An Immune quantitative network aimed for viral hepatitis B
Eduardo Asín-Prieto1, Zinnia P Parra-Guillen1, José David Gómez Mantilla1, Joris Vandenbossche2, Kym Stuykens2, Xavier Woot de Trixhe2, Juan José Perez-Ruixo2, Iñaki F. Troconiz1
1, Pharmacometrics & Systems Pharmacology Group, Department of Pharmacy and Pharmaceutical Technology, School of Pharmacy, University of Navarra, Pamplona 31008, Spain; 2, Janssen R&D, Beerse, Belgium
Background: The liver is a well-known immunotolerogenic environment characterized by absence of exacerbated immune responses, thus providing the adequate setting for liver infectious pathogens persistence such as the hepatitis B virus (HBV). A good understanding of viral dynamics and its interaction with the immune system is essential to identify key biomarkers, potential therapeutic target and predict responses to current or future therapeutic approaches. Different efforts have been undertaken to model individual aspects of the immune response and its interplay with the virus[1–3]. However, little has been done to integrate this information into multiscale QSP models. The FIRM represents an integrative effort of different sub-models in lung immunology[4]. The objective of this work is to provide a comprehensive overview and topological representation of a model able to characterize the full immune response against HBV.
Methods: A comprehensive bibliographic review in different public databases and repositories has been performed, with special focus on original studies performed in humans, to identify and characterise the main components (nodes) involved in the immune response to HBV and its viral dynamics. A topological representation of the interplay between the different identified elements has been created to describe the extracted information.
Results: An annotated repository with over 200 publications has been created. The full model has been divided into four interconnected sub-models characterising the viral dynamics, innate response and humoral and cellular responses. A total of 60 nodes, including viral components, immune cells, receptors and cytokines, in 3 different physiologic spaces (blood, lymph tissue and liver) have been identified together with their role in the system and implemented in a QSP model.
Conclusion: An immune platform beyond the FIRM[4] has been developed, which, once it has undergone model reduction, will be able to help understand, simulate and predict the response of and to different therapeutic agents against HBV. The resulting immune model can be used to (i) understand the mechanism of action of different agents and their effects (in terms of efficacy and safety), (ii) identify predictive biomarkers and/or (iii) optimise dose and dosing regimens and experimental designs of both in vitro and in vivo studies and clinical trials. Finally, the developed model has the potential to be extrapolated to other immune diseases.
References:
[1] Ciupe SM, Ribeiro RM, Perelson AS. Antibody responses during hepatitis B viral infection. PLoS Comput Biol 2014;10:e1003730. doi:10.1371/journal.pcbi.1003730.
[2] Long C, Qi H, Huang S-H. Mathematical modeling of cytotoxic lymphocyte-mediated immune response to hepatitis B virus infection. J Biomed Biotechnol 2008;2008:743690. doi:10.1155/2008/743690.
[3] Marchuk GI, Petrov R V, Romanyukha AA, Bocharov GA. Mathematical model of antiviral immune response. I. Data analysis, generalized picture construction and parameters evaluation for hepatitis B. J Theor Biol 1991;151:1–40.
[4] Palsson S, Hickling TP, Bradshaw-Pierce EL, Zager M, Jooss K, O’Brien PJ, et al. The development of a fully-integrated immune response model (FIRM) simulator of the immune response through integration of multiple subset models. BMC Syst Biol 2013;7:95. doi:10.1186/1752-0509-7-95.
