High rates of early termination (ET) yield undesired trial outcomes such as reduced statistical power, increased cost, and poor data quality. Digital tools can provide mechanisms to uncover risk of ET, allowing opportunity to intervene prior to conclusion of the trial.

 

• Typical rates of early termination in clinical trials range from 20-60%, depending on study design and therapeutic area. 
• Drug trials in CNS have among the highest dropout rates, with some therapeutic areas such as schizophrenia having > 60% expected dropout. 
• High rates of early termination (ET) yield undesired trial outcomes such as reduced statistical power, increased cost, and poor data quality. 
• Participants who are adherent with AiCure only (not including CSS central monitoring) are 17.4% less likely to early terminate compared to those who are non-adherent. 
• Furthermore, just the first 14 days of AiCure captured medication adherence can accurately predict the likelihood of a participant completing the study.