Virtual patients inspired by multiomics predict the efficacy of an anti-IFNα mAb in cutaneous lupus.

ABSTRACT: Lupus erythematosus is a heterogeneous autoimmune disease that requires treatments tailored to specific patient subsets. To evaluate in silico the efficacy of the anti-IFNα S95021 monoclonal antibody, we created a quantitative systems pharmacology model of cutaneous lupus and a virtual patient population, with attributes matching the diversity of actual patients. To this aim, we performed a multiomics profiling analysis of 337 lupus patients from the PRECISESADS cohort, thereby identifying four patient clusters with distinct immune dysregulation patterns, including various levels of type I interferon (IFN) pathway upregulation. Simulation of S95021 treatment in the virtual patient cohort (n = 241) predicted distinct clinical responses in patient clusters, with machine learnin

SUBMITTER: Hurez V 

PROVIDER: S-EPMC11804754 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature