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Title of the External Scientific Report Towards next generation risk assessment of chemicals: Development and application of physiologically based kinetic models in farm animals Leonie S. Lautz 2020 Towards next generation risk assessment of chemicals: Development and application of physiologically based kinetic models in farm animals Proefschrift ter verkrijging van de graad van doctor aan de Radboud Universiteit Nijmegen op gezag van de rector magnificus prof. dr. J.H.J.M. van Krieken, volgens besluit van het college van decanen in het openbaar te verdedigen op dinsdag 2 juni 2020, om 16.30 uur precies door Leonie Sophie Lautz geboren op 5 maart 1990 te Bad Oeynhausen, Duitsland 2 Promotoren Prof. dr. A.M.J. Ragas (Open Universiteit) Prof. dr. ir. A.J. Hendriks Copromotor Dr. J.L.C.M. Dorne (European Food Safety Authority, Parma, Italïe) Manuscriptcomissie Prof. dr. A.M. Breure Prof. dr. F.G.M. Russel Prof. dr. R. Gehring (Universiteit Utrecht) This research described in this thesis was funded by the European Food Safety Authority (EFSA) [Contract number: EFSA/SCER/2014/06]. 3 This is how you do it: you sit down at the keyboard and write one word after another until it is done. It’s that easy, and that hard. (Neil Gaiman) 4 Table of Contents Chapter 1 ................................................................................................................................................... 6 General introduction ................................................................................................................................... Chapter 2 ................................................................................................................................................. 13 Physiologically based kinetic models for farm animals: critical review of published models and future perspectives for their use in chemical risk assessment .............................................................................. Chapter 3 ................................................................................................................................................. 32 Generic physiologically based kinetic modelling for farm animals: Part I. Data collection of physiological parameters in swine, cattle and sheep ....................................................................................................... Chapter 4 ................................................................................................................................................. 42 Generic physiologically-based kinetic modelling for farm animals: Part II. Predicting tissue concentrations of chemicals in swine, cattle, and sheep .................................................................................................... Chapter 5 ................................................................................................................................................. 55 An open source physiologically-based kinetic model for the chicken (Gallus gallus domesticus): Calibration and validation for the prediction of residues in tissues and eggs ............................................ Chapter 6 ................................................................................................................................................. 78 General discussion and synthesis ............................................................................................................... Bibliography ............................................................................................................................................ 87 Appendices ............................................................................................................................................ 110 Summary / Samenvatting ..................................................................................................................... 117 Acknowledgments ................................................................................................................................. 122 Curriculum Vitae ................................................................................................................................... 124 5 CHAPTER 1 GENERAL INTRODUCTION 6 1. GENERAL INTRODUCTION 1.1. Principles of animal health risk assessment of chemicals Chemicals from anthropogenic and natural origins enter animal feed and human food as undesirable contaminant or components of a diet, such as persistent organic pollutants, phthalates and veterinary medicinal products (Dorne and Fink-Gremmels, 2013). These substances can have potential adverse effects on health and productivity of farm and companion animals (Berny et al., 2010; Guitart et al., 2010). Furthermore, the presence of residues of unauthorized substances, veterinary medicinal products or chemical contaminants in food may pose a risk factor for human health, due to potential accumulation and transfer within the food chain (EFSA, 2018b; Verstraete, 2013). The control of risks possibly associated with chemical contamination in food and feed is a priority of the European Union (Silano and Silano, 2017). Compared to human risk assessment, toxicological risk assessment in farm and companion animals is still a young discipline. In the food and feed safety area, animal health risk assessment of chemicals follows the classical steps of the risk assessment framework namely, hazard assessment, exposure assessment and risk characterisation (Dorne and Fink-Gremmels, 2013). Scientific advisory boards have not developed specific frameworks for risk assessment in animal health (farm and companion animals), but in practice, mostly the principles of human risk assessment are applied (EFSA, 2014a; EFSA Scientific Committee, 2019). Available methods and tools in human risk assessment were developed mostly for the pharmaceutical industry, where chemicals are developed for specific targets with certain physicochemical properties and with well-understood kinetics and metabolism (Hartung and Hoffmann, 2009; Sager et al., 2015). Very different from this, the risk assessment of most undesirable chemicals requires identifying unknown modes of action, usually in the absence of kinetic data, for many diverse chemicals with rather limited resources (Hartung and Hoffmann, 2009). Next to this, animal health risk assessment also has to account for differences related to species-specific and interspecies differences in kinetics, dose- dependent toxicity and methodologies to estimate exposure to characterise the risk in variety of animal species. In that respect, a major data gap and research need in this area applies to understanding species differences in kinetics and dynamic (pharmacodynamic or toxicodynamic) processes for single chemicals and mixtures of chemicals and the implementation of such data in current risk assessment practices (EFSA Scientific Committee, 2019). Harmonisation in methodology and terminology between human, animal and environmental risk assessment enhances the understanding of risk assessment issues associated with the 7 food chain and enables efficient use of resources and consistency among assessments (EFSA, 2014b; EFSA Scientific Committee, 2019). Currently, the use of kinetic data in animal health risk assessment is limited due to limited data availability, and when it occurs, it is often on an ad-hoc basis (Alexander et al., 2012; Clapham et al., 2019; Dorne and Fink-Gremmels, 2013). The differences in absorption, distribution, metabolism and excretion (ADME processes) between animal species and the limited data availability on those differences have consequences for the outcome of risk assessment and introduce uncertainty in risk characterisation. In order to protect animal health, it is essential to understand the transfer of chemicals residues in farm animals and to derive safe levels of exposure in feed. Improvement of uncertainty factors and the application of in silico models incorporating kinetics, e.g. one compartment models and physiologically based kinetic (PBK) models, are examples of refinements that may reduce uncertainties in current risk assessment practices, particularly in the extrapolation of toxicity data between various species (Dorne and Fink-Gremmels, 2013). To move towards the integration of new approaches in chemical risk assessment in the areas of human health, animal health and environment, several projects were launched by the European Food Safety Authority (EFSA). These projects involve the integration of kinetic tools (EFSA-Q-2014-00918; EFSA-Q-2015-00640) the modelling of population dynamics of aquatic and terrestrial organisms (EFSA-Q-2015-00554), and the modelling of human variability in kinetic and dynamic processes (EFSA-Q-2015-00641). 1.2. Allometric scaling Body mass is an important parameter, since it largely determines the morphology, physiology, and biology of organisms (Hendriks, 2007; Lindstedt and Schaeffer, 2002). Changes in body mass can result in changes of proportions of the body fluids and organs (Boxenbaum, 1980). In the context of risk assessment, some important kinetic parameters, including the clearance, volume of distribution and elimination half-life, can also be predicted based on the body mass (Huang and Riviere, 2014). Allometric scaling can be used to correlate variables between organisms of different size and is based on a power-law function (Equation 1): 푌 = 푎 ∗ 푀푏 (1) Where Y is the parameter of interest that has to be correlated with body mass (M). The constant a is proportionality factor for the particular parameter, whereas
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