Clinical Trial Protocol Skill

A clinical trial protocol stands or falls on a few linked decisions: a clear objective, a design that can answer it, endpoints that measure it, eligibility that defines who's studied, and a statistical plan that can detect the effect. This skill drafts a protocol synopsis that makes those decisions explicit and internally consistent, in the structure IRBs/ethics committees and regulators expect. (For a general academic or UX study, use research-protocol.)

Safety & compliance note: this is a drafting aid for expert review, not regulatory, medical, or statistical sign-off. Real trials require qualified investigators, a statistician, and IRB/ethics and regulatory approval (e.g. GCP, ICH, local law). Do not invent efficacy/safety data; mark assumptions for the study team to set.

Working from a brief

Given "a phase II trial of drug X for condition Y", produce the full synopsis anyway — infer a defensible design, endpoints, and eligibility appropriate to the phase and condition, and clearly label every inferred choice as a draft assumption for the study team and statistician to confirm. Never fabricate prior data or effect sizes; state them as placeholders to be set.

Required Inputs

Ask for these only if they aren't already provided (else infer and label as draft):

• Intervention & condition — what's being studied, in whom, and the phase.
• Objective / question — the primary question the trial must answer.
• Comparator — placebo, standard of care, or active control; and blinding.
• Outcome of interest — how benefit (and harm) will be measured.
• Constraints — known population, setting, and any regulatory context.

Output Format

Clinical Trial Protocol Synopsis: [title]

• 1. Background & rationale — the problem, prior evidence (mark placeholders), and why this trial.
• 2. Objectives — primary and secondary, each as a precise, testable statement.
• 3. Design — phase, type (RCT, etc.), allocation/randomisation, blinding, arms, and duration.
• 4. Population — setting, and explicit inclusion and exclusion criteria.
• 5. Interventions — the intervention and comparator: dose/regimen, administration, and concomitant rules.
• 6. Endpoints — primary endpoint (one, tied to the primary objective), secondary endpoints, and how/when each is measured.
• 7. Statistical considerations — analysis populations, the primary analysis, and a sample-size basis (with assumptions flagged for the statistician).
• 8. Safety — adverse-event definitions, monitoring/reporting, stopping rules, and any DSMB.
• 9. Ethics & conduct — informed consent, IRB/ethics approval, data integrity, and GCP adherence.

Close with assumptions to confirm and a reminder that a qualified investigator and statistician must own the final protocol.

Quality Checks

• The primary objective, primary endpoint, and primary analysis are aligned and consistent
• There is exactly one primary endpoint, clearly measurable and time-anchored
• Inclusion/exclusion criteria are explicit and operationally checkable
• Sample-size basis is stated with its assumptions flagged for the statistician
• Safety monitoring, reporting, and stopping rules are present
• Ethics/consent/IRB and GCP elements are included; no efficacy/safety data is invented

Anti-Patterns

• Do not invent prior efficacy/safety data or effect sizes — mark them as placeholders to be set
• Do not list multiple "primary" endpoints — pick one and demote the rest to secondary
• Do not let objective, endpoint, and analysis drift apart — they must answer the same question
• Do not present this as regulatory/statistical sign-off — it's a draft for expert review
• Do not omit safety monitoring and stopping rules — a protocol without them isn't approvable

Based On

Clinical research practice — objective-endpoint-analysis alignment, explicit eligibility, sample-size justification, and ICH-GCP safety/ethics structure.