Artificial Intelligence in Clinical Trials

\r\n Artificial intelligence could improve key parts of the clinical trial process, including selection and recruitment and patient monitoring, according to a study published in Trends in Pharmacological Sciences.


\r\n It takes between 10 and 15 years and costs between $1.5 and $2.0 billion to bring a new drug to market, researchers noted, and about half of this time and capital is dedicated to clinical trials.


\r\n But despite significant investments, clinical trials still have high failure rates, the team stated.


\r\n Clinical trial failures are mainly due to poor recruiting and selecting techniques, as well as an inability to effectively monitor patients. Artificial intelligence tools have emerged as a viable way to improve these processes and increase clinical trial success rates, researchers said.


\r\n “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,” said lead author and computer scientist Stefan Harrer, a researcher at IBM Research-Australia.


\r\n There are three types of AI being deployed by life science businesses which can provide a framework for improving efficiencies. Very broadly, AI can support 1) automation of a 

  • 10.1 Process Automation / Focus on Efficiencies
  • 10.2 AI Driven Data Analysis / Focus on Precision of Go / No Go Decision
  • 10.3 AI and Insight into the Data /Focus on Business Decisions

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