Accepted_test

The aim of the presented study is the development of mathematical models that meet the requirements of the current level of research in immunology, the distributed parameters systems in the space of phenotypic traits (e.g., affinity/avidity of receptors) and physical characteristics, the network models of interaction of cellular ensembles, structural modules of intracellular regulation. Fundamentally new elements of the proposed multi-physics modelling and analysis tools are (1) the use of methods of evolutionary dynamics on adaptive landscapes to describe the connectivity of populations of immune cells and the clonal repertoire under the influence of random antigenic forcing, (2) the formation of fitness landscapes to assess the information-entropy characteristics of the system and predict changes in its complexity and system efficiency, (3) the description of a hierarchical organization of regulatory processes, and (4) the application of meta-analysis algorithms for calibration of the processes described in models. We consider the mathematical model of lymphocytic choriomeningitis virus (LCMV) replication in infected cells has been developed and calibrated. The mathematical model describing the turnover kinetics of exhausted CD8 T cell population in chronic LCMV infection is presented and used to make predictions of the effect of anti-PDL-1 therapies. Based on the systems biology concept of multi-stability and the prediction of multiplicative cooperativity between virus-specific cytotoxic T cells and neutralising antibodies, we argue for the requirements to engage multiple immune system components for functional cure strategies.