We have developed a new test to help patients get the most effective antibiotic more quickly, reducing the overuse of unnecessary and ineffective antibiotics.

Key facts

• Antimicrobial resistance (AMR) is one of the greatest threats to public health worldwide. As a result, a growing number of infections cannot be treated with standard antibiotics.

• Reducing unnecessary antibiotic use is essential to slow the rise in AMR.

• We have developed a laser-based technology known as Multi-Excitation Raman Spectroscopy (MX-Raman) to identify which antibiotics would be most effective.

A global concern

It is estimated that AMR will lead to over ten million deaths per year by 2050. It is a massive global concern.

It happens when bacteria develop defences so antibiotics can no longer kill them and it spreads faster when antibiotics are used unnecessarily or when they don't work properly.

To find out which antibiotic should be used to treat a patient’s bacterial infection, doctors send a sample to a microbiology laboratory to be tested. Bacteria are grown on a petri dish to review how effectively antibiotics kill the bacteria. This can take up to two days. 

While they wait for the results, doctors often prescribe antibiotics to prevent a patient’s infection from getting worse, but sometimes it doesn’t work.

This unnecessary use of antibiotics and the delay in getting test results contributes to AMR.

Innovative testing

We are using lasers to measure tiny vibrations within the different molecules of patient samples and bacteria. Computational analysis then helps to analyse each bacterial sample to accurately identify which samples contained antibiotic-resistant bacteria and which antibiotics would be most effective at treating the infection.

The technique called MX-Raman, will be able to analyse the composition of a single drop of a bodily fluid and potentially cut delays to treatment from days to minutes.

Early results

The team, which includes Professor Sumeet Mahajan, Professor Jeremy Webb and Dr Callum Highmore, is excited by the test’s early performance.

They have been able to identify AMR in samples of new pathogens. This suggests we will be able to detect different AMR in bacteria we’ve not seen before and develop a rapid screening system. 

From lab to ward

We have patented the technique, the first step on the journey to it being fully established and commercialised.  

MX-Raman has the potential to make culture-based testing faster, quickly identifying the most effective antibiotic for each patient, speeding up treatment and freeing up hospital beds currently taken up while staff wait for results.

Because it can integrate with AI models, it's also able to adapt as new resistant bacteria and pathogens emerge, helping it keep up with a constantly changing threat, rather than being left behind.

By identifying the right antibiotic faster, MX-Raman could significantly cut the unnecessary and ineffective antibiotic use that drives AMR in the first place.