Winning More Studies With Feasibility Data Sponsors Trust

Feasibility questionnaires are the single most leveraged document your site produces. A sponsor or CRO reads it for ten minutes and decides whether you get a study worth six figures. Most sites fill them out from memory, round the numbers up, and wonder why selection goes elsewhere.

The sites that win consistently are rarely the biggest. They are the ones whose feasibility answers are specific, defensible, and matched to what the sponsor is actually worried about.

What the sponsor is really asking

Every feasibility question is a proxy for one concern: will this site enroll on time without creating work for me? When you read "how many patients with condition X do you see annually," the real question is how many you can reach, consent, and qualify under this protocol's criteria within the enrollment window.

So answer the real question. A number like "1,200 patients in the database" tells a sponsor nothing. "Roughly 400 active patients meet the diagnosis; applying the A1c and BMI ranges in the synopsis, we estimate 90–110 remain eligible; we would expect to consent 20–25 of those in the first four months" tells them you have done arithmetic they can trust.

Build the data before the questionnaire arrives

You cannot produce that answer in a 48-hour turnaround unless the underlying data already exists. Three things to put in place:

A queryable patient pool. Not a spreadsheet of names — a record set you can filter by diagnosis, key labs, age, concomitant medications, and last contact date. Even a modest EMR report plus a clean prescreening log beats institutional memory.

Historical performance by indication. For every study you have run, record: number consented, screen failures with reasons, randomization rate, time from site activation to first patient in, and enrollment versus your original projection. Sites commonly discover they have been over-projecting in one therapeutic area and under-projecting in another.

Funnel conversion rates. Outreach contacted to prescreen completed, prescreen passed to appointment booked, appointment to consent, consent to randomized. These let you work backwards from an enrollment target to the outreach volume required — and tell a sponsor exactly how you will get there.

Turn accuracy into a selling point

Most sites inflate projections. Sponsors know this and discount accordingly. Breaking that pattern is an advantage.

Include a short accuracy note: "On our last three cardiology studies, we projected 14, 10, and 18 randomizations and delivered 12, 11, and 15." A site that lands near its own forecast is operationally more valuable than one that promises 30 and delivers 9, because the sponsor can plan around you.

When your realistic number is lower than what the sponsor hopes for, say so and explain the constraint — a narrow washout window, a competing study drawing from the same pool. Flagging a competing enrollment conflict proactively builds more credibility than any inflated figure.

Make the file reusable

Maintain a standing feasibility packet you update quarterly: investigator CVs and current licensure, equipment and certification list, staffing with FTE allocation, monitoring and freezer capacity, IRB turnaround times, and your pool counts by major indication. Most questionnaires then become editing, not research — and faster turnaround itself influences selection.

Close the loop

After each study, compare what you projected to what happened and revise your conversion assumptions. Feasibility data that is corrected against reality a few cycles running becomes the most persuasive thing you can put in front of a sponsor.