The funding gap in drug repurposing

The drug may exist. The incentive may not.

A medicine developed for one condition can sometimes affect the biology of another. Finding that signal is only the beginning — someone still has to pay for the experiment that proves whether it is real. Meanwhile a new drug costs $1–4.4B and 10+ years, and over 90% fail in humans. The same broken math hits all 5,000 diseases, worst for the rare and neglected.

$1–4.4B

Avg cost per new drug — oncology, the starkest case

10+ yrs

Time to market · >90% fail in trials

~95%

Of rare diseases have no approved treatment

5,000

Diseases · most with no economic path to a cure

DeCure AI scientist — DeCure’s autonomous AI scientist

The path nobody funds

A cure can cost 10× less. It’s already on the shelf.

Drug repurposing — a new use for a medicine with known pharmacology and human exposure data — costs $8.4M–$300M: an 85–90% saving, in 3–6 years. Same across oncology, neuro, cardio, metabolic, immune, anti-infective and rare disease.

Why the cost collapses

Preclinical & Phase I skipped — toxicity, safety and dosing already approved by FDA/EMA.
Far lower failure rate — known molecules fail far less than ones built from scratch.
Manufacturing already exists — the supply chain is live and optimised.

The real-world numbers

$10–50M — academic / non-profit combination trials.
$60–100M — Big-Pharma registrational Phase III.
The EU launched REMEDi4ALL to unlock this — the science works; the funding doesn’t.

Paper on a repurposed drug — An approved drug → a new, publishable use

The catch · a broken incentive

So why isn’t every cheap cure already funded?

Because the business case can be weak — even when the science is strong.

Some second medical uses can be protected. But the protection is often narrower, more fragmented and harder to commercialise than a new molecule — and for rare or neglected diseases the market may be too small even when the biology is compelling. The result is a systematic gap: promising repurposing ideas that are too unprofitable for pharma, too expensive for a small academic lab and too early for a clinical sponsor. A 10×-cheaper route to a real answer is left on the shelf, not for scientific reasons.

The Solution · DeCure.ai

We fund the cures the market leaves behind.

DeCure attacks exactly that gap, across 12 research areas and 5,000 diseases — not just the profitable ones. AI finds the candidates, community GPUs fold them, stakers decide what gets pursued, and a real lab runs the experiment. Everything is published open-access.

01

Search

Map thousands of diseases against approved drugs, targets and the literature — at a scale no lab can match by hand.

02

Fold

Community GPUs run Boltz-2 on candidate drug–target pairs instead of arbitrary hashes — and earn $DECURE for it.

03

Direct

Stakers choose which of the twelve disease areas gets more of the research budget — conviction with a clock attached.

04

Test

A qualified lab runs the assay that can actually falsify the hypothesis — real biology, not just compute.

05

Publish

What worked, what failed and what should be tried next — open-access, free for anyone, forever.

A market failure on one side. A working research engine on the other. The token is what connects them.

Explore the 5,000 cures → Read the project

Sources (headline figures): King’s College London precision-oncology cost analysis · PatentPC drug-development data · Nature s41416-023-02502-9 & PMC10097740 (repurposing cost/time) · Oncology-Central · honcology.com · REMEDi4ALL (EU) & AIRC · Springer s12913-021-06425-0 · IQVIA / Quotidiano Sanità.

DeCure conducts research and publishes open-access papers; not medical advice and no claim that a cure exists. “Cure for X” denotes a research goal. $DeCure is an experimental utility / community token — not an investment, security or claim to profit, and confers no ownership of any paper. Figures are external estimates and ranges; outcomes are not guaranteed.