Research Data Reuse Programme

Most research data is used once,
then archived. Science pays the price.

A governed framework enabling institutions to make archived and unpublished data available for ethical secondary analysis — under their own governance, with patient consent honoured at every step.

Published Data
What the world can see
Summary statistics. Effect sizes. P-values. Conclusions drawn from data the reader can never access. Science built on shadows of the underlying reality.
  • Aggregated results only — no underlying patient data
  • Negative results typically excluded from publication
  • 2× more positive results published vs negative
  • No mechanism for cost recovery by the contributing institution
Source: Joanna Smith, PLOS Medicine, 2014 — The Role of Open Access in Reducing Waste in Medical Research →
Archived & Unpublished Data
The data that informs better science
Raw OCT scans. MRI sequences. Negative results. Inconclusive trials. Unpublished cohorts. Under proper governance, this data supports more reproducible, more representative science.
  • Raw patient data with full scientific context
  • Negative and inconclusive results preserved
  • Cross-institutional cohort analysis enabled
  • Data never leaves its source institution
85%
of biomedical research investment is avoidably wasted — flawed design, non-publication, poor reporting
Chalmers & Glasziou, The Lancet, 2009 →
30%
of applicable clinical trials have never submitted required results — per FDA internal analysis, 2026
FDA.gov, April 2026 →
$170B+
annual global waste implied by the 85% waste figure applied to ~$200B global health research spend
Glasziou & Chalmers, BMJ Blog →
How the Programme Works

Governance first.
Institutions in control. Always.

The Research Data Reuse Programme operates entirely within the framework of institutional governance, patient consent, and ethics committee oversight. Data never leaves its source.

01
Institutional Control at Every Step
Institutions decide what data is available, to whom, under what conditions, and for how long. UndosaTech provides the infrastructure — not the decision-making authority.
02
Patient Consent Honoured
Reuse happens only under explicit governance agreements that respect and enforce the original consent framework. No exceptions.
03
Public-Benefit Criteria Built In
Every secondary analysis request is evaluated against clear public-benefit criteria set by the contributing institution.
04
Full Audit Trails
Every data access event, analysis run, and governance approval is logged with immutable audit trails.
05
Cost Recovery for Institutions
A royalty marketplace enables NHS Trusts and universities to recover stewardship costs — turning archived cohorts into a sustainable long-term asset rather than a liability.
"Existing medical data is not fully exploited by machine learning primarily because it sits in data silos and privacy concerns restrict access. Without access to sufficient data, ML will be prevented from reaching its full potential."
Rieke et al., The Future of Digital Health with Federated Learning — npj Digital Medicine, 2020 →
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