"Our budget funds a trial smaller than our power calculation wants."
Study Design
Design decides whether your data can answer the regulatory question at all. We build trials the FDA can act on: the right endpoints, honest power, and adaptive options only where they earn their keep.
Discuss your design
Designs informed by integrated historical data
Our strategy is built on a foundation of comprehensive data insights. We leverage our proprietary integrated historical data to inform decisions, from sample size determination to adaptive design. That lets us predict potential challenges and optimize for the best possible outcomes to deliver a study strategy that is both scientifically sound and operationally efficient.
Data quality & technology
Quality data is paramount. We meticulously plan data gathering using SDTM and ADaM so data is standardized, clean, and ready for analysis. The process is integrated with EDC design, customized to your study's requirements for real-time, accurate collection from the start.
Adaptive trial design & modeling
- Optimal sample size for sufficient power on your primary endpoint
- Advanced modeling and simulation across a range of scenarios
- Adaptations and corrections that allow mid-study adjustment without compromising integrity
- Robust methods for inference so conclusions are statistically defensible
Advanced analysis
- Time Component Tests: evaluate efficacy over time for a granular view of effect and durability
- Interim analysis: planned assessments that can stop early for success or futility, saving time and resources
Translating success into a story the FDA can follow
The final step is presenting your study's results in a format that speaks to regulators and the scientific community. We handle all aspects of writing and formatting.
- Regulatory documents: meticulously planned, correctly formatted, with an outline that tells a clear, compelling story of your drug.
- Journal formatting: results adapted to specific journal requirements for publication.
Global Statistical Tests: powering the trial your budget can actually fund
When the sample size a conventional design demands is larger than the trial you can run, a Global Statistical Test lets the clinical-endpoint hypotheses be tested anyway. The paper sets out when GST applies, how it is pre-specified, and how it has been received in review.
The methods have names.
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ADCOMS
Detecting decline in prodromal and mild Alzheimer's disease, where single scales barely move over 18 months.
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iADRS
One score for cognition and function, so an effect on both does not split into two underpowered tests.
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APCC
Tracking cognitive change in people who do not yet have symptoms, for prevention trials.
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GST
Testing a treatment across many endpoints at once when no single endpoint can be powered on its own.
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TCT
Expressing an effect as time saved, so "slowed decline" means something to a patient and to a reviewer.
Publication → (opens in a new tab)
The category
Measuring change in slow, heterogeneous, hard-to-measure disease. That's the problem these exist to solve, and it's the only thing we've done for twenty-five years.
Browse the publicationsLeast expensive point to bring us in · Protocol drafting
Endpoint and population review. Later, it is the one decision you can't revisit.
Bring us in before the protocol locks
The earlier we join, the more design decisions are still open, and the more power we can protect.