See The Number That Surprised Five Sponsors Every enrollment plan starts as a set of assumptions dressed up as a forecast. The patient pool is deep enough. The eligibility criteria are workable. The interest is there. Each one feels solid because it matches what worked before. Then the study opens, and the number that arrives is not the number you planned around. The assumptions you never see are the ones that cost you The dangerous assumption is not the one you debate. It is the one so familiar that no one thinks to check it. A Market Feasibility Test (MFT), a patient survey run before a clinical research site opens, puts those assumptions in front of real patients and reports what they do, not what a benchmark predicts they will do. Antidote ran that test across five studies. The pattern held every time. 3% to 4% of respondents qualified across every indication tested, despite click-through above 3% and strong stated interest. (Antidote, 2026) Of the patients who qualified, 66% to 100% reported being very interested and willing to attend clinic visits. The demand was never the problem. The assumptions about who could clear the criteria were. Why reasonable assumptions still miss The estimates behind a forecast fail for reasons that look sound in the planning room:
- They arrive with authority. Historical data and published benchmarks feel like evidence, so teams treat them as settled instead of testing them against this protocol.
- They read as reasonable on paper. A criterion that removes most of your market can look modest in a document. The cost shows up in patient behavior, not in the wording.
- They surface late. Assumption quality goes unaudited until enrollment data forces the question, and by then the fix is a mid-study change at full cost. What the gap costs, and who carries it For the sponsor, an untested assumption becomes a timeline that slips and a budget that reopens after the plan was approved. For the patient, it means a study built around a...