How to run a longevity clinical trial, from question to clean data
Longevity studies mix biomarkers, functional tests, wearable data and questionnaires over long follow-up. This guide walks through the decisions in the order you will meet them, and shows where the data capture work sits.
- Endpoint and visit planning
- Wearable and diary data
- Free sandbox to rehearse
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The short version
- A longevity trial is still a clinical trial: a clear question, a protocol, ethics approval, informed consent, and a data system you can defend.
- The hard part is endpoints. Aging has no single accepted outcome, so decide early which biomarkers, functional measures and patient-reported measures you will collect, and why.
- Follow-up is long and data arrives from many places, so plan the visit schedule, wearable sync and diary windows before enrolment, not after.
- Build and test the data capture in a free sandbox first; you pay only when you go live with real participants.
- This page describes how to run a study. It makes no claim that any intervention slows aging, and it is not legal or regulatory advice.
Start here
What is different about a longevity trial
Most clinical trials test an intervention against a disease with a recognised clinical endpoint. Longevity research usually does not have that luxury. The outcomes of interest, such as biological age estimates, inflammatory and metabolic markers, grip strength, gait speed, cognition, sleep and self-reported function, are often surrogate or composite measures, and the field is still debating which ones are meaningful. That does not change how the study must be run, but it changes how carefully you must document your choices.
Three practical consequences follow. First, your protocol has to state each endpoint, how and when it is measured, and which one is primary. Second, because many measures are continuous and repeated, data quality problems such as missing visits, out-of-range values and unit mix-ups compound over time. Third, participants are often generally healthy, so recruitment, retention and compliance depend on making participation easy. If you want the product-side view of the same population, see EDC for longevity clinical trials; this guide stays on the process.
The sequence
Eight steps to run a longevity study
Do them roughly in this order. Each step feeds the next, and the data capture design in steps 5 to 7 is far cheaper to get right before the first participant than to repair after.
- 1
1. Write down the question and the primary endpoint
One sentence for the question, one named primary endpoint, and a short list of secondary and exploratory ones. Resist adding every biomarker you can afford. Each extra measure adds forms, visits, queries and analysis.
- 2
2. Choose the design and sample
Decide on parallel groups, placebo or sham control, blinding and duration. Use a sample size calculator with honest assumptions about variance and dropout, which tends to be higher in long follow-up.
- 3
3. Draft the protocol and schedule of assessments
List every visit and every measure at each visit. A schedule of assessments builder turns that grid into visits and forms, and exposes inconsistencies, such as a measure in the protocol that has no visit.
- 4
4. Get ethics and registration in order
Submit the protocol, consent and recruitment materials to your ethics committee or IRB before enrolling anyone (see the IRB submission checklist). Check whether the study must be registered in a public registry and when; journals and regulators have their own rules.
- 5
5. Build the forms and logic
Create eCRFs for eligibility, demographics, medical history, concomitant medications, vital signs, labs and adverse events, plus your study-specific measures. Add range checks and calculated fields so errors are caught at entry. See how to design an eCRF.
- 6
6. Add participant-reported and wearable data
Decide which symptoms, sleep, function or lifestyle data come from diaries and questionnaires, and which from a connected device. Set completion windows and reminders so participants are not asked to reconstruct weeks from memory.
- 7
7. Rehearse in a sandbox, then go live
Enrol a test participant, run every visit, trigger every edit check, sign as every role and export the data. Fix what is clumsy. Then move to live participants with consent.
- 8
8. Monitor, clean and close out
Watch enrolment, missed visits and compliance weekly, resolve queries as they appear, and lock the database only when the data are clean. See database lock and unlock.
Endpoints
Choosing and capturing endpoints
Group your measures by where the data comes from, because that decides how it is collected. Site-measured items such as blood pressure, anthropometrics, performance tests and lab draws belong in eCRFs completed by staff. Participant-reported items such as sleep quality, fatigue, mood or pain belong in questionnaires or diaries the participant completes on a phone. Device-derived items such as resting heart rate, sleep stages or activity come from a wearable the participant connects.
Treat laboratory panels carefully. Biomarkers are only comparable across visits if units and reference ranges are recorded consistently, especially when more than one lab is used. Capture records the unit, result and reference range for each analyte, and its AI form drafting can propose a lab table from a source document for you to review before anything is saved. Read more about the underlying concept in the biomarker glossary entry.
Validated instruments and licences
Many functional and cognitive scales are copyrighted. Check the terms before you use one. Capture can record licence details on patient questionnaires, but it does not supply or verify licensed instruments, so the licence stays with your study documents.
Haematology
| Row | Code | Unit | Range | Stratum |
|---|---|---|---|---|
| Haemoglobin | HGB | g/dL | 13.0-17.0 | Male 18-65 y |
| Haemoglobin | HGB | g/dL | 12.0-15.5 | Female 18-65 y |
| Platelets | PLAT | 10^9/L | 150-400 | All |
| ALT | ALT | U/L | 7-56 | All |
| Site QC flag | SITEQC | - | - | All |
Data map
Where each kind of longevity data comes from
| Data type | Example measures | Collected by | Main risk |
|---|---|---|---|
| Clinic measures | Blood pressure, weight, grip strength, gait speed | Site staff in an eCRF | Transcription and unit errors |
| Laboratory | Metabolic and inflammatory panels | Lab results entered or loaded into a lab table | Reference range and unit drift |
| Questionnaires | Sleep, fatigue, function, quality of life | Participant on a phone | Missed or back-filled entries |
| Wearable | Resting heart rate, activity, sleep | Device synced to the study | Gaps when a device is not worn or disconnected |
| Safety | Adverse events, concomitant medications | Site staff | Late or incomplete reporting |
Measures shown are examples of what a study might collect, not recommendations or endorsements of any marker.
Rehearse your visit schedule before you recruit
Build the study in the free sandbox, enrol a test participant and walk every visit. No credit card; you pay only when you go live.
Retention
Keeping long follow-up clean
Longevity studies often run for many months or years, and the usual enemy is attrition. Make each touchpoint short and predictable. Use visit windows so the team can see which visits are coming due and which are overdue, and send participants reminders by email or SMS for tasks. Keep diaries brief, using skip logic so a good day takes under a minute. See ePRO compliance reminders for how reminders and windows work.
For wearables, Capture uses a native sign-in connection: the study team turns a device on for the study, and each participant connects their own account from the study page, after which data syncs automatically with a last-sync time. Plan for gaps. Decide in advance how many days of wear make a week usable and write that into the analysis plan. For the device-specific side, see EDC for wearable device studies.
Finally, make safety reporting routine. Even in healthy volunteers, you need a consistent way to record adverse events, severity, relatedness and outcome, and to review serious events quickly. The adverse event eCRF template is a starting point.
Before first participant
Longevity trial readiness checklist
Primary endpoint named
One primary, a short list of secondary and exploratory measures, each with a defined method and timing.
Schedule of assessments agreed
Every measure mapped to a visit and a form; windows set.
Ethics approval and consent
Protocol, consent and recruitment materials approved before enrolment; consent version controlled.
Registration decision recorded
Whether and where the study is registered, and when, documented.
Forms and edit checks tested
Ranges, units and calculated fields checked in a sandbox with test participants.
Wearable and diary plan
Devices enabled, wear rules defined, reminders and windows configured.
Roles and access
Site staff, monitors and blinded roles set up with the right permissions.
Data export defined
Export format and data dictionary checked against the statistical analysis plan.
Where Capture fits
One system for the data, one audit trail
A longevity study usually needs EDC, eConsent, patient questionnaires and device data. Running them in separate tools means separate audit trails and manual reconciliation. Capture covers all of them in one platform with a field-level audit trail recording who changed what, when, the old and new value, and the reason. You build the study yourself, with an optional AI draft of visits and forms from an uploaded protocol that you review before saving.
Phase 1, 2 and 3 studies all run on the same platform, so a pilot can grow into a larger trial without a change of system. If you are comparing options, see how to choose an EDC system, and if you are working with a small team, how to run a clinical trial with a small team.
Do longevity trials need ethics approval?
Studies that involve human participants generally need ethics committee or IRB review before enrolment. Requirements vary by country and by the type of study, so check with your committee. This is not legal advice.
What endpoints can a longevity trial use?
There is no single accepted aging endpoint. Studies use biomarkers, functional tests, patient-reported measures and device data. Choose and justify them in the protocol, naming one primary endpoint.
Can a longevity study collect wearable data in Capture?
Yes. The study team enables a device for the study and participants connect their own account via the vendor sign-in; data then syncs automatically. Which devices are available depends on the study configuration.
How do I keep participants engaged over a long study?
Keep tasks short, use reminders by email or SMS, set completion windows and review compliance weekly so sites can follow up early.
Can I test the study before recruiting?
Yes. The free sandbox has every feature, with no credit card and no time limit. You pay only when you go live with real participants.
Does Capture make claims about longevity interventions?
No. Capture is software for collecting and managing study data. It makes no claim about the efficacy of any intervention.
Is a small longevity study a Phase 1?
It depends on the design and the intervention. Capture supports Phase 1, 2 and 3 studies, as well as non-phase observational and pilot work.
Keep exploring
Related pages
EDC for longevity clinical trials
The software view of the same studies.
Schedule of assessments builder
Turn the visit grid into forms.
EDC for wearable device studies
Device data in the study record.
How to run a pilot study
Start small before scaling.
Sample size calculator
Plan numbers with dropout.
Biomarker glossary
Terminology for biomarker endpoints.
Rehearse your longevity study today
Free sandbox with every feature. No credit card, pay only when you go live.