Wf. Ebling et al., FROM PIECEWISE TO FULL PHYSIOLOGICAL PHARMACOKINETIC MODELING - APPLIED TO THIOPENTAL DISPOSITION IN THE RAT, Journal of pharmacokinetics and biopharmaceutics, 22(4), 1994, pp. 259-292
Physiologically based pharmacokinetic modeling procedures employ anato
mical tissue weight, blood flow, and steady tissue/blood partition dat
a, often obtained from different sources, to construct a system of dif
ferential equations that predict blood and tissue concentrations. Beca
use the system of equations and the number of variables optimized is c
onsiderable, physiologic modeling frequently remains a simulation acti
vity where fits to the data are adjusted by eye rather than with a com
puter-driven optimization algorithm. We propose a new approach to phys
iological modeling in which we characterize drug diposition in each ti
ssue separately using constrained numerical deconvolution. This techni
que takes advantage of the fact that the drug concentration time cours
e, C-T(t), in a given tissue can be described as the convolution of an
input function with the unit disposition function (UDFT) of the drug
in the tissue, (i.e., C-T(t) = (C-a(t)Q(T))UDFT(t) where C-a(t) is th
e arterial concentration, Q(T) is the tissue blood flow and is the c
onvolution operator). The obtained tissue unit disposition function (U
DF) for each tissue describes the theoretical disposition of a unit am
ount of drug injected into the tissue in the absence of recirculation.
From the UDF, a parametric model for the intratissue disposition of e
ach tissue can be postulated. Using as input the product of arterial c
oncentration and blood flow, this submodel is fit separately utilizing
standard nonlinear regression programs. In a separate step, the entir
e body is characterized by reassembly of the individuals submodels. Un
like classical physiologic modeling the fit for a given tissue is not
dependent on the estimates obtained for other tissues in the model. Ad
ditionally, because this method permits examination of individual UDFs
, appropriate submodel selection is driven by relevant information. Th
is paper reports our experience with a piecewise modeling approach for
thiopental disposition in the rat.