Groundbreaking artificial intelligence can predict Ebola drugs' effectiveness 150 times faster

Supported by the University of Toronto, Chematria has managed to reprogram the country's fastest supercompute,  a 32,767-core IBM BlueGene/Q, with an algorith that simulates and analyses millions of potential medicines to predict their effectiveness against Ebola, Mashable reported.

Co-founder and CEO of Chematria, Abraham Heifets, said that what they are attempting would have earlier been considered only possible in science fiction. They intend to explore the possible effectiveness of millions of drugs, something that used to take decades of physical research and tens of millions of dollars, in mere days with their technology.

The system is driven by a virtual brain, modeled on the human visual cortex, that teaches itself by studying millions of datapoints about how drugs have worked in the past.  With this vast knowledge, Chematria's brain can apply the patterns it perceives, to predict the effectiveness of hypothetical drugs, and suggest surprising uses for existing drugs, transforming the way medicines are discovered.

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