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First RE-SAMPLE Publication Digital Therapeutics: Virtual Coaching Powered by Artificial Intelligence on Real-World Data

RE-SAMPLE celebrates its first publication - "Digital Therapeutics: Virtual Coaching Powered by Artificial Intelligence on Real-World Data" by Harm op den Akker, Miriam Cabrita, and Aristodemos Pnevmatikakis (iSPRINT). In this article, partners from Innovation Sprint lay out their vision of Healthentia as a Digital Therapeutics platform, employing the RE-SAMPLE use case as a running example.

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The article is available in open access at this link.

The Abstract:

An ever-increasing number of people need to cope with one or more chronic conditions for a significant portion of their life. Digital Therapeutics (DTx) focused on the prevention, management, or treatment of chronic diseases are promising in alleviating the personal socio-economic burden caused. In this paper we describe a proposed DTx methodology covering three main components: observation (which data is collected), understanding (how to acquire knowledge based on the data collected), and coaching (how to communicate the acquired knowledge to the user). We focus on an emerging form of automated virtual coaching, delivered through conversational agents allowing interaction with end-users using natural language. Our methodology will be applied in the new generation of the Healthentia platform, an eClinical solution that captures clinical outcomes from mobile, medical and Internet of Things (IoT) devices, using a patient-centric mobile application and offers Artificial Intelligence (AI) driven smart services. While we are unable to provide data to prove its effectiveness, we illustrate the potential of the proposed architecture to deliver DTx by describing how the methodology can be applied to a use-case consisting of a clinical trial for treatment of a chronic condition, combining testing of a new medication and a lifestyle intervention, which will be partly implemented and evaluated in the context of the European research project RE-SAMPLE (REal-time data monitoring for Shared, Adaptive, Multi-domain and Personalised prediction, and decision making for Long-term Pulmonary care Ecosystems).