When electric motors replaced steam, factories ran them through the same belts built for the old engine.

The power source changed. The process did not.

Output stayed flat for forty years.

Patient recruitment is repeating that history.

More patient reach. More trial sites. Health-record mining. Now AI.

New recruitment tools, same untested assumptions underneath. 

Top 3 assumptions that stall enrollment

Every recruitment plan rests on assumptions about who will qualify. These three break the most.

• The criteria fit the patients who exist.

• • The disease is common, but the exact patient the protocol describes is not.
  • Real-life scenario: A protocol wants patients on a specific second-line drug, stable for six months, with recent labs. Plenty have the condition, but one started three months ago, one switched brands, one has no labs. Each misses by one requirement.

• Prevalence predicts qualification.

• • Prevalence only counts the diagnosis.
  • Real-life scenario: The deck opens with millions diagnosed. But the protocol needs a confirmed subtype most patients do not know and were never tested for. One question at screening removes most of the pool.

• More sites mean more enrollment.

• • Every new site screens the same patients against the same criteria, so each one lands at the same low rate.
  • Real-life scenario: Enrollment is behind, so the sponsor opens more sites. Now more sites under-enroll, with more contracts and cost, and the same number of qualified patients at the end.

What do wrong assumptions cost?

Screen failure averages 36.3% across therapeutic areas, with ineligibility the leading reported reason. (Getz, 2019)

And when study plans that are built on assumption break mid-study, protocol amendments follow. According to a study from the Tufts Center for the Study of Drug Development (CSDD), 76% of protocols carry at least one, at a median direct cost near $141,000 for Phase II and $535,000 for Phase III. (Lusk, 2025)

Two Ways to face a Stalled Patient Qualification Rate

What does testing reveal?

A Market Feasibility Test (MFT) runs your draft protocol against real patients before sites open.

In one Parkinson's MFT, 214 patients came forward and 9 qualified. Every one of the nine asked to be contacted about a local study. Interest was abundant. A narrow device-history rule set the ceiling. (Antidote’s Parkinson’s MFT, n = 214, 2025)

What Sponsors ask before testing a protocol

• How much does a protocol amendment cost?

Amendments are common and expensive. Around 76% of protocols carry at least one, with median direct costs near $141,000 in Phase II and $535,000 in Phase III (Getz, 2024). Most trace to eligibility assumptions that were never tested against real patients.

• Can you forecast trial enrollment before opening sites?

Yes. A Market Feasibility Test runs the draft protocol against real patients and returns the real qualification rate before any site opens, so the enrollment plan starts from evidence rather than projection.

• Why do prevalence estimates overstate who will enroll?

Prevalence counts people who have the condition, not people who clear every criterion. Behavioral and treatment-history rules can cut qualified yield to low single digits even when patient interest stays high.

• What is a Market Feasibility Test (MFT)?

A test that measures the real qualification rate of a draft protocol against real patients before any clinical research site opens. It shows which criteria suppress qualified volume, before the budget is committed.