Peter MacCallum Cancer Centre (Peter Mac) is set to further enhance its position as a world-leading cancer, research, education and treatment centre through a Digital Health Cooperative Research Centre (DHCRC) research project to trial an end-to-end digital platform from Max Kelsen.
The platform, one of the first of its kind in Australia, will allow Peter Mac to securely capture and store its comprehensive pool of de-identified patient data to support innovative research and development and ultimately improve patient outcomes.
The project, coordinated by the Digital Health CRC, which is funded under the Commonwealth’s Cooperative Research Centres (CRC) Program, will see Peter Mac become one of the largest healthcare organisations in Australia to test global AI healthcare specialist, Max Kelsen’s unique, AI based data information platform.
The highly secure data platform will enable a patient outcome focused aggregation of previously disparate and siloed data sets, spanning each patient’s diagnosis, treatment and post treatment journey. Swinburne University of Technology is the research partner for the three-year project.
Associate Professor Kate Burbury, Director of Digital and Healthcare Innovations at Peter Mac, said the unique collaboration across academia, healthcare and commercial organisations represents a potentially transformative digital healthcare project.
“The goal of this exciting project is to integrate Peter Mac’s digital data and better understand the benefits that can come from unlocking large health datasets to support collaborative digital health research,” Associate Professor Burbury said.
“We also hope it will assist with establishing a pipeline for the development of regulated, scalable and transferable Software as a Medical Device (SaMD).
“We see significant opportunity for this project to improve clinician decision-making, patient outcomes and drive long term digital health product development and commercialisation,” she said.
Incorporating datasets from previously disparate technical systems, the project will enable Peter Mac to build digital capability for the health and research services; integrate digital innovations; and develop a digital ecosystem that will:
- Deliver safe, effective, high quality and patient-centred care;
- Accelerate research and discovery through collaboration and digital capability;
- Advance purpose-built health technology, including commercial applications;
- Guide strategic investment to support health services into the future;
Over the past seven years, Max Kelsen has developed and commercially applied innovative and successful AI based data management models to improve decision making in a wide range of industries, which have played a role in improving research in oncology and immunotherapy.
Nicholas Therkelsen-Terry, Max Kelsen CEO, said the concept of “data driven medicine” has the potential to improve and accelerate patient focused decision making, but before the application of AI, the task has been difficult because of the sheer size and complexity of siloed, clinical data sets and a reluctance of organisations to share them.
“Despite the best intentions of many stakeholders in healthcare and regulation, developing patient based innovation around data has been costly, time consuming and challenging from a regulatory perspective. With this project we are aiming to make it much simpler for researchers to access data which will allow them to build and deploy new innovations in clinical practice under the appropriate regulations – and do this faster and more cost-effectively through the application of game changing AI models,” Mr Therkelsen-Terry said.
The Peter Mac project presents a ground-breaking initiative that will give its researchers access to de-identified, highly secure, compatible and robust data in a consolidated and meaningful manner, to enable faster translation to clinical practice.
“With ethically applied AI and technological innovation in medicine, we can make significant improvements to how healthcare is delivered in Australia and beyond, while ensuring innovation is regulatory approved,” Mr Therkelsen-Terry said. “By creating a unique and applied data platform for the consolidation of important data, we can help medical practitioners deliver better and more personalised care.”
Data security at the heart of the project
The Max Kelsen platform uniquely ensures data is shared securely with access to data contained within the platform and maintains privacy through de-identification of all health records. It also meets all regulatory and governance standards through a universal consent approach that gives patient control over how their data is shared.
Professor Christopher Fluke from Swinburne University of Technology said from a research perspective this initiative presents a unique opportunity to bring a deep and diverse data set together on one scalable platform.
“There is an ever-growing breadth of medical data but its form and disparity can make it difficult to use to drive tangible research outcomes. This project will enable us to observe the ethical and risk considerations of using such a large and inclusive data set in practice and observe how data and AI can help improve and enhance decision making outcomes for clinicians and patients.”
Dr Stefan Harrer, Digital Health CRC Chief Innovation Officer, said uniting these partners represented a long-term opportunity that has the potential to transform how digital health data is stored and shared.
“This project will initially integrate a novel, scalable data linkage and management platform into Peter Mac’s digital infrastructure and then use it to develop a production-grade AI-powered image segmentation module for potential inclusion in clinical workflows,” Dr Harrer said.
“This will set a precedent for empowering clinical institutions to tap into the abundance of health data they hold in highly efficient ways and to deliver real value to patients in trusted and personalised ways.”
“Given the unstructured and fragmented nature of health data and its exponentially growing size, AI is poised to play a key role for analysing it. This comes with challenges. In order to gain regulatory approval and the trust of clinician users and patients, AI algorithms need to be fair, transparent and robust,” Dr Harrer said.
“Secure data management systems linking different data sources and modalities together efficiently, privately and in an interoperable manner are a key ingredient for developing such responsible AI systems.”