Towards improved PBTK modelling for organic (ionizable) chemicals
Our aim is to quantitatively understand and predict the uptake, distribution, transformation and excretion of organic chemicals in organisms. This knowledge will help to elucidate bioaccumulation and toxic effects of chemicals and should allow a risk assessment for organic chemicals without any animal testing.
In order to go beyond current state-of-the-art in this so called Physiology-Based-Toxico-Kinetic (PBTK) modelling of organisms we are working on various building blocks that we consider as crucial:
Currently we estimate partition coefficients of neutral organic chemicals to various proteins and lipids with the pp-LFER approach (Endo et al, 2013) based on molecular descriptors from our on-line data base (LSERD). Our main limitation in accuracy comes from the limited availability of good descriptor values. In the near future we hope to improve this situation by applying deep learning methods.
In contrast to neutral organic chemicals, sorption processes of ionic species are still not well understood. For sorption of ionic organic species in membrane lipids we have presented a promising approach (Bittermann et al., 2014) that will further be validated for polyvalent ions and zwitterions. Sorption of ionic species in storage lipids is assumed to be negligible. Equilibrium sorption of ionic species to albumin and structural proteins cannot be ignored though and is a matter of ongoing research in our group.
Transport across membranes:
spite of many years of intensive pharmaceutical research there appears to be no
sound mechanistic understanding of the passive diffusion of neutral organic chemicals
through lipid bilayers. This issue will be tackled in a future PhD project.
Recently, we have been able to measure and model the permeability of organic anions through phospholipid bilayers. Based on these results we developed a biophysical model for uncoupling toxicity which will be explored further.
In vitro - in vivo Extrapolation:
The vision of a chemical risk assessment without animal testing is built on the idea that relevant physico-chemical properties of chemicals can be derived from chemical structure. However, we also require information on toxic effects and biotransformation that cannot easily be transferred from chemical structure. This information is gained from in vitro test and must be extrapolated to whole organisms. This extrapolation procedure is part of our recent and ongoing research.