Applying of population PK-PD methods to analysis of viral dynamics of HIV/HCV-Coinfected Sustained Virological Responders and Nonresponders treated with PEG-IFN
Svetlana Vinogradova (1,2), Kirill Zhudenkov (1,3), Tatiana Karelina (1,2)
(1) Institute for Systems Biology SPb, Moscow, Russia; (2) Moscow State University, Moscow, Russia; (3) Gamaleya Institute for Epidemiology and Microbiology, Moscow, Russia
Objectives: Mathematical models have been widely used for understanding viral dynamics of hepatitis C virus (HCV) [1,2]. An adapted model of viral dynamics developed by Neumann et al. [2] was used to describe the kinetics and interaction of target cells, infected cells and viruses in HIV/HCV-coinfected patients. Previously it was reported that high inter-individual variability (IIV) on many PD parameters is observed, so population approach seems reasonable.
Methods: Plasma concentration of PEG-IFN (350 samples) and viral load (HCV RNA, 333 observations) arising from 24 HIV/HCV-coinfected patients were available from [1]. The viral inhibition was driven by the predicted PEG-IFN PK profile based on the population PK parameter estimates including IIV on rate of absorption of PEG-IFN and volume of distribution. The viral load data was fitted using FOCEI method in NONMEM and SAEM method in MONOLIX, assuming that viral load and number of target and infected cells was in steady-state before therapy was initiated, with baseline at V0, T0 and I0. The preferred model was selected based on the precision of parameter estimates, standard error of population parameters, correlation of estimates and log-likelihood. Goodness of fit plots for individuals were also checked.
Results: The preferred model is model with IIV on EC50 and infected cell loss rate. Population values of the parameters were close to median values obtained in [1]. We used nonparametric methods to compare parameters of the model for SVR group with those of NR group. The median EC50 didn't differ significantly between SVR and NR groups (0.42 vs 0.59). By contrast, the median infected cell loss rate is significantly faster in SVRs compared with NRs (0.51 vs. 0.12 days-1, P=0.029), that is in agreement with the results obtained in [1]. Introducing SVR/NR grouping as covariance parameter results in decreasing of log-likelihood, but not all the IIV parameters are estimated precisely (CV>50%).
Conclusions: The current analysis demonstrated that both FOCEI and SAEM algorithms implemented in NONMEM and MONOLIX are useful for fitting complex mechanistic models requiring multiple differential equations allowing good fitting and sufficiently precise parameter estimation.
References:
[1] Talal AH, Ribeiro RM, Powers KA, Grace M, Cullen C, Hussain M, Markatou M, Perelson AS. Pharmacodynamics of PEG-IFN alpha differentiate HIV/HCV coinfected sustained virological responders from nonresponders. Hepatology. 2006 May;43(5):943-53.
[2] Neumann AU, Lam NP, Dahari H, Gretch DR, Wiley TE, Layden TJ, Perelson AS. Hepatitis C viral dynamics in vivo and the antiviral efficacy of interferon-alpha therapy. Science. 1998 Oct 2;282(5386):103-7.
