Drug discovery

Cofounded by postdoctoral associate Wen Shuhao and postdoctoral fellows Ma Jian and Lai Lipeng, biotech startup Xtalpi "combines AI, quantum physics, cloud computing and robotic automation to find novel molecules that could be developed into new medicines,” reports Zinnia Lee for Forbes. “Xtalpi has also recently expanded into discovering new chemical compounds for applications such as agriculture, cosmetics, healthcare, as well as petrochemicals and new materials for electric vehicle batteries,” writes Lee.

Prof. Regina Barzilay joins The Economist’s “Babbage” podcast to discuss how artificial intelligence could enable health care providers to understand and treat diseases in new ways. Host Alok Jha notes that Barzilay is determined to “overcome those challenges that are standing in the way of getting AI models to become useful in health care.” Barzilay explains: “I think we really need to change our mindset and think how we can solve the many problems for which human experts were unable to find a way forward.”  

In a new paper, MIT researchers detail how they have used AI techniques to discover a class of “of antibiotics capable of killing methicillin-resistant Staphylococcus aureus (MRSA),” reports Helen Floresh for Fierce Biotech. “This paper announces the first AI-driven discovery of a new class of small molecule antibiotics capable of addressing antibiotic resistance, and one of the few to have been discovered overall in the past 60 years,” says postdoctoral fellow Felix Wong.

Researchers at MIT have used artificial intelligence to uncover, “a new class of antibiotics that can treat infections caused by drug-resistant bacteria,” reports Jeremy Hsu for New Scientist. “Our [AI] models tell us not only which compounds have selective antibiotic activity, but also why, in terms of their chemical structure,” says postdoctoral fellow Felix Wong.

Postdoctoral associate Wen Shuhao and postdoctoral fellows Ma Jian and Lai Lipeng co-founded Xtalpi, a biotech startup that uses “artificial intelligence to find chemical compounds that could be developed into new drugs,” reports Zinnia Lee for Forbes. “By combining AI, quantum physics, cloud computing and robotic automation, Xtalpi said it helps increase the efficiency and success rate of identifying novel drug compounds,” writes Lee. “The company has recently expanded into discovering new chemical compounds for agricultural technology, cosmetics and other applications.”

Researchers at MIT and elsewhere have used artificial intelligence to develop a new antibiotic to combat Acinetobacter baumannii, a challenging bacteria known to become resistant to antibiotics, reports Hannah Kuchler for the Financial Times. “It took just an hour and a half — a long lunch — for the AI to serve up a potential new antibiotic, an offering to a world contending with the rise of so-called superbugs: bacteria, viruses, fungi and parasites that have mutated and no longer respond to the drugs we have available,” writes Kuchler.

Researchers from MIT and McMaster University have used artificial intelligence to identify a new antibiotic that can fight against a drug-resistant bacteria commonly found in hospitals and medical offices, reports Ken Alltucker for USA Today. The researchers believe the AI “process used to winnow thousands of potential drugs to identify one that may work is an approach that can work in drug discovery,” writes Alltucker.

Researchers from MIT and elsewhere have used artificial intelligence to develop a new antibiotic to address Acinetobacter baumannii, a bacteria known for infecting wounds, lungs and kidneys, reports Harland-Dunaway for The World.

Using a machine-learning algorithm, researchers from MIT and McMaster University have discovered a new type of antibiotic that works against a type of drug-resistant bacteria, reports Brenda Goodman for CNN. Goodman notes that the compound “worked in a way that stymied only the problem pathogen. It didn’t seem to kill the many other species of beneficial bacteria that live in the gut or on the skin, making it a rare narrowly targeted agent.”

Researchers from MIT and McMaster University used a machine-learning algorithm to identify a new antibiotic that can treat a bacteria that causes deadly infections, reports Maya Yang for The Guardian. The researchers used an “AI algorithm to screen thousands of antibacterial molecules in an attempt to predict new structural classes. As a result of the AI screening, researchers were able to identify a new antibacterial compound which they named abaucin,” writes Yang.

Researchers from MIT and Harvard Medical School are investigating how exercise and high-fat diets can alter cells, genes and cellular pathways, reports Abby Patkin for Boston.com. “Their research could eventually help develop drugs that would mimic the effects of exercise and combat obesity,” explains Patkin.

Researchers from MIT and Harvard Medical School have conducted a study to see how exercise and high-fat diets can impact cells, reports WCVB. The researchers “say the data could eventually be used to develop drugs that could help enhance or mimic the benefits of exercise,” writes WCVB.

A new study by researchers from MIT and Harvard Medical School has helped identify the impact of exercise and high-fat diets on cells, reports Darren Botelho for NBC Boston 10. “Years from now, those researchers say the data could lead to a pill that would help not only with weight loss, but with the overall effect from exercise – a better wellbeing,” explains Botelho.

Prof. Manolis Kellis speaks with Boston 25 about his team’s work exploring the underlying mechanisms exploring how exercise influences weight loss, findings that could offer potential targets for drugs that could help to enhance or mimic the benefits of exercise. “Such an intervention would be a complete game changer and the reason for that is that the obesity epidemic has led to the U.S. having a decreased life span compared to all other developed countries,” says Kellis.

Scientists from MIT, Georgia Institute of Technology, Sun Yat-sen University and Beijing-based AI startup Galixir have developed a deep-learning toolkit that can predict biosynthetic pathways for natural products, which are a primary source of clinical drug discovery, reports Xinhua Net. “The researchers presented a toolkit called Bionavi-NP to propose NP biosynthetic pathways from simple building blocks in an oprtimal fashion, which requires no already-known biochemical rules,” writes Xinhua Net.