Large amounts of clinical and imaging data in hospital records are currently inaccessible for research. This data can give insights into prognosis, treatment and outcome.

The Australian Cancer Data Network (ACDN) will establish a nationally agreed capability to link regular treatment (clinical practice) and clinical trial data, for machine learning analysis with international links. This will improve accessibility and governance structures to support data users including clinicians, data scientists, governments and policy makers. It leverages the decentralised nature of the Australian Computer-Assisted Theragnostics (AusCAT) network for radiation oncology data extraction, reporting and distributed learning and takes analysis to the data.

This streamlines the administrative, ethical, political aspects of research, enabling learning across datasets that are otherwise difficult to merge due to size or ethical and governance challenges.

1 Expand AusCAT
ACDN expands the scale and accessibility of the existing Australian Computer Assisted Theranostics Network(OzCAT).
2 Link AusCAT to QOOL
ACDN will link to the QLD Oncology On-Line (QOOL) platform where Cancer Alliance Queensland (CAQ) has developed a consolidated model and repository that captures all cancer related patient data in QLD (QOR), an early adoption of QOOL in VIC, and the CancerVariations (CaVa) project in NSW.
3 Cohesion with the ARDC HeSANDA program
ACDN draws on previous work done with the ARDC in the 2019 Platform Projects and has built-in cohesion with the Australian clinical trials data platform and the ARDC health studies data program (HeSANDA).

Core features

A linked and distributed network
The ACDN will enable learning from locally stored patient level clinical practice data, linked with clinical trial data and international data.
Cross jurisdiction dataset use
The project enables learning across jurisdictions from higher level datasets ( e.g. across NSW, VIC, SA, WA and QLD).
Enhanced existing services
ACDN will leverage AusCAT - a pre-existing capability for distributed machine learning to improve cancer treatment. The ACDN will take analysis to the data itself and streamline the present ethical, administrative and political aspects of using these data sets.

Who is this project for?

  • Research organisations
  • Medical practitioners
  • Clinical research groups
  • Clinical trial research groups

What does this project enable?

ACDN will establish a nationally agreed platform to link regular treatment (clinical practice) and clinical trial data, for machine learning analysis with international links.

This will improve accessibility and governance structures to support data users including clinicians, data scientists, governments and policy makers.

Handy resources

University of New South Wales Visit
South Western Sydney Local Health District Visit
University of WollongongVisit
TROG Cancer ResearchVisit
CSIROVisit
Cancer Alliance Queensland Visit
Illawarra Shoalhaven Local Health DistrictVisit
Peter MacCallum Cancer Centre Visit
University of SydneyVisit
Sir Charles Gairdner HospitalVisit
Royal Adelaide HospitalVisit
ACT HealthVisit