Food Security Data Challenges Projects
Exploreabout Food Security Data Challenges Projects
Randomised controlled trials remain the gold-standard for comparing treatments for cancer patients, but it is well known they are expensive and tend to overestimate benefits in the real-world due to recruitment bias.
Routinely collected clinical data, allied with machine learning and AI models have enabled reliable estimates of treatment effects to be obtained from real-world data collected on all patients receiving particular treatments.
However, health providers are often reluctant to permit the release of even de-identified clinical data from their control or jurisdiction. This makes it very difficult to undertake studies that combine data from many cancer treatment centres in many jurisdictions to achieve sufficient statistical power.
The Australian Cancer Data Network (ACDN) links clinical practice, registry and clinical trial data allowing learning across jurisdictions without the data leaving its host institution.
The project will improve accessibility and governance structures to support data users including clinicians, data scientists, governments and policy makers both in Australia and internationally.
It leverages the decentralised nature of the Australian Computer-Assisted Theragnostics Network (AusCAT) which provides technical infrastructure to allow distributed analyses where the raw data stays in-place and only model parameters are exchanged between participating nodes.
This dramatically simplifies the ethics and data custodian approval processes for researchers, speeding up many projects and enabling others that were hitherto impossible.
The ACDN will expand the scale and accessibility of the existing AusCAT by linking to the Cancer Alliance Queensland’s QLD Oncology On-Line (QOOL) platform; an early adoption of QOOL in Victoria; and the Cancer Variations (CaVa) project in NSW.
ACDN has built-in cohesion with the Australian clinical trials data platform and the ARDC Health Studies National Data Asset (HeSANDA) program.
Research organisations, medical practitioners, clinical research groups and clinical trial research groups will benefit from the project’s core features:
Our partners are:
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.
The ACDN envisages a day when all patients receive evidence-based personalised therapy.
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