Predict Health Lab proposes a new clinical approach to identify health risk earlier — combining advanced biological data, longitudinal monitoring and Explainable Artificial Intelligence.
A Predictive Health Programme proposed for the United Arab Emirates.
LOCAL DATA. CLINICAL INTELLIGENCE. EARLIER ACTION.SCROLL TO EXPLORE ↓
01 / The missing link
THE UAE HAS BUILT THE DIGITAL FOUNDATION.
The UAE has made major advances in healthcare digitalisation, health data infrastructure, interoperability and artificial intelligence.
Yet technology alone does not prevent disease. The next challenge is to transform health data into the ability to recognise risk earlier — while there is still time to act.
ADVANCED HEALTHCARE
HEALTH DATA
DIGITAL INFRASTRUCTURE
ARTIFICIAL INTELLIGENCE
DATA
PATTERNS
PREDICTION
EARLIER ACTION
THE NEXT STEP IS NOT SIMPLY MORE DATA. IT IS KNOWING WHAT THE DATA CAN PREDICT.
02 / Why local data matters
AI LEARNS FROM DATA. POPULATIONS ARE NOT IDENTICAL.
Predictive models learn from the populations represented in their training data. Genetics, metabolism, epigenetics, microbiome, diet, lifestyle and environment can influence how disease develops and how risk appears over time.
A model developed predominantly from other populations should therefore not simply be assumed to perform identically in the Emirati population.
04 / From a focused cohort to larger-scale potential
DEEP LEARNING FROM A FOCUSED COHORT. POTENTIAL IMPACT FAR BEYOND IT.
The programme does not propose advanced biological testing for an entire population. Instead, a focused cohort is characterised in depth to identify relationships between advanced biological signals, routine clinical data and longitudinal disease trajectories.
If those relationships are successfully validated, the resulting knowledge could then be translated into risk criteria applicable to relevant health data already available within the UAE healthcare system.
UP TO 1,000 DEEPLY CHARACTERISED PARTICIPANTS
BIOLOGICAL + CLINICAL + LONGITUDINAL DATA
EXPLAINABLE AI
CANDIDATE PREDICTIVE SIGNATURES
CLINICAL VALIDATION
VALIDATED RISK CRITERIA
EXISTING UAE HEALTH DATA
POPULATIONS PRIORITISED FOR EARLIER EVALUATION
LEARN DEEPLY FROM A FOCUSED COHORT. BUILD THE FOUNDATION FOR LARGER-SCALE PREDICTIVE HEALTH.
Subject to clinical validation and UAE health-system governance. Risk prioritisation is not diagnosis; clinical decisions remain under medical supervision.
05 / Evidence before expansion
PROVE FIRST. SCALE SECOND.
Any broader implementation would follow clinical validation, measured outcomes and an explicit decision by the UAE.
Phase IBUILD → LEARN → VALIDATE → MEASUREEvidence and evaluation
UAE DECISION
Potential next phaseINTEGRATE → PRIORITISE → EXPANDSubject to successful validation
06 / The people behind the programme
BUILT BY SCIENCE. DESIGNED FOR CLINICAL REALITY.
Luis Perea
Co-Founder & CEO · Project Architect
Ricard Huélamo
Co-Founder & CEO · Strategy Director
Dr. Xavier Aldeguer
Medical Director
Prof. Josep Vehí
Chief Technology Officer
Marc Cirera
UAE Pilot Coordinator
CLINICAL MEDICINE · MICROBIOME · ARTIFICIAL INTELLIGENCE · DIABETES · PREDICTIVE HEALTH
Predict Health Lab is seeking an institutional dialogue with the UAE to explore the proposed Predictive Health Programme and the framework required for its clinical validation.
