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Before a new medicine enters human trials, there is typically three to five years of work behind the scenes, researching causes for diseases and compounds that may help treat them. But working with British AI startup Exscientia, a Japanese drug development company called Sumitomo Dainippon Pharma Co. is about to start phase 1 clinical trials after only 12 months.
The drug in question is DSP-1181, a prospective treatment for obsessive-compulsive disorder (OCD). OCD affects millions of people worldwide, to varying degrees, and can be debilitating in its psychological effects.
Exscientia, based in Oxford, UK, operates an exciting machine learning platform called Centaur Chemist. The platform allegedly takes years off the time required to research new compounds, by combining A.I. techniques with existing knowledge of how medicines interact with the human body.
The benefit of machine learning is that it can happen virtually, and far quicker than scientists are able to work in the real world. The platform can analyze millions of molecular combinations and attempt to identify which may be the safest and most effective in treating a given disease.
Perhaps even more important is the potential savings associated with using machine learning to develop new medicines. Typically, it costs over $1 billion to bring a new drug through from conception to market, with a lot of those costs borne out during the research phases. But taking out years of painstaking research will save both time and money, speeding up development and freeing up resources to develop yet more medicines.
There’s a lot riding on Exscientia and Sumitomo Dainippon’s trial. The first phase is to check how the drug affects the body, and how the body metabolises the drug. So this will not prove the medication’s efficacy.
But if DSP-1181 is shown to be safe, phases two and three can proceed, to see whether the drug can help OCD patients in the real world. And if it does, we’ll witness the dawn of machine learning in medicine.