Individualized Prediction of Response to Methotrexate Treatment in Patients with Rheumatoid Arthritis: A Pharmacogenomics-driven Machine Learning Approach Elena Myasoedova, MD, PhD – Mayo Clinic
4:10 PM – 4:20 PM ET
Circulating Biomolecules as Potential Biomarkers of Early and Establishedresponse to TNFi Therapy in Rheumatoid Arthritis Patients Maria Luque-Tevar, MSc – Rheumatology Department, Reina Sofia University Hospital/ Maimonides Institute for Research in Biomedicine of Cordoba (IMIBIC)/ University of Cordoba, Cordoba, Spain
4:20 PM – 4:30 PM ET
Histo-pathological Cellular Markers of Treatment Response to Rituximab and Tocilizumab in Matched Pre- and Post-treatment Synovial Biopsies from the R4RA Randomised Clinical Trial in Rheumatoid Arthritis Felice Rivellese, MD, PhD – Queen Mary University of London
4:30 PM – 4:40 PM ET
Identification of a Rule to Predict Response to Sarilumab in Patients with Rheumatoid Arthritis Using Machine Learning and Clinical Trial Data Ernest Choy, MD, FRCP – Cardiff University School of Medicine
4:40 PM – 4:50 PM ET
Whole Blood Transcriptional Changes Following Selective Inhibition of Janus Kinase 1 (JAK1) by Filgotinib in Adults with Moderately-to-Severely Active Rheumatoid Arthritis with Prior Inadequate Response to Methotrexate Peter C. Taylor, MD, PhD, MA – University of Oxford
