Connections from AI to the Pandemic

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Updates on How AI Being Employed to Speed COVID-19 Treatments and Management
June 4, 2020  1109

Medical researchers are employing AI to search through databases of known drugs to see if any can be associated with a treatment for COVID-19. (GETTY IMAGES)
By AI Trends Staff

Medical researchers are employing AI to search through databases of known drugs to see if any can be associated with a treatment for the new COVID-19 coronavirus.

An early success story comes from BenevolentAI of London, which using tools developed to search through medical literature,  identified rheumatoid arthritis drug baricitinib as a possible treatment for COVID-19.

In a pilot study at the end of March, 12 adults with moderate COVID-19 admitted to the hospital in either Alessandria or Prato, Italy, received a daily dose of baricitinib, along with an anti-HIV drug combination of lopinavir and ritonavir, for two weeks. Another study group of 12 received just lopinavir and ritonavir.

After their two-week treatment, the patients who received baricitinib had mostly recovered, according to a recent account in The Scientist.  Their coughs and fevers were gone; they were no longer short of breath. Seven of the 12 had been discharged from the hospital. In contrast, the group who didn’t get baricitinib still had elevated temperatures, nine were coughing, and eight remained short of breath. Just one patient from the lopinavir-ritonavir–only group had been discharged.

Researchers at Benevolent AI, along with collaborator Justin Stebbing, an oncologist at Imperial College London, published a letter to The Lancet on February 4, describing how they used AI to identify baricitinib’s potential to treat COVID-19.

AI “makes higher-order correlations that a human wouldn’t be capable of making, even with all the time in the world. It links datasets that a human wouldn’t be able to link,” stated Stebbing.

Benevolent researchers used the company’s knowledge graph—a digital storehouse of biomedical information and connections inferred and enhanced by machine learning—to identify two human protein targets to focus on: AP2-associated protein kinase 1 (AAK1) and cyclin g-associated kinase (GAK).   ... "