The use of technology-based adherence monitoring in the treatment of hepatitis C virus

Abstract

Direct-acting antivirals (DAAs) achieve high hepatitis C virus (HCV) cure rates and are forgiving to missed doses, but adherence-efficacy relationships have not been well defined. Traditional adherence measures (e.g. pill counts, self-report and pharmacy refills) over-estimate medication adherence. Newer technology-based tools have been used to provide more objective adherence data. Herein, electronic medication diaries (e-diaries), medication events monitoring system (MEMS^®) caps, electronic blister packs, electronic pill boxes, video-based directly observed therapy (vDOT), artificial intelligence platforms (AIPs), and ingestible sensor systems are described, and compared based on existing studies using DAA. Percent adherence, predictors of adherence, and HCV cure rates utilizing these technologies are included. DAA adherence with e-diaries was 95-96%, MEMS^® caps and ingestible biosensors were between 95% and 97%, blister pack weekly dosing ranged 73-98%, and daily dosing 73-94%, whereas electronic pill boxes ranged between 39% and 89%, vDOT was 98% and AIP 91-96%. Despite a wide range of adherence, high sustained virologic response (SVR) rates (86-100%) were observed across all studies utilizing these different technology-based tools. Current data support the forgiveness of DAA therapies to missed doses using tools that provide more quantitative adherence measures compared with self-report and provide insight on adherence-efficacy relationships for contemporary DAA.

Keywords: DAA; SVR; adherence; hepatitis C; technology-based tools.

Figure 1.

Schematic of electronic diary showing patient access, log drug dosing, and symptoms are logged manually (left), versus trial manager access (right), monitor, and visualize patient data. E-diary measures medication adherence, adverse effects, and provides schedule reminders.

Figure 2.

Schematic of the Medication Event Monitoring System (Electronic MEMS Caps) consisting of medication bottle equipped with an electronic chip cap (left), and the reader (center) for patients to download stored data that are exported to the software for visualization and analysis of adherence patterns by the provider (right).

Figure 3.

Schreiner MediPharm (left) versus Med-ic ECM (right). Schematic of the electronic blister pack system showing tablets pushed out from blister pack (equipped with radio frequency identification tag that records medication type, extraction time, specific cavity) and exportation of data via smartphone/reader for provider adherence analysis and follow-up.

Figure 4.

Schematic of a pill box – Wisepill RT2000 for medication adherence monitoring. As patients open the box, a cellular signal is sent to the web-based server, and research staff access and transfer the recorded data via a centralized server.

Figure 5.

Emocha—schematic of video directly observed (vDOT) technology illustrating patient-facing side allowing to record, review, and send medication ingestion, side effects, therapy progress, and adherence (left). The provider-facing side is accessible by research personnel for adherence review, analysis and follow-up from electronic devices (right).

Figure 6.

Schematic of the artificial intelligence platform (AIP) that uses audio-visual recognition systems to monitor dosing compliance (left) and store encrypted data to the web-based dashboards for provider review in real-time (right).

Figure 7.

Proteus Discover—overview of ingestible sensor system (top) depicting sensor-co-encapsulated pill, a wearable patch, and mobile device app from which stored medication adherence, physical, physiological/behavioral data are sent to provider web portal from the secure server once pill is ingested (bottom).