The drugs were identified in a paper published in the journal Nature Communications on Monday by researchers from the Massachusetts Institute of Technology, Harvard University and ETH Zurich in Switzerland.
The researchers said they plan to share their findings with pharmaceutical companies, but added that before any drugs can be replaced for use in elderly COVID-19 patients, clinical trials will be needed.
Caroline Uhler, a calculated biologyian at MIT’s Department of Electrical Engineering and Computer Science, explained that her team’s research on recycling existing drugs began as soon as the coronavirus began spreading early last year.
“The creation of new drugs will be permanently lost,” she said in a statement. Indeed, the only reasonable option is to reuse existing drugs.”
The value of re-positioning
As it turned out, vaccines began to appear faster than Uhler’s team identified drugs that were reusable, but that did not diminish the value of their research.
Uhler explained to TechNewsWorld that while data from many COVID-19 vaccines is encouraging because it has shown vaccines that protect against serious disease results, such as hospitalizations and deaths, it’s unclear how the vaccine will reduce less severe results, as well as long-term symptoms.
“In addition, vaccines are still scarce and expensive and, therefore, unfortunately it will take some time until the vaccine is available in all parts of the world,” she said. For these reasons, the discovery of drugs against COVID-19 remains critical despite the pace of vaccine development.”
When the pandemic broke out, researchers had good reason to believe that vaccine development could go “forever.” “Typically, vaccine trials take a minimum of four years, so this is an unusually fast event,” said Dr. William Greenough, a professor of medicine at John Hopkins University in Baltimore.
“In the past, re-positioning drugs could have been done faster than developing a vaccine, but that’s not true at this point,” he told TechNewsWorld.
Replacing drugs has the advantage of creating them from scratch. “One of the most important advantages is that they have been approved for human use,” said Dr. John Quackenbush, professor of computing biology and bio-news, and chair of the department of bio-statistics at Harvard T.H. University. Chan School of Public Health.
“They have passed basic safety tests and although they have not been tested for effectiveness for a particular target, we know that with the dosages they are currently prescribed, they will have no significant side effects or if there are side effects , we know what they are,” he told TechNewsWorld.
In addition, while the vaccine can protect people from getting COVID-19, a/k/a SARS-CoV-2, there are still millions of people with the disease who need treatment and can benefit from alternative medicines.
“There are so many people with COVID that we want to do something for them,” explains Elmer Bernstam, associate dean of research at UTHealth School of Biomedistry In Houston.
“At the moment, the treatments that we have are quite limited,” he told TechNewsWorld. If we already have the drug available, it is a much shorter path that leads to something more useful than creating a new drug or getting a new compound in the process.”
Aging leads to stiff lungs
To identify potential alternative candidates, the researchers turned to machine learning to identify changes in gene expression in lung cells caused by both disease and aging.
With the machine learning system, a specific protein, RIPK1, was identified as a promising target for a reusable drug by the research team, including Dr. MIT. students Anastasiya Belyaeva, Adityanarayanan Radhakrishnan, Chandler Squires, and Karren Dai Yang, as well as Ph.D. students Louis Cammarata of Harvard University and G.V. Shivashankar, professor of mechanical-genoology at the faculty of health sciences and technology at ETH Zurich in Switzerland.
The team also identified three drugs on the market that acted based on ripk1’s expression.
At the start of the study, the team focused on patients with the elderly coronavirus, as they were in more danger from the virus than other age groups. One of the common opinions about why the virus has such a devastating effect on older patients is that their immune system is not as strong as young people.
But Uhler and Shivashankar point to another difference. As people age, their lungs become stiffer.
“Previous research by Shivashankar lab has explained that if you stimulate cells on a harder substrate with cytokines, similar to what viruses do, they actually activate different genes,” Uhler explained. So that prompted this hypothesis. We need to look at aging along with SARS-CoV-2 – what are the genes at the intersection of these two paths?”
“Instead of looking at all 25,000 genes in the human genome, they were really smart in reducing search space,” Quackenbush said.
Big data tools
Even if the search space is reduced, researchers still need big data tools to solve their problems. Through autoencoder – a kind of artificial nerve network – a large list of drug candidates was created. To do that, the encodeer used two data sets – one showing how expression in different cell types reacts to a range of drugs already on the market, and the other shows how to react to SARS-CoV-2 infection. By comparing two data tanks, it is possible to identify drugs that are promising candidates for clinical trials.
Uhler explains that, in its standard form, an autoencoder consists of two neural networks – one that mapped data into lower dimensional space and one that mapped the data back to its original space. Neural networks are trained to minimize rebuild errors and, therefore, lower dimensional expressions are optimized to retain all important data features.
“The new feature of our approach is to use an underlying space that is higher than the original space,” she told TechNewsWorld. “In fact, we have in point that the use of such higher-height underlying space leads to a better generalization of the effects of a drug on different types of cells.”
She added that the theoretical insight into the functional class learned by autoencoders, which are crucial to the group’s drug discovery process, could have wide-scale implications. For example, the team is currently pursuing applications related to image recovery and paint printing.
That initial list was diminished by interactive map of proteins involved in the aging process and sars-CoV-2 infection paths. By overlapping the maps, researchers were able to identify the exact network of gene expression that a drug needs to fight COVID-19 in elderly patients.
With that information, researchers eventually identified RIPK1 as the target of drugs that can be used to treat COVID-19 and identify existing drugs that work on genes/proteins to have the potential to treat viruses. These drugs have previously been approved for cancer treatment.
Other drugs identified by researchers include ribavirin and quinapril, which have been clinically tested for COVID-19.
Although this study targets coronavirus, it can be used to fight other diseases. “It’s an important goal in our work to develop a platform that can be widely applied and has the potential to help fight future diseases,” Uhler told TechNewsWorld. “Therefore, our platform uses only the data available for a variety of diseases and can be quickly obtained to fight future diseases.”