While medication non-adherence in clinical trials has been widely recognized as a challenge in drug development, reported non-adherence rates have been largely anecdotal, isolated to individual studies, and varied widely in their estimations. A recently published study from Tufts’ Center for the Study of Drug Development (CSDD) and AiCure, an AI and advanced data analytics company focused on improving clinical trials, identified and quantified the scope of intentional non-adherence to clinical trial drugs. Published in Therapeutic Innovation & Regulatory Science (TIRS), the research is an adherence study to obtain data from directly observing dosing patterns among participants via computer vision and AI. Leveraging insights captured by AiCure’s proprietary medication adherence platform, the researchers deciphered between intentional and unintentional non-adherence, as well as identified factors predictive of noncompliance. By presenting a baseline measurement of overall non-adherence in clinical trials, the research helps to inform best practices to lower, and ultimately prevent, deliberately non-adherent behaviors.
The study, entitled “Assessing the Scope and Predictors of Intentional Dose Non-Adherence in Clinical Trials,” consisted of nearly 260,000 anonymized dosing results captured through AiCure’s platform, which were drawn from 2,796 study volunteers participating in 23 different clinical trials of nine psychiatric, neurological and neuromuscular diseases. The study’s key findings include:
“As the pharmaceutical industry faces intensifying pressure to optimize the drug development process, adherence and precise dosing over the course of a clinical trial are critical to achieving an accurate assessment of a treatment’s efficacy and effects as quickly and safely as possible,” said Ed Ikeguchi, MD, CEO of AiCure. “Today trial sponsors need to recruit a greater number of patients to combat the effects of non-adherence on trial results. This study’s findings inform a path to potentially shorter, more streamlined trials, which could not only lead to cost savings but also help bring life-saving drugs to patients faster.”
The study identified several factors that were associated with-and predictive of-unreported intentional non-adherence. Volunteers in later stage phase II and III clinical trials, as well as those of longer durations, had a higher likelihood of intentional non-adherence. This finding may be a result of study fatigue, skepticism around the drug’s effects, and patient burden as participation increases. Other factors included geographical location of the study and enrollment volume at the site. Understanding the reasons behind deliberate non-adherence may help sponsors develop targeted educational resources or proactive, personalized interventions to mitigate the impact of non-adherence.
The study’s findings have long-term implications for reducing trial timelines and enrollment volumes. Today, many drug developers typically increase the size of study populations by 15% to reduce the impact non-adherence has on a drug’s statistical relevancy, requiring longer and more expensive trials. For example, for a typical Phase III oncology study, clinical research sponsors may pay an additional $5-$7 million to augment enrollment to account for potential non-adherence. Employing tactics to identify and eliminate intentionally non-adherent participants early-particularly within the trial’s first week-will play a critical role in cutting costs and lead to leaner, statically relevant trials in the future.