AIMC Topic: Antirheumatic Agents

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Machine learning prediction and explanatory models of serious infections in patients with rheumatoid arthritis treated with tofacitinib.

Arthritis research & therapy
BACKGROUND: Patients with rheumatoid arthritis (RA) have an increased risk of developing serious infections (SIs) vs. individuals without RA; efforts to predict SIs in this patient group are ongoing. We assessed the ability of different machine learn...

Machine learning in the prediction of treatment response in rheumatoid arthritis: A systematic review.

Seminars in arthritis and rheumatism
OBJECTIVE: This study aimed to investigate the current status and performance of machine learning (ML) approaches in providing reproducible treatment response predictions.

Natural language processing to identify and characterize spondyloarthritis in clinical practice.

RMD open
OBJECTIVE: This study aims to use a novel technology based on natural language processing (NLP) to extract clinical information from electronic health records (EHRs) to characterise the clinical profile of patients diagnosed with spondyloarthritis (S...

Development of a Machine Learning Model to Predict the Use of Surgery in Patients With Rheumatoid Arthritis.

Arthritis care & research
OBJECTIVE: One in five patients with rheumatoid arthritis (RA) rely on surgery to restore joint function. However, variable response to disease-modifying antirheumatic drugs (DMARDs) complicates surgical planning, and it is difficult to predict which...

Patient groups in Rheumatoid arthritis identified by deep learning respond differently to biologic or targeted synthetic DMARDs.

PLoS computational biology
Cycling of biologic or targeted synthetic disease modifying antirheumatic drugs (b/tsDMARDs) in rheumatoid arthritis (RA) patients due to non-response is a problem preventing and delaying disease control. We aimed to assess and validate treatment res...

Association of TLR 9 gene polymorphisms with remission in patients with rheumatoid arthritis receiving TNF-α inhibitors and development of machine learning models.

Scientific reports
Toll-like receptor (TLR)-4 and TLR9 are known to play important roles in the immune system, and several studies have shown their association with the development of rheumatoid arthritis (RA) and regulation of tumor necrosis factor alpha (TNF-α). Howe...

Immunopeptidomic Data Integration to Artificial Neural Networks Enhances Protein-Drug Immunogenicity Prediction.

Frontiers in immunology
Recombinant DNA technology has, in the last decades, contributed to a vast expansion of the use of protein drugs as pharmaceutical agents. However, such biological drugs can lead to the formation of anti-drug antibodies (ADAs) that may result in adve...

Phase 1b Study of the Safety, Pharmacokinetics, and Disease-related Outcomes of the Matrix Metalloproteinase-9 Inhibitor Andecaliximab in Patients With Rheumatoid Arthritis.

Clinical therapeutics
PURPOSE: Andecaliximab (GS-5745) is a highly selective monoclonal antibody against matrix metalloproteinase-9 (MMP9), a proteolytic enzyme implicated in the pathogenesis of rheumatoid arthritis (RA). This study assessed the safety and pharmacokinetic...

Stability of infliximab solutions in different temperature and dilution conditions.

Journal of pharmaceutical and biomedical analysis
Infliximab is a monoclonal antibody widely used for the treatment of inflammatory diseases. Over the past few years, many studies have assessed that monoclonal antibodies are prone to aggregation under stress conditions. The aim of this study was to ...