“Normally, they do this manually, reading through all of these documents to find out what is relevant to the question they have in mind,” Finelli says.
“Here, AI can actually help to do this in a few clicks and bring the relevant information back to the user for further use, informing them how to design future experiments to find new ways to create a formulation for a new drug,” Finelli adds.
Novartis researchers also are leveraging Microsoft Azure in their work.
By using AI, researchers now can simulate thousands of experiments simultaneously.
Eventually, scientists at Novartis aim to use computer models to help predict promising molecular structures or to reveal which experiments might be most useful in testing, maintaining quality while shortcutting a testing process that now can take years.
“Now you can do 10,000 experiments simultaneously, get the results, then use those to design the next 10,000 experiments,” Bishop says.
“So the revolution is beginning to unfold. Deep learning is completely changing the way we think about simulating physical systems – it might be (simulating) two galaxies colliding or weather systems or the climate. And it might be small molecules binding with proteins – in other words, the whole process of how drugs work,” Bishop adds.
To conduct its molecular simulations, Novartis relies on expertise provided by the Microsoft Research Lab in Cambridge and, in smaller ways, by ongoing work occurring at Microsoft Research Labs in Amsterdam, Beijing and Redmond, Washington, Bishop says.
But at the center of all that discovery, humans continue to be the most vital engine.
Lab workers at Novartis.
As part of its strategic partnership with Microsoft, Novartis is bringing AI to the desktop of every company associate. At Novartis, they call this “the enablement of citizen data scientists.”
“Business is becoming increasingly data driven. The way I see it, one needs to embed AI-based tools – small engines of AI – into every aspect
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