Winning More Studies by Making Your Feasibility Data Provable

Feasibility questionnaires are the first real audition for a study. Sponsors and CROs read dozens of them, and most come back looking identical: confident enrollment projections, a vague patient population estimate, and a therapeutic area list that overlaps with every other site in the region. Sites that win more awards usually aren't better at selling — they're better at proving.

Why Most Feasibility Responses Fail

The common pattern is an overstated number with nothing behind it. A site claims it can enroll 20 patients in six months. The sponsor has no way to verify that, so they discount it. When the site under-delivers, that number becomes a liability at the next feasibility round.

The second failure mode is slowness. Feasibility windows are often short, and a response that arrives after the CRO has already shortlisted sites doesn't get read carefully, no matter how good it is. Sites that can turn a questionnaire around in a day or two get a real advantage simply by being in the first batch reviewed.

Build the Database Before You Need It

The single highest-return investment is a searchable record of your patient population that you can query on demand. That means:

• Condition-level counts from your EHR or practice partners, refreshed quarterly, not estimated from memory.
• Key stratifiers that show up in eligibility criteria repeatedly: age bands, comorbidities, prior therapy exposure, common lab ranges, treatment-naive versus experienced.
• A consented contact pool with records of who agreed to be recontacted for future research, tagged by condition.
• Referral relationships — which physicians actually send patients, and how many per quarter.

When a feasibility form asks how many patients with a given diagnosis you can access, the difference between "approximately 200" and "214 active patients in our system as of last month, of whom 61 meet the age and prior-therapy criteria" is the difference between a maybe and a site visit.

Track Your Own Performance Honestly

Sponsors increasingly have their own data on site performance. Getting ahead of it works better than hoping they don't look. Keep running metrics on:

1. Screened-to-enrolled ratio by therapeutic area.
2. Time from site activation to first patient in.
3. Retention and completion rates.
4. Protocol deviation counts per study.
5. Query resolution turnaround.

Present these as a one-page site performance summary you attach to every feasibility response. Include the studies that went poorly with a short note on what you changed. Sites commonly find that acknowledging a slow enroller and explaining the fix builds more credibility than a clean-looking record with no context.

Make Your Projections Defensible

Instead of a single enrollment number, show your arithmetic. Start from the eligible pool, apply a realistic contact rate, a pre-screen pass rate, and a screen failure rate drawn from your own history in that indication. Land on a monthly randomization figure and state the assumptions. A projection with visible math invites a conversation; a bare number invites skepticism.

Treat Feasibility as a Standing Process

Assign ownership. One person should be responsible for keeping population counts current, logging completed study metrics within two weeks of database lock, and maintaining a library of reusable answers about staffing, equipment, IRB timelines, and space.

The sites that win consistently aren't guessing better. They've made the data collection routine so that responding well costs them an hour instead of a week.