Towards Personalized Medicine in Rheumatoid Arthritis

Abstract

Rheumatoid arthritis (RA) is a chronic, incurable, multisystem, inflammatory disease characterized by synovitis and extra-articular features. Although several advanced therapies targeting inflammatory mechanisms underlying the disease are available, no advanced therapy is universally effective. Therefore, a ceiling of treatment response is currently accepted where no advanced therapy is superior to another. The current challenge for medical research is the discovery and integration of predictive markers of drug response that can be used to personalize medicine so that the patient is started on “the right drug at the right time”. This review article summarizes our current understanding of predicting response to anti-rheumatic drugs in RA, obstacles impeding the development of personalized medicine approaches and future research priorities to overcome these barriers.

Keywords:

• genetics
• omics
• biomarkers
• machine learning
• precision medicine

Disclosure

Dr James Bluett reports grants from Pfizer, travel/conference fees from Fresenius Kabi, travel/conference fees from UCB, outside the submitted work. The authors report no other conflicts of interest in this work.