Understanding the Complex Patterns Observed during Hepatitis B Virus Therapy

Abstract

Data from human clinical trials have shown that the hepatitis B virus (HBV) follows complex profiles, such as bi-phasic, tri-phasic, stepwise decay and rebound. We utilized a deterministic model of HBV kinetics following antiviral therapy to uncover the mechanistic interactions behind HBV dynamics. Analytical investigation of the model was used to separate the parameter space describing virus decay and rebound. Monte Carlo sampling of the parameter space was used to determine the virological, pharmacological and immunological factors that separate the bi-phasic and tri-phasic virus profiles. We found that the level of liver infection at the start of therapy best separates the decay patterns. Moreover, drug efficacy, ratio between division of uninfected and infected cells, and the strength of cytotoxic immune response are important in assessing the amount of liver damage experienced over time and in quantifying the duration of therapy leading to virus resolution in each of the observed profiles.

Global Dynamics and Implications of an HBV Model with Proliferating Infected Hepatocytes

“…Current antiviral therapies include standard interferon and PEGylated interferon therapies for short-term use and nucleoside/nucleotide analogues for long-term use [51][52][53], but there are still open questions about the optimum timing and ordering of the treatments [54,55]. Models that have made slightly different assumptions have fit their models to existing datasets showing complex virus dynamics resulting from clinical trials [22,27,29,37,38,41,43,[56][57][58].…”

“…While the effects of modifying the first two assumptions to more biologically realistic alternatives have been thoroughly studied [30,31,35,36], here we make a special study of the dynamic implications of relaxing the assumption that infected hepatocytes do not reproduce. It must be noted that many HBV infection models also remove this assumption [16,[38][39][40][41][42][43], with Dahari et al [38], for example, suggesting that differing proliferation dynamics among healthy and infected hepatocytes could help explain varying patterns of viral load decays observed after treatment initiation, while Reluga et al [39] applied a similar model to chronic hepatitis C viral dynamics. Goyal et al [42] suggested that infected hepatocytes proliferating to produce uninfected daughter cells may be an important dynamic in preventing acute HBV infection, which directly affects up to 99% of hepatocytes, from progressing to the chronic state.…”

Early events in hepatitis B infection: the role of inoculum dose

“…Mathematical models have provided a reliable platform for in-depth analysis, quantification, and mechanistic description of host-pathogen interactions [23][24][25][26][27][28][29][30][31][32][33][34][35][36]. In particular, they have been used to determine how inoculum dose correlates with pathogen kinetics and immune response development.…”

Special Issue “Mathematical Modeling of Viral Infections”

“…This issue on mathematical modelling of viral infections covers a number of viruses: HCV [ 12 , 13 , 14 , 15 ], hepatitis B virus (HBV) [ 16 , 17 ], HIV [ 18 ], influenza [ 19 ], and even viruses that are used to combat cancer [ 20 ]. Moreover some of the modelling, although applied to specific diseases, has wider applications as they describe intracellular processes that are common to a number of infections [ 12 , 13 , 14 ].…”

“…The impact of antiviral therapy was investigated by several groups. Rodriguez et al determined the processes and state of chronic HCV infection that delineated the patterns of viral decay under therapy [ 17 ]. Cao and McCaw compare the two main types of influenza models and describe the best circumstances for each model’s use to predict the results of antiviral therapy [ 19 ].…”