OUD
Opioid use disorder
Primary indication
~40M
people globally · WHO 2024
Stage
TRL 5 · prototype in clinical use
Subreal Limited · London · est. 2024
Making addictions predictable.
Subreal is building the predictive layer for addiction medicine — across neurological, physiological and psychometric signal, from regulated clinical software to a foundation model for recovery and the medicines that will follow.
·Backed by · Built with · In partnership with
02The Problem
Relapse and deterioration are detected too late — after disengagement or crisis.
Substance use disorders are chronic, and relapse is part of recovery. The clinical tools we monitor with — sporadic questionnaires, self-reported craving and mood scales — were not built to catch the moment-to-moment changes that prevention requires.
They are prone to recall bias, social desirability, and long gaps between contacts. By the time the next appointment arrives, the window for intervention has often closed.
40–60%
Relapse within 1 year
of discharge from SUD treatment
4–5
Treatment cycles
before long-term recovery (~2 yrs average)
#1
Cause of death
in US adults aged 15–49 — overdose
03Programs
One company, three surfaces — clinical software, a foundation model, and the medicines that follow.
Subreal works across the data, model and intervention layer of addiction medicine. Each programme reinforces the others — clinical deployment generates the longitudinal record, the record trains the model, and the model opens routes to better treatment.
01
Subreal-CARE
Regulated clinical software
A class IIb investigational SaMD for opioid, alcohol and benzodiazepine use disorders. A patient app and clinician dashboard turn neurological, physiological and psychometric signal — captured through short video check-ins and digital biomarkers — into near-term risk and a route to intervention.
02
Subreal-General
Foundation model · RECOVERY-FM
A multimodal foundation model for addiction recovery. Pretrained on longitudinal patient journeys — EHR timelines, clinical notes, prescriptions, psychometrics and digital biomarkers — then adapted to relapse, overdose, disengagement and pharmacological-response tasks.
03
Discovery
Evidence & medicines
An emerging programme using our data and models to support evidence generation and the discovery of new pharmacotherapies for addiction — including GLP-1 receptor agonists studied via brain organoids and prospective neurological cohorts.
“We bring objectivity to a field that has, for too long, relied on what the patient remembers to tell us.”
04Indications
Three indications, one regulated system.
Subreal-CARE is built as a single platform configured for three substance classes that account for the majority of preventable relapse, overdose and treatment dropout worldwide.
AUD
Alcohol use disorder
Primary indication
~400M
people globally · WHO 2024
Stage
TRL 5 · prototype in clinical use
BZD
Benzodiazepine use
Secondary indication
~30M
long-term users · est.
Stage
TRL 4 · feature extension
Stable operational performance, integration with UK addiction services, and full medical-device conformity (Class IIb) are the upcoming milestones across all three indications.
05Research
Built on evidence generation, not press releases.
05.1 / Active studies & collaborations
- PaperCHEATA · Nottingham University Hospitals NHS TrustJMIR · 2025 · doi.org/10.2196/87186
- ProtocolUniversity of Sheffield HallamOSF protocol · doi.org/10.17605/OSF.IO/9WXGV
- QualitativeDigital health from the patients' perspective: a thematic analysis of semi-structured interviewsUniversity of Sheffield Hallam
- PolicyInnovation pathways in addiction: funding, R&D, commercialisation — a global study of longitudinal pathways of innovative companies in addictionUniversity of St Andrews
05.2 / Near-future research
Here are some of our future research directions. Let us know if you can engage.
GLP-1 inhibitors in addiction
via brain organoids and drug-interaction studies
Prospective neurological cohorts
including fMRI in active addiction recovery
NLP on clinical notes
predicting patient outcomes from free-text records
Propose a collaboration→michal.bartler@subreal.io
06Method
A five-step loop, repeated until the risk drops.
Built to medical-device standards. The same loop feeds Subreal-CARE today and the longitudinal record that Subreal-General will learn from tomorrow.
- M1CaptureShort video check-ins, validated psychometrics and passive app-use phenotyping — collected daily inside the patient app, designed to feel like care, not measurement.
- M2ExtractVideo is converted into digital biomarkers spanning neurological, physiological and psychometric signal — a multimodal feature set unique to each patient.
- M3PredictOur model fuses these biomarkers with the patient's longitudinal history to estimate near-term risk of relapse and overdose.
- M4EscalateWhen risk crosses a pre-specified safety threshold, the treating team is alerted with the context that matters.
- M5InterveneThe clinician decides — contingency management, motivational interviewing, or pharmacological action. We surface, they treat.
08Team
Michał Bartler
Founder & CEO
“What if we could predict relapse and overdoses, and make the whole recovery journey more predictable?”
M. Bartler · Founder & CEO
Michał founded Subreal in 2024 to build an AI-based Software as a Medical Device for substance use disorders. Subreal is a Polish-British company headquartered in London and operating across the UK clinical research ecosystem.
The team works at the intersection of digital biomarkers, machine learning and regulated medical software — and partners with academic groups across St Andrews, Nottingham, Sheffield Hallam and Birmingham.
08.1 / Advisors
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