In vitro models of human development and their potential application in developmental toxicity testing

Recent publications describe the development of in vitro models of human development, for which applications in developmental toxicity testing can be envisaged. To date, these regulatory assessments have exclusively been performed in animal studies, the relevance of which to adverse reactions in humans may be questioned. Recently developed cell culture-based models of embryo-fetal development, however, do not yet exhibit sufficient levels of standardisation and reproducibility. Here, the advantages and shortcomings of both in vivo and in vitro developmental toxicity testing are addressed, as well as the possibility of integrated testing strategies as a viable option in the near future.

Evaluation of research activities and research needs to increase the impact and applicability of alternative testing strategies in risk assessment practice

The present paper aims at identifying strategies to increase the impact and applicability of alternative testing strategies in risk assessment. To this end, a quantitative and qualitative literature evaluation was performed on (a) current research efforts in the development of in vitro methods aiming for alternatives to animal testing, (b) the possibilities and limitations of in vitro methods for regulatory purposes and (c) the potential of physiologically-based kinetic (PBK) modeling to improve the impact and applicability of in vitro methods in risk assessment practice. Overall, the evaluation showed that the focus of state-of-the-art research activities does not seem to be optimally directed at developing in vitro alternatives for those endpoints that are most animal-demanding, such as reproductive and developmental toxicity, and carcinogenicity. A key limitation in the application of in vitro alternatives to such systemic endpoints is that in vitro methods do not provide so-called points of departure, necessary for regulators to set safe exposure limits. PBK-modeling could contribute to overcoming this limitation by providing a method that allows extrapolation of in vitro concentration-response curves to in vivo dose-response curves. However, more proofs of principle are required.

Integrated Testing Strategies and the Prediction of Toxic Hazard

Over the past 20-30 years there has been a move towards reducing the use of animals in toxicity testing for industrial chemicals, pharmaceuticals, personal care and household products, for economic, scientific and animal welfare reasons. The need for alternatives has been emphasised by the EU REACH regulation, which requires the evaluation of tens of thousands of new and existing chemicals, and also within the pharmaceutical industry owing to the increasing rate at which drugs are being withdrawn from the market due to adverse effects not detected during preclinical testing. Significant effort is being placed into the development of non-animal test procedures using existing data, bioinformatics, in chemico, in silico and in vitro approaches and ethical human studies. Information from these diverse sources needs to be used intelligently and selectively leading to the development of what have become known as Integrated Testing Strategies (ITS). In this chapter factors that need to be considered in the development, evaluation, acceptance and use of ITS will be discussed.

QSAR models for reproductive toxicity and endocrine disruption activity

Reproductive toxicity is an important regulatory endpoint, which is required in registration procedures of chemicals used for different purposes (for example pesticides). The in vivo tests are expensive, time consuming and require large numbers of animals, which must be sacrificed. Therefore an effort is ongoing to develop alternative In vitro and in silico methods to evaluate reproductive toxicity. In this review we describe some modeling approaches. In the first example we describe the CAESAR model for prediction of reproductive toxicity; the second example shows a classification model for endocrine disruption potential based on counter propagation artificial neural networks; the third example shows a modeling of relative binding affinity to rat estrogen receptor, and the fourth one shows a receptor dependent modeling experiment.

Biokinetic modeling and in vitro-in vivo extrapolations

The introduction of in vitro methodologies in the toxicological risk assessment process requires a number of prerequisites regarding both the toxicodynamics and the biokinetics of the compounds under study. In vitro systems will need to be relevant for measuring those structural and physiological changes that are good indicators for adverse effects. Furthermore, the dose metric found to have an effect in the in vitro system should be relevant. One element in defining the appropriate dose metric is related to the kinetic behavior of the compound in the in vitro system: binding to proteins, binding to plastic, evaporation, and the interaction between the culture medium and the cells. Ways to measure and model "in vitro biokinetics" are described. Second, the appropriate dose metric in vitro, e.g., the effective concentration, will need to be extrapolated to relevant in vivo exposure scenarios. The application of physiologically based biokinetic modelling is essential in such extrapolations. The parameters needed to build these models often can be estimated based on nonanimal data, namely chemical properties (QSARs) and in vitro experiments.

Assessing the reproductive toxicity of some (con)azole compounds using a structure-activity relationship approach

The present research investigates the study of a set of 27 (con)azoles and their reproductive toxicity. (Con)azoles are used as fungicides and herbicides in agriculture for treatment of fruits, vegetables, cereals, and seeds, or as human antimycotic therapeutics. According to EEC Directive 91/414, active substances used in plant protection products must undergo reproductive toxicity testing. Reproductive toxicity is a complex biological endpoint, which includes many different biological processes and, therefore, it can only to a limited extent be assessed by a single quantitative structure-activity relationship (QSAR) model. The proposed SAR models are built using unsupervised methods, such as hierarchical clustering, principal component analysis and self-organizing maps, with the aim of studying the similarity relationships between structures. The molecular structures are represented with a set of topological and structural descriptors. The models showing clusters, closest neighbours or outliers may support the categorization and the classification of (con)azoles as potential reproductive toxicants.