In silico methods and models are increasingly used for predicting properties of chemicals for
hazard identification and hazard characterisation in the absence of experimental toxicity …

Early toxicity assessment plays a vital role in the drug discovery process on account of its
significant influence on the attrition rate of candidates. Recently, constant upgrading of …

Herein, a robust and reproducible eXplainable Artificial Intelligence (XAI) approach is
presented, which allows prediction of developmental toxicity, a challenging human-health …

Chemical space modelling has great importance in unveiling and visualising latent
information, which is critical in predictive toxicology related to drug discovery process. While …

ABSTRACT Introduction The application of Artificial Intelligence (AI) to predictive toxicology
is rapidly increasing, particularly aiming to develop non-testing methods that effectively …

Despite being extremely relevant for the protection of prenatal and neonatal health, the
developmental toxicity (Dev Tox) is a highly complex endpoint whose molecular rationale is …

Consensus strategies have been widely applied in many different scientific fields, based on
the assumption that the fusion of several sources of information increases the outcome …

This study utilized effect-directed analysis (EDA) combined with full-scan screening analysis
(FSA) to identify aryl hydrocarbon receptor (AhR)-active compounds in sediments of inland …

Abstract Many New Approach Methodologies (NAMs) have been developed for the safety
assessment of new ingredients. Research into reproductive toxicity and teratogenicity is a …

Endocrine-disrupting potential was evaluated during the sewage treatment process using in
vitro bioassays. Aryl hydrocarbon receptor (AhR)-, androgen receptor (AR)-, glucocorticoid …