Comparison of predictions of developmental toxicity for compounds of solvent data set

Development of in silico classification models for binding affinity to the glucocorticoid receptor

The endocrine disrupting properties of chemicals acting through the glucocorticoid receptor (GR) have attracted considerable interest. Since there are few data for most chemicals on their endocrine properties in silico approaches seem to be the most appropriate tool for screening and prioritizing chemicals for planning further experiments. In this work, we developed classification models for binding affinity to the glucocorticoid receptor using the counterpropagation artificial neural network method. We considered two series of 142 and 182 compounds and their binding affinity to the glucocorticoid receptor as agonists and antagonists, respectively. The compounds belong to different chemical classes. The compounds were represented by a set of descriptors calculated with the DRAGON program. The clustering structure of sets was studied with standard principal component method. A weak separation between binders and non-binders was found. Another classification model was developed using the counterpropagation artificial neural network method (CPANN). The final classification models developed were well balanced and showed a high level of accuracy, with 85.7% of GR agonist and 78.9% of GR antagonist correctly assigned in leave-one-out cross-validation.

Human-Based New Approach Methodologies in Developmental Toxicity Testing: A Step Ahead from the State of the Art with a Feto-Placental Organ-on-Chip Platform

Developmental toxicity testing urgently requires the implementation of human-relevant new approach methodologies (NAMs) that better recapitulate the peculiar nature of human physiology during pregnancy, especially the placenta and the maternal/fetal interface, which represent a key stage for human lifelong health. Fit-for-purpose NAMs for the placental-fetal interface are desirable to improve the biological knowledge of environmental exposure at the molecular level and to reduce the high cost, time and ethical impact of animal studies. This article reviews the state of the art on the available in vitro (placental, fetal and amniotic cell-based systems) and in silico NAMs of human relevance for developmental toxicity testing purposes; in addition, we considered available Adverse Outcome Pathways related to developmental toxicity. The OECD TG 414 for the identification and assessment of deleterious effects of prenatal exposure to chemicals on developing organisms will be discussed to delineate the regulatory context and to better debate what is missing and needed in the context of the Developmental Origins of Health and Disease hypothesis to significantly improve this sector. Starting from this analysis, the development of a novel human feto-placental organ-on-chip platform will be introduced as an innovative future alternative tool for developmental toxicity testing, considering possible implementation and validation strategies to overcome the limitation of the current animal studies and NAMs available in regulatory toxicology and in the biomedical field.