Uncovering combination therapies for Immune-Mediated Inflammatory Diseases through systems biology analysis on longitudinal patient data 3497

Description Despite advancements in targeted therapies, most patients with immune-mediated inflammatory diseases (IMIDs) fail to achieve sustained remission. Combining existing drugs has the potential to overcome this. We performed bulk and scRNA-Seq analyses of longitudinal blood samples of patients from six IMIDs including rheumatoid arthritis, psoriasis, psoriatic arthritis, Crohn’s disease, ulcerative colitis, and systemic lupus erythematosus. A total of 186 patients were analyzed at the initiation of a targeted therapy and at the time of clinical response. Using a novel systems biology approach, we determined drug pairs with the highest likelihood of synergy. scRNA-Seq data on 2.1 million PBMCs validated the top drug combinations. Our analysis identified anti-TNF and anti-IL6R therapies as highly complementary for RA. This combination mitigated non-responder molecular signatures, generated transcriptional profiles resembling those of healthy individuals, and demonstrated specificity and non-redundancy. The complementarity was validated using independent data. Longitudinal scRNA-Seq analysis of PBMCs corroborated the combinatorial effect, identifying a population of monocytes as key mediators of efficacy. Through systems biology analysis of patient data, we have found that the combination of anti-TNF and anti-IL6R therapies shows significant potential to overcome the current therapeutic ceiling in RA. The drug combination is currently under evaluation in a clinical study. Funding Sources This work was supported by the DocTIS2 project, funded by the European Union’s Horizon 2020 Research and Innovation Programme under Grant Agreement N° 848028 Topic Categories Computational and Systems Immunology (COMP)