The Case for Digital Pill Use in Clinical Trials

Medication adherence in clinical trials is significantly overestimated through every phase of drug development. This can cause a reduction in statistical power, potentially resulting in incorrect conclusions regarding efficacy, safety, tolerability, and dose-response relationships, in addition to major cost overruns. Digital pill systems enable adherence measurement through an embedded ingestible sensor paired with an external receiver. An oral pharmaceutical product is over-encapsulated by a pharmaceutical-grade shell containing a biocompatible sensor. Upon exposure to gastrointestinal fluid, the shell dissolves and the sensor is activated. Medication ingestion data is transmitted via a digital signal. Clinicians and researchers use this data to track, in real time, when and if a medication was taken. These systems have demonstrated a 99.4% rate of accuracy, and have over 15-years of supporting experience and safety data. Spurred by the accelerated adoption of technology in healthcare and in everyday life, patients have become tech-savvy. They quickly adapt to these devices, and are able to use them safely and effectively. Digital pills can be implemented in most types of studies. In early-stage trials such as pharmacokinetic and pharmacodynamic studies, or dose-finding studies, accurate information on maximum-tolerated dose levels is essential and cannot be established unless study participants are highly adherent. In later-stage pivotal trials, effective medication adherence tracking can strengthen the dataset and confidence in the study results. Significant nonadherence may generate results that do not meet statistical or clinical significance for the critical endpoints, resulting in at worst, a failed trial, or at best, the need to enroll additional patients at substantial additional cost. Most clinical trials fail to achieve statistical significance, and poor medication adherence is often an important contributor. A digital pill system can ensure the quality and integrity of adherence data, increase confidence in the overall study data, and improve clinical trial efficiency