Clinical decision support
RAID-ML
Prediction model
Super Learner ensemble predicting 6-month treatment outcomes using baseline RAID domains.
Development
Validation
External trials
MDR launch
Precision medicine for RA
Better treatment decisions for rheumatoid arthritis.
Advancing precision medicine for Rheumatoid Arthritis (RA) through machine learning to predict treatment outcomes and close the remission gap.
Why it matters
RA care still depends too much on trial and error.
Rheumatoid arthritis treatment has advanced dramatically, yet many patients still move through months of uncertainty before finding an effective therapy.
That delay can mean persistent inflammation, worsening fatigue and function, and avoidable pressure on specialist services.
Tobora focuses on the decision point before escalation becomes obvious: using baseline and early clinical signals to support a more precise first treatment strategy.
Methotrexate remains the cornerstone of early RA therapy. However, 50-60% of patients still fail to achieve clinical remission.
Disease context
RA is common enough to demand better tools.
Estimates vary by case definition, age group, registry vs survey source, and study year; not directly comparable across countries.
RA prevalence by region
% pop.
Global average
0.46%
Norway
0.78%
Sweden
0.77%
Finland
0.80%
USA
0.60%
Canada
1.20%
United Kingdom
0.67%
China
0.42%
India
0.49%
Brazil
0.60%
Pipeline
Interactive tools moving from research toward practice.
Patient engagement
Tobora Record
Digital record
Dynamic patient-reported outcome tracking for RAID, DAS28, and longitudinal monitoring.
Prototype
Beta testing
Deployment
Strategic partners
Built with clinical and academic collaborators.
