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Determination of drug absorption rate in time‐variant disposition by direct deconvolution using beta clearance correction and end‐constrained non‐parametric regression
Author(s) -
Neelakantan S.,
VengPedersen P.
Publication year - 2005
Publication title -
biopharmaceutics and drug disposition
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.419
H-Index - 58
eISSN - 1099-081X
pISSN - 0142-2782
DOI - 10.1002/bdd.468
Subject(s) - deconvolution , disposition , pharmacokinetics , parametric statistics , absorption (acoustics) , chemistry , drug , metabolic clearance rate , absorption rate , linear regression , regression analysis , pharmacology , chromatography , mathematics , statistics , medicine , physics , psychology , optics , social psychology
A novel numerical deconvolution method is presented that enables the estimation of drug absorption rates under time‐variant disposition conditions. The method involves two components. (1) A disposition decomposition‐recomposition (DDR) enabling exact changes in the unit impulse response (UIR) to be constructed based on centrally based clearance changes iteratively determined. (2) A non‐parametric, end‐constrained cubic spline (ECS) input response function estimated by cross‐validation. The proposed DDR‐ECS method compensates for disposition changes between the test and the reference administrations by using a ‘beta’ clearance correction based on DDR analysis. The representation of the input response by the ECS method takes into consideration the complex absorption process and also ensures physiologically realistic approximations of the response. The stability of the new method to noisy data was evaluated by comprehensive simulations that considered different UIRs, various input functions, clearance changes and a novel scaling of the input function that includes the ‘flip‐flop’ absorption phenomena. The simulated input response was also analysed by two other methods and all three methods were compared for their relative performances. The DDR‐ECS method provides better estimation of the input profile under significant clearance changes but tends to overestimate the input when there were only small changes in the clearance. Copyright © 2005 John Wiley & Sons, Ltd.