling stock of antibiotics. However, useful mechanism-based methods of resistance detection are for surveillance, they do not provide the guidance physicians need to make confident decisions about antibiotic choice at the point of care. The currently used susceptibility testing methods take too long, and in some cases are poor predictors of treatment efficacy. Clearly, new methods are needed that combine speed and accuracy. This is where FAST comes in. The combination of speed, accuracy and broad drug/bug combination applicability makes the FAST method an attractive solution to the susceptibility testing capability gap. We recently demonstrated same-day susceptibility results by combining the FAST method with machine learning-based data analysis. In this webinar we introduce the FAST method, demonstrate its breadth of application and show how the data can be analysed with currently available open source software.

 

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