Insight: Big Pharma bets on AI to speed up clinical trials

Major pharmaceutical companies are increasingly using artificial intelligence (AI) to accelerate drug development and potentially save millions of dollars. Companies like Amgen, Bayer, and Novartis are training AI to scan billions of health records, prescription data, medical insurance claims, and their internal data to find trial patients, in some cases halving the time it takes to sign them up. The U.S. Food and Drug Administration (FDA) has received about 300 applications incorporating AI or machine learning in drug development from 2016 through 2022, with over 90% of those applications coming in the past two years.

AI is also being used to reduce the number of participants needed for clinical trials. For example, Bayer used AI to cut the number of participants needed by several thousand for a late-stage trial for an experimental drug. The company is now planning to use real-world patient data to generate an external control arm for a study, potentially eliminating the need for patients taking a placebo. However, some scientists are concerned that drug companies will try to use AI to come up with external arms for a broader range of diseases, which could overestimate the success of a drug.

Key takeaways

Major pharmaceutical companies are increasingly using artificial intelligence to expedite patient recruitment for clinical trials, potentially saving time and money in drug development.
AI tools like Amgen's ATOMIC are being used to scan large amounts of data to identify potential trial participants, significantly reducing the time it takes to enroll patients.
German drugmaker Bayer has used AI to reduce the number of participants needed for a late-stage trial, saving millions of dollars and several months of recruitment time.
Despite the potential benefits, there are concerns about the use of AI in creating external control arms for trials, with some scientists warning it could lead to overestimation of a drug's success.

Insight: Big Pharma bets on AI to speed up clinical trials

Key takeaways

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