Antibiotic resistance: how AI can tackle the superbug threat
As with other classes of drug, AI is helping scientists to discover novel antibiotics more quickly and accurately than traditional methods have allowed in the past.
Ordinarily, to identify even one promising antibiotic candidate, hundreds of possible molecules must be screened – and without technology to automate the process, it’s a hugely time-consuming task. The ability to computationally predict the properties and activity of new molecules with AI, however, can save researchers time, money and resources that would otherwise be wasted on testing compounds that prove to have little or no value.
In February last year, scientists at Massachusetts Institute of Technology (MIT) discovered a powerful new antibiotic compound using deep-learning methods. The AI model used is designed to identify compounds that kill bacteria using different mechanisms to those of existing antibiotics, and is capable of screening over a hundred million candidates in mere days.
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