Violeta Balbás-MartÃnez(1)-Leire Ruiz-Cerdá(1), Ignacio González-GarcÃa(4), Itziar Irurzun-Arana(1), José David Gómez-Mantilla(1-2), Chuanpu Hu(4), Honghui Zhou(4), An Vermeulen(5), Iñaki F. Trocóniz(1-2).
(1)Pharmacometrics & Systems Pharmacology, Department of Pharmacy and Pharmaceutical Technology, University of Navarra, Pamplona, Spain. (2)IdiSNA, Navarra Institute for Health Research. Navarra, Spain (3)Pharma Mar, Madrid, Spain (4)Model Based Drug Development, Janssen Research and Development, LLC, Spring House, PA 19477, USA (5)Janssen Research and Development, a division of Janssen Pharmaceutica NV, Beerse B-2340, Belgium
Objectives: To develop a Systems Pharmacology (SP) model for IBD able to evaluate therapeutic targets for different types of IBD patients, focused on the change in the Crohn Disease Activity Index (CDAI) in each scenario. Additionally it was intended to identify a subgroup of patients non responders to an anti-TNFα therapy (current standard) and propose alternative therapies for such individuals.
Methods: A Boolean Network model, based on an exhaustive bibliographic review, was implemented in the SP platform AITOR [1]. The network contained 48 nodes (20 of them reported to be altered in IBD patients) and 226 interactions. Simulations of the immune response were performed assuming chronic response to four different types of microbial antigens. CDAI was analysed through the increase or decrease of the relative expression of the main nodes associated with clinical manifestations in IBD (Metalloproteinases, Perforin and Granzime B) [2-3]. Relative expression of nodes was calculated as obtaining the activation probability of each node after the network reached the attractor state. The network was evaluated comparing the results of the simulations to the reported results of clinical trials for five investigated molecules: anti-IFNγ, anti-TNFα, anti-IL2, anti-IL17 and anti-IL21.
Results: Only anti-TNFα decreased the simulated CDAI score in typical IBD patients. Anti-IL17 showed a slight improvement in the simulated CDAI score. Anti-IFNγ, anti-IL2 and anti-IL21 did not show any improvement of the CDAI score when simulated alone. Simulations of an anti-TNFα therapy showed less efficacy in patients with antigen impairment elimination (alteration in NK or Defensins function). A combined simulated therapy of anti-IL17, anti-TNFα and anti-IFNγ showed an improvement in the CDAI score reduction compared to anti-TNFα alone.
Conclusions: The obtained results satisfactory replicated the outcome of reported clinical trials. Anti-TNFα may not show efficacy in individuals with impaired antigen elimination. A combination of anti-IL17, anti-TNFα and anti-IFNγ could show more improvement in the CDAI score than other therapies. The proposed SP model is potentially useful to identify new therapeutic targets and to optimize therapy combinations. Simulation of more polymorphisms could lead to efficient patient stratification.
References:
[1] Itziar Irurzun-Arana, Methodology for Boolean Modeling of Biological Networks Applied to Systems Pharmacology. PAGE meeting 2015 conference abstract http://bit.ly/1GOyLRx.
[2]Biancheri, Paolo, Antonio Di Sabatino, Gino R. Corazza, and Thomas T. MacDonald. 2013. “Proteases and the Gut Barrier.” Cell and Tissue Research 351 (2): 269–80.
[3] Cupi, Maria Laura, Massimiliano Sarra, Irene Marafini, Ivan Monteleone, Eleonora Franzè, Angela Ortenzi, Alfredo Colantoni, et al. 2014. “Plasma Cells in the Mucosa of Patients with Inflammatory Bowel Disease Produce Granzyme B and Possess Cytotoxic Activities.” Journal of Immunology 192 (12): 6083–91.
Reference: PAGE 25 () Abstr 5992 [www.page-meeting.org/?abstract=5992]
Poster: Drug/Disease modeling - Other topics