Artificial Intelligence for Clinical Trial Design

Suboptimal patient selection and recruiting techniques, paired with the inability to monitor and coach patients effectively during clinical trials, are two of the main causes for high trial failure rates.High failure rates of clinical trials contribute substantially to the inefficiency of the drug development cycle, in other words the trend that fewer new drugs reach the market despite increasing pharma R&D investment. This trend has been observed for decades and is ongoing.AI techniques have advanced to a level of maturity that allows them to be employed under real-life conditions to assist human decision-makers.AI has the potential to transform key steps of clinical trial design from study preparation to…

• MI
  Massachusetts Institute of Technology