Kit Yee Au-Yeung

An ingestible sensor for measuring medication adherence.

In this paper, we describe the design and performance of the first integrated-circuit microsensor developed for daily ingestion by patients. The ingestible sensor is a device that allows patients, families, and physicians to measure medication ingestion and adherence patterns in real time, relate pharmaceutical compliance to important physiologic metrics, and take appropriate action in response to a patients adherence pattern and specific health metrics. The design and theory of operation of the device are presented, along with key in-vitro and in-vivo performance results. The chemical, toxicological, mechanical, and electrical safety tests performed to establish the devices safety profile are described in detail. Finally, aggregate results from multiple clinical trials involving 412 patients and 5656 days of system usage are presented to demonstrate the devices reliability and performance as part of an overall digital health feedback system.

Feasibility of an ingestible sensor-based system for monitoring adherence to tuberculosis therapy.

Poor adherence to tuberculosis (TB) treatment hinders the individual’s recovery and threatens public health. Currently, directly observed therapy (DOT) is the standard of care; however, high sustaining costs limit its availability, creating a need for more practical adherence confirmation methods. Techniques such as video monitoring and devices to time-register the opening of pill bottles are unable to confirm actual medication ingestions. A novel approach developed by Proteus Digital Health, Inc. consists of an ingestible sensor and an on-body wearable sensor; together, they electronically confirm unique ingestions and record the date/time of the ingestion. A feasibility study using an early prototype was conducted in active TB patients to determine the system’s accuracy and safety in confirming co-ingestion of TB medications with sensors. Thirty patients completed 10 DOT visits and 1,080 co-ingestion events; the system showed 95.0% (95% CI 93.5–96.2%) positive detection accuracy, defined as the number of detected sensors divided by the number of transmission capable sensors administered. The specificity was 99.7% [95% CI 99.2–99.9%] based on three false signals recorded by receivers. The system’s identification accuracy, defined as the number of correctly identified ingestible sensors divided by the number of sensors detected, was 100%. Of 11 adverse events, four were deemed related or possibly related to the device; three mild skin rashes and one complaint of nausea. The system’s positive detection accuracy was not affected by the subjects’ Body Mass Index (p = 0.7309). Study results suggest the system is capable of correctly identifying ingestible sensors with high accuracy, poses a low risk to users, and may have high patient acceptance. The system has the potential to confirm medication specific treatment compliance on a dose-by-dose basis. When coupled with mobile technology, the system could allow wirelessly observed therapy (WOT) for monitoring TB treatment as a replacement for DOT.

A networked system for self-management of drug therapy and wellness

Background: A networked wellness system is under development to document actual ingestions of oral medications, to differentiate types/doses of drugs taken simultaneously, and to provide these data along with other metrics to patients and providers for individually tailored care. Methods: After ingestion, an edible sensor (embedded in drug) is activated by stomach fluid and communicates to a wearable monitor that identifies the sensor as unique and records ingestion time/date. The monitor also collects physiologic data and communicates via mobile phone to a secure server that integrates the data with other wireless devices (e.g. blood pressure, weight). Summary reports are generated periodically for patient and physician review. Results: No adverse effects were observed in animals using repeated, exaggerated doses of sensors. Two drug-sensor form factors have been tested in 3392 human ingestions with no major and very few minor adverse effects. Sensitivity was 97.0% and specificity was 97.7% when compared to directly observed ingestion. The system identified and differentiated up to 4 simultaneously ingested sensors with an identification accuracy of 100%. Data integration with multiple devices and report generation have been piloted successfully. Conclusions: Pre-clinical and early clinical system safety appear satisfactory; data integration and communication appear to be feasible. By providing context-rich information and fostering communication, this system may enhance patient-provider relationship and care coordination.