Development of a Predictive Digital Biomarker Using Remote Breathalyser Monitoring in Alcohol Use Disorder (BRISA)
A digital tool predicting alcohol relapse using clinical background, daily breathalyser samples and machine learning
BRISA is a collaborative public-private project between Amsterdam UMC, Dedimo Research & Development, and UPC-BarcelonaTech. The aim is to develop a digital biomarker that supports remote clinical treatment for Alcohol Use Disorder (AUD) using data collected from clinical records, daily breathalyser tests and questionnaires.
Alcohol use is one of the largest causes of preventable disease worldwide. In the Netherlands alone, it is associated with up to €4.2 billion in societal costs annually. AUD affects a large and diverse population, yet many individuals never seek care due to stigma, accessibility issues, or a lack of resources. Innovation is needed to improve treatment outcomes and reach patients in their everyday environments, besides improving effectivity by preventing relapse during and after treatment.
This project introduces a predictive biomarker based on breathalyser data, clinical information, and l questionnaires. Machine learning is used to analyse the interaction between submitted samples, missed tests, and personal clinical data to assess the risk of relapse or treatment dropout. The digital biomarker aims to give clinicians a clearer view of patient status and empower timely, data-driven intervention decisions. The aim is to improve the effectivity and efficiency of remote intervention, improving accessibility for those in underserved or rural regions.
Deliverables include a validated digital biomarker, a clinician support tool, and an implementation guideline for integration into clinical workflows. By the project’s end, we aim to demonstrate reduced treatment burden, improved patient adherence, and a personalised care model that is both scalable and economically efficient.
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