AI-assisted development of new antibiotic to tackle Acinetobacter baumannii infections
Acinetobacter baumannii is a pesky bacterium that causes infections in wounds, lungs, and kidneys, and is notoriously difficult to treat because it can stick around on surfaces for long periods and has a high fatality rate if left unchecked. However, researchers at McMaster University in Canada used artificial intelligence (AI) to develop a new antibiotic that could help tackle these infections. In an interview with the World’s host Marco Werman, Jonathan Stokes and Gary Liu from McMaster University shared insights into their research.
The problem with Acinetobacter baumannii
Acinetobacter baumannii is a bacterium that is commonly found in soil and water, but it can also colonize human skin, making it easy to transmit in hospitals and healthcare facilities. The bacterium can cause a range of infections, including pneumonia, bloodstream infections, and wound infections. What makes it particularly challenging to treat is that it is resistant to many antibiotics, making it a top priority for researchers to develop new treatments.
How AI helped develop a new antibiotic
Stokes and Liu’s research involved using AI to help identify new compounds that could be effective against Acinetobacter baumannii. They used a machine learning algorithm that analyzed more than 6,000 compounds to identify those that could be active against the bacterium. The algorithm was trained on data from previous studies to predict which compounds were likely to be effective.
Once the algorithm identified promising compounds, Stokes and Liu conducted laboratory experiments to test their efficacy. They found that one compound, named halicin, was particularly effective against Acinetobacter baumannii. Halicin was originally developed to treat diabetes, but the researchers discovered that it could also be effective against bacterial infections.
The promise of halicin
Halicin has several advantages over traditional antibiotics. First, it can kill a wide range of bacteria, including those that are resistant to traditional antibiotics. Second, it works by disrupting the bacterial membrane, making it less likely that bacteria will develop resistance to it. Finally, it is relatively easy to synthesize, meaning that it could be produced at scale and made widely available.
The researchers also found that halicin was effective in treating infections in mice, suggesting that it could be effective in humans as well. However, more research is needed to determine the safety and efficacy of halicin in humans, and it may take several years before it is widely available.
Acinetobacter baumannii is a significant challenge for healthcare professionals, and the development of new treatments is essential to combat its spread. The use of AI in drug discovery is a promising approach that could help identify new compounds that could be effective against this bacterium. The development of halicin is an exciting development in the fight against Acinetobacter baumannii, and further research is needed to determine its potential as a treatment option.
- AI in medicine
- Bacterial infections treatment
- Machine learning and healthcare
- AI-assisted diagnosis
- Antibiotic resistance and AI
News Source : The World from PRX
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