Explore the platform
Everything in the platform.
Decentralized & wearables
Run a trial without a building. Continuous, real-world data from the devices people already wear.
Safety & physiology
Adverse-event escalation, objective crash detection, and pacing — read from the body, not a questionnaire.
Patient-led self-trials
A rigorous n-of-1 study anyone can run, with an honesty layer that refuses to overclaim.
Research operations
Adaptive platform designs, electronic data capture, CDISC export, and an audit trail that holds up.
One source of truth
One study, two points of view.
Researchers get a real-time command center. Patients get a calm, guided app. Both look at the same data the moment it's collected — no exports, no reconciliation, no lag.
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.
Built to run a trial without a building.
A site shouldn't decide who gets to join the research. TrialPilot reaches participants wherever they are, captures real-world data continuously, and keeps a cohort engaged — no commute required.
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.
The real world, continuously
Vitals, activity, sleep, and symptoms flow in from Apple Health, Android Health Connect, and clinical-grade wearables — so you measure what happens between visits, not just the few minutes at one.
See a dropout coming
Engagement analytics surface who's drifting before they're gone, so a coordinator can reach out in time. The patient stays supported; the study keeps its statistical power.
Meet patients where they are
Asynchronous check-ins and passive collection let people take part from their couch. Attention gets raised only when something actually needs it.
Studies that look like the world
Match participants on demographics, history, and eligibility so a trial finally reflects the population it's meant to serve — not just whoever lives near a site.
Research without borders
Run a study anywhere, reaching rural and underserved communities that brick-and-mortar trials have always left out.
One link. One scan. They're in.
Share a link or QR code in an email, a post, or a flyer. The patient scans it, downloads the app, and lands inside your study. No searching, no phone tag, no paperwork.
The body keeps the data. We help you read it.
TrialPilot turns everyday wearable signals into clinically meaningful, within-person insight — purpose-built for energy-limiting and complex chronic conditions, where the truth lives between clinic visits.
Left: the researcher's PEM episode timeline, built from ordinary check-ins and wearable data. Right: the participant's own pacing read — a heart-rate ceiling learned from their resting rate, not a number off a chart.
Escalation that respects the patient
Anyone can flag a safety concern on a reporter-not-actor model — the person who notices is never forced to be the one who acts. Signals route to the right people instantly, with a privacy wall between identity and clinical data.
Hours, not the next visit
Continuous monitoring watches wearable streams and patient reports for adverse events and worrying trends, so a problem surfaces while there's still time to act on it.
Catch the crash, objectively
For ME/CFS and Long COVID, TrialPilot detects post-exertional malaise from normal participation — check-ins plus wearable data — against a versioned, patient-anchored definition. A tap-only flow adds context without burdening someone who's already crashing.
Your envelope, not a generic target
A personal heart-rate ceiling, time-over-threshold, an orthostatic-aware POTS split, and a morning readiness read from resting HR and HRV — framed as a pattern, never a prediction. Quiet by default: it never nags.
Heart rate during physical tests
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.
A check-in, never an alarm
A coordinator can queue a one-way, templated check-in that arrives as a considerate local notification. It's rate-limited, never stacks, expires on its own, and stays quiet when someone is unwell.
Give patients a rigorous trial of their own.
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.
A real n-of-1, not a journal
Guided single-case studies with on-device single-case experimental design and segmented-regression analytics. Real statistics, computed on the phone — not vibes.
You pick what matters
Choose your own primary endpoint — fatigue, cognition, autonomic symptoms — as a primary, secondary, or exploratory measure, over a duration you commit to up front.
An honesty layer, built in
A power-bar gate and a provisional early-signal “peek” show exactly how much your data can support — so a hopeful trend is never dressed up as proof.
A result you can trust at a glance
A within-person Green / Yellow / Red read that never cries red on missing data, links a serious drop straight to safety reporting, and keeps a history of every study you run.
Share — or don’t
One toggle lets you contribute findings to the wider community or keep a self-trial entirely private. Your data, your call.
Lived experience becomes evidence
Aggregated, consented self-trials turn what patients live through into a real signal — surfacing what deserves a full study, faster than the old pipeline ever could.
The serious machinery, handled.
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.
One protocol that keeps learning
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.
A clean dataset, by construction
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.
MedDRA & WHODrug, in line
Adverse events and medications are coded against standard dictionaries, and open questions live as tracked queries on the record itself — every change attributable, every answer kept.
Database lock and CDISC export
Soft and hard database locks with an audited unlock, plus CDISC SDTM and define.xml export — the deliverables a regulator expects, generated straight from the source data.
Fits the stack you already run
Connect EHR/EMR systems, lab networks, and research tooling through a comprehensive API. TrialPilot slots into your ecosystem instead of replacing it.
Identity separated by default
Participant identity lives apart from clinical data at the database boundary, so de-identified analysis is the path of least resistance — designed for FDA, EMA, and ICH expectations, not bolted on at audit time.
Get started
Be part of the trial of the future.
Join the public beta on iOS or Android, explore live studies, or start a self-trial of your own — free, today.