Physiologically-based models and in silico models

The first key recommendation is the need for human TK data in hazard assessment to better understand interspecies differences, human variability. Such TK data will ultimately link exposure, internal dose and toxicity using physiologically-based models for risk assessment purposes.

Such TK is needed to:

- understand the relevance of test species to the human situation from a TK point of view (e.g. evolutionary conservation of enzymes and their respective isoforms) parallel to the investigation of species differences in TD (e.g. receptors, signalling pathways…);

- design sound physiologically-based models integrating species differences in TK and TD and/or human variability in TK for the hazard assessment in metabolic, excretion and transport pathways; - provide a scientific basis to set Assessment Groups based on TK for multiple chemicals particularly when the metabolic route is a key event (bioactivation to a toxic metabolite or TK interactions such as inhibition of cytochrome P-450). Criteria to set these assessment groups using TK data would also need to be considered using a WoE approach including consideration of interspecies differences and human variability (relevance of the metabolic route in test species to the human situation, availability of human data on metabolism (in vitro/in vivo). This recommendation has already been formulated in the context of the scientific report on combined exposure to multiple chemicals (EFSA, 2013).

Improvement of in vitro methods for generating TK data

A key to generating TK data in humans is the improvement of current in vitro methods to measure human absorption (bioavailability, …), distribution (volume of distribution, protein binding, hepatic extraction), metabolism (e.g. Vmax, Km, inhibition constants…) for phase I (cytochrome P-450, esterases…) and phase II (UDP-glucuronyl transferases, glutathione-s-transferases), isoforms involved in gut metabolism versus hepatic metabolism, transporters (e.g. transport via P-glycoprotein, Organic Anion Transporter Proteins (OATP),….), and excretion of chemicals.

6.2.2. Physiologically-based models

Further exploration of the use of physiologically-based models in chemical risk assessment is recommended, namely:

- to develop a guidance on the use of physiologically-based models in chemical risk assessment. This includes toxicokinetic and toxicodynamic models incorporating data from standard in vivo assays and alternative methodologies (in vitro methods and in silico data (QSAR, read-across, TTC)). The guidance could explore, through tiered approaches, the relevance and needs for such models in a context-dependent manner (data-poor chemical specific situation, prioritisation, data-rich chemical specific situation, combined exposure)

- to develop prototype physiologically-based models using specific case studies to integrate exposure (external dose), internal dose and TK information and toxicity data for hazard assessment purposes. These models can also be used to refine uncertainty factors used in hazard assessment (categorical or

chemical-specific) as recommended in the scientific report on combined exposure to multiple chemicals.

- It is recommended to develop relatively simple models that may refine the link between exposure (external dose), basic TK data (internal dose), and toxic effects in the short term. For example, case studies could be explored to develop models for single compounds and binary mixtures based on in vitro and in vivo data. In the mid-term, as knowledge advances, a full exploration of full physiologically-based toxicokinetic models and physiologically-based toxicokinetic-toxicodynamic models that would integrate more complex quantitative knowledge can then be explored and implemented (e.g. inter-species differences, human variability in TK and TD, epidemiological data, in vitro models, in silico models). Finally, it is worth highlighting that the data used to build the models and their associated uncertainty should be described and analysed in a transparent manner to optimise their use and ensure reproducibility.

- A practical need to further develop such physiologically-based models is the need for databases providing critical parameters such as physicochemical properties, biological and physiological, toxicokinetic and toxicity variables (body weight, age, ventilation rate, Vmax, Km, clearance, bioavailability, half life, AOPs), and bioinformatic tools/algorithms, to analyse and integrate the data. 6.2.3. In silico tools

Further work is needed to explore application of in silico tools in chemical risk assessment. This will allow to use currently available databases comprising vast amount of physicochemical and toxicological data and validate the available predictive models to reduce animal use. In addition, it will provide the opportunity to explore the applicability domain of the predictive methods and their degree of specificity. It can be foreseen that the domain of applicability of such tools will be encompassing human health, animal health, and ecological risk assessment.

Development of a framework for systematic and harmonised approach for the use of in silico tools (SAR, QSAR, read-across) is recommended. It is proposed to further explore their use as potential tools to 1. support the hazard identification of genotoxic compounds by building batteries of models based on structural alerts, toxicity data and existing databases, 2. design physiologically-based models, 3. elucidate the mode of action (including toxicity pathways) for the prioritisation of chemicals. A key aspect of these applications is the need to compare the currently available (Q)SAR tools in a transparent way to allow optimisation and calibration of the models.

Further development is proposed for the read-across methodologies in terms of further investigations into their use in the hazard assessment of chemicals, particularly to integrate (Q)SAR and physicochemical properties with TK and TD data (potency estimates, AOP) using specific chemicals as case studies for „proof of concept‟. This can also be useful to explore category-approaches for prioritisation of chemicals, especially for data-poor substances (e.g. flavourings, emerging contaminants…) using for example the OECD QSAR toolbox or the ADMET-SAR tool.

Potential refinements of the TTC approach for hazard assessment have been previously discussed by the Scientific Committee of EFSA in their recent TTC opinion (EFSA SC, 2012). The key recommendations can be highlighted as: 1. Re-evaluation and update of the Kramer classes and toxicological databases to improve accuracy, applicability, and availability of in silico models. 2. Development and refinement of models for the prediction of TK (bioaccumulation in humans, and quantitative simulation of metabolite degradation/formation) and TD (genotoxic potential, carcinogenic potency) with, as far as possible, an understanding of MoA.