Patient Relevant Osteoarthritis endpoints using Big data Evaluation
PROBE to advance osteoarthritis care with power of AI
Osteoarthritis (OA) occurs when the cartilage and other tissues in our joints deteriorate, resulting in pain, stiffness, and disability. It already affects more than 500 million people globally, and this number is expected to rise sharply in the next decades as populations age.
There is currently no cure for osteoarthritis, and efforts to develop treatments are hampered by several factors, including the heterogeneous nature of the disease (there may be several different subtypes of osteoarthritis), the slow progression of the disease, our limited understanding of the underlying causes of the disease, and a lack of adequate tools to measure meaningful changes in the disease in the context of a clinical trial.
The aim of PROBE is to use a big data approach, powered by cutting-edge artificial intelligence (AI) and machine learning (ML), to advance the care of people living with knee osteoarthritis. At the heart of the project will be a federated database and a federated learning platform, where sensitive patient data is stored locally behind secure firewalls and does not need to be transferred elsewhere. Machine learning models are trained on this locally stored data, allowing knowledge to be generated while safeguarding patient confidentiality – the resulting anonymised readouts can be transferred and shared as needed.
SBA Research is among other aspects responsible for:
- The overall data security and privacy aspects within the project
- The technical parts of the data protection impact assessment
- Co-developing the federated database network and federated learning algorithms
- Data imputation and synthetic data generation
Official Project Lead: Erasmus Medical Centre, Rotterdam, Novartis Pharma AG