Hope for new antibiotics using artificial intelligence

By Katie Reeves
Sub-edited by Jasmine Wing

The danger of antibiotic resistance is recognised by the World Health Organisation as one of the biggest overall threats to global health that we currently face. However, there is finally some promising news, and it’s all down to the incredible power of artificial intelligence.

Although antibiotic resistance is a process which occurs naturally, the overuse and misuse of antibiotics have rapidly accelerated this process. There have been many efforts to clamp down on prescriptions of antibiotics and to educate people on when they are not necessary, however, the impact of this has not been anywhere near considerable enough to reduce the impending threat to our future.

The rise of the superbug appears to be inevitable until some enormous changes are made in society. In essence, if not enough new antibiotics are created in time to cope with the copious amounts of newly-resistant bacteria, what were once simple infections could once again become life-threatening. Routine operations will become incredibly dangerous. And the world risks heading back to a time before antibiotics when many illnesses were completely untreatable.

Luckily, a step in the right direction has come in the form of a team of researchers who have successfully managed to create a powerful new antibiotic compound using a machine-learning algorithm, or A.I. The system has been designed to identify antibiotics that use different mechanisms to kill bacteria than our existing antibiotics. This machine is able to screen an impressive one hundred million chemical compounds in just days. One of these compounds has been found to kill some of the most dangerous known bacteria including strains that are resistant to all known antibiotics. Researchers also have hope that this method will help to uncover many more potentially useful compounds that can help in the fight against antibiotic resistance in the years to come.

Find out more detailed information about this discovery at: Cell

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