AI-designed medicine to be used in human trials for the first time

  • Clinical trials will begin this year for a new drug for Obsessive Compulsive Disorder developed using Artificial Intelligence.

    The pharmaceutical industry spends billions each year developing and testing new drugs to treat illnesses, but the entire process for drug development can take years of painstaking work. Modern research techniques have helped researchers to discover the molecular mechanisms behind many diseases inside our cells, and labs will test thousands of candidate compounds to see which ones interact with that mechanism.

    This first step of the process is extremely time-consuming and may yield just one or two promising candidate medications, which must then be synthesised and tested in the real world and prove that it's stable enough before eventually proceeding to trials. Many promising drugs fail at each stage of the process, raising the total cost of new drug development.

    Sifting through thousands of candidate molecules is an ideal task for artificial intelligence, and British start-up Exscientia has been working with Japanese pharmaceutical firm Sumitomo Dainippon Pharma to do just that. The project involved developing an AI to search for viable molecules in a massive list of potential candidate drugs, cutting the drug development time down from five years to just 9 months.

    The company is now gearing up to run human clinical trials of the new drug, and are reporting that it's the first human trials of a medication developed by AI. This first drug is based on a molecule named DSP-1181 and is designed to treat sufferers of Obsessive Compulsive Disorder (OCD), but the AI-based approach can be applied to any medical condition.

    The trials will begin in Japan this year, and if successful will be rolled out worldwide. The company is also working on new drugs for cancer and cardiovascular disease, two of the biggest killers globally, and is aiming to begin trials of new medications by the end of the 2020.

    Source: BBC News

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