AI for Protocol Design & Feasibility
Better protocols. Fewer amendments.
AI in protocol design and feasibility assessment — eligibility-criteria optimization, amendment prediction, comparator selection and site-fit scoring.
"Can we pre-test our protocol before locking it?"
AI feasibility platforms simulate protocol impact on eligible-patient pool and predict amendment risk before lock — reducing late-stage protocol amendments by 25%+.
AI in protocol design is rapidly becoming standard. Teams that pre-test eligibility, predict amendment risk and optimize comparators before lock save quarters of trial delay downstream.
What we’re seeing in the data.
Eligibility-criteria optimization
Each criterion shrinks pool — quantify trade-offs.
Amendment risk is predictable
AI flags high-risk patterns ex ante.
Comparator selection benefits from AI
Active vs SOC choice clearer.
How to think about it.
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01
Sim eligibility on real-world
EHR-based pool.
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02
Optimize criteria
Trade-off curve.
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03
Predict amendment risk
Pattern-based.
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04
Refine comparator
Active vs SOC.
What separates a good answer from a defensible one.
EHR variability.
AI usage flagging.
Sponsor governance.
Where the signal comes from.
Common questions.
Which AI use case has highest ROI?
Eligibility-criteria optimization, by a wide margin.
Is the regulator OK with this?
Yes — AI as design support is now standard practice.
Want this answered on your data?
We build decision systems on top of analyses like this — so the next question takes minutes, not weeks.
Talk to a strategist