Osteoarthritis (OA) is characterized by irreversible cartilage degradation with very limited therapeutic interventions. Drug candidates targeted at prototypic players had limited success until now and systems based approaches might be necessary. Consequently, drug evaluation platforms should consider the biological complexity looking beyond well-known contributors of OA. In this study an ex vivo model of cartilage degradation, combined with measuring releases of 27 proteins, was utilized to study 9 drug candidates. After an initial single drug evaluation step the 3 most promising compounds were selected and employed in an exhaustive combinatorial experiment. The resulting most and least promising treatment candidates were selected and validated in an independent study. This included estimation of mechanical properties via finite element modelling (FEM) and quantification of cartilage degradation as glycosaminoglycan (GAG) release. The most promising candidate showed increase of Young's modulus, decrease of hydraulic permeability and decrease of GAG release. The least promising candidate exhibited the opposite behaviour. The study shows the potential of a novel drug evaluation platform in identifying treatments that might reduce cartilage degradation. It also demonstrates the promise of exhaustive combination experiments and a connection between chondrocyte responses at the molecular level with changes of biomechanical properties at the tissue level.
Keywords: Cartilage biomechanics; Combinatorial drug treatment; In vitro model; Multiplex proteomics; Systems biology.