Healthcare is evolving towards a system of predictive, preventive, and precision care. A personalised medicine approach is expected to lead to better health outcomes, improved treatments, and reduction in toxicity due to variable or adverse drug responses.
The goal of Project IASIS is to seize the opportunity provided by a wave of data heading our way and turn this into actionable information that would match the right treatment with the right type of patient.
A current challenge is that there are large, heterogeneous sets of data ranging from different sources, which if combined would enable the best decisions to be made, allowing for diagnosis and treatment to be personalised to each individual.
IASIS is testing this approach in two disease areas – lung cancer and Alzheimer’s disease – but with the longer-term ambition that this approach will be more widely applicable to other disease areas.
The vision of IASIS will be achieved by the following specific objectives:
- Design a unified conceptual schema to represent all the diverse sources of available data.
- Build an adaptive system able to manage data and content collected incrementally.
- Provide actionable knowledge about disease diagnosis, prognosis, and treatment to policy makers.
- Promote cooperation among clinicians and policy makers.
- Define strategies for working that protect privacy and engender trust.