eCAP - Ehealth CAPsule for digestive disease diagnostics and therapy

eCAP aims to deliver a novel medical device which combines a smart capsule with an e-health platform for better diagnostics, patient empowered disease management and hence, improved outcomes for patients with gastrointestinal (GI) diseases.

Our project will create a modular and implantable capsule with multi-sensing capacity that enables GI physiology monitoring for a controlled time period, leveraging the minimally invasive surgical approach of flexible endoscopy. eCAP will use a worldwide ubiquitous smartphone communication standard, together with cloud computing technology and application interfaces to integrate, process and interpret longitudinal physiological data collected by the capsule.

The digital platform is designed to improve the accuracy and clinical usefulness of standard test data by incorporating patient reported outcome measures.

The clinician is able to personalize the test for the patient and receive accurate and meaningful results from this multi-stream data input with interpretation aided by Artificial Intelligence.

The universality of the eCAP solution will allow dissemination of advanced GI disease diagnostics to patients and doctors worldwide, including low resource environments.

During the project, we will demonstrate eCAP?s clinical value and cost savings using gastroesophageal reflux disease (GERD), a worldwide, common, and extremely costly problem, as a clinical target.

Clinical evaluation with health-economics analysis will be conducted in France, Ukraine and Kenya, and a specific education program will be developed to train practitioners to use the novel technology. eCAP builds on several years of R&D by our consortium in the field of implantable capsules for GI disease diagnostics.

Its ambition is to facilitate a shift in GI diagnostics from its current unscalable analogue version to a patient centered e-health tool and to make Europe the leader in the rapidly growing field of connected medical devices for remote patient monitoring.