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- W1553771325 abstract "The most rigorous scenario for testing a candidate rheumatoid arthritis therapeutic would be to use clinically relevant biomarkers and readouts to monitor disease development in an animal model that has a mechanism of disease that reflects the human condition. Treatment should begin when the full spectrum of arthritic processes, including bone damage, is present. We have tried to take this approach to evaluate a novel EP4 receptor antagonist (ER-886046) for its anti-arthritic potential. This work aimed not only to test a potential drug, but to also demonstrate a strategy for performing a more clinically relevant evaluation of future candidate arthritis treatments. A variety of biomarkers including: radiographic evaluation, clinical scoring, histology analysis, F4/80 macrophage immunohistochemistry, luminol bioluminescent imaging and (99m)Tc-MDP-SPECT imaging were evaluated as disease readouts in the mouse anti-collagen antibody induced arthritis model (CAIA). CAIA mice were treated either prophylactically or therapeutically with ER-886046 and the compound's efficacy was probed using the various biomarkers and compared to the reference drugs prednisolone and celecoxib. The various biomarkers effectively measured different aspects of arthritis pathology and consistently demonstrated the efficacy of ER-886046. The compound was found to be effective even when dosed therapeutically after bone damaging processes had initiated. The results presented herein demonstrate how biomarkers and a clinically relevant experimental design can be used to evaluate a candidate therapeutic. Utilization of clinically relevant biomarkers may provide a means for more translatable pre-clinical testing of candidate therapeutics and may provide information on their mechanism of action." @default.
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- W1553771325 date "2013-01-01" @default.
- W1553771325 modified "2023-10-12" @default.
- W1553771325 title "Evaluation of a candidate anti-arthritic drug using the mouse collagen antibody induced arthritis model and clinically relevant biomarkers." @default.
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