Bioinformatics approach to identifying effective sensitising therapeutics for rheumatoid arthritis

Abstract

Rheumatoid arthritis (RA) is a chronic autoimmune disorder that has a significant impact on quality of life and work capacity. It remains difficult to treat effectively, so this thesis develops a bioinformatics pipeline to repurpose existing drugs and identify synergistic combinations. By analysing high‑quality transcriptomic datasets from public repositories, the work links RA‑related gene expression patterns to compounds predicted to reverse harmful molecular signatures. Overall, the findings demonstrate that the proposed framework is an effective tool for accelerating drug discovery and suggest promising therapeutic avenues that warrant further experimental and clinical investigation.

Thesis is embargoed until 31st July 2027.

Date of Award	Jul 2025
Original language	English
Sponsors	Department for the Economy
Supervisor	Shu-Dong Zhang (Supervisor), Tony Bjourson (Supervisor) & David Gibson (Supervisor)