™
Not because of your ingredient,
But because of your study population!
In most clinical trials:
A larger sample size is required to compensate for poor selection criteria
Result: $$$ spent, with no returns
You are not short of innovation.
You are testing it on the wrong biology.
Precision Recruitment
Reduce heterogeneity at entry
Improve responder probability
Adaptive Trial Design
We don’t improve your ingredient.
We improve the biology you test it on.
Traditional Model
(High Risk – Compromised Signal)
Heterogeneous Participant Pool
Broad Inclusion / Exclusion
Symptom-Based Screening
Biological Variability
Diluted Effect Size
Low Responder Density
Reduced Probability of Statistical Significance
(Controlled Risk – Optimized Signal)
Product-Target MOA Mapping
Defined Responder Biology
Phenotype-Enriched Pre-screening/ Screening
Reduced Biological Variability
Run-in Period (Early Response Assessment)
Responder Enrichment (Responder-Only Selection)
Precision Randomization
Contact us to know more
Adaptive Interim Analysis (Pre-defined Checkpoints)
Sample Size / Endpoint Optimization
Increased Responder Density
Higher Effect Size & Signal Clarity
Higher Probability of Statistically Significant Outcomes
