Drug-resistant infections are a major public health threat around the world, responsible for more than a million deaths each year.

So scientists are constantly trying to find and develop new antibiotics.

Miles O'Brien reports on how researchers now say AI is helping to speed up their search.

This is the front line in a biological arms race to salvage the crumbling foundation of modern medicine, antibiotics.

They make surgery routine, protect cancer patients, and turn once deadly infections into minor inconveniences.

Let's take a look at gonorrhea first.

The discovery of penicillin changed everything, not least the treatment of sexually transmitted disease.

It is a great boom to the private physician, the clinics, and of course, to the patients.

But success comes with a fatal paradox.

The more we deploy this life-saving medicine, the less effective they are in the long term.

Melissa Anatar is a clinical microbiologist at Massachusetts General Hospital.

It's unlike any other drug where when we use antibiotics, we, by definition,

lose them because we're in this constant race with bacteria, where the bacteria can evolve

resistance to our antibiotics in real time. Bacteria developed resistance to antibiotics

through a simple process of evolution. In any infection, there are millions of bacteria,

and some have mutations that help them survive a drug. When antibiotics are used, they kill the

vulnerable bacteria, but the resistant ones survive, multiply, and spread. Over time, these resistant strains become dominant, making the

drugs less effective or even useless. There's kind of this never-ending war. These microorganisms

are just not going to quit. They do not quit. But neither does she or her colleagues here at the

Broad Institute of MIT and Harvard.

Historically, to find and test new antibiotics, researchers would gather up some molecules

stored in a deep frozen library of compounds and then apply them one by one to a pathogen

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