There’s been a lot of conversation about artificial intelligence over the last decade, as the controversial science fiction-turned-non-fiction technology begins to trickle into various economic sectors. Now, for the first time in history, an AI system created by British company Exscienta has invented a drug molecule that is entering phase 1 human trials.
The molecule has been found to treat obsessive-compulsive disorder (OCD), but the noteworthy news is that the normal 5-year period for synthesizing a drug and preparing the best version for trial was cut down to just 12 months because it was placed into the brain of an intelligent machine.
Exscienta chief executive Prof Andrew Hopkins described the breakthrough to the BBC as a “key milestone in drug discovery”.
“We have seen AI for diagnosing patients and for analyzing patient data and scans, but this is a direct use of AI in the creation of a new medicine,” said Hopkins.
“There are billions of decisions needed to find the right molecules and it is a huge decision to precisely engineer a drug,” he added. “But the beauty of the algorithm is that they are agnostic, so can be applied to any disease.”
Hopkins went on to predict that by the end of the year, all drug molecules could be discovered or created by artificially intelligent systems.
This could significantly bring down costs of drug R&D for pharmaceutical companies since the process of discovery, synthesizing, and trialing a drug in most countries is so expensive. The enormous costs place enormous risks on any new drug endeavor, especially during the 5 years of groundwork that needs to be done by well-educated and well-paid employees.
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If the attempts to bring an experimental drug to market fail after phase I, II, or phase III clinical trials, the development cost is even greater. AI could reduce costs of labor and R&D of pharmaceuticals by 80%.
The front-loaded savings means that more drugs for more diseases can be synthesized and moved into trials. This would be especially valuable for patients with diseases that are uncommon, because a smaller market might be one that pharmaceutical companies would otherwise avoid.
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