(725d) A Dynamic Physiology Based Pharmacokinetic MODEL for Assessing Lifelong Internal Dose | AIChE

(725d) A Dynamic Physiology Based Pharmacokinetic MODEL for Assessing Lifelong Internal Dose



A
comprehensive Physiology Based Pharmacokinetic model for assessing LIFELONG
internal dose

Dimosthenis
A. Sarigiannis, Spyros P. Karakitsios

Aristotle
University of Thessaloniki, Department of Chemical Engineering, Thessaloniki
54124, Greece

Introduction

            A
generic dynamic lifetime PBPK model, capable to describe xenobiotics
ADME (Absorption, Distribution, Metabolism, Elimination) processes was
developed to support chemical risk assessment.  All physiologic parameters are given by
functions of time describing the several lifetime stages (from embryo
conception through mature life), including the differences of enzymatic
activity, depended on the ontogenesis of the regulating genes. In addition, the
organ/blood partition coefficients are given by generic formulas taking into
account the lipid composition of the tissue and the Kow
of the toxic compound in consideration. The generic model was applied to Bisphenol A, describing also the ADME procedure of its
metabolites, namely and BPA-glucuronide. Because BPA-glucuronide is the dominant metabolite, it is excreted
totally in urine, thus the overall model allows as to link external exposure to
urine biomonitoring data.

            The
main controversy regarding BPA toxicity is related to its toxicokinetic
behavior; although BPA glucuronidation
acting as detoxification mechanism is complete and fast, due to the reduced
metabolic capacity of infants-neonates, there is still ample opportunity of
internal exposure [1,2]. Existing biomonitoring
studies regarding BPA exposure cannot provide substantial support, because most
of them track only urinary metabolites (BPA-glu), hence are useful only for assessing the overall daily
dose. Due to the fast metabolism of BPA to BPA-glu,
the extent of red blood cells binding (fraction of 0.95) and the limitations of
the analytical techniques, the related biomonitoring
studies either fail to detect free-BPA in the plasma, or when they do, the
observed values are considered a result of background contamination from labware and indoor dust [3], an opinion which is under
strong contestation [4]. BPA was found to produce adverse neurodevelopmental
effects in rats given an oral dose considered as environmentally relevant, but
the results were under serious criticism by the regulatory authorities [5,6] mainly
based on the validity of the applied methods (not GLP compliant). Additional
arguments included the relevance of bioavailability for the same normalized
oral dose among rodents and humans, due to substantial differences in BPA
excretion route (humans only via urine, rodents feces and urine due to hepatobilic recirculation) and rate of elimination and
excretion (elimination half life time 5.3 h and 10.5h for humans and rodents
respectively).

Methodology

            The
overall modeling system was developed in asclXtreme (AEgis¨ technologies), allowing us to derive
dynamic estimations. Ours is a double PBPK model coupling the mother-fetus
interaction (see figure 1) As such, the first complex describing mother
physiology includes additionally the breast and the uterus compartments. The
second complex describes the fetus and consequently the infant development.

            For
the several tissue compartments of the model, ADME procedure regarding mass
conservation is given by the following formula:


                            (1)

where Vi represents the volume of tissue group i, Qi is the blood flow
rate to tissue group iCAj is the concentration of chemical j in arterial blood, and Cij and CVij
are the concentrations of chemical j in
tissue group i and
in the effluent venous blood from tissue i, respectively. Metabij is
the rate of metabolism for chemical j in
tissue group i;
liver, being the principal organ for metabolism would have significant
metabolism and, with some exception, usually Metabij is equal
to zero in other tissue groups. Elimij represents the rate of elimination from
tissue group i (e.g.,
biliary excretion from the liver), Absorpij represents uptake of the chemical
from dosing (e.g., oral dosing), and PrBindingij represents protein binding of
the chemical in the tissue.


 Untitled-1

Figure 1: Visual representation of the Mother-Fetus generic PBPK model

            The
parameters related to organ volumes (V) and blood flows (Q)
were taken from the International Commission on Radiological Protection report [7]
and fitted to time (t) (in Datafit 9.0 software) in order
to derive continuous time depended non lineal polynomial formulas in the form
of:

                                                                                        (2)

            The
blood/tissue partition coefficients are contaminant specific and are estimated
by the tissue lipids content and the octanol/water
partition coefficient of the contaminant by the following formula [8]:


                                                                         (3)

Results

            Considering
that the software implements dynamic simulation through time allowing to track
internal dose profile either on a daily basis depending on the nutritional
schedule and/or other routes of exposure, or to simulate continuously the
internal dose through life time from the moment of conception (even if for the
first three months internal dose cannot be determined). Considering the average exposure scenarios as indicated by EFSA, the
results of the corresponding run (from gestation to two post-natal years) are
presented in Figure 2. The bold line in the middle indicates the steady-state
concentration of free plasma BPA through these stages as derived by this run,
the thump area around this line indicates the range of uncertainty for each
developmental stage, originated either by the uncertainty/variability on
intrinsic clearance capacity, or by uncertainty in the exposure scenarios,
compiling the results of the Monte Carlo analysis when the exposure scenarios
change.


Figure 2: Continuous assessment of free plasma BPA
from the developing fetus and infant until the age of two

Discussion
and conclusions

            The
generic PBPK model developed in this study successfully addressed the internal
exposure assessment of abundant contaminants with minor modifications. The identification
of the parameters affecting internal exposure give us
guidance for applying the necessary protective measures.

            The
complexity of exposure scenarios to BPA, employing multiple pathways and
routes, as well as the differences of enzymatic activity during different
developmental stages, posed specific needs to the modeling framework [9]. The
model gives the capability to reconstruct exposure by urine biomarker data. In
this way, the overall uptake is estimated, but based on
knowledge of the different routes contribution, actual
internal dose is estimated. This feed-forward procedure is an additional
asset of this generic PBPK model, ensuring better data exploitation and
interpretation.

References

 ADDIN EN.REFLIST [1]         Edginton,
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[2]         Ginsberg, G. and
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[3]         Dekant, W. and
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[4]         Vandenberg, L.N.,
Chahoud, I., Heindel, J.J., Padmanabhan, V., Paumgartten, F.J.R. and
Schoenfelder, G. (2010). Environmental Health Perspectives  118, 1055-1070.

[5]         EFSA. (2006) Opinion
of the Scientific Panel on Food Additives, Flavourings, Processing Aids and
Materials in Contact with Food on a Request from the Commission related to
2,2-bis(4-hydroxyphenyl)propane (bisphenol A) European Food Safety Agency.

[6]         EFSA. (2008)
Toxicokinetics of Bisphenol A - Scientific Opinion of the Panel on Food
additives, Flavourings, Processing aids and Materials in Contact with Food
European Food Safety Agency.

[7]         ICPR.
(2002) Basic anatomical and physiological data for use in radiological
protection: reference values, in The
International Commission on Radiological Protection
, J. Valentin, Editor.

[8]         Poulin, P. and
Krishnan, K. (1996). Toxicology and Applied Pharmacology  136(1), 126-130.

[9]         Vandenberg, L.N.,
Maffini, M.V., Sonnenschein, C., Rubin, B.S. and Soto, A.M. (2009). Endocrine
Reviews 30(1), 75-95.