P Veng-Pedersen1. 1. University of Iowa, College of Pharmacy, S227, Iowa City, IA 52242, USA. veng@uiowa.edu
Abstract
OBJECTIVE: To present an overview of noncompartmentally-based modeling which is a modeling that makes use of systems analysis, predominantly linear systems analysis (LSA). FINDINGS: Fundamental elements of LSA presented from a linear operational viewpoint have a sound foundation in molecular stochastic independence (MSI). Powerful LSA procedures based on MSI presented such as convolution, deconvolution and disposition decomposition analysis (DDA) enable PK predictions and evaluations of drug input and delivery using models with simple general structures and few verifiable assumptions. DDA nonparametrically differentiates the unit impulse response (UIR) into generalized elimination and distribution functions. DDA applied in a linear and nonlinear context is central to many LSA procedures such as analytically exact direct deconvolution, nonparametric evaluation of drug elimination and distribution, steady state predictions, evaluation of mean time parameters for drug delivery and disposition (mean residence time, mean transit time, mean arrival time), relative tissue affinity (residence time coefficients), nonparametric exact clearance correction of UIR, and time variant convolution and deconvolution. The general response mapping operation procedure of LSA presented provides a powerful rational alternative to problematic structured modeling of multivariate PK systems. CONCLUSION: The wide arsenal of underutilized LSA-based kinetic analysis tools provide a rational, powerful alternative to traditional kinetic modeling.
OBJECTIVE: To present an overview of noncompartmentally-based modeling which is a modeling that makes use of systems analysis, predominantly linear systems analysis (LSA). FINDINGS: Fundamental elements of LSA presented from a linear operational viewpoint have a sound foundation in molecular stochastic independence (MSI). Powerful LSA procedures based on MSI presented such as convolution, deconvolution and disposition decomposition analysis (DDA) enable PK predictions and evaluations of drug input and delivery using models with simple general structures and few verifiable assumptions. DDA nonparametrically differentiates the unit impulse response (UIR) into generalized elimination and distribution functions. DDA applied in a linear and nonlinear context is central to many LSA procedures such as analytically exact direct deconvolution, nonparametric evaluation of drug elimination and distribution, steady state predictions, evaluation of mean time parameters for drug delivery and disposition (mean residence time, mean transit time, mean arrival time), relative tissue affinity (residence time coefficients), nonparametric exact clearance correction of UIR, and time variant convolution and deconvolution. The general response mapping operation procedure of LSA presented provides a powerful rational alternative to problematic structured modeling of multivariate PK systems. CONCLUSION: The wide arsenal of underutilized LSA-based kinetic analysis tools provide a rational, powerful alternative to traditional kinetic modeling.