Field: Sustainable living
Global Technical function: Managing
Technical Function Unit: Modelling, Networking, Software tool
Geographic Area: France


Physiologically Based Pharmacokinetic (PBPK) modelling tools correlate environmental contamination threats with effects on the human health in order to make complex assessments of sustainable living achievement. PBPK models are a way to mathematically transcribe the anatomical, physiological, physical, and chemical descriptions of the occurrences involved in the complex processes of absorption, distribution, metabolism and excretion of synthetic or natural chemical substances in humans and other animal species. This mathematical technique is conventionally used in pharmaceutical research drug development and health risk assessment. The obtained models are used for managing disparate data from experiments, abstracting and combining them. By using existing information on the anatomical and physiological structure of the body, (and to a certain extent, on biochemistry) the models give access to internal body concentrations of chemicals or their metabolites. PBPK models are used to show the effects from exposure to a substance in those cases linear dose-response models cannot be used, due to variations in absorption, distribution, metabolism etc. between individuals. 

The models are specifically facilitating interpolation and extrapolation of knowledge between:

  • Doses: from high to low concentrations (which are more commonly found in the environment)
  • Exposure duration: from continuous to discontinuous, or single to multiple exposures
  • Routes of administration: from inhalation exposures to ingestion
  • Species: transpositions between different species, for instance when testing a new drug or when human experiments are not found ethical
  • Individuals: different sex and ages and from non-pregnant women to pregnant

The PBPK modelling tool developed within the 2-FUN project focus on extrapolating from adults to children and on predicting metabolic interactions between chemicals in mixtures: Health risk assessments related to chemicals in the environment are traditionally done on individual substance basis, thus missing the interactions between different chemicals that could change the effects from them. Newer assessment methods such as PBPK models coupled with biologically based dose-response models are increasingly used in health risk assessment as they can also take into account for the metabolic interaction between chemicals. The models are compartmental  and represent predefined organs or tissues, based on a system of differential equations representing blood flows, organ volumes etc.  The project team developed a general stochastic whole-body model based on detailed compartmentalization of the human body, including new relationships for time evolution of physiological and anatomical parameters. The challenge was to capture the complex cascade reactions, including the description of intermediate and finale metabolites involved in the chain of reaction. The transportation of each type of metabolite requires a set of equations, often resulting in very complex models. As an example, the transportation of tetrachloroethylene in the body required an overall model with 140 differential equations and about 150 parameters. The equations were manually written based on information from scientific publications. 

The PBPK model developed within the aforementioned project have been integrated in a commercial software tool along with the multimedia modelling software from the same project. However, there might be a need for additional standardization. Thus, the technology readiness level reaches a level 8 on the TRL scale.

The project was running from February 2007 to January 2011, funded under the EU sixth framework programme (FP6), a grant funding programme,and focusing on health issues related to environmental conditions and pressures. Gathering 12 project partners coordinated by the Institut National de l’Environnement Industriel et des Risques in France, the project team used a multidisciplinary networking approach which engaged experts from various research fields.