Review evaluates how AI could boost the success of clinical trials

July 17, 2019

In a review publishing July 17 in the journal Trends in Pharmacological Sciences, researchers examined how artificial intelligence (AI) could affect drug development in the coming decade.

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 $1.5-2B to get 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 for patient recruitment, and AI-based monitoring systems aim to boost study adherence and decrease dropout rates.

"AI is not a magic bullet and is very much a work in progress, yet it holds much promise for the future of healthcare and drug development," says lead author and computer scientist Stefan Harrer, a researcher at IBM Research-Australia.

As part of the review and based on their research, Harrer and colleagues reported that AI can potentially boost the success rate of clinical trials by:The authors also identify several areas showing the most real-world promise of AI for patients. For example:The review also evaluated the potential implications for pharma, which included:The authors also identified several important takeaways for researchers:Because AI methods have only begun to be applied to clinical trials in the past 5 to 8 years, it will most likely be another several years in a typical 10- to 15-year drug-development cycle before AI's impact can be accurately assessed.

In the meantime, rigorous research and development is necessary to ensure the viability of these innovations, Harrer says. "Major further work is necessary before the AI demonstrated in pilot studies can be integrated in clinical trial design," he says. "Any breach of research protocol or premature setting of unreasonable expectations may lead to an undermining of trust-and ultimately the success-of AI in the clinical sector."
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This work was supported by IBM Research. All authors declare no conflicts of interest and no disclosures.

Trends in Pharmacological Sciences, Harrer et al.: "Artificial Intelligence for Clinical Trial Design" https://www.cell.com/trends/pharmacological-sciences/fulltext/S0165-6147(19)30130-0

Trends in Pharmacological Sciences (@TrendsinPharma), published by Cell Press, is a monthly review journal that contains succinct articles on the most exciting recent developments in pharmacology and toxicology research. Topics covered in the journal range from molecular to behavioral pharmacology, and from current techniques to theoretical pharmacology. Visit: http://www.cell.com/trends/pharmacological-sciences . To receive Cell Press media alerts, please contact press@cell.com.

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