Modelling Cytomegalovirus Growth Kinetics in Immunocompromised Children
Ben K Margetts (1,2,3), Judith Breuer (2,3), Nigel Klein (2,3), and Joseph F Standing (1,2,3)
(1) UCL CoMPLEX, London, UK, (2) Great Ormond Street Institute of Child Health, London, UK, (3) Great Ormond Street Hospital NHS Foundation Trust, London, UK
Objectives: To produce a three compartment cytomegalovirus (CMV) viral kinetic (VK) model that is able to accurately predict viral loads (VL) whilst maintaining parameter identifiability.
Methods: 69 VK profiles containing a total of 1598 CMV qPCR observations were extracted from haematopoetic stem cell transplant (HSCT) patients treated between 2010 and 2014. In addition to these profiles, we also extracted all drug administration and lymphocyte count data available for these children.
A single compartment model assuming logistic growth inhibited by antiviral treatment and immune response was initially fit to these data, but was not able to account for many of the defining features in the VK profiles. In response to this, a traditional 3 compartment VK model [1] was fitted to these data (using NONMEM 7.3), with antiviral treatment as a covariate on viral replication, and age-scaled total lymphocyte count as a covariate on total VL and infected cell reservoir. In order to confer parameter identifiability in this model, uninfected cell parameters were fixed to endothelial cell estimates.
Results: Model diagnostic plots were promising, demonstrating clear improvement in the model’s predictive power, with it able to consistently predict key disease progression events for the majority of patients. Simulations produced from the 3 compartment model were a substantial improvement over those produced by the single compartment model. It was able to capture a wide range of VK profiles, including slow exponential increases in VL, rapid decreases, and sharp oscillatory reactivation-like events. Parameter estimates were appropriate, demonstrating highly variable drug efficacy, a fast literature-supported [2] viral doubling time of ~ 1.1 days, and a potent immune response.
Conclusions: We have improved upon our single compartment CMV VK model, producing a more predictive, clinically applicable, three-compartment CMV VK model. This model can now be used to better inform us of the VK risk factors for developing drug resistant strains, allowing us to study the growth kinetics leading to CMV inter-host strain competition and viral persistence. Alongside these studies, we can now investigate the use of this model and its covariates for modelling other serious post-HSCT infections including Adenovirus and Epstein-Barr Virus.
References:
[1] Perelson AS. Modelling viral and immune system dynamics. Nat Rev Immunol. (2002): 2(1)
[2] Emery, Griffiths, et al. The Dynamics of Human Cytomegalovirus Replication in Vivo. J Exp Med. (1999): 190(2)