AIMC Topic: Antirheumatic Agents
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Ligand supplementation restores the cancer therapy efficacy of the antirheumatic drug auranofin from serum inactivation.
Nature communications
Aug 9, 2025
Auranofin, an FDA-approved antirheumatic gold drug, has gained ongoing interest in clinical studies for treating advanced or recurrent tumors. However, gold ion's dynamic thiol exchange nature strongly attenuates its bioactivity due to the fast forma...
Disease activity and treatment response in early rheumatoid arthritis: an exploratory metabolomic profiling in the NORD-STAR cohort.
Arthritis research & therapy
Jul 26, 2025
BACKGROUND: The variability in treatment response in people with rheumatoid arthritis (RA) warrants the prediction of patients at high risk of treatment failure. Identification of biomarkers linked to clinical remission in RA is currently a challenge...
A longitudinal cohort study uncovers plasma protein biomarkers predating clinical onset and treatment response of rheumatoid arthritis.
Nature communications
Jul 21, 2025
Rheumatoid arthritis (RA) is a systemic inflammatory condition posing challenges in identifying biomarkers for onset, severity and treatment responses. Here we investigate the plasma proteome in a longitudinal cohort of 278 RA patients, alongside 60 ...
A robust machine learning approach to predicting remission and stratifying risk in rheumatoid arthritis patients treated with bDMARDs.
Scientific reports
Jul 4, 2025
Rheumatoid arthritis (RA) is a chronic autoimmune disease affecting millions worldwide, leading to inflammation, joint damage, and reduced quality of life. Although biological disease-modifying antirheumatic drugs (bDMARDs) are effective, they are co...
Deep molecular profiling of synovial biopsies in the STRAP trial identifies signatures predictive of treatment response to biologic therapies in rheumatoid arthritis.
Nature communications
Jul 2, 2025
Approximately 40% of patients with rheumatoid arthritis do not respond to individual biologic therapies, while biomarkers predictive of treatment response are lacking. Here we analyse RNA-sequencing (RNA-Seq) of pre-treatment synovial tissue from the...
Clinical prediction models for medication adverse events in patients with rheumatic and musculoskeletal conditions: A systematic literature review.
Seminars in arthritis and rheumatism
Apr 11, 2025
OBJECTIVES: This systematic review aims to identify, summarize, and evaluate the methodological quality of existing clinical prediction models (CPMs) that predict adverse events (AEs) associated with medications prescribed for rheumatic and musculosk...
Artificial intelligence to predict treatment response in rheumatoid arthritis and spondyloarthritis: a scoping review.
Rheumatology international
Apr 7, 2025
To analyse the types and applications of artificial intelligence (AI) technologies to predict treatment response in rheumatoid arthritis (RA) and spondyloarthritis (SpA). A comprehensive search in Medline, Embase, and Cochrane databases (up to August...
Common genetic variants do not impact clinical prediction of methotrexate treatment outcomes in early rheumatoid arthritis.
Journal of internal medicine
Apr 6, 2025
BACKGROUND: Methotrexate (MTX) is the mainstay initial treatment of rheumatoid arthritis (RA), but individual response varies and remains difficult to predict. The role of genetics remains unclear, but studies suggest its importance.
Leveraging machine learning for drug repurposing in rheumatoid arthritis.
Drug discovery today
Mar 11, 2025
Rheumatoid arthritis (RA) presents a significant challenge in clinical management because of the dearth of effective drugs despite advances in understanding its mechanisms. Drug repurposing has emerged as a promising strategy to address this gap, off...
Predicting abatacept retention using machine learning.
Arthritis research & therapy
Feb 1, 2025
BACKGROUND: The incorporation of machine learning is becoming more prevalent in the clinical setting. By predicting clinical outcomes, machine learning can provide clinicians with a valuable tool for refining precision medicine approaches and improvi...
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