A new mathematical framework
Extract more insight
from less data.
We help R&D teams, clinical centres, and research labs analyse complex datasets with fewer samples, lower costs, and no information loss.
01 — Industries
Your industry, our expertise.
Pharma & Biotech
Detect biomarker signals on cohorts 10–100× smaller than what GWAS requires.
Explore →Hospitals & clinical research
Patient-level insight on rare-disease and oncology cohorts.
Explore →CROs & data platforms
White-label or API. Lower compute, higher reproducibility.
Explore →Academic research labs
Publish more from data you already have.
Explore →AgriTech & breeding
Selection on tens to hundreds — not thousands.
Explore →Cosmetics & consumer health
Robust efficacy findings from clinical panels of 20–80.
Explore →02 — Solutions
What are you trying to achieve?
Accelerate R&D
Statistically robust findings from dramatically fewer samples.
See how →Analyse small cohorts
Built for small N from the ground up. Viable from N = 20.
See how →Enhance your analytics
Plug-in non-parametric layer for CROs and data platforms.
See how →Publish stronger results
Peer-reviewed, fully transparent method. Backed by 6 publications.
See how →Optimise selection programs
Genetic selection on smaller populations. Multi-gene signals.
See how →03 — The science behind EpiKern
Where others see noise, we see structure.
-
Step 1
Traditional methods lose information
Standard analytics bin data into categories (histograms, count plots). This erases individual-level precision. Statistics like mean and variance are computed on a simplified version of reality.
-
Step 2
We preserve every data point
Our framework analyses the full informational structure of the dataset. When measurement precision increases, data points become unique identifiers — like barcodes. We read those barcodes.
-
Step 3
More insight, less data
By preserving information that others discard, we detect patterns and associations that remain invisible to traditional tools — even with dramatically smaller sample sizes.
Signal emerging from a field of measurements.
Trusted & validated
Published in
Physiological Genomics · Journal of Theoretical Biology · Physical Biology
Supported by
PSL · EPHE · University of Nottingham
Funded by
Wellcome Trust · MS Society · Leverhulme Trust
Developed through years of academic research. Validated in peer review. Deployed in industry.
04 — Get in touch
Ready to do more with less?
Whether you're exploring a new dataset or facing a small-cohort challenge, we'd like to understand your situation and see if our approach fits.
- Emailcontact@epikern.com
- HoursMon–Fri · 9:00–18:00 CET