Machine-learning algorithms may help pharmaceutical companies identify old drugs that can be rehashed to treat the COVID-19 coronavirus in elderly patients, according to a study published in Nature Communications.
More than two million people worldwide have been killed by the human malware, and more than 100 million have caught the bio-nasty, according to official statistics. As governments race to vaccinate billions of people to stop the spread of the SARS-CoV-2 coronavirus, a group of researchers from MIT, Harvard University, and ETH Zurich are looking to old-fashioned medicines to treat infected patients.
Want to let an AI-powered doctor loose on patients? Try slapping a food-label-like sticker on it, says Uncle Sam
“Making new drugs takes forever,” said Caroline Uhler, lead author of the paper, and an assistant professor focused on computer science and biology at MIT. “Really, the only expedient option is to repurpose existing drugs.”
Here’s where AI systems come in handy. Searching through large databases of available drugs and inspecting their pharmacological effects to identify those that could treat a COVID-19 infection is no easy feat. Massive amounts of data have to be carefully analysed to home in on the right drug candidates that will effectively treat COVID-19.
The researchers decided to focus on the fact that older people tend to suffer most from the virus because their lung tissue becomes stiffer with age. They built software that walked back from proteins and genes linked to both aging and coronavirus infections to their genetic root cause, and then searched for available drugs that tackle the effects of those genes. The idea being that those drugs should also lessen the blow of the virus, and help a patient recover.
Here’s how MIT described the team’s work:
“By intersecting the resulting combined SARS-CoV-2 and aging interactome with the targets of the top-ranked FDA-approved drugs from the previous analysis, we identify serine/threonine and tyrosine kinases as potential drug targets for therapeutic interventions,” the group’s paper stated.
All of this led to the scientists homing in on RIPK1, a protein that has been linked to cell death. It’s hoped that drugs can alleviate the effects of COVID-19 by altering the function of RIPK1. Choosing compounds that affect the enzymes involved in the function of the protein could prevent symptoms like inflammation.
Uhler said the team plans to share their results with pharmaceutical companies, and won’t know how effective their predictive model is until elderly patients are enrolled in real clinical trials. “Rigorous in vitro experiments as well as clinical trials are needed to validate the identified candidate drugs,” their paper added. ®
Source: https://go.theregister.com/feed/www.theregister.com/2021/02/17/ai_algos_covid/
