Systems biology for battling rheumatoid arthritis: application of the Entelos PhysioLab platform

Syst Biol (Stevenage). 2005 Dec;152(4):256-62. doi: 10.1049/ip-syb:20050053.

Abstract

A large-scale mathematical model, the Entelos Rheumatoid Arthritis (RA) PhysioLab platform, has been developed to describe the inflammatory and erosive processes in afflicted joints of people suffering from RA. The platform represents the life cycle of inflammatory cells, endothelium, synovial fibroblasts, and chondrocytes, as well as their products and interactions. The interplay between these processes culminates in clinically relevant measures for inflammation and erosion. The simulation model is deterministic, which allows tracing back the mechanism of action for a particular simulation result. Different patient phenotypes are represented by different virtual patients. The RA PhysioLab platform has been used to systematically and quantitatively study the predicted therapeutic effect of modulating several molecular targets, which resulted in a ranking of putative drug targets and a workflow to confirm the simulations experimentally. In addition, critical pathways were identified that drive the predicted disease outcome. Within these pathways, targets were identified from public literature that were not previously associated with arthritis. The model provides insights into the biology of RA and can be used as a platform for hypothesis-driven research. Case studies of therapies directed against IL-12 and IL-15 illustrate the approach, with emphasis on the analysis of system dynamics.

MeSH terms

  • Algorithms
  • Antirheumatic Agents / administration & dosage*
  • Arthritis, Rheumatoid / drug therapy*
  • Arthritis, Rheumatoid / immunology*
  • Computer Simulation
  • Cytokines / immunology
  • Drug Therapy, Computer-Assisted / methods*
  • Humans
  • Immunologic Factors / immunology*
  • Models, Immunological*
  • Software
  • Systems Biology / methods*
  • Treatment Outcome

Substances

  • Antirheumatic Agents
  • Cytokines
  • Immunologic Factors