Comparison of pharmacokinetic parameters estimated by the experimental R package 'nlmixr' and MONOLIX
Elvira Erhardt (1), Tom Jacobs (2), Mauro Gasparini (1)
(1) Politecnico di Torino, Turin, Italy, (2) Janssen Pharmaceutica NV, Beerse, Belgium.
Objectives: To develop a compartment model for infusion data and to compare its parameter estimates produced by two functions of the newly developed R-package 'nlmixr' and by MONOLIX.
Methods: The parameters of the compartmental model were first estimated with non-linear least-squares estimation. These results served as initial values in the following step, the extension of the model to a non-linear mixed effects model [1]. The mixed model estimations were conducted in a frequentist way with 'nlmixr' [2]. More precisely, the analytical as well as the ordinal differential equations (ODE's) model was fitted using the software package mentioned above. In MONOLIX [3], the frequentist maximum-likelihood estimation (MLE) was calculated and the parameter estimates together with the model fit of all three models were compared.
Results: It was shown that a three-compartment model with linear elimination is describing the plasma concentration data of the population adequately. The two different approaches of the 'nlmixr'-package delivered very similar estimates. However, these parameter estimates differed compared to MONOLIX.
Conclusions: The two functions tested included in the recently developed 'nlmixr' package for R offer a fast and satisfactory estimation of pharmacokinetic population data with results similar to those obtained with MONOLIX.
References:
[1] Pinheiro, J. and D. Bates (2000). Mixed-Effects Models in S and S-PLUS. Statistics and Computing. Springer New York.
[2] Wang, W. (2016). nlmixr: an R package for fitting PK and PKPD models. https:// github.com/nlmixrdevelopment/nlmixr/blob/master/inst/nlmixr-intro.pdf. [Online; accessed 20-February-2017].
[3] Lixoft (2016). Monolix 2016R1 User guide. http://monolix.lixoft.com/single-page/. [Online; accessed 20-February-2017].
