Pharma & biotech
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.
The challenge
Evidence teams depend on site visits, paper diaries and retrospective claims or EHR extracts. Each source sees a slice: claims show what was billed, EHRs show what happened in clinic, and diaries show what patients remembered. What patients experience day to day, after enrollment and after launch, is largely missing, and long-term follow-up is costly to sustain through sites.
Toggle the chart to compare what a visit-based record shows with what the continuous record shows for the same synthetic patient.
PRO score (0–24) over 120 days
Observations3
Events in periodNot visible
Events with no nearby visit3 of 3
Illustrative · synthetic data
Site burden
Visits are expensive
Every additional assessment adds cost for sites and participants.
Diaries
Incomplete data
Paper and recall-based diaries weaken endpoints.
Post-launch
Evidence gap
Real-world response data after approval is limited and slow to obtain.
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 fatigue burden
Treatments and interventions
Exposure · dose · reported experience
Behavior and daily life
Average daily activity
Week 4 / Disease4 /10 · Structured experience report
Week 4 / TreatmentInterval · No administration recorded this week
Week 4 / Behavior25 min · Short walks resumed
Separate measures and independently scaled channels; values appear in their own units. Temporal alignment does not establish causality.
Use cases
Between-visit data to support enrichment and digital endpoint work.
Years of follow-up after one-time and gene therapies, without constant site visits.
Continuous natural-history data across dispersed patient populations.
Real-world outcomes evidence for payer and HTA conversations.
An engagement app that supports patients and captures what matters.
Implementation
Endpoints, populations, regions and data channels.
Center-agnostic, worldwide: US, Middle East, Europe.
Sites begin collection after protocol, consent, configuration, and source checks.
One longitudinal record per patient, across sources.
Exports and views for clinical, medical affairs and HEOR.
Products used
Configurable disease profiles and structured PROs for patients, in one app.
Explore this workflowCohort-level questions, trajectory summaries and response patterns across the program.
Explore this workflowCohort views, RWE and research exports, and APIs for your data science teams.
Explore this workflowBenefits
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 evaluationWhat each stakeholder receives
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.
Clinical operations
Track PRO completion by site and week, and see where follow-up is slipping.
Medical affairs
Consented, aggregated trajectories after launch support scientific exchange and evidence planning.
HEOR
Person-week datasets with a data dictionary, ready for analysis.
Worked examples
Sponsor and CRO
Week 0
Participants onboard via the app at the site visit.
Weekly
MG-ADL and fatigue reported remotely.
Week 8
Completion dashboard flags one site for support.
Database lock
Remote and site data delivered as one dataset.
Illustrative · synthetic data
Medical affairs
Launch
Patient program offers the app.
Months 1–6
Consented real-world response captured.
Month 6
Descriptive report supports evidence planning.
Illustrative · synthetic data
Evidence
Joined Mayo Clinic Platform's Solutions Studio; participation is not clinical validation.
Required approvals depend on the research protocol and responsible institution.
Patient counts, observation periods and evidence reviews are stated per study.
Clarrio.ai does not diagnose, treat, or replace clinical judgment.
Therapeutic areas
FAQ
Also see Longevity & preventive health and Health systems & hospitals.
Request a demo
Explore how clinical, treatment and behavioral information align around your program and the research or review questions your team needs to answer.
Opens the Calendly booking page in a new tab.
Prefer to write first? Send an inquiry and the team will reply.