Doctors believe Artificial Intelligence is now saving lives, after a major advancement in breast cancer screenings. A.I. is detecting early signs of the disease, in some cases years before doctors would find the cancer on a traditional scan. Scientists have found a drug that could combat drug-resistant infections – and they did it using artificial intelligence. Using a machine-learning algorithm, researchers at the Massachusetts Institute of Technology (MIT) and Canada's McMaster University have identified a new antibiotic that can kill a type of bacteria responsible for many drug-resistant infections. The compound kills Acinetobacter baumannii, which is a species of bacteria often found in hospitals.

Scientists using artificial intelligence have discovered a new antibiotic that can kill a deadly superbug. According to a new study published on Thursday in the science journal Nature Chemical Biology, a group of scientists from McMaster University and the Massachusetts Institute of Technology have discovered a new antibiotic that can be used to kill a deadly hospital superbug. The superbug in question is Acinetobacter baumannii, which the World Health Organization has classified as a "critical" threat among its "priority pathogens" – a group of bacteria families that pose the "greatest threat" to human health. According to the WHO, the bacteria have built-in abilities to find new ways to resist treatment and can pass along genetic material that allows other bacteria to become drug-resistant as well. A baumannii poses a threat to hospitals, nursing homes and patients who require ventilators and blood catheters, as well as those who have open wounds from surgeries.

Since the discovery of penicillin in the late 1920s, antibiotics have "revolutionized medicine and saved millions of lives." Unfortunately, the effectiveness of antibiotics is now threatened by the increase of antibiotic-resistant bacteria globally. Antibiotic-resistant infections cause the deaths of up to 1.2 million people annually, making them one of the leading causes of death. There are several factors contributing to this crisis of resistance to antibiotics. These include overusing and misusing antibiotics in treatments.

Humans have been using antibiotics for about 100 years. For 30 years the competent authorities have been warning of the future problem of antibiotic resistance, since higher doses or different antibiotics are needed to end them. Pathogens, whether bacteria, fungi or protists, that have been traditionally stopped with antibiotics have naturally developed resistance to the drugs used against them. This is due to the process of constant evolution that occurs in nature, but health authorities point out that the misuse and abuse of antibiotics has helped this adaptation to take place much faster than expected. Health authorities suggest that by the end of the 21st century the current antibiotics will no longer be useful and that from 2050 we may already notice the lack of response from many of them. It is estimated that by then about 10 million people will die each year from resistant infections.

Imagine you're a scientist who needs to discover a new antibiotic to fight off a scary disease. How would you go about finding it? Typically, you'd have to test lots and lots of different molecules in the lab until you find one that has the necessary bacteria-killing properties. You might find some contenders that are good at killing the bacteria only to realize that you can't use them because they also prove toxic to humans. But what if, instead, you could just type into your computer the properties you're looking for and have your computer design the perfect molecule for you? That's the general approach IBM researchers are taking, using an AI system that can automatically generate the design of molecules for new antibiotics.

With the search for new antibiotics becoming increasingly urgent, artificial intelligence offers valuable help. Smart software developed by Leiden PhD candidate Alexander Kloosterman searched genomes of bacteria and found clusters of DNA that code for proteins that have an antibiotic effect. "This new search method is enormously promising." The discovery was published in PLoS Biology. Professor of Molecular Biotechnology Gilles van Wezel from the Leiden Institute of Biology (IBL) initiated the research together with visiting professor Marnix Medema.

Antibiotic resistance is no joke. We need new antibiotics, and we need them fast. In the US alone, nearly three million people¹ get infected with antibiotic-resistant bacteria or fungi every year¹. But very few new antibiotics are being developed to replace those that no longer work. That's because drug design is an extremely difficult and lengthy process -- there are more possible chemical combinations of a new molecule than there are atoms in the Universe.

RESEARCH TRIANGLE PARK – IBM scientists have utilized artificial intelligence to help speed up development of molecules for potential use in new "novel antibiotics" that are needed as the spread of antibiotic resistance grows and the need for new drugs increases. In a blog post and a paper published in Nature Biomedical Engineering, the IBM team said the system would help pace the way to "accelerated discovery." "[O]ur IBM Research team has developed an AI system that can help speed up the design of molecules for novel antibiotics. And it works," wrote Aleksandra Mojsilovic and Payel Das in the blog. Noting the rise of resistance to antibiotics, the two said the threat "is no joke. We need new antibiotics, and we need them fast."

Anewly designed artificial intelligence tool based on the structure of the brain has identified a molecule capable of wiping out a number of antibiotic-resistant strains of bacteria, according to a study published on February 20 in Cell. The molecule, halicin, which had previously been investigated as a potential treatment for diabetes, demonstrated activity against Mycobacterium tuberculosis, the causative agent of tuberculosis, and several other hard-to-treat microbes. The discovery comes at a time when novel antibiotics are becoming increasingly difficult to find, reports STAT, and when drug-resistant bacteria are a growing global threat. The Interagency Coordination Group (IACG) on Antimicrobial Resistance convened by United Nations a few years ago released a report in 2019 estimating that drug-resistant diseases could result in 10 million deaths per year by 2050. Despite the urgency in the search for new antibiotics, a lack of financial incentives has caused pharmaceutical companies to scale back their research, according to STAT. "I do think this platform will very directly reduce the cost involved in the discovery phase of antibiotic development," coauthor James Collins of MIT tells STAT.

In late February, a paper appeared in the journal Cell with encouraging news regarding one of the world's most persistent public health problems. Researchers at Massachusetts Institute of Technology and Harvard University had used artificial intelligence to identify a chemical compound with powerful antibiotic properties against some of the world's most drug-resistant strains of bacteria -- a welcome discovery in a world where 700,000 people die every year from drug-resistant infections. It was the first time an antibacterial compound had been identified this way. The researchers named it halicin, in honor of the computer HAL in the film 2001: Space Odyssey. While the global need for new antibiotics to treat drug-resistant infections is as pressing as it was at the start of the year, the world's attention has been diverted by the novel coronavirus pandemic, and the hunt for a vaccine that can halt Covid's spread.