Rheumatoid arthritis is an autoimmune disease that causes joint inflammation, pain, and damage, affecting about 1 in 100 adults. Current treatment includes drugs like methotrexate, biologic injections targeting TNF or IL-6, and JAK inhibitor pills. Many people now achieve remission or low disease activity, though finding the right treatment often requires trial and error.
What's actually going on in research
Trials are testing new JAK inhibitors with different selectivity profiles, bispecific antibodies that hit two immune targets at once, and drugs that target other immune pathways like IL-17 or IRAK4. Researchers are also studying how to predict which patients will respond to which drugs, aiming to replace the current trial-and-error approach with precision matching.
Bispecific antibodies
These engineered proteins block two different immune signals at once, potentially offering stronger control than single-target drugs. Several are in mid-stage trials for people who haven't responded to standard biologics.
Precision medicine
Studies are identifying blood markers and genetic signatures that predict response to specific drugs. The goal is to match people to the right treatment on the first try rather than cycling through options.
IRAK4 inhibitors
These oral drugs target a different immune pathway than JAK inhibitors. Early trials suggest they may work for people who don't respond to current treatments.
What to know before you search
Eligibility typically depends on disease activity level, how long you've had symptoms, which treatments you've tried, and whether certain antibodies are present in your blood.
What types of trials are currently open
- Treatment trials — Testing new biologics, pills, or combination therapies to see if they control joint inflammation better than current options.
- Head-to-head trials — Comparing two active treatments directly to see which works better for specific groups of patients.
- Early arthritis trials — Testing whether aggressive early treatment can prevent joint damage or achieve drug-free remission.
- Biomarker studies — Collecting blood and tissue samples to identify markers that predict treatment response or disease progression.
- Prevention trials — Testing whether treatment can prevent arthritis in people with elevated antibodies but no joint symptoms yet.
Recently added Rheumatoid Arthritis trials
Evaluation of the Prevalence, and Immunological Characteristics of Small Fiber Neuropathy in Patients With Primary Sjögren's Syndrome
The investigators propose to conduct a prospective study evaluating the prevalence of SNN in pSS patients and to find clinical characteristics and specific immunological profiles in pSS patients with SFN. Peripheral nervous system involvement account for 15% of pSS cases. Among peripheral nervous system complication, SFN appears to be prevalent. However the association between pSS and SFN has been scarcely evaluated. There are not many relevant studies using similar methodology to evaluate pSS patients for small fiber dysfunction. Furthermore, autoimmune mechanisms are thought to play a key role in SFN pathogenesis in pSS and the association between SFN and specific immunological profiles has been poorly studied. So the aim of this study is to evaluate the prevalence of SFN in pSS patients by using the Sudoscan which is a fast and non- invasive tool. The Sudoscan could offer an accessible alternative for early SFN detection, improving patient management. The secondary purpose is to analyze systemic and immunological profiles, as well as disease's activity and quality of life of patients with pSS-related SFN.
GenAI-Assisted Rheumatoid Arthritis Bone Erosion Risk Assessment and DMARD Selection
Rheumatoid arthritis (RA) is a chronic autoimmune disease characterized by progressive joint damage and bone erosion. Accurate assessment of RA bone erosion risk (RABER) and appropriate disease-modifying antirheumatic drug (DMARD) selection are critical to preventing irreversible disability. Recent advances in generative artificial intelligence (GenAI), particularly large language models (LLMs), enable integration of heterogeneous clinical data and may improve clinical decision-making. However, there is limited real-world evidence (RWE) evaluating whether GenAI can meaningfully augment physician decision-making in routine care. This prospective, single-arm, nonrandomized interventional study evaluates the feasibility and impact of GenAI-assisted clinical decision support on physician assessment of rheumatoid arthritis bone erosion risk and disease-modifying antirheumatic drug selection in routine inpatient care. Treating physicians document their initial risk assessments and treatment decisions before reviewing patient-specific GenAI reports and subsequently record their assessments and decisions after reviewing the reports. The study evaluates changes in physician clinical decision-making within a learning health system framework. Final treatment decisions remain under the responsibility of the treating physicians. The study does not evaluate long-term patient clinical outcomes.
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