Abstract
The ability of rodent immune-mediated arthritis models to quantitatively predict therapeutic activity of anti-arthritis agents is poorly understood. Two commonly used preclinical model of arthritis are adjuvant-induced arthritis (AIA) and collagen-induced arthritis (CIA) in rats. The objective of the current study is to investigate the relationship between efficacy in AIA and CIA in rats, and clinical efficacy in rheumatoid arthritis patients using translational PK-PD analysis. A range of doses of indomethacin (a nonsteroidal anti-inflammatory drug), and three disease-modifying anti-rheumatic drugs (DMARD), methotrexate, etanercept, and tofacitinib, were evaluated in AIA and CIA rats. Dexamethasone was included in this study as a positive control. Ankle diameter AUC (AUCankle) and ankle histopathology summed scores (AHSS) were used as efficacy endpoints for activity against disease symptoms (joint inflammation) and disease progression (joint damage), respectively. Translational PK-PD analysis was performed to rank-order preclinical efficacy endpoints at clinically relevant concentrations. For each drug tested, inhibition of both AUCankle and AHSS scores were generally comparable in both magnitude and rank order. Overall, based on both AUCankle and the AHSS inhibition, the rank ordering of preclinical activity for the DMARDs evaluated was tofacitinib > etanercept ≥ methotrexate. This ranking of preclinical efficacy was consistent with reported clinical efficacy. Of interest, indomethacin showed equal or often better efficacy than the three DMARDs evaluated on inhibiting AHSS despite having limited ability to prevent joint damage clinically in patients. The translational value of performing PK-PD analysis of arthritis models in rats is discussed.
- animal models
- arthritis
- drug discovery
- mathematical modeling
- pharmacodynamics
- pharmacokinetic / pharmacodynamic modeling
- pharmacokinetics
- The American Society for Pharmacology and Experimental Therapeutics