An AI Tool to Make Clinical Trials More Inclusive

Clinical trial success often depends on enrolling people who meet study criteria within a specific time period.

Sometimes the inability to find enough appropriate people for a clinical trial leads to inferior conclusions. But a new software allows clinicians to include more diverse participants safely, by analyzing real-world cancer patient data.

Most clinical trials endeavor to sign up low-risk people. They exclude elderly individuals, pregnant women or people with co-morbidities other than the targeted condition. Such exclusions weed out those who are physically weak, or have toxic drug intolerance, in order to ensure trial uniformity. This strategy excludes some people who might benefit from the treatment being studied. Sometimes it results in a smaller-than-optimal study group which compromises, delays or even ends the trial.

Eligibility criteria are often established by using old trial data or by arbitrary trial design decisions. A recent study looked at ways electronic health records (EHRs) could modify a trial’s eligibility criteria to grow...