Osteoarthritis (OA) is a joint disease involving the degradation of joint cartilage and bone. Strongly associated with aging and joint injury, incidence increases greatly with age and evidence of OA is thought to be present in over 80% of those over 75. The disease results in progressively worsening pain and loss of mobility. OA is currently treated with pain relief and in some cases surgery, which aims to improve mobility. However, there are currently no treatment regimes that can slow or halt disease progression. Clinical trials of treatments targeting mediators of OA have so far been unsuccessful. It is clear that more research is needed on the biochemical pathways in OA and their reaction to disease-modifying treatments.

Cytokines, a class of short-lived signalling molecules, are implicated in OA. Concentrations of a wide range of cytokines are raised in OA cartilage, leading to excessive cartilage turnover, cell death and inflammation. Anti-cytokine therapy is used successfully to treat several cytokine related disorders, most notably Rheumatoid Arthritis (RA). However despite the success of these treatments in RA and the similarities between RA and OA, trials of anti-cytokine therapy for OA have not shown significant benefit.

We present here a spatial model of cartilage implemented in the Compucell3D framework. We discuss why the Compucell3D modelling framework is particularly suitable for modelling of cartilage disease and show how this type of model can simulate both normal tissue and osteoarthritis tissue. We demonstrate how the cytokine feedback networks can lead to ongoing degradation where there is a predisposition to osteoarthritis, with various initiating factors.  We then show how treatment strategies that target the cytokine network can interrupt the feedback mechanisms, halting disease progression.