Objectives:
To provide the necessary modelling framework for:
- Assessing time history internal exposure profile, focusing on susceptible developmental stages (WP4)
- Linking external exposure (consumer and environmental) (Stream 3) to the target tissue dosimetry relevant to in vitro testing responses (WP5)
- Supporting integrative bioinformatics and systems toxicology modelling (WP7)
- Reverse dosimetry assessment: Linking biomonitoring data (biomarkers of exposure) to exposure (Stream 3)
- Linking biomonitoring data to internal concentration of xeniobiotics and their metabolites in target tissues and health effects (Stream 5)
Description of work and role of partners:
WP6 aims at integrating exposure data and modelling output with HBM data. It will develop a lifetime (including gestation and breastfeeding) generic PBBK model incorporating mixtures interaction and a framework for biomonitoring data assimilation. Coupled to the systems biology models of WP7, the PBBK model will be used to reconstruct exposure from HBM data. PBBK modelling can also be used to estimate the proportion of population exposed to internal doses of xenobiotics above levels associated with health risk. At individual level, PBBK models will be combined with multimedia models to identify sources of exposure. In doing this work, the modelling development done in the frame of 2FUN and 4FUN will be taken into account so as to avoid duplication of effort.
Overall, WP6 aims to i) provide the time history of the internal exposure profile, focusing on susceptible developmental stages; ii) assimilate the biomonitoring data related to the cohorts studied in Stream 5; and iii) derive reliable Biologically Effective Dose/Biological Pathway Activating Dose values for the compounds of interest so that they can be associated to observed health outcomes.
Task 6.1 Development of generic multi-route lifetime PBBK model (including gestation and breastfeeding) that incorporates also in utero exposure and mixtures interactions (AUTH, TNO, URV)
The developed generic PBPK model will incorporate:
• Lifespan evolution in physiology, from the moment of conception till 80 years of life-time (the model will be differentiated by gender)
• Detailed description of pregnancy (mother-foetus interaction), as well as modeling for pregnancy of twins, addressing the differences between monochorionic/diamnotic or monochorionic/monoamnotic
• Lactation (toxicants concentration in milk) period
• Detailed compartmental description of human anatomy and receptor binding
• Detailed description of inhalation, dermal and oral routes of exposure
• Interaction of mixtures at the level of metabolism
The model will take stock of the relevant prior work done in the frame of the 2FUN and 4FUN projects. Thus, the PBBK modeling framework developed in these projects will serve as starting point; this will be enhanced and extended towards a generic PBBK model for use in HEALS. The generic character of the model will be ensured by the capability of assessing new chemicals or chemicals with limited information. In this case, the model will be linked to QSAR models, so as to calculate chemical-specific input parameters of PBBK models (partition coefficients and metabolic parameters such as the maximal velocity (Vmax) and Michaelis affinity constant (Km) or the intrinsic clearance (Vmax/Km). Integration of structure- or property-based algorithms with physiological or the intrinsic clearance (Vmax/Km). Integration of structure- or property-based algorithms with physiological information would provide a scientifically sound means of generating first-cut estimates of the pharmacokinetic behaviour of data-poor chemicals
Task 6.2 Developing a modeling framework for human biomonitoring data assimilation by linking biomarker data to exposure burden from multiple routes and comparing them to Biologically Effective Doses (AUTH)
Interpretation of biomonitoring data will be carried out by:
- Exposure reconstruction, which stands for the re-assessment of the external exposure that is consistent with the measured biomonitoring data. A tiered approach will be followed as a function of data availability (periodicity and size of sampling, specimen type) and requirements of the exposure reconstruction analysis (temporal analysis of exposure, contribution from different routes) ranging from use of simple exposure conversion factors, up to Maximum Likelihood Estimates–PBBK modelling with synthetic biomarker data and Markov Chain Monte Carlo analysis.
- Estimation of the proportion of population exposed to internal doses of xenobiotics above levels associated with health risk. The latter can involve the use of specific omics results (metabolomics analysis from WP5) and associations of BED to early biological responses. In addition, BED might be potentially quantifying the effect of compound-induced extracellular perturbations on metabolic states, so to setup a feedback loop that re-defines the clearance and production rates in the PBBK model using dynamic flux analysis. Flux distributions of endogenous and exogenous compounds calculated by flux balance analysis (FBA) are used to adjust clearance and production rates in the PBBK model. After simulating one time step in the PBBK model, new clearance rates constrain the next FBA step.
This will provide an additional link to the systems biology pathway models developed in WP7 for the endpoints identified in Stream 5. The HBM data interpretation and assimilation techniques developed herein will be applied in all case studies of stream 5 as necessary to relate external exposure concentrations to internal dose both in the whole body and in target tissue or biological fluid as appropriate for assimilation with the HBM data available in the populations studied in Stream 5.
