A population model for respiratory syncytial virus (RSV) kinetics using transit compartments based on human challenge data

Aims: Respiratory syncytial virus (RSV) causes acute respiratory tract infections, and is a major cause of hospital admissions and death in young children world-wide (1,2). Currently, no effective treatments exist in adults or children that can prevent or minimise the disease severity following exposure to the virus. The aims of this work were to develop a population model describing the viral kinetics of RSV in nasal lavage, and to describe how these kinetics were altered after treatment with an investigational RSV fusion inhibitor.

Methods: A target-cell limited viral kinetics model with delayed virus production developed by Baccam et al. for influenza A infections (3) is commonly used to describe RSV kinetics. However, the incubation period is considerably longer for RSV than influenza (4). As such, the model was adapted by increasing the number of transit compartments for the infected, non-producing and infected, producing cell populations to allow for a biologically more realistic description of the prolonged transition between the cell populations during the time course of the RSV infection. To ensure identifiability of the model, the virus elimination rate constant was fixed to a literature value of 0.125 hr-1, and the elimination rate constant of the infected, producing cells was assumed to be equal to the transition rate constant for the infected, non-producing cells. The initial number of target cells was set to 4108 according to the literature (3), while the bioavailability of the inoculum dose was estimated to obtain the initial number of virions in the system. The transit compartment model that best described the placebo data was carried forward into the PKPD model development for the investigational fusion inhibitor. Model development was conducted in NONMEM v7.3 (ICON Development Solutions, Hanover MD) using the SAEM estimation algorithm followed by importance sampling. Beal’s M3 method was applied to account for data below the lower limit of quantification (5).

Results: The best placebo model included four transit compartments for infected, non-producing cells, and a single compartment for producing cells. This model fitted the placebo data significantly better than the prior (literature-based) model (3) and was able to capture peak viral load unlike the Baccam model. Between-subject variability was included on the infection rate constant and virus production rate constant, and was found to be high (>200%), with a significant negative correlation (Pearson’s Correlation Coefficient = -0.97). The effect of treatment with the fusion inhibitor on RSV kinetics in nasal lavage was best described by a non-dose dependent transformation of the infectious virions into a non-infectious state.

Conclusion: An extended target-cell limited viral kinetics model with delayed virus production using a series of transit compartments was successfully applied to describe the viral kinetics of RSV in nasal lavage and the impact of treatment with a fusion inhibitor in a human challenge model.

1. Nair H el al. Global burden of acute lower respiratory infections due to respiratory syncytial virus in young children: a systematic review and meta-analysis. The Lancet. 2010;375(9725):1545–5.
2. Rudan I et al. Epidemiology and etiology of childhood pneumonia. Bulletin of the World Health Organization. 2008;86(5):408–16B.
3. Baccam P et al. Kinetics of influenza A virus infection in humans. Journal of Virology. 2006; 80(15):7590–9.
4. Lessler J et al. Incubation periods of acute respiratory viral infections: a systematic review. Lancet Infect Dis. 2009;9(5):291-300.
5. Beal SL. Ways to fit a PK model with some data below the quantification limit. J Pharmacokinet Pharmacodyn. 2001;28(5):481–504.