The platform
Enrollment, wearable data, safety monitoring, adaptive designs, managed data capture, and patient-led self-trials — the entire study on one platform. Here's what's inside.
Currently in preview. Product screens are illustrative; availability depends on your app version and study setup. Upcoming features remain labeled below.
Explore the platform
Save-and-resume assessments, queued actions, and clear recovery states for real life and imperfect connections.
Bring eligible activities closer to home, with participant reports and supported health records from connected devices.
Adverse-event review, post-exertional symptom patterns, and pacing context from check-ins and supported health records.
A structured personal study with repeated measures, single-subject analysis, and visible uncertainty.
Adaptive platforms with a real DSMB process, decentralized-first sites, clean data, CDISC export, and operations you can measure.
One source of truth
Researchers get a study workspace. Participants get a calm, guided app. Their records connect as data synchronizes, with role-based access and context about freshness and missing observations.
Left: the researcher's organization view — every study, its enrollment, and its principal investigator at a glance. Right: the participant's own studies and self-trials. Same data, two roles.
Good data starts with an experience people can actually live with. TrialPilot protects progress, handles supported work through weak connections, and makes the next step clear.
Save progress in supported assessments and resume within the study window. Check whether work is saved locally or has been received by the study.
Supported mobile check-ins, symptom reports, self-trial updates, and study actions can queue for synchronization. Check the saved or pending status; browser and security-sensitive actions have separate connectivity requirements.
TrialPilot shows when your work is saved or waiting to sync, then gives you a clear way forward if something needs attention.
Some moments should never be guessed at. Consent and security-sensitive actions stay online-only, with clear guidance instead of silent retries.
A participant’s address should not be the only factor in reaching research. TrialPilot supports remote activities, check-ins, and health sharing; study eligibility, visits, equipment, and support arrangements still determine how someone can take part.
Left: the coordinator watches assessment and check-in completion across the whole cohort. Right: the participant capturing symptoms from home — the moment that fills those columns.
Collect supported vital, activity, and sleep records through Apple Health and Health Connect, alongside symptom reports. Coverage and freshness depend on the device, permissions, and synchronization.
Review completion, engagement, and missing-data patterns to plan coordinator follow-up. These signals help identify questions; they do not establish whether someone will drop out.
Asynchronous check-ins and supported health sharing let participants complete eligible activities at home. Study teams determine how information is reviewed and followed up.
Use study criteria, self-screening, and coordinator review to evaluate eligibility. Combine outreach with practical participant support; measure representation rather than assume it.
Offer eligible activities closer to rural and underserved communities. Locations, approvals, language, equipment, and support still need to be planned for each study.
Share a link or QR code in an email, post, or flyer. Participants review eligibility and consent, then follow the enrollment process. Keep the study code when an app install is needed.
Review everyday health records alongside participant reports to explore within-person patterns. These tools are designed with energy-limiting and complex chronic conditions in mind; they do not diagnose a condition or replace clinical review.
Left: the researcher's PEM episode timeline, built from ordinary check-ins and wearable data. Right: the participant's pacing self-trial timeline, keeping daily check-ins and assessments together.
Record a safety concern and route it for review by the people responsible under the study’s procedures. Reporting and resolution are separate responsibilities, with permissions and a record of follow-up.
Bring participant reports and available health observations into review between scheduled visits. Staff coverage and study procedures determine response times; this is not an emergency service.
For ME/CFS and Long COVID studies, combine check-ins and supported health records to explore post-exertional worsening against the study’s definition. A participant report adds personal context; a detected pattern is not a clinical diagnosis.
Review personal heart-rate thresholds, time over threshold, and available resting-heart-rate and HRV context. Interpret pacing and orthostatic patterns with your clinician; they are not exercise targets or a prediction of how you will feel.
Capture beat-by-beat heart rate through assessments like the NASA Lean and sit-to-stand, with per-value provenance — device, manual, or corrected — that always keeps the original reading for a defensible record.
Supported coordinator check-ins use one-way templates with delivery limits and expiry. Notification settings, device permissions, synchronization, and study configuration affect whether a reminder appears.
Some people can't wait for the next big study. Self-Trials bring real single-subject methodology to them — without pretending an n-of-1 is something it isn't. They design it, run it, and read the result, right from the app.
Guided single-case studies pair repeated observations with on-device single-case and segmented-regression analysis. The method and available data determine what an estimate can support.
Choose your own primary endpoint — fatigue, cognition, autonomic symptoms — as a primary, secondary, or exploratory measure, over a duration you commit to up front.
Data-sufficiency indicators and provisional early signals keep uncertainty visible. A promising trend still needs careful interpretation and does not establish treatment effectiveness.
Review within-person summaries alongside missing observations, data quality, and prior self-trials. Follow the study’s reporting instructions for safety concerns.
Choose the sharing options supported for your personal self-trial. Review those choices separately from the consent and data obligations of any investigator-led study you join.
Shared, consented observations can help frame questions for further research. Aggregation does not remove bias or make a personal experiment equivalent to a controlled clinical trial.
Decentralized doesn't mean less rigorous. Underneath the calm app is the full apparatus a modern trial needs — adaptive designs, clean data, coding, locks, and exports — so your team can spend its time on the science instead of the plumbing.
Run a perpetual, multi-arm protocol with deterministic randomization, response-adaptive allocation inside preset guardrails, factorial domains, and a blinding firewall that keeps interim looks away from the people who shouldn't see them.
Every interim look is frozen and hashed. The statistical analysis center builds an open and a closed report from it, the DSMB records its recommendation against them, and each step traces to the same bytes. The people who prepare the analysis never vote on it.
Re-estimate an arm's sample size or enrich enrollment to the patients who benefit, only within bounds written into a locked rule. New arms go through the IRB first, and first-in-human arms start with gated sentinel cohorts.
Add sites for the visits home can't do, like a scan or an infusion, and say why each one needs a clinic. Every participant gets a site of record, and risk and enrollment are tracked by site.
Each sponsor sees only its own arms, from its own organization, and never an interim result. When its arm leaves the platform, it receives a frozen data package with its arm and concurrent controls only.
Data collection time, cleaning time, decision turnaround from each interim cut, dataset build time, enrollment forecasts by site and arm checked against reality, and cost per arm from an append-only ledger.
Serious adverse events are compared between the safety workflow and the trial dataset before lock. Every disagreement becomes a query, and a missing event can be copied across with its source recorded.
A versioned, fully audited managed dataset with an edit-check engine and a query workflow — discrepancies get caught and resolved in the flow, not in a spreadsheet three months later.
Review coded terms and tracked queries with an attributable history. Licensed MedDRA and WHODrug dictionaries are not connected in the preview; supplying and validating those connections is separate work.
Use soft and hard database locks with audited unlocks, plus supported CDISC SDTM and define.xml generation. Validate mappings and outputs for your protocol and intended submission.
Plan connections to research tooling around available APIs and exports. EHR, laboratory, and vendor integrations require separate scoping and validation.
Participant identity lives apart from clinical data at the database boundary. De-identified coordinator views and study-scoped permissions define how teams access research records.
Coming next
A look at the next participant experience. These features are in development and are not yet released.
Configure questionnaires, check-ins, wearable sharing, visits, intervention logs, supplies, and payments. Optional work stays separate from required completion.
Sites can also link an already-enrolled participant to an approved app activity plan while preserving their original study timeline.
See what needs attention, what is coming up, what is waiting, and what is complete. Quiet weeks stay quiet, and saved-on-device work is clearly labeled until received.
The plan brings assigned activities, visits, kit updates, payment records, routine help requests, and released summaries together.
Offer approved home, site, or local-provider visit options. Participants can request an available alternative for the team to arrange.
Completed questionnaires stay complete when an arrangement changes. Provider availability and clinical suitability are confirmed by the site.
Give routine requests an owner, acknowledgment, status, and outcome. Participants can follow progress and reopen a request when they still need help.
Device, visit, kit, callback, and study questions stay distinct from urgent safety reporting. Staff email requires a configured delivery service.
Before you plan your study
Built-in health sharing uses Apple Health and Health Connect. EHR, laboratory, EDC, courier, and provider-calendar connections require separate scoping; named vendor connectors are not included in this preview.
Audit trails, consent workflows, and exports support study processes. They do not certify regulatory compliance. Sponsors and sites must qualify their intended use, approvals, and operating procedures.
Browser-compatible studies support participation without an install. Some activities and native health-data collection require the mobile app. Available options depend on the study; provider arrangements remain site-coordinated.
