Case Studies
Real-world examples showing how efficient statistical designs reduce clinical trial costs by $3-18M per trial and accelerate time to market by 12-18 months.
$35.7M
Total savings across case studies
14-30%
Sample size reduction
12-18mo
Earlier market access
11,750×
ROI per program
Oncology Phase II: 30% Sample Size Reduction
Single-arm Phase II evaluating objective response rate (ORR). Baseline tumor burden correlates ρ=0.55 with response, enabling significant sample size reduction.
$3.6M
saved
30%
reduction
3.6 months faster
timeline
Cardiovascular Phase III: Early Stopping
4-look O'Brien-Fleming design with non-binding futility. Trial stopped early at Interim Analysis 2 when efficacy boundary was crossed.
$18.1M
saved
24%
reduction
12 months faster
timeline
Rare Disease: Bayesian Decision Framework
Quantitative probability analysis enabled informed decision-making where classical p-value thresholds would have led to incorrect no-go decision.
18 months earlier access
saved
Improved go/no-go
reduction
FDA BTD granted
timeline
Full Program: Integrated CUPED + GSD + Bayesian
Phase II → Phase III development using all three methodologies. Demonstrates the compounding value of integrated efficient design.
$14.1M
saved
14%
reduction
16 months earlier BLA
timeline
Three Methodologies, One Platform
CUPED
Covariate-Adjusted Power Analysis reduces sample size by 15-35% by leveraging baseline-outcome correlations.
FDA May 2023 guidance calls this “low-hanging fruit”
Group Sequential
Interim analyses with stopping boundaries reduce expected sample size by 20-40% under efficacy scenarios.
FDA calls these “simplest adaptive designs”
Bayesian
Predictive probability enables quantitative go/no-go decisions vs. binary p-value thresholds.
FDA January 2026 guidance extends to drugs/biologics
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