For research and industry
The rare disease research ecosystem has sophisticated infrastructure for two types of data: clinician-assessed clinical data and patient-reported outcome data collected at scheduled timepoints. The type it lacks is the third — the continuous, ecologically valid observations that describe what living with a rare disease actually involves on the days when no clinician is watching and no questionnaire has been scheduled. That is what Wimly generates.
Existing patient-reported data platforms face a structural problem that compromises their scientific value: engagement decay. Patients complete intake questionnaires, submit initial observations, and disengage — producing datasets skewed toward early-stage, highly motivated participants and missing precisely the long-term continuous observations that give longitudinal studies their scientific value.
The cause is design: platforms built to extract data from patients for clinical or research purposes give patients no immediate reason to keep contributing. The patient's experience of using them is extractive — they contribute and receive nothing of personal value in return. Rational disengagement follows.
Wimly resolves this at the architectural level. Every patient interaction returns something of value in the same session — structured personal insight, clinical connection, or community knowledge. Patients do not contribute for researchers and wait for value later. They contribute because the platform is immediately useful to them, on every day they use it, including the worst ones. The longitudinal dataset that results does not suffer from the engagement decay and selection bias that undermine every existing patient-reported data collection platform. The data is better because the patient's experience of generating it is better.
The dataset
Continuous, not episodic
Patient observations are generated daily, not at scheduled clinical timepoints. The dataset captures the progression between appointments — falls, functional changes, medication responses, adaptive strategies — with temporal resolution that no registry questionnaire or scheduled PRO instrument can approach.
Ecologically valid
Observations are generated in the patient's daily environment, not in a clinic waiting room under assessment conditions. The fatigue pattern that follows exertion by two days. The speech change that is worse in the afternoon. The balance variation correlated with sleep quality. This is what ecological validity means in practice — and it is what differentiates Wimly data from any clinical or trial-endpoint dataset.
Domain-structured and machine-readable
Every observation is tagged at input by functional domain, disease stage context, and temporal markers. The dataset is not unstructured text mined retrospectively for signals — it is structured from the moment it is generated, producing data with the organisation and consistency required for downstream analysis without extensive preprocessing.
Paired patient-clinician records
The Continuous Care Layer generates a data type that does not exist elsewhere: patient self-reported observations paired with clinician acknowledgements — including clinical response, any action taken, and the temporal relationship between patient-reported change and clinical recognition. This pairing provides contextualisation that no purely patient-reported or purely clinical dataset offers independently.
Consent-governed and patient-transparent
Research contribution is a separate, explicit, granular patient consent decision. Patients can see exactly what data is shared, with which organisations, and for what stated purpose — at all times, through a governance transparency portal. Consent is revocable. The patient is a knowing participant, not a data source.
Research use cases
Natural history studies
Continuous daily observations from a longitudinal cohort provide progression data at a temporal resolution that bi-annual clinical assessments cannot achieve. Disease trajectories, variance patterns, and the relationship between patient-reported functional change and clinical measurement become visible in a way the current evidence base does not support.
Trial endpoint development
Trial endpoints should reflect what matters to the people living with the disease. Patient Intelligence data provides a continuous record of what patients actually notice, track, and consider significant — the empirical foundation for outcome measures that reflect patient reality rather than measurement convenience.
Regulatory real-world evidence
Regulators increasingly require real-world evidence alongside trial data. Patient Intelligence is a category of real-world evidence that sits alongside clinician-assessed outcomes and traditional PRO measures — continuous, ecologically valid, and generated under a consent and governance architecture designed to meet regulatory standards.
PRO instrument development and validation
The observations patients actually make about their disease — the dimensions of experience they track spontaneously, the language they use, the temporal relationships they notice — provide the empirical basis for developing PRO instruments that capture what patients consider meaningful, not just what researchers have historically found measurable.
The thing that floored me was the granularity. Traditional outcome measures give me a snapshot every three months. Wimly gave me a continuous stream of patient-reported observations with timestamps, context, and consistency I couldn't have designed a better instrument for. And the patients didn't even know they were generating research-grade data. They were just living their lives.
Rare disease researcher
Self-assessment
A short self-assessment to identify which collaboration model fits your organisation's current priorities.
Access to structured research data is provided through a formal governance pathway: tiered consent architecture (patients select granular levels of data sharing), anonymisation pipelines, a published Data Trust Covenant that defines permissible use categories, and a governance transparency portal where patients can see who has accessed their data and for what purpose. Consent is patient-initiated, granular, and revocable. Research access is not a default — it is an explicit opt-in, separate from the patient's core platform consent.
Through design, not obligation. The platform is built around a single principle: every patient input must return something of value in the same session. Patients do not log observations for researchers and wait for value to arrive later — they log observations and receive structured personal insight, clinical connection, or community knowledge immediately. The minimum viable interaction is designed for the worst day, not the best one. This is not a retention strategy — it is an architectural constraint. The result is a longitudinal dataset that does not suffer from the engagement decay and dropout bias that compromise existing patient-reported data platforms.
The Continuous Care Layer generates a data type that does not exist elsewhere: patient self-reported observations paired with clinician acknowledgements of those observations — including the clinician's structured response, any clinical action taken, and the temporal relationship between patient-reported change and clinical recognition. This pairing provides a level of clinical contextualisation that no purely patient-reported dataset and no purely clinical dataset can offer independently. It has specific scientific value for natural history studies, PRO instrument validation, and regulatory real-world evidence submissions.
Research access is provided through the formal governance pathway described above — a submitted research proposal reviewed against the Data Trust Covenant, patient community consent, and an agreed data sharing agreement. The research gateway is not yet active; access will be available once the SCA community reaches sufficient scale to generate statistically meaningful longitudinal data. If your organisation is interested in a research partnership or wants to be notified when the gateway opens, contact us through the contact page.
Get early access
Wimly is here.
Wimly v1 is approaching. Founding supporters get access on day one and a role in shaping how the platform develops.
