Konstantinos Biliouris (1), Marc Lavielle (2), Mirjam N Trame (1)
(1) Center for Pharmacometrics and Systems Pharmacology, Department of Pharmaceutics, College of Pharmacy, University of Florida, Orlando, USA, (2) Inria Saclay, POPIX team, Saclay, France
Objectives: Quantitative Systems Pharmacology (QSP) models are progressively entering the arena of contemporary pharmacology [1]. The efficient implementation and evaluation of complex QSP models necessitates the development of flexible computational tools that are built into QSP mainstream software. The objective of this study was to develop a versatile Matlab-based tool that accommodates complex QSP models and executes Monte Carlo simulations as well as automatic construction of Visual Predictive Checks (VPCs) [2] and Quantified VPCs (QVPCs) [3].
Methods: A computational tool, dubbed MatVPC, was built in Matlab 2013a for the simulation and automatic construction of VPC and QVPC plots of QSP models. In this tool, the user simply inputs i) the NONMEM-like dataset with observations, ii) the model equations, iii) the model parameters, and MatVPC outputs VPCs, QVPCs and Monte Carlo simulation plots at will. Unlike comparable computational tools, MatVPC is a unique all-in-one package that integrates the following: 1) it is publicly open, 2) it constructs VPC plots of complex QSP models, 3) it offers automatic data binning using a rigorous approach [4], 4) it constructs QVPC plots of complex QSP models, 5) it performs Monte Carlo simulations of the model and plots the results with any requested summary statistics and 6) it provides the option of post-plotting modification of graphical settings.
Results: Two models were implemented in MatVPC to illustrate its functionality: i) a three compartment pharmacokinetic model with oral and intravenous bolus dosing and ii) a pharmacodynamic model describing the body weight time course. These models were inserted in MatVPC and the respective VPCs and QVPCs were generated. The VPCs constructed with MatVPC were validated against VPCs constructed with the gold standard tools in pharmacometrics community [5], PsN/Xpose (coupled with NONMEM) and Monolix.
Conclusions: MatVPC is publicly available at https://sourceforge.net/projects/matvpc/ and can be utilized by users with little or no prior Matlab experience. Collectively, MatVPC constitutes a useful addition to the openly available toolboxes exploited by quantitative as well as clinical pharmacologists.
References:
[1] Visser SAG et al. Implementation of quantitative and systems pharmacology in large pharma. CPT: pharmacometrics & systems pharmacology (2014), 3(10): 1-10.
[2] Karlsson M and Holford N. A tutorial on visual predictive checks. PAGE meeting, Marseille, France, 2008.
[3] Post TM et al. Extensions to the visual predictive check to facilitate model performance evaluation. Journal of pharmacokin and pharmacodyn (2008), 35.2 : 185-202.
[4] Lavielle M and Bleakley K. Automatic data binning for improved visual diagnosis of pharmacometric models. Journal of pharmacokin and pharmacodyn (2011), 38(6):861-871.
[5] Vlasakakis G et al., White paper: landscape on technical and conceptual requirements and competence framework in drug/disease modeling and simulation, CPT:pharmacometrics & systems pharmacology (2013), 2.5:e40.
Reference: PAGE 24 (2015) Abstr 3429 [www.page-meeting.org/?abstract=3429]
Poster: Methodology - Other topics