Therapeutic area · Epilepsy, myasthenia gravis, migraine
Seizures, migraine attacks and neuromuscular fluctuations happen at home, at work and overnight. Clarrio.ai connects those moments to the clinical record so research and care teams see the full course of disease. Align clinical, treatment and behavioral information on one shared longitudinal timeline, where available and appropriate to the program.
What Clarrio.ai captures
Longitudinal health intelligence
Align clinical observations, medication or intervention history, and daily-life context without losing source meaning. Available data and review boundaries depend on the program.
One person / one shared timeline
Illustrative research data · Synthetic demonstration
Health and disease trajectories
Reported headache days / week
Treatments and interventions
Exposure · dose · reported experience
Behavior and daily life
Average sleep
Week 4 / Disease4 days · Symptom diary
Week 4 / TreatmentDose change · 20 mg daily recorded
Week 4 / Behavior6.1 h · Lower activity reported
Separate measures and independently scaled channels; values appear in their own units. Temporal alignment does not establish causality.
The evidence gap
Neurology relies heavily on what patients remember. Seizure diaries, headache calendars and fatigue scales are completed on paper or recalled at the next visit, weeks after the events themselves. Recall is selective: recent and severe episodes are remembered, mild or nocturnal ones often are not.
Context is missing too. Sleep disruption, stress, missed doses and menstrual timing are well-known factors around episodic neurological conditions, yet they are rarely recorded alongside the event. For research teams this means sparse endpoints, wide variance and costly site visits to fill the gaps.
Epilepsy
Nocturnal and focal seizures are under-reported in self-kept diaries, weakening frequency endpoints.
Migraine
Attack frequency, duration and acute-medication use change week to week; monthly recall blurs that pattern.
myasthenia gravis
Fatigable weakness fluctuates within days; a clinic snapshot can miss the worst periods entirely.
Multiple sclerosis & Parkinson's
Mobility, fatigue and cognition drift gradually, and the drift is hard to see from quarterly assessments.
The challenge
Seizures, migraine attacks and myasthenia gravis fluctuations are episodic. A neurologist typically sees a patient a few times a year and relies on recall or paper diaries to understand everything in between. Diaries are incomplete, recall is biased toward recent or severe events, and context such as sleep, stress or missed doses is rarely captured alongside the episode.
Toggle the chart to compare what a visit-based record shows with what the continuous record shows for the same synthetic patient.
Symptom score (0–10) over 120 days
Observations2
Events in periodNot visible
Events with no nearby visit3 of 3
Illustrative · synthetic data
Recall
Diaries fill in late
Entries are often completed just before an appointment, weakening their accuracy.
Context
Triggers go unrecorded
Sleep, stress and adherence are rarely linked to the episode they preceded.
Evidence
Weak real-world data
Pharma teams lack continuous, structured data on response in everyday life.
How Clarrio.ai addresses the gap
Structured event capture
Patients log episodes in seconds in the Patient App, with time, duration, severity and optional triggers.
Passive context
Sleep, activity and heart rate from consented wearables are aligned to each logged event.
Validated questionnaires
Disease-specific PROs scheduled at protocol-defined intervals, with reminders that adapt to completion.
Clinical linkage
Diagnoses, medications and visit notes integrated via FHIR/HL7 so events sit next to treatment history.
Data captured
Select a layer. Exact sources depend on deployment configuration and data permissions.
Captured from patients or caregivers in the Patient App.
Product workflow
Select a step to see what happens. Sources are captured through the Patient App and integrations, harmonized on the Platform and summarized by Intelligence.
Sources
Clarrio.ai workflow
Outputs
Stakeholder outputs
Each role receives a different view of the same longitudinal record. Values are synthetic.
Neurologist
A chronological view of episodes since the last visit, each with sleep, activity and medication context.
Patient
Patients log an episode in seconds, and can see their own patterns over time.
Medical affairs
Aggregated, consented data shows how symptom scores evolve across a cohort in everyday life.
Worked examples
Patient with myasthenia gravis
Day 1
Weekly MG-ADL completed in app.
Day 58
Fatigue rises; patient logs poor sleep.
Day 63
Score returns toward baseline.
Day 100
Neurologist reviews the episode with its context at the visit.
Illustrative · synthetic data
Patient and caregiver
Week 1
Caregiver logs events on the patient's behalf.
Week 3
Cluster linked to missed doses.
Visit
Timeline replaces paper diary in the consultation.
Illustrative · synthetic data
FAQ
Research & operational outputs
90-day episode timeline
Every event with sleep, activity and medication context on one axis.
Responder characterization
Cohort views comparing episode patterns before and after treatment start.
Adherence summary
Dose confirmations aligned with episode clusters, for exploration, not attribution.
Data-completeness report
Per-participant coverage so study teams know where follow-up is needed.
Pharmaceutical & biotech
Denser, more complete real-world endpoints for observational studies and post-launch evidence.
Hospitals & neurologists
A dated summary of the period since the last visit, instead of reconstructing it from memory.
CROs & research teams
Remote collection that reduces site visits and manual diary transcription.
Patients & caregivers
A quick way to record what matters, and a clearer conversation at the next appointment.
Program evaluation
These are the KPIs we agree with customers before deployment, measured against their own baseline. Data coverage, patient experience and clinical outcomes answer different questions. Higher engagement alone does not demonstrate better health or lower utilization.
Explore benefits and evidence| Lever | How it is measured |
|---|---|
| Data completeness | Share of expected diary days with an entry |
| Questionnaire completion | PROs completed on schedule relative to PROs due |
| Study retention | Participants active at study end relative to enrolled |
| Reconciliation time | Staff hours spent transcribing and querying diaries |
| Cost per analyzable patient | Total collection cost relative to participants meeting completeness threshold |
Illustrative use case
Medical affairs team, illustrative
Month 0
Protocol defines attacks, acute-medication use and MIDAS at baseline and month 3.
Months 1–3
Participants log attacks in the app; wearables add sleep context automatically.
Month 2
Completeness report flags 14 participants with gaps; coordinators follow up remotely.
Month 4
Analysis-ready dataset exported with data dictionary and audit trail.
Illustrative · synthetic data
Clarrio.ai has joined Mayo Clinic Platform's Solutions Studio, supporting its mission to advance interoperable, data-driven healthcare innovation. This does not imply endorsement or clinical validation.
Explore Neurology RWE Solutions
Explore Neurology RWE SolutionsEvidence interpretation
Separate patient diaries, caregiver observations and device signals. An unanswered diary is not an episode-free day. Functional impact and recall periods matter when selecting questionnaires and when translating the record into evidence for care teams or payers.
Benefits in practice
Pharma & biotech
Routine records can describe encounters and prescriptions while leaving daily function, symptom burden and experience under-observed. Adding remote data can fill selected gaps, but a large dataset is not automatically decision-ready. Population selection, questionnaire suitability, exposure timing and missing observations can all change the interpretation of a longitudinal analysis.
01
Define the population, observation window, outcome concept and intended decision before selecting sources.
02
Combine appropriately scoped Patient App reports with available clinical and device data in the Platform; keep reported experience separate from recorded events.
03
Use source-aware review to inspect context and quality. Agree variable definitions, analysis methods and limitations with the study team.
Clinical development, medical affairs and HEOR teams can work from a common record while asking different questions. Clinical operations needs coverage by site and timepoint; an evidence analyst needs definitions and provenance; medical affairs needs an account of the population and study limitations. Those outputs should not be treated as interchangeable.
Participants have a structured way to contribute the experience that encounters may miss. Questions should be meaningful, proportionate and appropriate to the population. Explain the study purpose, who reviews submissions and whether reporting receives an individual response; a research diary is not an emergency service.
A payer-facing evidence package should connect patient experience to a defined decision question and relevant population. Include baseline characteristics, follow-up, missingness and the analysis method. Patient-reported experience can complement other evidence, but it does not alone establish comparative effectiveness, economic value or a coverage recommendation.
Workflow illustration · not a customer result or live record
Assess suitability against the research question: provenance, completeness, accuracy and relevance. Predefine the analysis rather than choosing a favorable pattern after viewing the results. Publication and payer use require appropriate scientific review.
Explore evidence and evaluationPayers & health economics
Claims and encounter datasets can describe recorded utilization without fully capturing function, experience or the practical burden of a program. Patient reports add a different perspective, but they can be incomplete or drawn from a population unlike the members covered by a payer. The task is to establish whether those observations are suitable for a specific appraisal question, not to turn engagement into a savings claim.
01
Specify the relevant covered population, decision, comparator where needed and evaluation horizon.
02
Review provenance, participation, measurement windows and missingness before examining results.
03
Combine appropriately governed patient experience with relevant clinical or utilization evidence; document assumptions and limits for expert appraisal.
HEOR and population-health teams can examine how reported experience varies across the observation period and which groups are represented. A useful output explains the denominator behind a measure and the observations excluded from analysis. Governance must also define the permitted purpose of any linkage to payer-held data.
The member perspective should remain visible in a program evaluation: burden, everyday function, access and what participants consider meaningful. Reporting should not become an unexplained condition of receiving services. Explain the collection purpose and permitted uses in a way members can understand.
Decision support means an inspectable evidence package, not an automatic reimbursement verdict. Include the target population, relevant baseline differences, data sources, follow-up and limitations. Cost and utilization conclusions need appropriate data and analysis; neither can be inferred from app activity or observation coverage.
Workflow illustration · not a customer result or live record
Separate program participation, patient-reported experience, clinical outcomes and economic endpoints. Define each before collection, use an appropriate comparison where the question requires one and examine whether findings transfer to the covered population.
Explore evidence and evaluationPatients, members & caregivers
A person can complete many questions without understanding why they are being asked or who will read the answers. Device observations may look precise while missing personal context. A useful longitudinal journey starts with the person's priorities and makes the reporting purpose, burden and review arrangements understandable.
01
Agree what the care or research program needs to learn and what participation involves.
02
Use appropriate reports alongside available observations; distinguish the patient's own answers from caregiver observations.
03
Discuss a dated interval with the responsible professional, including what is missing and what matters to the person.
Teams gain context for a more specific conversation, but should not assume that a missed report means a person disengaged. Accessibility, fatigue, language and connectivity may affect reporting. Define support and review arrangements before introducing new questions.
Patients and members can keep a dated account of experiences they might otherwise forget. Caregivers can contribute observations when appropriately scoped, without replacing the person's own perspective. Personal patterns invite discussion; they are not instructions or proof that a particular routine produced an outcome.
A program's apparent reach can hide who could not participate. Payers and commissioners should examine access, reporting burden and representativeness alongside outcome evidence. Patient experience is an important perspective in appraisal, not a shortcut to an economic conclusion.
Workflow illustration · not a customer result or live record
Ask whether reporting is understandable, manageable and meaningful. Examine completion alongside accessibility and support needs. A high completion rate alone does not show that people feel heard or that a program has improved their health.
Explore evidence and evaluationRelated solutions
Investigate disease trajectories, treatment exposure and patient experiences in real-world settings. Clarrio.ai aligns clinical, treatment and behavioral observations to support defined research questions.
See solutionConnect clinical information with longitudinal treatment and patient-generated data for research and appropriate healthcare workflows. A shared timeline preserves source context for professional review.
See solutionRequest a demo
Explore how clinical, treatment and behavioral information align around your program and the research or review questions your team needs to answer.
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