On average, drug discovery and development of a single pharmaceutical takes 4.5 to 5 years, with upward of 10 years considered common. But British start-up Exscientia and Japanese pharmaceutical firm Sumitomo Dainippon Pharma have turned this on its head by leveraging artificial intelligence (AI) to reduce the timeline to less than one year—and that AI-created drug is now entering a Phase I human clinical trial.
DSP-1181, a long-acting, potent serotonin 5-HT1A receptor agonist, is intended for the treatment of obsessive-compulsive disorder (OCD). In Japan, approximately 1 million people suffer from OCD, while the disorder affects 3 million persons in the United States.
During development, Exscientia applied its Centaur Chemist Artificial Intelligence platform, which has generated nearly 100 billion novel compounds through evolutionary design. DSP-1181 was created using algorithms that sifted through potential compounds, checking them against a huge database of parameters.
“We believe that this entry of DSP-1181, created using AI, into clinical studies is a key milestone in drug discovery,” Andrew Hopkins, CEO of Exscientia, said in a release. "This project’s rapid success was through strong alignment of the integrated knowledge and experiences in chemistry and pharmacology on monoamine GPCR drug discovery at Sumitomo Dainippon Pharma with our AI technologies."
Since the Centaur Chemist debuted in 2012, Exscientia has made pharmaceutical collaborations part of their modus operandi. In addition to Sumitomo Dainippon, Exscientia has ongoing collaborations with:
- Bayer for the drug discovery in cardiovascular and oncology disease
- Celgene for the discovery of small molecule therapeutic drug candidates in oncology and autoimmunity
- Sanofi for the design of bispecific small molecules for metabolic disease
- Sunovion for the discovery/optimization of novel medicines for psychiatric disorders
- GSK for the discovery of novel and selective small molecules for up to 10 disease-related targets
- Roche for the design of pre-clinical drug candidates in oncology.
The AI pharmaceutical company also has several co-development agreements, and its own pipeline focused on immuno-oncology, innate immunity and fibrosis.
In a November 2019 article, referencing the average cost of R&D at $2 billion per drug, executives from Deloitte stressed the importance of finding ways to improve the efficiency and cost-effectiveness of bringing new drugs to market. As Exscientia showed with DSP-1181, one way to do that by leveraging AI.
“AI applications in drug discovery have already delivered new candidate medicines, in some cases in months rather than years,” Deloitte executives wrote. “If adopted at the drug discovery stage, AI solutions have the potential to kick-start the productivity of the entire R&D process. Biopharma companies need to develop a robust strategy to integrate AI solutions into traditional processes.”