Can AI powered diagnostics revolutionize antimicrobial stewardship? Machine learning based prediction of antimicrobial resistance (AMR) in short and long read sequencing data

Antimicrobial resistance (AMR) has emerged as one of the principal public health problems of the 21st century. It threatens the effective prevention and treatment of an ever-increasing range of infections caused by bacteria no longer susceptible to the common medicines used to treat them.

 

The World Health Organization (WHO) has identified pathogen whole genome sequencing as a promising solution for the surveillance of bacterial outbreaks and the spread of AMR. Recent advancements in microbial genomics have indeed progressed our ability to detect pathogens but the detection and interpretation of AMR in an actionable way remains challenging. In this webinar, Dr. Arne Materna will share how Ares Genetics uses machine learning and validated laboratory workflows to bridge the limitations of microbial genomic sequencing to enable actionable infectious diseases testing and surveillance.

 

Learning Objectives