How AI-driven platforms can save failing trials by using data to hone protocols, identify sub-populations with shared traits, and ensure the right patients are recruited to demonstrate success
Failed clinical trials can cost sponsors more than a billion dollars, and waste years of time developing a drug that will never get to market. However, these losses can now be mitigated through the use of artificial intelligence (AI) and machine learning-driven platforms that identify sub-populations of patients within a clinical trial who could respond positively to a treatment.
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