A Critical Role for Immune System Response in Mediating Anti-influenza Drug Synergies Assessed by Mechanistic Modeling

Abstract

Influenza virus infections represent a serious public health problem worldwide, due to the rapid emergence of drug resistance. One strategy to improve treatment efficacy is to combine drugs that act synergistically. Potentially useful drug combinations are typically identified through empirical testing using in vitro and animal models, but the complexity of the clinical situation warrants the use of more careful analysis and sophisticated approaches. To explore new approaches, we constructed a mechanistic model representing the interaction of antiviral drugs with the viral replication pathway and human immune responses. Simulation of combination therapy using oseltamivir and amantadine predicted significant therapeutic synergy only when immune response was included, in agreement with previous in vitro and in vivo studies using amantadine-resistant strains. Our model can be used to predict the optimal doses for combination therapy, and also raises questions about current drug evaluation methods that do not account for immune system interactions.

Figure 1

Modular structure of the full mechanistic model. The full model is comprised of five individual modules (in italics). Only the details of the virus life cycle module are shown. AMT, amantadine; APC, antigen presenting cells; E1, healthy uninfected epithelial cells; E2, refractory epithelial cells; E3, epithelial cells with influenza A virus (IAV) particles; E4, epithelial cells with replicated IAV; IFNA1, interferon-α1; IM, immune response module; OC, oseltamivir carboxylate; OP, oseltamivir phosphate; M2, M2 channel; NA, neuraminidase. Where possible, reaction arrows are labeled with parameters as found in Supplementary Tables S1 and S2 online.

Figure 2

Fitting of the pharmacokinetics (PK) modules for oseltamivir phosphate (OP) and amantadine (AMT). The PK modules for OP (a) and AMT (b) were parameterized based on a series of PK studies with single or multiple doses. In all plots, solid lines are best fits of the model and circles are measurements. (a) Left: Plasma OP and oseltamivir carboxylate (OC) concentrations of the oseltamivir loading (OL) group (150 + 75 mg) of a multidose study in Thai subjects; right: a 150-mg single-dose study in Japanese and Caucasian subjects. (b) Left: AMT plasma concentrations in the 100-mg once-daily group of a multidose study; right: plasma concentration averaged between young and elderly subjects in a 200-mg single-dose study.

Figure 3

Model simulation of the immune responses after infection. (a) Best fits of viral titers (upper panel) and interferon (IFN)-α (IFNA1) changes (bottom panel) after infection. Solid lines are model best fits while circles are experimental values. (b) Model simulation describes the dynamics of innate and adaptive immune responses. The population of infected antigen presenting cells (APCs) (dashed line) reach the highest point 48 h postinfection. Because infected APCs are the major source of secreted IFN-α in the beginning, the dashed curve is superimposed perfectly with the first peak of the solid curve (IFN-α/IFNA1). The second, minor peak of IFN-α (IFNA1) coincides with the migration of cytotoxic T cells (dash-dotted curve) to lung. TCID50, 50% tissue culture infection dose.

Figure 4

Comparison of model simulations of monotherapy with or without immune modules. Side-by-side comparison of the model without (−IM) and with (+IM) immune modules. Circles are experimental measurements (E) while solid lines are best fits (S) (S). (a) Best fits of viral titers after treatment with placebo, OP 75 mg twice daily, and OP 150 mg twice daily. (b) Best fits of viral titers after treatment with placebo or AMT 150 mg twice daily. (c) Simulated time course of viral titers (solid lines) or fraction of uninfected target cells (dashed lines) after influenza A infection. Note that the y-axes for viral titers are on the left while the y-axes for the uninfected fraction are on the right side of the plots. AMT, amantadine; OP, oseltamivir phosphate; TCID50, 50% tissue culture infection dose.

Figure 5

Comparison of model prediction of drug synergy with or without immune systems. Side-by-side comparison of the predicted synergy (S) between oseltamivir phosphate (OP) and amantadine (AMT) by models without (−IM) or with (+IM) immune systems. x-Axis is the dose of OP used in the combination; y-axis is the dose of AMT used. For each dose combinations, S is predicted and its value is color coded. The color map is shown to the right. Four types of influenza A virus (IAV) strains are simulated: wild type (a), AMT resistant (b), OP resistant (c), and double resistant (d). For all IAV strains, the +IM model predicts a greater degree of synergy across most dose combinations compared to the −IM model.