AI could shorten pharmaceutical trials, boost patient matching, Intel report says

Efforts to implement artificial intelligence, advanced analytics and machine learning could have multiple applications for the healthcare and pharmaceutical industries, according to a new report from Intel.  


The report, “Harnessing AI and Analytics to Drive Digital Transformation,” comes as health systems across the country are working to deploy advanced data analytics to provide faster care for their patients.  


The applications of AI technology aren’t just limited to clinical trials — earlier this week Radiological Society of North America released a report outlining the opportunities and challenges AI could have for digital imaging.

RSNA called for more research into automated image labeling and annotation methods, including information extraction from the imaging report, electronic phenotyping, and prospective structured image reporting.

AI-based algorithms can optimize clinical trial design by eliminating testing criteria that increases time but has a minimal impact on the overall effectiveness of what is being tested, Intel noted.

For pharmaceutical companies, this means simplifying clinical trials, reducing trial costs and accelerating time to market for new drugs by streamlining product design.


Trials that leverage the platforms capabilities can get real-time information about protocol adherence while helping patients manage medication, perform structured tests and report symptoms, and utilize smartphone applications to collect electronic diaries and patient reported outcomes (PROs).

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