Researchers from the Massachusetts Institute of Technology (MIT) have used artificial intelligence (AI) to design two new antibiotics effective against antibiotic-resistant bacteria, or “superbugs”.
This is a potentially exciting development, but it’s important to note there are several hurdles to overcome before we might see these antibiotics used in the real world. And if this eventuates, it’s likely to be some years away.
Frequent overuse of antibiotics in medicine and agriculture has led to the evolution of new strains of bacteria resistant to an increasing range of antibiotics. This global public health crisis makes the development of new antibiotics a significant challenge.
Antibiotic-resistant superbugs contribute to around 5 million deaths worldwide annually, and directly cause more than 1.2 million deaths.
It’s estimated superbug infections could lead to more than A$2.5 trillion in lost economic output globally by 2050.
Antibiotic resistance is also increasingly a problem of inequity, with many poorer countries unable to access newer antibiotics to overcome resistant bacteria.
The researchers used AI to design antibiotics against two prominent superbugs: Neisseria gonorrhoeae and methicillin-resistant Staphylococcus aureus (MRSA).
N. gonorrhoeae causes the sexually transmitted disease gonorrhoea, which has developed high levels of resistance to antibiotics in recent years. The inability to treat it effectively has contributed to a rapid spread of the disease. There were more than 82 million new cases in 2020, mostly in developing nations.
MRSA is a resistant strain of the bacteria Staphylococcus aureus (often referred to as “golden staph”). S. aureus can cause skin infections or serious blood and organ infections. Patients who get sick with the resistant MRSA strain are estimated to be 64% more likely to die as a result of an infection.
To address these challenges, the MIT team harnessed generative AI in two ways.
