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.
Original language | English |
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Pages (from-to) | 89-114 |
Number of pages | 26 |
Journal | Open Access Rheumatology: Research and Reviews |
Volume | 16 |
DOIs | |
Publication status | Published - 18 May 2024 |
Keywords
- biomarkers
- genetics
- machine learning
- omics
- precision medicine