Dmitry S. Grebennikov’s research while affiliated with Sechenov University and other places

Mathematical model of immune system and its adaptation in response to the evolutionary dynamics of pathogens based on solution the Hamilton-Jacoby -Bellman and Feynman-Kac-Kolmogorov equation.

Optimal disturbances of the periodic solution of the hepatitis B dynamics model corresponding to the chronic recurrent form of the disease are found. The dependence of the optimal disturbance on the phase of periodic solution is analyzed. Four phases of the solution are considered, they correspond to clinically different periods of development of the immune response and severity of the disease, namely, activation of antiviral immune reactions, attenuation of reactions, peak and minimum viral load. The possibility of using optimal disturbances to exit the domain of attraction of the considered periodic solution using minimal impact is studied. The components of disturbances that may underlie the phenomenon of spontaneous recovery from chronic hepatitis B observed in clinical practice are identified.

We formulate a compartmental model of the murine lymphatic system with the transfer rate parameters derived from the data on the geometric characteristics of the lymphatic system (LS) graph structure and the Hagen–Poiseuille-based values of the lymph flows through the system components, i.e., vertices and edges. It is supplemented by the physics-based model of lymph node draining-related function which considers a paradigmatic view of its geometry with one- and three-afferent lymphatic vessels and one efferent vessel, and the lymph flow described by the Darcy–Starling equations. We discuss further modelling work needed to gain a predictive understanding of the LS function in response to various perturbations including infections and therapeutic treatments.

This work is devoted to the technology developed by the authors that allows one for fixed values of parameters and tracing by parameters to calculate stationary solutions of systems with delay and analyze their stability. We discuss the results of applying this technology to the Marchuk–Petrov antiviral immune response model with parameter values corresponding to hepatitis B infection. The presence of bistability and hysteresis properties in this model is shown for the first time.

Optimal disturbances of a number of typical stationary solutions of the hepatitis B virus infection dynamics model have been found. Specifically optimal disturbances have been found for stationary solutions corresponding to various forms of the chronic course of the disease, including those corresponding to the regime of low-level virus persistence. The influence of small optimal disturbances of individual groups of variables on the stationary solution is studied. The possibility of transition from stable stationary solutions corresponding to chronic forms of hepatitis B to stable stationary solutions corresponding to the state of functional recovery or a healthy organism using optimal disturbances is studied. Optimal disturbances in this study were constructed on the basis of generalized therapeutic drugs characterized by one-compartment and two-compartment pharmacokinetics.

The infectious disease caused by human immunodeficiency virus type 1 (HIV-1) remains a serious threat to human health. The current approach to HIV-1 treatment is based on the use of highly active antiretroviral therapy, which has side effects and is costly. For clinical practice, it is highly important to create functional cures that can enhance immune control of viral growth and infection of target cells with a subsequent reduction in viral load and restoration of the immune status. HIV-1 control efforts with reliance on immunotherapy remain at a conceptual stage due to the complexity of a set of processes that regulate the dynamics of infection and immune response. For this reason, it is extremely important to use methods of mathematical modeling of HIV-1 infection dynamics for theoretical analysis of possibilities of reducing the viral load by affecting the immune system without the usage of antiviral therapy. The aim of our study is to examine the existence of bi-, multistability and hysteresis properties with a meaningful mathematical model of HIV-1 infection. The model describes the most important blocks of the processes of interaction between viruses and the human body, namely, the spread of infection in productively and latently infected cells, the appearance of viral mutants and the development of the T cell immune response. Furthermore, our analysis aims to study the possibilities of transferring the clinical pattern of the disease from a more severe state to a milder one. We analyze numerically the conditions for the existence of steady states of the mathematical model of HIV-1 infection for the numerical values of model parameters corresponding to phenotypically different variants of the infectious disease course. To this end, original computational methods of bifurcation analysis of mathematical models formulated with systems of ordinary differential equations and delay differential equations are used. The macrophage activation rate constant is considered as a bifurcation parameter. The regions in the model parameter space, in particular, for the rate of activation of innate immune cells (macrophages), in which the properties of bi-, multistability and hysteresis are expressed, have been identified, and the features cha rac terizing transition kinetics between stable equilibrium states have been explored. Overall, the results of bifurcation analysis of the HIV-1 infection model form a theoretical basis for the development of combination immune-based therapeutic approaches to HIV-1 treatment. In particular, the results of the study of the HIV-1 infection model for parameter sets corresponding to different phenotypes of disease dynamics (typical, long-term non-progressing and rapidly progressing courses) indicate that an effective functional treatment (cure) of HIV-1-infected patients requires the development of a personalized approach that takes into account both the properties of the HIV-1 quasispecies population and the patient’s immune status.

The immune system is a complex distributed system consisting of cells, which circulate through the body, communicate and turnover in response to antigenic perturbations. We discuss new approaches to modelling the functioning of the immune system of humans and experimental animals with a focus on its ‘complexity’. Emerging mathematical and computer models are reviewed to describe the immune system diversity, the cell/cytokine network communication structures, hierarchical regulation, and evolutionary dynamics of immune repertoires.

Developing physiologically meaningful mathematical models that describe multilevel regulation in a complex network of immune processes, in particular, of the system of interferon-regulated virus production processes, is a fundamental scientific problem, within the framework of an interdisciplinary systems approach to research in immunology. Here, we have presented a detailed high-dimensional model describing HIV (human immunodeficiency virus) replication, the response of type I interferon (IFN) to the virus infection of the cell, and suppression of the action of IFN-induced proteins by HIV accessory proteins. As a result, this model includes interactions of all three processes for the first time. The mathematical model is a system of 37 nonlinear ordinary differential equations including 78 parameters. Importantly, the model describes not only the processes of the IFN response of the cell to virus infection, but also the mechanisms used by the virus to prevent effects of the IFN system.

The immune system is a complex multiscale multiphysical object. Understanding its functioning in the frame of systemic analysis implies the use of mathematical modelling, formulation of data consistency criterion, estimation of parameters, uncertainty analysis, and optimal model selection. In this work, we present some promising approaches to modelling the multi-physics immune processes, i.e., cell migration in lymph nodes (LN), lymph flow, homeostatic regulation of immune responses in chronic infections. To describe the spatial-temporal dynamics of immune responses in lymph LN, we propose a model of lymphocyte migration, based on the second Newtons law and considering three kinds of forces. The empirical distributions of three lymphocytes motility characteristics were used for model calibration using the KolmogorovSmirnov metric. Prediction of lymph flow in a lymph node requires costly computations, due to diversity of sizes, forms, inner structure of LNs and boundary conditions. We proposed an approach to lymph flow modelling based on replacing the full-fledged computational physics-based model with an artificial neural network (ANN), trained on the set of pre-formed results computed using an initial mechanistic model. The ANN-based model reduces the computational time for some lymph flow characteristics by four orders of magnitude. Calibration of MarchukPetrov model of antiviral immune response for SARS-CoV-2 infection was performed. To this end, we used previously published data on the viral load kinetics in nasopharynx of volunteers, and data on the observed ranges of interferon, antibodies and CTLs in the blood. The parameters, which have the most significant impact at different stages of infection process, were identified. Inhibition of immune mechanisms, e.g., T cell exhaustion, is a distinctive feature of chronic viral infections and malignant diseases. We propose a mathematical model for the studies of regulation parameters of four exhausted T cell subsets in order to examine the balance of their proliferation and differentiation determined by interaction with SIRPa+ PD-L1+ and XCR+1 dendritic cells. The model parameters are evaluated, in order to study the reinvigoration effect of aPD-L1 therapy on the homeostasis of exhausted cells.

Developing physiologically meaningful mathematical models that describe multilevel regulation in a complex network of immune processes, in particular, of the system of interferon-regulated virus reproduction processes, is a fundamental scientific problem, within the framework of an interdisciplinary systematic approach to research in immunology. Here, we have presented a detailed high-dimensional model describing HIV (human immunodeficiency virus) replication, the response of type I interferon (IFN) to penetration the virus into cell, and suppression of the action of IFN-induced proteins by HIV accessory ones. As a result, developed model for the first time includes interactions of all three processes. The mathematical model is a system of 37 non-linear ordinary differential equations including 78 parameters. The peculiarity of the model is that it describes not only the processes of the IFN response of the cell to virus infection, but also the mechanisms used by the virus to prevent effects of the IFN system.