Osteoarthritis afflicts over 500 million people, but personalized therapy guidance is limited. We develop a multiscale, cell signaling driven in silico model, or digital twin, to enable personalizing rehabilitation and drug therapies. We use existing in vitro and clinical data and collect new data for generation and validation of the model. The ultimate model is driven by radiography, biochemical markers, and 2D video analysis, and is assisted by artificial intelligence. This project will renew scientific thinking about the multiscale factors controlling disease development. Personalized therapy guidance will foster the improved health of aging population and can reduce overall costs related to osteoarthritis. This project will be conducted in the University of Eastern Finland, in collaboration with University of Iowa, University of Liège, Griffith University, and Helsinki University Hospital. See two relevant publications: doi: 10.1371/journal.pcbi.1010337; doi: 10.1002/jor.25177.

2024

2028