Online Reporter
LONDON. – Artificial intelligence is inventing new drugs against Parkinson’s disease, antibiotic-resistant super bugs and many rare diseases.
It’s progress that many scientists never dreamed possible.
For around half a century, humanity has been slowly losing its battle against bacteria.
The most powerful weapons we have in this fight, antibiotics, are increasingly ineffective as drug resistance spreads.
Around 1.1 million people now die every year from infections that were until recently easily treated.
And the death toll is expected to rise to more than eight million by 2050 unless urgent action is taken.
Developing new antibiotics is a frustratingly slow and expensive process.
Between 2017 and 2022, just 12 new antibiotics were approved for use, the majority of which were similar to existing drug-types that bacteria are already developing resistance to.
The field has been chronically neglected due to a lack of interest from drug companies and underfunding.
But now researchers are looking to close the gap – and some are betting on artificial intelligence to help them do it.
“We can – in a matter of days or hours – look at massive libraries” of chemical compounds to identify those that display antibacterial activity, says James Collins, professor of medical engineering and science, at Massachusetts Institute of Technology in Cambridge, US.
“With the help of AI, Collins and his team have already discovered two new compounds that could prove vital weapons against the highly drug-resistant infections gonorrhoea and MRSA.
It is just one example of how AI is opening up a new era of drug discovery – promising progress on some of the most intractable medical problems of our time. Scientists are now pointing AI at conditions with no known cure such as Parkinson’s Disease, and thousands of rare diseases, in the hope of new breakthroughs.
Collins and his team trained a generative AI model to recognise the chemical structures of known antibiotics. This allowed the algorithm to learn what it takes to kill bacteria.
The researchers then used the AI to screen more than 45 million different chemical structures for their ability to target Neisseria gonorrhoeae, the bacteria that cause gonorrhoea, and Staphylococcus aureus, a significant source of infections in the form of MRSA. – BBC
Mathew Masinge