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Open Access Highly Accessed Research article

The use of a physiologically based pharmacokinetic model to evaluate deconvolution measurements of systemic absorption

David G Levitt

Author Affiliations

Department of Physiology University of Minnesota, 6-125 Jackson Hall, 321 Church St. S.E., Minneapolis, MN 55455, USA

BMC Clinical Pharmacology 2003, 3:1  doi:10.1186/1472-6904-3-1

Published: 19 March 2003

Abstract

Background

An unknown input function can be determined by deconvolution using the systemic bolus input function (r) determined using an experimental input of duration ranging from a few seconds to many minutes. The quantitative relation between the duration of the input and the accuracy of r is unknown. Although a large number of deconvolution procedures have been described, these routines are not available in a convenient software package.

Methods

Four deconvolution methods are implemented in a new, user-friendly software program (PKQuest, http://www.pkquest.com webcite). Three of these methods are characterized by input parameters that are adjusted by the user to provide the "best" fit. A new approach is used to determine these parameters, based on the assumption that the input can be approximated by a gamma distribution. Deconvolution methodologies are evaluated using data generated from a physiologically based pharmacokinetic model (PBPK).

Results and Conclusions

The 11-compartment PBPK model is accurately described by either a 2 or 3-exponential function, depending on whether or not there is significant tissue binding. For an accurate estimate of r the first venous sample should be at or before the end of the constant infusion and a long (10 minute) constant infusion is preferable to a bolus injection. For noisy data, a gamma distribution deconvolution provides the best result if the input has the form of a gamma distribution. For other input functions, good results are obtained using deconvolution methods based on modeling the input with either a B-spline or uniform dense set of time points.