Machine learning in drug discovery, together with artificial intelligence, is transforming the pharmaceutical industry by accelerating the development of new treatments.
Historically, the process of discovering and developing new drugs has been painfully slow, fraught with failure, and incredibly expensive. However, new developments in AI-driven methodologies, particularly in digital chemistry and biology, are creating unprecedented opportunities to accelerate drug discovery, said Stephen Mackinnon (pictured), vice president of applied machine learning at Recursion Pharmaceuticals Inc.
“Machine learning helps us understand more about the world. It helps us understand more about the biology so that when we go into that big experiment of a clinical trial, we can take that risk,” he said. “We are better equipped with knowledge of what that drug does, what that drug does to the system, what the drug does to the body, so we can make a more informed decision about what goes forward.”
Mackinnon spoke with Savannah Peterson of theCUBE Research at the Anyscale Ray Summit, during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed how AI and machine learning are transforming drug discovery by accelerating research, improving predictions, and enabling new experimental approaches. (*Disclosure below.)
How machine learning in drug discovery is revolutionizing pharmaceutical research
By using AI and machine learning, companies can now run millions of experiments simultaneously. This scale is unthinkable without automation and advanced data analytics, Mackinnon explains.
“The world of external data and the way drug discovery has happened over the last 20, 40 years has been very targeted,” he said. “Scientists have developed very specific tests and experiments that they would only perform for one program at a time to develop one drug at a time. And they do indeed exist. There are little bits of information here and there. But at Recursion we challenge that to a certain extent.”
As AI continues to evolve, its role in drug discovery will only become more important. According to Mackinnon, companies are already seeing success in clinical trials, with new drug candidates emerging from AI-driven research methods.
“Recursion is one of the companies with the largest portfolios of clinical assets today. There is a delay phase associated with this. “Many of the clinical trials happening now are from the early days of research,” he said. “But ultimately a lot of that was made possible by the computer. A lot of that was made possible by our ability to rethink the scientific model for the veracity of disease, by looking at the cells and disrupting them in different ways. So we certainly see many more opportunities coming along.”
Here’s the full video interview, part of SiliconANGLE and theCUBE Research’s coverage of the Anyscale Ray Summit 2024 event:
(*Disclosure: Anyscale Inc. sponsored this segment of theCUBE. Neither Anyscale nor other sponsors have editorial control over the content on theCUBE or SiliconANGLE.)
Photo: SiliconANGLE
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