Our Research (In-Silico Biology applied to Covid19 drug repurposing) has been published in Nature – Systems Biology & Applications

I am incredibly proud to announce that, a little more than 2 weeks ago, our Biology team at Elsevier ( Anastasia Nesterova ? Anton Yuryev ,? Hongbao Cao ?and Chris Cheadle) together with our Academic collaborators at Rochester General Hospital led by Prof. Gordon Broderick , have published a paper in the prestigious journal?Nature?– Systems Biology & Applications – entitled:

“Old drugs, new tricks: leveraging known compounds to disrupt coronavirus-induced cytokine storm” –?Link here.

This is a very important milestone for us as it establishes our scientific credibility in the field of?Digital or?In-Silico?Biology, and opens the door to?more collaborations and business, both with Academic partners and Pharma/Biotech companies. As with several other key initiatives such as our Drug-Drug Interactions Calculator (link here) led by my colleague Olivier Barberan , or Safety Margin (link here) also led by Olivier Barberan and Catherine Noban , or, on the Chemistry side, Reaxys Predictive Retrosynthesis (link here) led by Ivan Krstic and Abhinav Kumar – it demonstrates that Elsevier has more to offer than its already “Best in class scientific and regulatory content”: We take our own content, FAIRify it, apply modern ML/AI tools and address some of the most challenging Life Sciences question (e.g.: understanding diseases' mechanism, identifying biological targets ...).

We also execute on 2 key objectives:

1. Becoming a strategic partner: our Academic and Corporate customers are putting their names with us on scientific papers; we are jointly presenting at Scientific conferences, and ultimately, they trust us to bring cutting-edge innovation to their scientists
2. Bringing truly innovative solutions to the market: with us, the research doesn’t stay in the lab; we follow a lean innovation process to understand customers’ challenges, and we turn research into innovation, make it use-friendly, and create services and solutions for our customers to adopt. With In-Silico Biology, we have already executed 1 paid proof of concept with a Biotech, and we are now testing the possibility of an?end-user version (thanks to our super talented UX team Flavia Messina , Maria Baron Jorgos Achtsivassilis, MBA, FCX-I )

So, what is In-Silico Biology and what is this paper about??

The simplest way to describe In-Silico Biology is to compare it to?what a GPS is to an old-school map:

With a map

• i know where i start
• i know where i want to go
• but i must figure out, on my own, what is the best way …
• and if you’re like me, there are chances that you’ll get lost!

A GPS indicates:?

• The optimal way, based on your criteria (shortest, fastest, cheapest)
• Points of interest (restaurants, …) and even give you feedback from the community (??????????)
• It lets you experiment with various itinerary, and tells you what’s the traffic

With a GPS, before you start, you have already an idea of what the journey will look like, where you will stop for lunch and when you will arrive

In-Silico Biology is like a GPS for Biology:

Biologists analyse a conventional “disease pathway” and need to figure out what is the best target (i.e.: the arrival of our journey), by looking at a very complex "static map", with many potential roads. Also, the map might be incomplete, but they won't know by just looking at it. And in the end, they need to spend a lot of time in the lab testing various hypothesis, that often don’t work (i.e.: taking a road, and then going back because it’s a dead-end).

With In-Silico Biology, we start with a static disease pathway, that we convert into a?computer readable network?that can?explain the observed experimental data?(for instance the concentration of a certain biomarkers)

We apply various?machine learning models?to?identify point of interventions?(i.e.: target(s))

And we use our?large databases of drugs and compounds?to identify those that may?alter the course of the disease

What is this article about?

In the "Nature Systems Biology and Application" paper, we applied In-Silico Biology to?Covid19 Acute Respiratory Distress Syndrome (ARDS). We mapped out the pathway corresponding to the disease, turned it into a computable network, and then identified potential targets and corresponding drugs (i.e.: drug repurposing).

With In-Silico Biology we give Experimental Biologists a?“simulation of a disease”, we tell them if they have all the information or if they need to do further experiments (if their view of the disease is incomplete and cannot explain what they observe in their experiments), we tell them with a degree of certainty what are the most promising targets to go after, and which drugs they should test in the lab.?In short,?we give them an itinerary for their experiments and tell them about all the points of interests?… so that they?discover things that they didn’t know and waste less time in the lab testing things that are very likely to fail.

As you can read, I am very excited and I hope to bring this innovation to the market soon (with the guidance from our most experienced innovation champion? Sherry Winter ), and thanks to our lean innovation process (thanks Min Seok Choi and John Toomey ) we are making material progress, and we are getting very promising feedback from the community.

Stay tuned to hear more about this exciting research ... and if you have a challenging project to tackle, reach out to me!

Thibault