A groundbreaking AI algorithm was used to discover a new antibiotic that can kill drug-resistant bacteria called superbugs.
The rising prevalence of deadly drug-resistant bacteria is one of the greatest dangers to human health. Many kinds of bacteria that cause infections today are resistant to some drugs. For example, penicillin isn’t used as often today because many strains of bacteria have developed a resistance to it.
Some bacterial species, like Acinetobacter baumannii, are resistant to whole hosts of antibiotics, making them incredibly dangerous and difficult to treat. Acinobacter can cause life-threatening complications including meningitis and pneumonia if treatments don’t take effect.
Researchers at MIT and McMaster University discovered a drug that kills Acinetobacter using a carefully trained AI algorithm. They named the drug abaucin in their paper published in the journal Nature Chemical Biology Thursday.
Why Is This Superbug-Fighting AI Antibiotic Algorithm So Important?
This could be an extraordinarily important find for a multitude of reasons. Firstly, Acinetobacter is a particularly difficult bacteria to kill. This is because it can survive on hard surfaces, like on the doorknobs of hospitals, for a long time.
While it sits there, it can pick up genes from its environment via a process called transformation. Some of these genes give it increased protection against antibiotics. This becomes a major problem when Acinetobacter bacterium with one of these genes infects a human.
When antibiotics are used to try to treat the infection, bacteria with resistance to the drug will be the only ones to thrive, reproduce and potentially spread. The abuse, misuse (and sometimes the correct use) of the antibiotic could also boost the resistance of the bacteria even further as those with the greatest resistance will perform and reproduce the best.
Jonathan Stokes, an author of the paper, called Acinetobacter “public enemy No. 1 for multidrug-resistant bacterial infections.”
Scientists and healthcare professionals are extremely worried that these bacteria will continue to build resistance against all of our effective antibiotics until there is nothing left to treat the infections. Drug-resistant bacteria is already a leading cause of death worldwide, killing more than 1 million people a year.
The news that the AI algorithm used in the MIT and McMaster’s lab was a success constituted terrific news to everyone working in the field of antibiotics. Many experts hope that abaucin will only be the first landmark antibiotic discovered with this method and that it will change the biotech world forever.
The current drug discovery process has been a pitiful failure in finding new antibiotics and classes of antibiotics in particular. Only 1 or 2 new classes of antibiotics have been found and approved in the last 35 years, while bacteria have been building resistance against our old antibiotics.
How Does The Superbug-Fighting Antibiotic AI Algorithm Work?
It’s important to keep expectations low, even with the advancements in AI. The new AI-assisted method is not altogether different from the current drug discovery technique called high-throughput screening.
High-throughput screening is a simple process where researchers synthesize an inordinate amount of chemicals that could potentially be effective treatments of some sort.
Slightly modified versions of current drugs (or molecules already known to be effective) are often the main focus of these tests, which makes it difficult to discover entirely new drug classes.
The main benefit of the AI algorithm is increased efficiency. Instead of looking through the data by hand to choose the best candidates to test further, machine learning can help the researchers pick the most promising candidates faster and more accurately.
Similar algorithms, trained with information on how large numbers of molecules interact with bacteria, could also be helpful in suggesting which molecules to test in the first place. The current applications of AI in drug development today are likely only the beginning.
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