Bringing a new drug to the clinic is a tortuous and extremely expensive process fraught with commercial risk. It seems that Artificial Intelligence is beginning to challenge this reality.
In a worldwide first, it was announced last week that human clinical trials of a compound designed using an AI platform are about to commence. The compound, DSP-1181, is the product of the joint research of Oxford-based Exscientia (CEO: Prof. Andrew Hopkins) and Sumitomo Dainippon Pharma (CEO: Hiroshi Nomura) and is about to undergo phase I clinical tests in humans as a potential therapy for obsessive-compulsive disorder.
Phase I trials are small studies in humans which aim to find the best dose of a new drug with the fewest side effects. Investing in such trials shows that a pharmaceutical company has significant confidence in a promising drug candidate. However, it takes an average of 4.5 years to identify a promising drug candidate and get it to such a stage using conventional research techniques. According to Exscientia and SDP, by using Exscientia’s AI algorithms it took less than 12 months to complete the exploratory research phase to identify DSP-1181 as a potentially clinically effective serotonin 5-HT1A receptor agonist.
Although there is unlikely ever to be a shortcut to the painstaking clinical trials that a candidate drug must navigate to ensure its safety and effectiveness, the power of AI will accelerate initial research and development, thus shortening the overall time to clinic and reducing costs and risk. This can only be a boon to a world in need of new medicines to treat rare and emerging diseases, or to treat diseases which are developing resistance to existing drugs at alarming rates.
"We have seen AI for diagnosing patients and for analysing patient data and scans, but this is a direct use of AI in the creation of a new medicine."