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Submit your study brief
Indication, phase, objective, constraints.
AI-Powered Trial Design Planning
Design your trial.
Check it before you submit.
- Compare design options side-by-side
- Check assumptions against regulatory guidance
- Draft protocol and SAP language in minutes
Trusted by clinical teams in biotech & pharma
Before The Trial
From lead candidate to IND filing — parallel workstreams, hidden dependencies, and costly rework loops.
Lead Candidate
Target / MOA
Indication
Safety Profile
Modality
Tox Studies
CMC / GMP
PK / ADME
Dose Selection
Meeting Prep
Briefing Package
IND Filing
Parallel
Revise
Rework
Dependency
Characterization
Development
Regulatory Prep
Rework
The Problem
Trial design is slow, and errors cascade across protocols, endpoints, and SAPs.
Study Brief
Indication
Objective
Timeline
Constraints
Population
Eligibility
Analysis
Design
Endpoints
Hypothesis
Sample Size
Protocol
SAP
Review
Revise
Align
Mismatch
Redo
Input
Design Cascade
Deliverables
Review Loops
Rework
How It Works
From brief to structured design draft.
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Get design options with tradeoffs
Endpoints, sample size, protocol and SAP drafts.
3
Check against FDA guidance
Gaps flagged for your team's review.
Output Preview
One brief. Three design paths.
Recommended
PFS primary + ORR secondary
Event-driven, strong signal.
Tradeoff
Slower readout than ORR-only
Better interpretability.
Assumptions
mPFS 4.0 vs 6.3 mo
HR 0.63, 1:1, one futility look.
Population
2L metastatic NSCLC
Post platinum-based progression.
Stratification
Biomarker status at baseline
Pre-randomization capture.
Eligibility
Measurable disease, adequate organ function
Prior therapy restrictions applied.
Flag
Confirm screening assumptions
Enrollment feasibility check needed.
Primary
Progression-free survival
Per RECIST v1.1.
Estimand
Treatment policy strategy
HR with sensitivity analyses for intercurrent events.
Population
ITT primary
All randomized, by assigned arm.
Method
Stratified log-rank + Cox
KM curves, sensitivity analyses.
Flag
Confirm interim boundaries
Alpha spending rules to review.
Why TrialCraft
Built for how trial teams actually work.
FDA guidance checks
Flags potential issues before your team reviews.
All-in-one workspace
Endpoints, sample size, protocol, SAP — one place.
Built for clinical trials
Not a generic chatbot. Trained on regulatory precedent.
Expert team on call
Senior biostatisticians for hands-on support.