Last year, when Italy was under siege by COVID-19, scientists from Exscalate4Cov, a public-private consortium of 18 institutions across Europe led by Italian pharmaceutical company Dompé farmaceutici, had just started the hunt for find a cure for COVID-19. Eight scientists, all from across Europe, gathered in a virtual room to discuss potential molecules. Each scientist held up a 3D render of a molecule they simulated and walked through it with the others. Inside that space, scientists could together scour these molecules, separate them, enlarge them, and link them to possible compounds. They asked each other questions and, on a virtual whiteboard, outlined the possibilities for success and failure in each complex. This virtual framework also allowed them to compare molecules side by side.
Armed with $ 3 million in funding from the European Union, the group collected treatment suggestions and analyzed those suggestions using supercomputers. In October, they submitted their first candidate for a Phase III clinical trial in Europe: a generic osteoporosis drug called Raloxifene.
The trial is now over. “We are awaiting the final results, but we are very confident about the possible success of the clinical trial,” says Andrea Beccari, scientific manager at Exscalate and head of research and development platforms at Dompé farmaceutici. The result will not only determine whether raloxifene will work against COVID-19, but it could also inform the design of new drugs.
To create a new drug, scientists first look at how a disease enters human cells, and then devise a mechanism to interfere with that infection. Traditionally, they’ve done it on paper, sketching out proteins and simulating how a molecule or compound might bind to them. Current software often does not provide enough visual landscape for scientists to understand the full extent of the relationship between molecules, especially those with multiple bonding sides. That’s why Exscalate worked with a company called Nanome, which hopes to accelerate drug development by providing scientists with a way to visualize molecules in three-dimensional space on an Oculus headset.
Beccari said that using supercomputers, the group took a list of 400,000 potential molecules and simulated their ability to cling to proteins of the COVID-19 virus. In addition to analyzing them via computers, they also used virtual reality to better understand how these compounds might bind to COVID-19 viral proteins and how they would work in humans. What was important to predict was whether a drug would be able to reach the lungs.
“For example, Remdesivir, which is a very good antiviral molecule, has very little effect on humans simply because it does not reach the lungs in sufficient concentration,” explains Beccari. But in their machine-learning-based analysis, they found a family of molecules capable of inhibiting the virus and reaching the lungs, he says. The first of these molecules is raloxifene.
“Computers always generate solutions,” Beccari says. “But all of these simulations aren’t good just because the computer says so.”
Beccari says the platform gives scientists a lot more information than they can easily glean from a two-dimensional format. This ultimately speeds up their ability to sift through molecules their supercomputers suggest as plausible candidates. In the future, he would like to see 3D platforms like Nanome integrate with other platforms and tools. For example, his organization created an ultra-fast algorithm to understand the docking of molecules. It would be great, he says, to do both their IT work and their collaborative work in one space.
Going forward, the group will work on designing drugs similar to raloxifene that enhance its current capabilities against COVID-19. In this context, says Becarri, collaboration between scientists will be particularly essential. “In the age of artificial intelligence, we think people still rule,” he says.