Why disease flares, variability, and treatment response are difficult to understand in autoimmune conditions
Understand how autoimmune disease progression, flare dynamics, treatment experience, and outcomes unfold in the real world, including symptoms, function, and behavior that are not captured in claims or clinical data.
See autoimmune disease dynamics in your population
Claims and clinical data show what happened. They don’t explain:
- How flares emerge, evolve, and resolve between clinical visits
- How symptoms and function vary within the same individual over time
- How patients respond to treatment in real-world settings
- What drives disease burden and variability across populations
- How disease activity and symptom burden evolve between clinical visits and across real-world settings
- What triggers autoimmune disease flares in the real world?
- How do symptoms and functional impact change over time?
- How do patients respond to treatment outside clinical settings?
- What biological signals are associated with flare onset and resolution?
- How does real-world disease variability differ from clinical trial assumptions?
This enables:
- Longitudinal tracking of disease activity within the same individuals
- High-frequency insight into symptoms, flares, and functional impact
- Triggered biospecimen collection at the time of disease activity
- A more complete understanding of treatment response beyond clinical settings
Who patients are
- Age, sex, gender identity, race and ethnicity
- Income, education, employment, and household structure
- Insurance type, out-of-pocket costs, affordability perception
- Access barriers including transportation, food, and care access
What patients experience
- Daily flares, pain, fatigue, and disease activity captured through high-frequency patient-reported outcomes
- Validated instruments (e.g., HAQ-DI, BASDAI) to quantify symptom severity and variability
- Within-patient variability in disease experience over time
What patients do
- Activity levels, sleep, and heart rate captured through connected devices
- Impact on work productivity, participation, and daily function
- Behavioral patterns associated with disease activity
What shapes treatment experience and response
- Medication history, persistence, and adherence patterns
- Switching behavior and patient-reported treatment response
- Real-world treatment experience across therapies
What biological signals are associated with disease activity
- Biospecimen collection during flare events
- Biomarker data linked to symptom dynamics and disease activity
- Integration of molecular and patient-reported data
Why disease burden varies across patients
- Differences in symptom severity and progression
- Variability in treatment response
- Impact on quality of life and daily function
What clinical data adds
- Diagnoses, comorbidities, and disease history from clinical records (EHR)
- Procedures, specialist visits, and treatment history
- Healthcare utilization patterns across clinical settings
Real-world outcomes and experience
- Disease progression and flare patterns over time
- Functional impact and quality of life
- Long-term treatment response and disease control
Evidation partners include top biopharma companies , as well as consumer health companies, technology companies, non-profit organizations, and government agencies.











work with us