This research project investigates the inter- and intraindividual variability in the absorption of antiviral drugs used to treat Feline Infectious Peritonitis (FIP). The project aims to better understand the relationship between drug exposure and therapeutic effect. This knowledge will be used to optimise dosing strategies, ensuring that each cat receives an effective and safe dose, ultimately improving treatment outcomes for FIP.
TK Plate 2.0 builds upon the open-source EFSA platform TK-Plate, which integrates physiologically based kinetic (PBK), kinetic-dynamic (PBKD), toxicokinetic-toxicodynamic (TK-TD), and dynamic energy budget (DEB) models for humans and food-producing animals. The platform offers a user-friendly graphical interface to apply these models in the risk assessment of pesticides, food and feed additives, and contaminants.
There is a growing need to expand these models beyond single chemicals to include multiple chemicals and biological stressors in both farm and wild mammalian species, as well as birds. Achieving this requires a deeper understanding of the toxicokinetic and toxicodynamic processes that link chemical exposure to adverse health outcomes across species.
Innovative methods such as allometric scaling, QSAR, machine learning, and deep learning can support the prediction of key parameters like partitioning, metabolism, kinetic rates, bioaccumulation, and substrate-enzyme/transporter interactions. Moreover, the impact of biological stressors and welfare conditions on TK and TD processes must be integrated.
The overarching goal is to advance biologically based models that can address complex risk assessment scenarios involving chemical mixtures, biological stressors, and animal welfare considerations in species relevant to food and feed safety.