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Artificial intelligence (AI) could boost the success rate of clinical trials, according to a review by researchers from IBM Research‐Australia and MIT published in Trends in Pharmacological Sciences. Big Pharma and other drug developers are grappling with a dilemma: the era of blockbuster drugs is coming to an end. At the same time, adding new drugs to their portfolios is slow and expensive. It takes on average 10–15 years and $1.5–2 billion to bring a new drug to market; approximately half of this time and investment is devoted to clinical trials. Although AI has not yet had a significant impact on clinical trials, AI‐based models are helping trial design, AI‐based techniques are being used in patient recruitment, and AI‐based monitoring systems aim to boost study adherence and reduce dropout rates. The researchers found that AI can boost the success rate of clinical trials by efficiently measuring biomarkers that reflect the effectiveness of the drug being tested; identifying and characterising patient subpopulations best suited for specific drugs. Fewer than one‐third of all phase 2 compounds advance to phase 3 testing, and one in three phase 3 trials fail, not because the drug is ineffective or dangerous, but because the number or types of patients are inadequate. Start‐ups, large corporations, regulatory bodies, and governments are all exploring the use of AI for improving clinical trial design. The authors also identify several areas in which AI may be of greatest benefit for patients: AI‐enabled systems could allow patients more access to and control over their personal data; coaching by AI‐based apps could be undertaken before and during trials; AI could assist continuous monitoring of individual patients’ adherence to protocols; and AI techniques could help guide patients to trials of which they may not have been aware. Finally, AI could support precision medicine; for instance, by improving the efficiency and accuracy with which professionals diagnose, treat and manage neurological diseases.