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KVAL: Rapid-Diag: Decision-making tool for rapid diagnostics of infection and antibiotic resistance


In the NFR funded AMR-Diag(project nr. 273609), Associate professor Rafi Ahmad proposed a novel and rapid new method to detect antimicrobial resistance (AMR) in patient samples. Today detection tests for AMR are routinely performed in microbiology labs by culturing (growing the microorganism) all over the country and the rest of the world. By culturing bacteria in the presence of antibiotics, you can determine which antibiotics they respond to, but it is a timely process (total time 3 – 4 days, up to a week)). In the AMR-Diag project, the use of rapid DNA extraction and sequencing in combination with bioinformatics and machine learning (ML) showed that the time from sample to answer can be readily decreased (> 18 hours) by this new method. The advantage of this is that the health care professional will have fast answers to the questions of what is the causative pathogen, which resistance genes are present in the sample, predict the phenotype, and thereby be helped in his/her decision on what antibiotic treatment to prescribe. This will, in turn, lead to the reduced and correct use of antibiotics, potentially save time and costs and most importantly, save lives. It will also contribute to preventing antibiotic resistance to increase a severe and life-threatening development that globally is out of control. This project will demonstrate the principles and methods from the AMR-Diag project in a proof of concept (PoC) study. This will include demonstrating the path from patient sample to sequence result and bioinformatic/ML interpretation. It will also include an alpha-version of such a software component. We propose to call this Rapid-Dig: Decision-making tool for rapid diagnostics of infection and antibiotic resistance. In the second part of the project, we will develop a business plan and demonstrate the concept to the health care decision-makers in Norway and microbiology labs (users), starting with Helse Sør-Øst. Klosser Innovation and INN are the project partners.

Project leader: Rafi Ahmad

Started: 2021

Ends: 2021

Category: Statlige høyskoler

Sector: UoH-sektor

Budget: 5e+05


Address: Elverum