Whole-body physiology-based pharmacokinetic model

Whole-body physiology-based pharmacokinetic (WB-PBPK) models contain an explicit representation of organs and tissues that have a relevant impact on the absorption, distribution, metabolism, and excretion (ADME) of a drug or radiopharmaceutical. WB-PBPK models enable simulation of concentration curves for each specific organ, blood, and thus the distribution throughout the whole body. WB-PBPK models have been widely used in drug research, and their usage is expanding to the field of PET imaging, especially after the introduction of scanners with long axial field.

WB-PBPK model
Figure 1. An example of WB-PBPK. Each arrow represents a first-order fractional rate constant. For usage in PET studies, time delays and dispersion in vasculature could be modelled by adding a compartment before each organ. Each radioactive metabolite would need their own compartments and rate constants. Depending on the kinetics of the radiopharmaceutical and its metabolites, most organs could be lumped in to one compartment.

PET applications


Obvious PET applications of WB-PBPK models are in estimation of dosimetry, for the radiopharmaceutical itself, and for radionuclide therapy (Siebinga et al., 2021).

Tissue classification

As a first step, current classification methods could provide input for WB-PBPK model, to avoid manual ROI drawing. WB-PBPK model could also be used to improve the tissue classification methods on individual level.

Input function

Arterial blood is the common input function to all tissues, and this has been used to derive model-based input function by fitting a model to several tissue regions simultaneously. WB-PBPK model and long axial field of view (LAFOV) PET scanners allow us to include all major organs in the estimation, thus hopefully making these methods more reliable. The organs with very high blood flow and blood content (especially the lungs) would be important.

Introduction of a few venous blood samples to the WB-PBPK model could be very useful. Simplistic models have already been used in PK studies to model the arteriovenous difference, for example by adding "standard arm" with predefined parameters into PBPK model. Arteriovenous difference modelling has already found its way in PET imaging (Syvänen et al., 2006).

Most radiopharmaceuticals form radioactive metabolites in vivo. Radioactive metabolites in the blood have different organ distribution than the parent radiopharmaceutical, and to account for that, each radioactive metabolite would need its own compartments and rate constants. While this complicates the model, it may also enable more reliable results with fewer metabolite samples. Compartmental models have been introduced for fitting measured input function and for metabolite correction to reduce noise and to allow better interpolation and extrapolation from few blood samples. These methods have only relied on the plasma measurements, and would benefit from additional information.

Optimal solution would be to develop new radiopharmaceuticals that have minimal amounts of radioactive metabolites in the blood. Traditionally, radiopharmaceuticals have been developed for brain PET, where blood-brain barrier keep out many of the metabolites, but this is not the case in peripheral organs. FDG can be used to assess the metabolic rate of glucose in most organs, because its metabolites are mostly trapped intracellularly, and not redistributed via circulation.

Drug PK studies

In drug PK studies the organ distribution of a drug is not known, but only blood ("central compartment") has been available for measurement. Therefore the WB-PBPK models have had to be simplified to include only few kinetic compartments; see the PK one-compartment, two-compartment, and three-compartment models. The two-compartment "whole-body" model has been applied to PET radiowater studies.

Obtaining measured concentration curves from all the major organs simultaneously would immensely improve the reliability of PBPK estimation, when labelled drug molecule is available.

See also:


Bergström M, Långström B. Pharmacokinetic studies with PET. Progr Drug Res. 2005; 62: 280-317. doi: 10.1007/3-7643-7426-8_8.

Bourne DWA: Mathematical Modeling of Pharmacokinetic Data. CRC Press, 1995. ISBN 1-56676-204-9.

Fischman AJ, Alpert NM, Rubin RH. Pharmacokinetic imaging - a noninvasive method for determining drug distribution and action. Clin Pharmacokinet. 2002; 41(8): 581-602. doi: 10.2165/00003088-200241080-00003.

Jann MW, Penzak SR, Cohen LJ (eds.): Applied Clinical Pharmacokinetics and Pharmacodynamics of Psychopharmacological Agents. Adis, Springer, 2016. doi: 10.1007/978-3-319-27883-4.

Kuepfer L, Niederalt C, Wendl T, Schlender JF, Willmann S, Lippert J, Block M, Eissing T, Teutonico D. Applied concepts in PBPK modeling: how to build a PBPK/PD model. CPT Pharmacometrics Syst Pharmacol. 2016; 5(10): 516-531. doi: 10.1002/psp4.12134.

Rosenbaum S (ed.): Basic Pharmacokinetics and Pharmacodynamics - An Integrated Textbook and Computer Simulations. 2nd ed., Wiley, 2017. ISBN 9781119143154.

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Updated at: 2022-04-04
Created at: 2021-11-22
Written by: Vesa Oikonen