Validation of video tracking platform for automated quantification of osteoarthritis-like pain behaviour in the rat

Abstract

Osteoarthritis (OA) remains one of the leading causes of chronic pain while pharmaceutical treatments for OA-pain are limited and inefficient. Unfortunately, translational pain research is challenging and currently used assays have great limitations. The aim of this thesis project is to validate BlackBox One platform for automated acquisition and analysis of reliable, quantitative and objective data of spontaneous, unrestricted pain-like behaviour in rats treated with Tanezumab in complete Freund’s adjuvant- (CFA) and monosodium iodoacetate (MIA) -induced OA-like pain models. BlackBox was compared to CatWalk XT platform in the ability to assess weight bearing, and additional BlackBox behavioural parameters were explored. Effect of circadian rhythm was assessed with BlackBox in naïve rats, and monoarthritic pain models were induced by CFA tibiotarsal and MIA knee intra-articular injections with intra-venous Tanezumab treatment. The study found no effect of circadian rhythm in the analysis of the inspected behavioural parameters. Furthermore, both platforms recorded the reduced weight bearing due to the injured limb in CFA- and MIA-induced models as well as the analgesic efficacy of Tanezumab, with BlackBox displaying narrower or similar variation compared to CatWalk. Surprisingly, Distance Travelled was the sole parameter capturing only the reduction in this behaviour caused by the model, but not efficacy of Tanezumab. Additionally, Toes Spread parameter displayed great potential in recognising pain phenotype in the models. We successfully validated BlackBox One for the tested application, with the findings of the study and the growing capabilities of the platform supporting the use of BlackBox for potentially even beyond OA-research.