“The World’s Terror” might actually help speed up Drug Discovery

Artificial Intelligence. The point when humanity remembers nothing more than Elon sitting there and smoking weed.

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*Never believe fake rumors*

At last we have came to the stage when we can truly talk about the benefits of artificial intelligence. We will be observing one of the most crucial positions of the humankind – medicine.

AI drug chemical structure illustration

A new cryptographic system could allow pharmaceutical companies and academic labs to work together to develop new medications more quickly — without revealing any confidential data to their competitors.

The centerpiece of this computing system is an artificial intelligence program known as a neural network. The AI studies information about which drugs interact with various proteins in the human body to predict new drug-protein interactions.

The Real Deal: Scientists Invade!


“This work is visionary,” says Jian Peng, a computer scientist at the University of Illinois at Urbana-Champaign not involved in the study. “I think [it] will lay the groundwork for the future of collaborations in biomedicine.”

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MIT computational biologist Bonnie Berger and colleagues Brian Hie and Hyunghoon Cho evaluated their system’s accuracy by training a neural network on about 1.4 million drug-protein pairs. Half of these pairs were drawn from the STITCH database of known drug-protein interactions; the other half comprised drug-protein pairs that don’t interact. When shown new drug-protein pairs known to interact or not, the AI picked out which sets interacted with 95 percent accuracy.

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To test whether the system could identify hitherto unknown drug-protein interactions, Berger’s team then trained the neural network on nearly two million drug-protein pairs: the entire STITCH dataset of known interactions, plus the same number of noninteracting pairs. The fully trained AI suggested several interactions that had never before been reported or that had been reported but were not in the STITCH database.


“Whenever you want to do a study on a large number of people on behavior, on genomics, on medical records, legal records, financial records — anything that’s privacy-sensitive, these kinds of techniques can be very useful,” says computer scientist David Wu of the University of Virginia in Charlottesville.


This brings us to the thought of to what ranges may artificial intelligence gain up to… And I purely believe this is not the end…

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