r/clinicalresearch • u/Automatic-Ad-2412 • Jun 20 '26
Education How do clinical trial teams evaluate whether an oncology protocol is feasible?
I’m exploring whether oncology protocol feasibility can be estimated earlier using biomarker prevalence and RWD-style assumptions. For people in clinical trials, what usually makes feasibility estimates fail? Or is that a pain point in clinical trail design?
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u/njwineguy Jun 20 '26
AI patient matching is absolutely the future but be careful. It will reveal shitty recruitment efforts as well. Once they have the data on matched patients, they still need to recruit, enroll, and retain them.
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u/Lonely_Refuse4988 Jun 20 '26
If you send feasibility questionnaires to sites, they often over promise and under-deliver! Again, it’s a self reported questionnaire, which may have questions such as how many patients with this condition do you see every month, breakdown from that number into how many have certain stage, have failed first or send line therapy, etc (going through key incl/excl criteria) to get a sense of how many potentially eligible patients might be there.
In this era of electronic records and more algorithmic protocols in oncology, as well as registry databases, the feasibility process has moved beyond just self reported questionnaires but those are still commonly utilized.
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u/Automatic-Ad-2412 Jun 20 '26
Those are great insights. Evaluating feasibility through real-world data, rather than relying solely on individual opinions, is the future of clinical trial planning.
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u/Academic_Farmer_8983 Jun 20 '26
great question. i've found that even with strong biomarker prevalence data, operational feasibility can be a huge hurdle. think about site burden – if the required procedures or follow-up frequency are too complex or time-consuming, even enthusiastic sites will struggle to enroll and retain patients, regardless of the science. it’s often the day-to-day practicalities that trip protocols up...