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Insilico Medicine, Arctoris announce technology partnership to discover new COVID-19 drugs

InSilico Medicine today announced a technology partnership with Arctoris Pharma to discover new therapeutics and meet regulatory hurdles to bring important new treatments to patients with blinding diseases of the eye. By working together, the two organizations can reduce clinical trial costs and expedite development of effective therapies for eye diseases.

We live in a world that has advanced at an accelerated pace since the emergence of large, complex systems: medical algorithms on computers are able to show us how the biological world functions. And in silico medicine advances are only one part of the picture. New therapies, from cells to drugs, are also made possible because of new computational tools.

Arctoris has developed the world’s first engine that can accelerate new drug discovery. I got to know the team at Arctoris while I was an editor at Thomson Reuters and was impressed by their ingenuity. The engine shows that more than ever we need visionary individuals to innovate what is possible. I know that I found it engaging. Now I know that InSilico Medicine will benefit from it.

Why does this matter? Well, for starters, we’re going to see more drugs discovered through new technologies. We’ve achieved big things in the last few years with this kind of thing, and they are of obvious use. I don’t know who the future of drug discovery is going to be, but because of Arctoris and InSilico Medicine, we can be reasonably confident that it will be driven by science and science alone.

What’s important is that such advances will lead to medicines that are quicker to develop and could be brought to patients more quickly than in the past. That means lower costs, which will improve access to important medicines for people. So, we’re going to see more effective therapies faster, and once they’re there they’ll be affordable.

And that’s very good news, indeed. In the U.S., a drug is going to be expensive if its development has to go through expensive clinical trials. Indeed, it usually does. Which is why, through its research programs, InSilico Medicine is really adding to the drive to solve the problem of high drug costs.

Again, to make things clearer, here’s how it works. Depending on the details, InSilico Medicine can find enzymes that are not required in the eye but which are very important to the functioning of cells in other tissues. It can then predict which of those enzymes the eye needs to solve a disease. Furthermore, InSilico Medicine can get inside the cells in the eye to study the processes at work, and also to probe the molecular interactions that have a role in disease.

How does this all add up? Well, InSilico Medicine and Arctoris have actually been working together for a while. For instance, Arctoris has invented new technologies in the field of cell profiling. Cell profiling provides a highly detailed look inside the body and, as a result, has a lot of applications for drug discovery. But even with this kind of technological advance, researchers were unable to identify the specific enzymes that are important to the eye.

So, Arctoris came up with an idea to find those enzymes by combing a database of known genes. But where to look for these enzymes? This is where InSilico Medicine comes in. All of the other technologies are focused on the cell itself and its relationship to DNA and RNA. But this is actually an application of the same technology: in silico medicine. It’s also an example of the kind of exploration that can be pursued by many companies if they act together, rather than piecemeal.

I think this new collaboration is of interest because of all of the big changes in how we study life, including disease. We’re coming out of the era in which cell-mapping might be taken for granted as something that’s done with great precision and speed. With the rise of computational biology, we can get closer to living organisms on computers than ever before.

And Arctoris has one of the leading and easiest-to-use technology tools for doing this kind of work, in my opinion. I like the team there.

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