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Smartphone Measured Eye-Based Digital Biomarkers for Drug Use Detection

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A mobile application for an eye-scanning drug abuse test

Substance addiction is associated with health issues as well as social problems such as violence. To tackle addiction-related abuse, the PrevictDrugs project has introduced a daily sobriety-monitoring approach based on eye scanning with a mobile phone.

Digital Economy icon Digital Economy
Health icon Health

In Europe, healthcare resources for treating addiction focus on out-patient relapse prevention strategies. Therefore, healthcare professionals must be able to monitor patients daily to assess their risk of relapse. However, the lack of tools for the real-time identification of treatment deviation or relapse hampers the successful treatment of patients.

A mobile app for self-monitoring

The EU-funded PrevictDrugs project has developed an innovative medical platform for the voluntary self-monitoring of drug use through a mobile application. The Previct mobile application relies on proprietary technology that employs smartphone cameras to detect drug use or sobriety. Patients are asked to record a 10-second-long video of their eyes, using the Previct mobile application. This eye-scanning test is used to analyse eye biomarkers associated with pharmacodynamically induced pupil reactions, through a process known as pupillometry. “PrevictDrugs combines eye-monitoring sobriety tests with behavioural assignments as well as mood and emotions questionnaires, to help improve remote care,” explains project coordinator Maria Winkvist. The information is sent in real time to a healthcare professional through a cloud-based portal, allowing for fast feedback and optimal support. Using artificial intelligence (AI), the PrevictDrugs platform also evaluates patient data and identifies relapse patterns and risk, one of the biggest challenges for drug treatment today. This supports correct patient prioritisation and prompt intervention.

Advantages and impact on patients

PrevictDrugs comes as an add-on to the available support tools developed by the Kontigo Care company against alcohol and gambling addiction. These tools have demonstrated the value of remote digital addiction treatment and digital biomarkers. The Previct e-health solution was designed to assess the personal risk of relapse overall and to transform addiction management from reactive to proactive. Importantly, the communication tools motivate patients to make positive behavioural changes for long-term results. Also, the real-time monitoring offers a sense of safety to patients, who know that caregivers will promptly intervene in case of a relapse. PrevictDrugs offers convenience and complete privacy during drug screenings. Moreover, it is expected to enhance personalised therapy outcomes and result in notable cost-efficiency of out-patient treatments.

PrevictDrugs prospects

The PrevictDrugs project has appointed Kontigo Care to conduct a feasibility study: it offers a valuable understanding of the market, targeted users, competitive landscape, and regulatory pathways. “The unique nature of the PrevictDrugs platform provides a strong business case for its commercialisation,” emphasises Winkvist. Ongoing product development entails the optimisation of the working prototype and validation in a clinical setting. This will take place through addiction clinics across Europe. The Previct platform for alcohol and gambling is already in use in almost 50 % of the Swedish market; efforts to expand to Finland, Norway and the Netherlands are under way. Data collected so far constitute the biggest collection of addiction and behavioural information that can be employed to further improve AI-based predictions for relapse identification. Winkvist notes: “The Previct AI model could detect a relapse in addiction, three to five days in advance; we believe that in the future, it could be possible to detect a relapse as early as two weeks in advance.”


PrevictDrugs, drug, addiction, eye, alcohol, gambling, abuse, mobile application, AI, e-health, precision medicine, pupillometry