Next generation physiologically based kinetic (NG-PBK) models in support of regulatory decision making

Abstract

The fields of toxicology and chemical risk assessment seek to reduce, and eventually replace, the use of animals for the prediction of toxicity in humans. In this context, physiologically based kinetic (PBK) modelling based on in vitro and in silico kinetic data has the potential to a play significant role in reducing animal testing, by providing a methodology capable of incorporating in vitro human data to facilitate the development of in vitro to in vivo extrapolation of hazard information. In the present article, we discuss the challenges in: 1) applying PBK modelling to support regulatory decision making under the toxicology and risk-assessment paradigm shift towards animal replacement; 2) constructing PBK models without in vivo animal kinetic data, while relying solely on in vitro or in silico methods for model parameterization; and 3) assessing the validity and credibility of PBK models built largely using non-animal data. The strengths, uncertainties, and limitations of PBK models developed using in vitro or in silico data are discussed in an effort to establish a higher degree of confidence in the application of such models in a regulatory context. The article summarises the outcome of an expert workshop hosted by the European Commission Joint Research Centre (EC-JRC) - European Union Reference Laboratory for Alternatives to Animal Testing (EURL ECVAM), on "Physiologically-Based Kinetic modelling in risk assessment - reaching a whole new level in regulatory decision-making" held in Ispra, Italy, in November 2016, along with results from an international survey conducted in 2017 and recently reported activities occurring within the PBK modelling field. The discussions presented herein highlight the potential applications of next generation (NG)-PBK modelling, based on new data streams.

Keywords: In silico; In vitro; PBPK; PBTK; Physiologically based kinetic models; Toxicokinetics.

Fig. 1

(a) Schematic representation of a physiologically based kinetic (PBK) model, (b) with an example of a typical PBK model-output (time-dependent chemical concentration in blood).

Fig. 2

(a) Number of papers published per year within the last 60 years. The search was conducted using the online repository PubMed on the 7th of March 2018, with key words string including “PBPK OR PBBK OR PBTK OR PBK”. (b) The number of papers (Fig. 2 A) published with key words string including “PBPK OR PBBK OR PBTK OR PBK” were normalized to the following terms: Toxicology; Pharmacology; Chemical Safety OR Risk assessment; Forensic Sciences and Veterinary.

Fig. 3

An example of a schematic decision tree to decide what tier of PBK model to apply when encountering data-poor or data-rich chemicals during model parameterization and based on problem formulation.

Fig. 4

Credibility matrix showing comparative loci for a model based on traditional in vivo data-based approaches and for a model based on an alternative approach (i.e., in vitro, in silico methods, and/or micro-scale systems). The rationale for the locations of the model types, indicated by stars and letters, are given in the side-bar legend. For example, in silico models placed at the top right, might consist of a simple model ‘a’ based on a limited set of data, for instance in a QSAR. This leads to a more sophisticated, but still heuristic, model ‘b’ based on the understanding gained from model ‘a’. The predictions from models ‘a’ and ‘b’ are used to design in vitro tests that enable the development of model ‘c’, which can be validated using the rational-empirical approach, thus enhancing its credibility. Finally, this leads to the development of clinical studies and model ‘d’, supported by its predecessors and quantitatively validated or confirmed using clinical data. This places model ‘d’ in the bottom left corner, as a model whose predictions stakeholders, including regulators, practitioners, and patients, will likely use to make decisions (adapted from , proposed by [46]).