Non-animal predictions of the behaviour of chemicals in the body
Computer models that predict the bioavailability of chemicals in a body play a substantial role in the transition towards toxicity testing strategies without animal experimentation. However, the development of such computer models solely on the basis of in vitro and/or in silico input data remains a challenge. Uncertainties with respect to the impact of different strategies to parameterize the models, the quality of the input data as well as the difficulty of determining whether all relevant processes are included in the model, requires that the model predictions still need to be evaluated on a case-by-case basis against in vivo data (e.g. plasma concentrations observed in animals or humans). Key for the transition towards non-animal testing strategies is to move away from this case-by-case evaluation and optimization of the models against in vivo data and to identify other strategies for the evaluation of the adequacy of in vitro- and in silico-based computer models to estimate in vivo plasma and tissue concentrations. To enable this, knowledge on the predictive value of different in vitro and/or in silico input methods that can be used for the development of the computer models is needed. In addition, insight in chemical characteristics is needed that would indicate whether a chemical is within or outside the applicability domain of the model performance.
The project will contribute to the development of novel approaches to achieve safe innovations without animal testing. Understanding the bioavailability of chemicals in the body is a crucial first step in estimating chemical hazards. These insights are relevant in the selection of chemicals for further development as well as in the conversion of in vitro toxicity data into human dose−response or potency information
Scientifically this project delivers an important tool to the “animal free testing toolbox”. In combination with existing effect assays the accuracy of in vitro tests will strongly improve, thereby increasing the regulatory acceptance of animal free tests and reducing ethically undesirable animal testing. This strongly contributes to the policy of the Dutch Government (“Transitie Proefdiervrije Innovatie”) to be a front runner in animal free testing by 2025. The project will meet societal needs for reliable methods to predict the toxicity of chemicals that are less reliant on animal studies and more directly relevant to the human situation. The animal-free methods will allow for improved selection of promising chemical entities in product development, reducing time and costs for chemical and product development.
The goal of the first part of the project is to evaluate the performance of physiologically based kinetic (PBK) models that are built based on in vitro and in silico input data to predict plasma concentrations in rats and humans. In the second part of the of the project, possibilities to improve the model predictions based on in vitro input data for transporter kinetics or extrahepatic metabolic processes will be evaluated.
Task 1.1 Literature search on rat kinetic input data for the development of the PBK models and available in vivo rat data for the model evaluation.
Task 1.2 Generation of new rat in vitro and in silico kinetic data for a range of chemicals as input for the rat PBK model.
Task 1.3 Development of an R pipeline to predict Cmax in plasma of rats for a range of chemicals based on different input approaches.
Task 1.4 Evaluation of the predictive value of the PBK model predictions, exploring the characteristics of chemicals that cannot be adequately predicted and application of the results obtained on a set of in-house BASF chemicals.
Task 2.1 Literature search on human kinetic input data for the development of the PBK models and available in vivo human data for the model evaluation.
Task 2.1 Generation of new human in vitro and in silico kinetic data for a range of chemicals as input for the human PBK model.
Task 2.3 Development of an R pipeline to predict Cmax in plasma of humans for a range of chemicals based on different input approaches.
Task 2.4 Preparation of two draft manuscripts based on the evaluations of the rat and human PBK models.
Task 3.1 Literature search on available in silico calculators to predict transporter kinetics of chemicals.
Task 3.2 Generation of new in vitro transporter kinetic data.
Task 3.3 Performing correlation studies between the transporter kinetic data and the observed difference in predicted and observed ratios.
Task 3.4 A draft manuscript on the use of in vitro and in silico transporter data to predict whether a chemical is likely to be adequately predicted by a minimal PBK model or not.
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