Remaining 84 The solution
The Remaining 84 · A movement by PAICON

What happens when AI ignores 84% of the world?

When AI doesn't see you, it can't serve you. Remaining 84 is PAICON's commitment to rebuild health AI with true global representation at its core. Built for 100%, rooted in the 84%
medicine forgot.

Join the movement PAICON's vision
The problem

A narrow few are teaching AI to treat everyone.

For decades, clinical research has drawn from a narrow slice of humanity. That gap is now being amplified by the AI models built on top of it, models that decide how every disease is detected, dosed, and treated, at planetary scale.

01 · Visibility

When AI doesn't see you

Health AI is leaving 84% of the world behind.

  • Clinical trials and models trained mainly on Western populations
  • The Remaining 84 stay invisible to AI systems built without them
  • Bias creates misdiagnosis, treatment failure, regulatory setback
02 · Cost

Exclusion is expensive

Clinically, financially, and at the scale of regulation.

  • 75% of clinical trial participants are Caucasian
  • $5B lost in 5 years across 15 drugs to representation failures
  • >80% of health AI is trained on non-representative datasets
03 · Why it matters

Representation is precision

Genetic variation across ancestries decides treatment outcomes.

  • Variants and drug response differ across ancestries
  • Underrepresented groups miss tailored diagnostics
  • Inclusive data yields safer, more generalizable models
PAICON's vision

Medicine was built on a narrow slice of humanity. We are rebuilding it for everyone.

Precision medicine must serve everyone, not just a privileged few. The Remaining 84 are not edge cases. They are the majority, the data never collected, the cohorts never validated.

Across the world, ancestry shapes disease biology, yet AI training data is overwhelmingly Caucasian. Every other ancestry is largely invisible to today's models.

01 · Our mission

Redefine innovation through inclusion.

We deliver ethical, globally validated health AI, bridging scientific excellence with real-world relevance across every disease, every ancestry, every geography.

02 · Our approach

No patches, no shortcuts, no exceptions.

Just responsible precision, built to honor every life, everywhere. Technology that doesn't only treat, it empowers, across all populations.

03 · Our promise

Real progress leaves no one behind.

Equity is not a feature. It is the foundation. Every dataset, model, and validation cohort we deliver is built to that standard.

Key opinion leaders · From ByteSight

Why representation matters,
in their words.

When modern humans migrated out of Africa and started to populate the whole globe, they carried with them only a small part of African genetic variation. So what that means is that more genetic diversity is in Africa than every other population.
Prof. Segun Fatumo Prof. Segun Fatumo Chair of Genomic Diversity at QMUL
My own cancer test came back with a variant of unknown significance. What that really meant was: I'm Latina, and my genome isn't represented in international databases. The science simply didn't know what my result meant. That experience showed me the cost of lacking diversity in genomics.
Dr. Catalina Lopez-Correa Dr. Catalina Lopez-Correa Chief Global Strategy Officer at Genome Canada
Most clinical trials, because it has always been done that way, are done with white, middle-aged subjects. These trials completely neglect that young and old people, females, and people with other ethnic backgrounds might function fundamentally differently, and that a drug that works in a white, middle-aged man might not work in a woman of African descent.
Dr. Christian Tidona Dr. Christian Tidona CEO & Co-founder, BioMed X
Remaining 84 — by Dr. Manasi Aichmueller Ratnaparkhe
The book

The book medicine has been waiting for someone to write.

By Dr. Manasi Aichmueller Ratnaparkhe, CEO & Co-Founder of PAICON · PhD in Cancer Biology
& Genetics (DKFZ) · MBA (LSE)

84% of the world's population is underrepresented in the data that drives modern medicine. The Remaining 84 has been receiving medicine built for someone else.

This is not a book about diversity as a social obligation. It is a book about what medicine misses when it builds its foundations on a fraction of humanity, and what becomes possible when it decides to build them for everyone.

Pre-order the book
Campaign 2025

A 4-part series on where exclusion begins, and what it is costing.

We mapped the path representation bias takes through science, pharma, and patients, and what PAICON is doing to change it. Tap a chapter to scroll through the full carousel.

Ch. 01

Exclusion is Expensive

What 16-percent training data is costing pharma, science, and patients.

Ch. 02

Diversity is Essential

Why ancestry matters for biomarkers, drug response, and survival.

Ch. 03

History Repeats Itself

From clinical trials to AI: a 70-year pattern, and how it propagates.

Ch. 04

Where Exclusion Hurts

What inclusive AI actually looks like, and what PAICON is doing about it.

The science behind it

Understand the evidence.

Representation in medical data isn't an opinion, it's a documented scientific problem. These public, peer-reviewed and institutional resources explain why diverse data matters for everyone.

Links open external, publicly available sources. PAICON is not affiliated with these publishers.

Let's connect

Join the movement.
Build health AI
for 100%.

Reach out and our team will get back to you promptly. Whether you're optimizing a single step or scaling the entire pipeline, we'll show you exactly where PAICON's data and models fit.

Download the whitepaper
LET'S CONNECT