Knowledge-generation framework combining a novel Biomimetic Investigation platform and hiGh throughput screening for unravelling bone MECHanotransduction mechanisms in view of precision orthopedic medicine (BIGMECH)

Bone fractures and their clinical management represent a heavy and growing socio-economic burden worldwide. In several pathological conditions bone self-healing fails, causing severe pain and immobility to the patients. Besides the conventional surgical and graft approaches, bone tissue engineering (TE) is emerging as a promising strategy for promoting bone fracture healing. However, due to scientific and regulatory challenges, bone TE is not yet implemented in clinical practice and bone TE constructs are currently adopted as three-dimensional (3D) bone tissue models for in vitro bone research and pre-clinical studies. In parallel, the non-invasive pulsed electromagnetic field (PEMF) stimulation is empirically adopted in orthopedic clinical practice for boosting the endogenous bone healing, without any standardized guidelines. One of the main reasons hindering bone TE translation and PEMF treatment standardization is that the biological response activated in bone tissue by physical stimuli, defined as bone mechanotransduction, is only partially known. The ambition of the BIGMECH project is to build a pioneering knowledge-generation framework unravelling for the first time the cell-scale signaling pathways and the tissue-scale effects induced in bone tissue by native-like physical stimuli combined with PEMF stimulation. For this purpose, the main technological aim will be the optimization of a novel biomimetic investigation platform, based on a smart bioreactor system and 3D scaffold-based bone tissue models. In detail, a perfusion bioreactor will be upgraded for enabling in vitro adaptive dynamic culture of 3D constructs under tunable and combinable physical stimuli (shear stress, intermittent pressure, PEMF stimulation) and real-time monitored conditions. Unique 3D-printed scaffolds, mimicking the complex bone microarchitecture, will be developed and, seeded with mesenchymal stem cells, will be cultured within the bioreactor for developing reliable 3D bone tissue models. The biomimetic platform will then be used for applying native-like physical stimuli without and with PEMF stimulation on the 3D bone tissue models. High throughput transcriptomics will reveal intracellular signaling events triggered by the imposed physical stimuli. Transcriptomic data will be treated by high performance machine learning (ML) tools for decrypting complex networks and for extracting the relationships between gene expression and applied physical stimuli. As main scientific result, a novel mechanotransduction Knowledge Base will be released as open and free database. The combination of the pioneering biomimetic investigation platform, cutting-edge high throughput screening, and high performance ML tools will enable reaching a thorough understanding of the correlations between applied biophysical stimuli and biological response, with the final aim to define the rationale basis for improved biophysical stimulation treatments, in view of precision orthopedic medicine.