The aim of this ERC-POC project was to develop novel imaging biomarkers for analyzing osteoarthritis (OA) progression from µCT-imaged tissue samples and investigate the commercialization potential of the developed technology. During the project, we developed novel biomarkers for detecting OA-induced changes in articular cartilage (AC) and subchondral bone (SB) from µCT-imaged rat knee joints. Our solution offers novel tools for both academic and pharmaceutical research capable of addressing the major limitations of current gold-standard methods in OA histopathology. The methods and models were developed in collaboration with academic partners and tested in both academic and industrial uses. We also investigated the potential commercialization paths, focusing on delivering the methods to potential customers either by using software-as-a-service (SaaS) model or as a contract research organization (CRO), and examined the technological and financial challenges and opportunities of the different commercialization strategies.
The major benefit of µCT-imaging over the conventional histopathological imaging is the fast non-destructive sample preparation, which brings agility and accuracy to the analyses with optimal resolution. Our automated analytical tools bring significant added value to research and development of OA therapies in pharmaceutical sector through quantitative analysis and high-quality visualizations. Automated 3D analyses of OA induced tissue changes allow the disease progression to be quantified more accurately and facilitates potential discovery of new OA phenotypes. These qualities are especially important in pharmaceutical sector when researching disease modifying drugs. Our aim is to bring the novel MUOTO-technology to biomedical imaging sector through the SaaS model. SaaS model allows us to commercialize the technology in computationally and cost-efficient manner. Furthermore, bringing the technology to the user via cloud computing allows it to be distributed globally without major hurdles.
