Automation, Analytics, AI, And The Future Of Trial Monitoring

High clinical trial failure rates often stem from difficulties experienced in recruiting and retaining patients. A clinical trial may initially suffer from problems in finding and recruiting participants. And once they join the study, patients may drop out if the clinical trial team cannot monitor and coach them effectively.

High failure rates, in turn, drive inefficiencies in pharmaceutical research and development. Although investments continue to increase, fewer medications are brought to market when clinical trial failure rates stay high.

To counteract these downfalls, more clinical trial teams have begun using artificial intelligence and automation to recruit and retain more patients. Discover how predictive analytics allow clinical trial teams to make better prognostications about patient behavior— so they can reach out before a patient vanishes from the study.