Pasteur AI: when artificial intelligence learns to ‘read’ bacteria to fight antibiotic resistance

Very promising results, even at very low doses

The results are particularly encouraging. Indeed, artificial intelligence recognises an antibiotic’s mode of action with near-perfect accuracy. Better still, it detects the effect of a molecule at sub-inhibitory concentrations – that is, even before the bacteria stop multiplying. This capability is a major asset for identifying candidates that conventional tests would have ruled out.

Even more surprising is that the model is capable of indicating when a molecule acts in an unprecedented way. This ability could prove decisive in discovering new classes of antibiotics – the very ones most needed to overcome current resistance.

The approach has also been validated on another bacterium, Klebsiella pneumoniae, which causes serious infections and is often multi-drug resistant. This provides initial evidence that the method could be applied to other microorganisms.