Scientists have used artificial intelligence to identify a new antibiotic that could prove to be quite useful in fighting a deadly drug-resistant bacteria commonly found in hospitals and medical offices.
Researchers report they used an AI algorithm to predict molecules that would neutralize the drug-resistant bacteria Acinetobacter baumannii. Researchers discovered a potential antibiotic, named abaucin, “can effectively suppress” the growth of the stubborn bacteria on the skin of mice, according to a study this week in the journal Nature Chemical Biology.
While the preliminary results on the potential new drug would need to be validated in larger studies, researchers believe the process used to winnow thousands of potential drugs to identify one that may work is an approach that can work in drug discovery.
“There’s a lot of trepidation around AI, and I genuinely understand it,” said Jonathan Stokes, lead author of the paper and an assistant professor of biomedicine and biochemistry at McMaster University in Ontario, Canada. “When I think about AI in general, I think of these models as things that are just going to help us do the thing we’re going to do better.”
Stokes teamed up with researchers from the Broad Institute of MIT and Harvard to screen for potential antibiotics to use on A. baumannii, a superbug that can cause infections in the blood, urinary tract, and lungs. This bacteria usually invade hospitals and healthcare settings, infecting vulnerable patients on breathing machines, in intensive care units, and undergoing operations.
The bug is one of many so-called “drug-resistant” bacteria. It had infected 8,500 in hospitals and killed 700 in 2017, according to the Centers for Disease Control and Prevention.
How Did the Researchers Use AI to Pinpoint A Particular Antibiotic?
In order to specifically target the deadly drug-resistant strain, the researchers evaluated 7,684 drugs and the active ingredients of drugs to find out which ones would be most effective against the bacteria which was grown in the lab.
Stokes said the lab team developed AI models to predict which ones would have the highest likelihood of antimicrobial activity, narrowing the field to 240 drugs or active ingredients. Researchers then narrowed the field again through testing before discovering a molecule RS102895, renamed abaucin, that appeared to be potent against the superbug.
Researchers said they could screen a much larger volume of potential drugs by using the predictive power of AI and machine-learning techniques. The study said while existing high-throughput screening can evaluate a few million drugs or chemical ingredients at once, algorithms developed from machine learning can assess “hundreds of millions to billions” of drug molecules.
Citadel and AI for Drug Discovery
Just as Stokes and his team used AI to find novel molecular formulas for the development of a new antibiotic specifically for combating a particular strain of deadly bacteria, Citadel Discovery was launched in 2021 with the purpose of giving a kind of “open access” to the data and technology that will drive the future of pharma research streamlining and lowering the costs of drug discovery and biological research.
The costs of drug discovery continue to rise, with current estimates exceeding $2 Billion. Not to mention that bringing a drug successfully through all clinical trial phases takes, on average, 10-12 years in research and development. Artificial intelligence and machine learning in drug discovery hold the key to reducing these costs and timelines.
You can read much more about how AI is redefining drug discovery in my new book Quantum Care: A Deep Dive into AI for Health Delivery and Research. It’s a comprehensive look at how AI and machine learning are being used to improve healthcare delivery at every touchpoint, with a particular emphasis on drug discovery and Pharma research.
Rohit Mahajan is the President and Co-Founder of Citadel Discovery. He has particular expertise in the development and design of innovative solutions for clients in Healthcare, Financial Services, Retail, Automotive, Manufacturing, and other industry segments.
Citadel Discovery is dedicated to leveraging AI and MI for the purpose of democratizing access to the data and technology that will drive the future of biological exploration, drug discovery, and health technologies. If you would like to benefit from our expertise in these areas or if you have further questions on the content of this article, please do not hesitate to contact us.
