282153 A Dynamic Physiology Based Pharmacokinetic MODEL for Assessing Lifelong Internal Dose

Thursday, November 1, 2012: 1:45 PM
326 (Convention Center )
Dimosthenis Sarigiannis and Spyros Karakitsios, Chemical Engineering, Aristotle University of Thessaloniki, Thessaloniki, Greece

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


            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).


            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:


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.

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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:


            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]:



            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.


 ADDIN EN.REFLIST [1]         Edginton, A.N. and Ritter, L. (2009). Environmental Health Perspectives  117(4), 645-652.

[2]         Ginsberg, G. and Rice, D.C. (2009). Environmental Health Perspectives  117(11), 1639-1643.

[3]         Dekant, W. and Všlkel, W. (2008). Toxicology and Applied Pharmacology  228(1), 114-134.

[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.

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